IsAlgo - AI Trend Strategy► Overview:
The AI Trend Strategy employs a combination of technical indicators to guide trading decisions across various markets and timeframes. It uses a custom Super Trend indicator and an Exponential Moving Average (EMA) to analyze market trends and executes trades based on specific candlestick patterns. This strategy includes options for setting stop losses, take profit levels, and features an alert system for trade notifications.
► Description:
This strategy focuses on identifying the optimal "entry candle," which signals either a potential correction within the ongoing trend or the emergence of a new trend. The entry criteria for this candle are highly customizable, allowing traders to specify dimensions such as the candle's minimum and maximum size and body ratio. Additional settings include whether this candle should be the highest or lowest compared to recent candles and if a confirmation candle is necessary to validate the entry.
The Super Trend indicator is central to the strategy’s operation, dictating the direction of trades by identifying bullish or bearish trends. Traders have the option to configure trades to align with the direction of the trend identified by this indicator, or alternatively, to take positions counter to the trend for potential reversal strategies. This flexibility can be crucial during varying market conditions.
Additionally, the strategy incorporates an EMA alongside the Super Trend indicator to further analyze trend directions. This combined approach aims to reduce the occurrence of false signals and improve the strategy's overall trend analysis.
The learning algorithm is a standout feature of the AI Trend Strategy. After accumulating data from a predefined number of trades (e.g., after the first 100 trades), the algorithm begins to analyze past performances to identify patterns in wins and losses. It considers variables such as the distance from the current price to the trend line, the range between the highest and lowest prices during the trend, and the duration of the trend. This data informs the algorithm's predictions for future trades, aiming to improve accuracy and reduce losses by adapting to the evolving market conditions.
► Examples of Trade Execution:
1. In an Uptrend: The strategy might detect a suitable entry candle during a correction phase, which aligns with the continuing uptrend for a potential long trade.
2. In a Downtrend: Alternatively, the strategy might identify an entry candle at the end of a downtrend, suggesting a potential reversal or correction where a long trade could be initiated.
3. In an Uptrend: The strategy may also spot an entry candle at the end of an uptrend and execute a short trade, anticipating a reversal or significant pullback.
4. In a Downtrend: The strategy might find a suitable entry candle during a correction phase, indicating a continuation of the downtrend for a potential short trade.
These examples illustrate how the strategy identifies potential trading opportunities based on trend behavior and candlestick patterns.
► Features and Settings:
⚙︎ Trend: Utilizes a custom Super Trend indicator to identify the direction of the market trend. Users can configure the strategy to execute trades in alignment with this trend, take positions contrary to the trend, or completely ignore the trend information for their trading decisions.
⚙︎ Moving average: Employs an Exponential Moving Average (EMA) to further confirm the trend direction indicated by the Super Trend indicator. This setting can be used in conjunction with the Super Trend or disabled if preferred.
⚙︎ Entry candle: Defines the criteria for the candle that triggers a trade. Users can customize aspects such as the candle's size, body, and its relative position to previous candles to ensure it meets specific trading requirements before initiating a trade.
⚙︎ Learning algorithm: This component uses historical trade data to refine the strategy. It assesses various aspects of past trades, such as price trends and market conditions, to make more informed trading decisions in the future.
⚙︎ Trading session: Users can define specific trading hours during which the strategy should operate, allowing trades to be executed only during preferred market periods.
⚙︎ Trading days: This option enables users to specify which days the strategy should be active, providing the flexibility to avoid trading on certain days of the week if desired.
⚙︎ Backtesting: Enables a period during which the strategy can be tested over a selected start and end date, with an option to deactivate this feature if not needed.
⚙︎ Trades: Detailed configuration options include the direction of trades (long, short, or both), position sizing (fixed or percentage-based), the maximum number of open trades, and limitations on the number of trades per day or based on trend changes.
⚙︎ Trades Exit: Offers various strategies for exiting trades, such as setting limits on profits or losses, specifying the duration a trade should remain open, or closing trades based on trend reversal signals.
⚙︎ Stop loss: Various methods for setting stop losses are available, including fixed pips, based on Average True Range (ATR), or utilizing the highest or lowest price points within a designated number of previous candles. Another option allows for closing the trade after a specific number of candles moving in the opposite direction.
⚙︎ Break even: This feature adjusts the stop loss to a break-even point under certain conditions, such as reaching predefined profit levels, to protect gains.
⚙︎ Trailing stop: The trailing stop feature adjusts the stop loss as the trade moves into profit, aiming to secure gains while potentially capturing further upside.
⚙︎ Take profit: Up to three take profit levels can be established using various methods, such as a fixed amount of pips, risk-to-reward ratios based on the stop loss, ATR, or after a set number of candles that move in the direction of the trade.
⚙︎ Alerts: Includes a comprehensive alert system that informs the user of all significant actions taken by the strategy, such as trade openings and closings. It supports placeholders for dynamic values like take profit levels, stop loss prices, and more.
⚙︎ Dashboard: Provides a visual display of detailed information about ongoing and past trades on the chart, helping users monitor the strategy’s performance and make informed decisions.
► Backtesting Details:
Timeframe: 15-minute BTCUSD chart.
Initial Balance: $10,000.
Order Size: 4% of equity per trade.
Commission: 0.01%.
Slippage: 5 ticks.
Risk Management: Strategic stop loss settings are applied based on the most extreme price points within the last 18 candles.
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Price Action Pattern Breakout Strategy: Wedge,Triangle,ChannelIntroducing the Price Action Pattern Breakout Strategy: Wedge,Triangle,Channel 💹🚀
The "Price Action Pattern Breakout Strategy: Wedge, Triangle, Channel" is a dynamic and automated trading strategy that excels in recognizing and capitalizing on breakout opportunities within the realm of powerful price action patterns. It is finely tuned to achieve exceptional precision in detecting three distinct pattern types: Wedge, Triangle, and Channel. This diversity equips you to confidently navigate a wide range of market scenarios and opportunities.
This strategy automates trade entries and exits upon confirmed pattern breakouts, this eliminates human errors in correctly recognizing patterns and prevents emotional decisions. This strategy is designed to work across different time frames, making it suitable for both short-term and long-term traders. Whether you're a day trader, swing trader, or investor, this strategy provides the flexibility you need to thrive in diverse market conditions.
💎 How it Works:
▶️ In this strategy, three price action patterns have been utilized, one of which is the "Wedge" pattern. The Wedge pattern has consistently demonstrated a high level of credibility, typically resulting in sharp and rapid price movements following a confirmed breakout from this pattern. This characteristic makes the Wedge pattern highly noteworthy in our strategy. The second pattern is the "Triangle" pattern, which, depending on its formation, whether ascending or descending, can indicate a strong continuation or reversal of the trend. The last pattern is the "Channel" pattern. The reason for using the Channel pattern is its versatility in various market conditions and its tendency to produce reliable results.
In the snapshot below, you can observe the types of patterns that this strategy is capable of identifying at a glance:
▶️ This strategy employs two types of targeting systems: Fixed Targets and Trailing Targets.
Fixed Targets is the default targeting system of the strategy, incorporating two primary targets: TP1 (Target Point 1) and TP2 (Target Point 2). These targets are thoughtfully adjusted in alignment with specific rules for each pattern. With Fixed Targets, you have the flexibility to designate the position size percentage for your exits at TP1 and TP2. For instance, should you opt to allocate 60% of your position size to TP1, as soon as the price triggers the first take profit level, 60% of your initial position is gracefully closed, leaving the remaining 40% to exit the trade upon reaching TP2.
Trailing Targets represent the strategy's alternative targeting system. With this system, the trailing stop becomes active once the price reaches the specified trigger point. The strategy then exits the trade based on the defined offset percentage and price retracement from the trailing limit.
▶️ This strategy relies on a single type of stop loss, determined by previous pivot points and adjusted based on the trade's direction, whether long or short, placing the stop loss above or below the prior pivot. This stop loss approach has demonstrated reliability when used alongside price action patterns.
In addition to this fixed stop loss, you can specify a percentage buffer, offering protection against potential stop hunting due to market fluctuations. This buffer helps protect your positions from sudden price swings. For example, selecting a 1% buffer means your stop loss will be positioned 1% higher or lower concerning the last pivot, depending on your trade's direction. This added layer of security ensures your trades remain resilient and less vulnerable to market volatility.
▶️ A practical feature of this strategy is the "Risk-Free" option. Once activated, it continuously monitors price movements, and as soon as the price progresses in the trade's direction and surpasses the designated Risk-Free Trigger Point in percentage, the stop loss is dynamically shifted from its initial position to the entry price, effectively making the trade "risk-free." This means that if the trade doesn't go as expected, we exit at the entry point, incurring neither profit nor loss from the trade.
Additionally, you have the flexibility to fine-tune the modified stop loss, positioning it slightly above or below the entry price through the configuration of a specified percentage. This allows for effective consideration of commission fees in your trading strategy.
▶️ Risk management is a crucial concept in trading, playing a significant role in a trader's long-term success. This strategy introduces a unique feature called "Fixed Loss Position Sizing", where upon activation, you can limit the risk exposure to a specified percentage of your capital per trade. Set your preferred risk percentage along with the intended leverage. The strategy independently considers your available capital and designated leverage, determining the position size before executing any trade.
In the case of a stop loss, your loss is limited to the specified risk percentage. For instance, with a $1000 account and a 1% risk set, the strategy adjusts each trade's size to ensure a maximum loss of $10 if the stop loss is triggered. Enabling this feature will ensure disciplined risk management, aligning potential losses precisely with your predetermined risk percentage, contingent upon your total available capital.
▶️ Another feature of this strategy is a sophisticated mechanism called "Loss Compensation". When enabled, Loss Compensation dynamically adjusts the position size after a loss, aiming to recover from previous losses in subsequent trades. This adaptive mechanism continually modifies the position size to mitigate the impact of consecutive losses until reaching a user-defined limit for consecutive loss compensations.
The feature's configurability allows users to set the maximum number of consecutive losses to compensate for and also includes an option to factor in trading fees from prior trades into the compensation calculation. Loss Compensation operates in conjunction with the 'Fixed Loss Position Sizing' setting, ensuring that once losses are sufficiently compensated, subsequent entries revert to the predefined configurations within the 'Fixed Loss Position Sizing' settings.
This advanced tool ensures a stable risk management approach by changing trade sizes dynamically according to past results during consecutive loss periods.
▶️ This strategy incorporates a feature known as the "Counter-Pattern Breakout", altering its approach to wedge, triangle, and channel pattern breakouts. Normally, the strategy relies on standard pattern signals to determine whether to enter long or short positions based on breakout directions.
For example, in an ascending channel or a rising wedge pattern, the strategy typically seeks a short position opportunity upon a confirmed breakout in the lower line, and breakouts from the upper line are disregarded by the strategy. But with this feature enabled, strategy disregards the conventional pattern signals, seizing breakouts from upper or lower lines to open corresponding positions. For instance, in the ascending channel or the rising wedge pattern example, the strategy might enter a long position if the upper line breaks or a short position if the lower line breaks.
This introduces a more adaptive and opportunistic trading style, allowing you to capitalize on price movements, irrespective of the typical signal direction indicated by the pattern.
▶️ This strategy is fully compatible with third-party trading bots, allowing for easy connectivity to popular trading platforms. By leveraging the TradingView webhook functionality, you can effortlessly link the strategy to your preferred bot and receive accurate signals for position entry and exit. The strategy provides all the necessary alert message fields, ensuring a smooth and user-friendly trading experience. With this integration, you can automate the execution of trades, saving time and effort while enjoying the benefits of this powerful strategy.
⚙️ How to Use & Configure User Settings:
To fully utilize the "Price Action Pattern Breakout Strategy: Wedge, Triangle, Channel," it's essential to consider and comprehend the following steps. They play a crucial role in enhancing its functionality and achieving its utmost potential outcomes:
1. General Strategy Settings:
Enable Dark Mode if using a dark TradingView theme for improved chart visibility.
Select the Strategy's Trade Direction: Long, Short, or Both.
Choose Pattern Recognition Accuracy: High for precise recognition but fewer positions, Low for more positions with slightly less accuracy.
Enable 'Prevent New Entry on Opposite Signal While In Position' to avoid new trades if the opposite signal occurs.
Switch to Indicator Mode if solely using the strategy as an indicator or in combination with other strategies.
2. Pattern and Pivot Configuration:
Consider configuring the Number of Patterns and Pivot Lookback Lengths. Here, you can personalize the pivot lookback lengths for wedge, triangle, and channel patterns across eight different settings on your chart. For lower time frames, consider larger lengths to reduce chart noise. Alternatively, to maintain clarity on your chart, you can disable multiple patterns with different lengths while ensuring at least one pattern remains enabled.
Note that enabling more patterns doesn't always equate to increased potential profit. Sometimes, fewer patterns result in greater profit potential, and vice versa. Experiment with lengths and the number of patterns to determine the most profitable and optimal outcome for your trading symbol and timeframe.
3. Targeting System Selection:
Choose between 'Fixed Targets' or 'Trailing Targets' for your targeting system.
'Fixed Targets' is the default setting, operational when 'Trailing Targets' are turned off.
Set the TP1 Position Size as a percentage, defining the size for TP1, and the rest exits at TP2.
Optionally activate 'Skip Entry if TP1 is Passed' to bypass entering positions if the price has exceeded TP1.
Alternatively, opt for the 'Trailing Target' for dynamic exits based on trigger points and offsets. Note that this option disables fixed targets.
4. Stop Loss Configuration:
Determine the number of candles to consider for stop loss placement based on the last pivot.
Optionally add a percentage to the stop loss to create a buffer against market fluctuations, guarding your positions from sudden price swings.
5. Risk Management Configuration:
You can activate the 'Risk-Free' feature, making your trades risk-free by moving the stop loss to the entry price upon reaching a specified trigger point.
You have the possibility to enable 'Fixed Loss Position Sizing' to limit risk to a percentage of total capital per trade, ensuring prudent risk management.
You can employ 'Use Real-Time Balance for Each Entry' to precisely calculate fixed loss position sizing according to the real-time balance for every entry.
The 'Loss Compensation' feature can be activated to automatically adjust trade sizes during consecutive losses and compensate for prior incurred losses.
Loss compensation continues adjusting trade sizes until it reaches the defined limit of consecutive losses specified in the 'Maximum Consecutive Losses To Compensate' field.
You can factor in commission fees by specifying a percentage in the 'Include Trading Fees in Compensation (%)' field, providing an option for more accurate loss compensation calculations.
You have the option to enable 'Limit Compensation to Real-Time Balance' to prevent consecutive loss compensation from exceeding your current real-time account balance.
It's important to note that for the 'Loss Compensation' feature to operate, the 'Fixed Loss Position Sizing' must be enabled.
6. Counter-Pattern Breakout Configuration:
In this section you have the option to enable the "Counter-Pattern Breakout" feature to adjust the strategy's approach to wedge, triangle, and channel pattern breakouts. Once enabled, the strategy disregards traditional pattern signals and capitalizes on breakouts from either the upper or lower lines, initiating corresponding positions accordingly.
Choose between 'Fixed Target' or 'Trailing Target' for your targeting system. If you opt for the 'Fixed Target', set a specific target point as a percentage, serving as the default target for counter-pattern breakouts. Alternatively, choose the 'Trailing Target' for dynamic exits based on trigger points and offsets. Do keep in mind that selecting the 'Trailing Target' option disables the fixed target setting.
Keep in mind that for standard, non-counter-pattern breakouts, the target point settings in their respective sections remain applicable, distinct from the settings configured for targeting within this section.
Note that the stop loss configurations are shared across standard pattern and counter-pattern breakouts and can be adjusted within the stop loss section.
7. Info Tables:
In the info tables section, you can show or hide different tables on the charts. This includes the backtest table, the current balance table displaying available funds, and a table showcasing Maximum Consecutive Wins or Losses. Choose which to display according to your preferences and specific needs.
8.Date & Time Range Filter:
Utilize the Date & Time Range filter feature to precisely select a start and end date, including time, to filter data within the chosen range.
When connecting this strategy to a trading bot for automated trades, ensure to set the start date and time to the intended initiation moment to avoid undesired outcomes as this directly affects the real-time balance calculations of the strategy.
8. Integration with Third-Party Bots:
To automate trading, leverage the strategy's compatibility with third-party trading bots. Seamlessly integrate the strategy into well-known trading platforms by using alert message fields to input commands from third-party trading bots, enabling automated trade execution for both long and short positions.
By furnishing these adjustable settings, the strategy empowers you to personalize it according to your unique requirements, thereby bolstering the adaptability and efficacy of your trading approach.
🔐 Source Code Protection:
The 'Price Action Pattern Breakout Strategy: Wedge, Triangle, Channel' source code is engineered for precision, reliability, and effectiveness. Its original and innovative design warrants protection and restricted access, preserving the strategy's exclusivity. Safeguarding the code maintains the strategy's integrity and distinctiveness, providing users with a competitive advantage in their trading endeavors.
Strategy Developer ToolSolar Strategies: Strategy Developer Tool Complete Guide
This guide provides full explanation of the intended purpose of our script along with individual explanation of each input and the logic behind them coupled with general knowledge which we find useful in using our tool regarding elements of risk and strategy. Use this information wisely and understand we are not providing financial advise, this is a learning tool meant to help advance traders knowledge of the markets and their strategies which are formed as such.
Basics
Before getting into the specifics of how to use our strategy developer tool, it's important to understand a few basic fundamental things about it. The purpose of the tool is to allow the user to optimize a strategy through back testing with our strategy tracker and 50+ user inputs. The way you optimize your strategy depends on a couple things:
The state of the current and recent previous market.
The timeframe you trade on.
The types of trades you prefer. (swings, scalps, etc.)
How much risk you are willing to take on.
Risk Basics:
Going off the last bullet point on the list above, risk plays a huge part in how you optimize your strategy, with that being said here are a few general rules of risk as they relate to trades:
The more trades you take on, the more risk you are opening your strategy up to.
If done correctly, more trades will often result in more profit with slightly lower accuracy, and more risk.
The less trades you take on, the easier it is to have higher accuracy because ideally by rooting out the losing trades, you are left with fewer overall trades but mostly winning trades.
Less trades with higher accuracy often result in less profit but will 100% be less risky than the opposite. (More trades, less accurate, more profit, MORE RISK)
Input Basics:
More trades, less trades, more risk, less risk, what does this all mean as it relates to our tool?
The 50+ user inputs that allow you to optimize and create your strategy all effect when the script takes a trade.
Many of the inputs are essentially conditions. By changing these inputs, what you are doing is changing how specific the conditions need to be in order to take a trade.
This is how the inputs tie into the bullet point list above regarding risk and the number of trades you take on. By raising or lowering certain inputs, you are making the conditions more or less specific on when to trade.
Making conditions more specific will allow for less trades to be taken and will often result in a higher win rate, and less associated risk.
Making conditions less specific will allow for more trades to be taken and depending on the state of the market, could result in more profit being realized, but at the same time opens you up to more risk because you are stating a more general set of conditions in order to take a trade.
How does it work?
Our strategy developer tool is based on two simple factors in order to identify specific areas in the market deemed good for trade. They are as follows:
Directional momentum to identify when a move might happen.
A confirmation of the desired move.
Indicators:
The tool gets its information on these two factors from two custom built indicators which are hard coded into the script. These two indicators and the inputs which affect them can be found labeled with Indicator 1 or Indicator 2 in the tool's settings.
When the conditions are met based on the factors of both indicators, it then decides your stop losses and take profits using pivot points.
Indicator 1 is the momentum indicator.
Indicator 2 looks for confirmation of the move.
Hedges:
Since nothing is ever certain when trading, our tool also aims to minimize potential loss before it can happen by incorporating hedges when a signal prints in the opposite direction of the trade you are currently in.
To identify when to hedge, the candles will appear with the opposite color of your original trade. Candles, while in a long trade, appear as green and candles while in a short trade appear as red. While in a long trade the only time red candles will appear is when a hedge occurs and vice versa for shorts.
Example: If you just took a long trade based on a long signal that the script gave off, but a short signal prints off while you are in the long, you are directed to sell half your long position and enter that half into a short position. Since there is now more uncertainty in the long because of the short signal, minimizing your position size and having a smaller position in the opposite direction allows you to cover your bases if the trade moves against you. If it doesn’t move against you and ends up going long as originally intended, you are not to lose any money, likely a small profit or break even when all is said and done.
In order to give the hedges a greater change of hitting, the take profits are smaller than a normal trade, this way even if your hedge wasn’t necessary and the original trade does not move against you, it's likely that your hedge will still win, and you can just consider it a small scalp to further your profits on the original trade.
Doubles:
Besides minimizing loss, we also aim to maximize the potential gain. When a second signal prints off in the direction of the trade you are currently already in, the tool directs you to double your position size.
The signal for doubling is a label with “2x” written inside.
The logic here is similar to hedging but in the opposite way. Just as a signal in the opposite direction creates uncertainty, a signal in the same direction indicates more certainty hence doubling your position size.
Example: If you are currently in a long position and you get a second long signal, you would then double your existing position since two long signals printing off before the first one has a chance to play out indicates a stronger chance of movement in the intended direction of your trade.
User Inputs
Upon opening the tools settings tab, you will find all the user inputs which can then be modified to fit your desired strategy. In this section of our guides, you will find individual explanations and use cases for each input so you can correctly use them to your best advantage.
Strategy Tracker Table:
By ticking this input on, the strategy tracker table will be visible to the user. (Default is on)
Indicator 1 Greater Than: Long:
By ticking this input on, you are adding a condition the script will then look for in order to take a long. (Default is on)
This condition is that an average of indicator 1, which searches for momentum, must fall above a certain level, which is determined in the next input.
The purpose of this is to ensure that the average momentum is not too low because this would indicate prolonged downwards movement on the timeframe of the market being observed, making a long position riskier.
Indicator 1 Greater Than Input: Long:
This input correlates to the previous input directly above.
If Indicator 1 Greater Than: Long is ticked on, then one of the conditions in order to take a long position will be that the average of indicator 1 must fall above the level which you set in this input.
max level 100, min level 0
Indicator 1 Less Than: Long
By ticking this input on, you are adding a condition the script will then look for in order to take a long position. (Default is on)
This condition is that an average of indicator 1, which searches for momentum, must fall below a certain level, which is determined in the next input.
The purpose of this is to ensure that the average momentum is not too high, because this would indicate a prior significant upwards movement or trend on the timeframe of the market being observed.
Taking a long position while the average momentum is at higher levels exposes the risk of longing as the market has started to pull back from a peak or when the market has just reached a peak.
Indicator 1 Less Than Input: Long
This input correlates to the previous input directly above.
If Indicator 1 Less Than: Long is ticked on, then one of the conditions in order to take a long position will be that the average of indicator 1 must fall below the level which you set in this input.
max level 100, min level 0
Indicator 1 Greater Than: Short
By ticking this input on, you are adding a condition the script will then look for in order to take a short. (Default is on)
This condition is that an average of indicator 1, which searches for momentum, must fall above a certain level, which is determined in the next input.
The purpose of this is to ensure that the average momentum is not too low because this would indicate prolonged downwards movement or trend on the timeframe of the market being observed.
Taking a short position while the average momentum is at lower levels exposes the risk of shorting as the market has started to recover from a bottom or when the market has just reached a bottom.
Indicator 1 Greater Than Input: Short
This input correlates to the previous input directly above.
If Indicator 1 Greater Than: Short is ticked on, then one of the conditions in order to take a short position will be that the average of indicator 1 must fall above the level which you set in this input.
max level 100, min level 0
Indicator 1 Less Than: Short
By ticking this input on, you are adding a condition the script will then look for in order to take a short position. (Default is on)
This condition is that an average of indicator 1, which searches for momentum, must fall below a certain level, which is determined in the next input.
The purpose of this is to ensure that the average momentum is not too high, because this would indicate a prior significant upwards movement or trend on the timeframe of the market being observed.
Taking a short position while the average momentum is at higher levels exposes the risk of shorting as the market is currently in a strong uptrend.
Indicator 1 Less Than: Short
This input correlates to the previous input directly above.
If Indicator 1 Less Than: Short is ticked on, then one of the conditions in order to take a short position will be that the average of indicator 1 must fall below the level which you set in this input.
max level 100, min level 0
Summary of Input Group: Indicator 1 Greater/Less Than Long/Short
This grouping of inputs is best used as a filter of sorts, much like many of the other inputs which are also essentially filters of the market to find areas ripe for trade. Specifically, however, this group of inputs is especially powerful because if used correctly, it can specify a range for the average momentum to fall in when looking for either long or short trades. Think of it like a sweet spot where the average is not too high nor too low. In combination with the numerous other inputs which will shortly be explained, this sweet spot can be a great indication. Keep in mind that once you find a working range, this will not last forever. Conditions in the market are ever changing and as such your inputs, in this case the range the average momentum must fall in, will also need to change with the market conditions.
Bars Since Crossover:
This input simply describes a crossover of the momentum indicator (indicator 1) and its average.
In the category How does it work? Two main factors are discussed, the first being directional momentum to determine when an upwards move might happen. The crossover correlated to this input is the directional momentum as mentioned earlier.
As also mentioned in How does it work? The second factor is a confirmation of the desired upwards move. This confirmation is a crossover of the current price and indicator 2 which will be further addressed later on.
What's important to understand about the two key factors at play in regard to Bars Since Crossover is that this input is determining a condition which looks for a certain number of bars prior to the confirmation of indicator 2 which the crossover of momentum and its average has happened on indicator 1.
Example: Bars Since Crossover input is set to 10. This means that the crossover of momentum and its average from indicator 1 must be within 10 bars prior to the confirmation from indicator 2. If this happens then this condition is met for a long position.
Bars Since Crossunder:
This input simply describes a crossunder of the momentum indicator (indicator 1) and its average.
In the category How does it work? Two main factors are discussed, the first being directional momentum to determine when a downwards move might happen. The crossunder correlated to this input is the directional momentum as mentioned earlier.
As also mentioned in How does it work? The second factor is a confirmation of the desired downwards move. This confirmation is a crossunder of the current price and indicator 2 which will be further addressed later on.
What's important to understand about the two key factors at play in regard to Bars Since Crossunder is that this input is determining a condition which looks for a certain number of bars prior to the confirmation of indicator 2 which the crossunder of momentum and its average has happened on indicator 1.
Example: Bars Since Crossunder input is set to 10. This means that the crossunder of momentum and its average from indicator 1 must be within 10 bars prior to the confirmation from indicator 2. If this happens then this condition is met for a short position.
Summary of Input Group: Bars Since Crossover/Crossunder
These two inputs can have a large effect on the types of trades being taken and the risk which your strategy opens up to. The idea is that in order for the two key factors described in How does it work? to be correlated and therefore indicate a strong directional move, the two events must happen within a somewhat small period of time. If the period of time between the two events taking place is too large, then it's riskier for your strategy due to a delay in directional momentum and the necessary confirmation. It's important to note that this “small period of time” is relative to the security you're trading and the timeframe its being trades on. Small could mean 5 bars in some cases or 20 bars in others, this is why our custom back tester exists. So that the process of optimization on different securities and different timeframes is smooth and only requires adjustments to inputs then your own analysis of the back test results.
Indicator 1 Input Long
Defines how strong the upwards momentum needs to be in order to take a long position.
When optimizing your strategy, this input is likely to have some of the most effect on when the script takes a long position.
The reasoning for this is because the level you set for this input is the level which indicator 1 must close above following the crossover of its average.
Example: Indicator 1 Input Long set to 50, this means that when the momentum crosses over its average from indicator 1, upon the close of this crossover the momentum must be above the level 50 in order for this condition to be met to take a long position.
The higher the level, the stronger the upwards momentum must be, and therefore by using higher levels for this input, the script will search for stronger directional moves leaving less chance for the trade to move against you.
Indicator 1 Input Short
Defines how strong the downwards momentum needs to be in order to take a short position.
When optimizing your strategy, this input is likely to have some of the most effect on when the script takes a short position.
The reasoning for this is because the level you set for this input is the level which indicator 1 must close below following the crossunder of its average.
Example: Indicator 1 Input Short set to 40, this means that when the momentum crosses under its average from indicator 1, upon the close of this crossunder the momentum must be below the level 40 in order for this condition to be met to take a short position.
The lower the level, the stronger the downwards momentum must be, and therefore by using lower levels for this input, the script will search for stronger directional moves leaving less chance for the trade to move against you.
Summary of Input Group: Indicator 1 Input Long/Short
These two inputs are so important to your strategy because at the end of the day no matter how you set it up, it's still a momentum-based strategy. With that being said the level of momentum or the strength needed in order to take trades is of course going to be a key decider in the successfulness of the strategy. When optimizing these two inputs make sure to take into account what the overall market conditions are, meaning if it’s a bull market maybe make the momentum needed to take a long slightly less comparatively to the amount needed to take a short, in other words make long conditions less specific and short conditions more specific. Slight variations of this input can have very big effects, even changing it by 1 or 2 can make a major difference. In might even be good to consider starting optimization with these inputs and then work the rest of the strategy out from there. A lot could be said about these inputs and more docs will be added in order to further explain more strategy approaches revolving around them, for now don’t hesitate to ask any questions.
Indicator 2 Red
This input is used as a sort of chop filter at its base level, however if used correctly it can be a much broader filter for what areas of the market you want to trade in.
Indicator 2 shows as either red or green and is used as a confirmation when price crosses over it following the crossover of momentum and its average from indicator 1 to take a long position.
If ticked on, Indicator 2 Red states a condition in order for the script to take a long position. (Default is on)
The condition is that upon the crossover of the current price and Indicator 2, 10 bars ago indicator 2 must have been red.
The reason for this input is because the current color of indicator 2 upon the crossover must also be red. However, this condition is hard coded in and cannot be changed by any input.
This is because the type of trade being targeted is that of a type of reversal or continuation.
If indicator 2 showed green 10 bars ago and is currently red this would indicate that a top was just reached, and price is reversing downwards making this not a good area to take a long.
Another scenario if indicator 2 showed green 10 bars ago and is currently red is that there is currently a sideways trend going on or otherwise known as chop, also not an ideal area to take a long
However, if 10 bars ago indicator 2 was red and it's currently red this would indicate a more prolonged pullback.
If all conditions are met and we know that price has been pulling back, now we can enter a long with more knowledge pointing to price reversing upwards from a downwards trend, or continuing its upwards trend after a pullback.
Indicator 2 Green
This input is used as a sort of chop filter at its base level, however if used correctly it can be a much broader filter for what areas of the market you want to trade in.
Indicator 2 shows as either red or green and is used as a confirmation when price crosses under it following the crossunder of momentum and its average from indicator 1 to take a short position.
If ticked on, Indicator 2 Green states a condition in order for the script to take a short position. (Default is on)
The condition is that upon the crossunder of the current price and Indicator 2, 10 bars ago indicator 2 must have been green.
The reason for this input is because the current color of indicator 2 upon the crossunder must also be green. However, this condition is hard coded in and cannot be changed by any input.
This is because the type of trade being targeted is that of a type of reversal or continuation.
If indicator 2 showed red 10 bars ago and is currently green this would indicate that a bottom was just reached, and price is reversing upwards making this not a good area to take a short.
Another scenario if indicator 2 showed red 10 bars ago and is currently green is that there is currently a sideways trend going on or otherwise known as chop, also not an ideal area to take a short.
However, if 10 bars ago indicator 2 was green and it's currently green this would indicate a more prolonged upwards movement.
If all conditions are met and we know that price has been moving up, now we can enter a short with more knowledge pointing to price reversing downwards from an upwards trend, or continuing its downwards trend after a bounce up.
Summary of Input Group: Indicator 2 Red/Green
Similar to Indicator 1 Greater/Less Than Long/Short, the goal of these inputs is to try to get a picture of what the previous recent market has been doing. By getting this picture it's easier to find different areas of the market more ideal for trades. Different from Indicator 1 Greater/Less Than Long/Short though, Indicator 2 Red/Green is directly correlated to the price action in the market rather than the momentum. By switching these on or off you are setting more or less specific conditions for taking trades. Some markets require this extra condition to lower your risk in your strategy, however others may not.
Pivot Low
This input is used to define the number of bars the script will look back to grab a pivot low when taking a long position.
This pivot low is then used to set the stop loss when entering a long position.
This input is very important and optimizing it correctly can be extremely crucial to your strategies success.
The Strategy Developer tool uses a 1:1 risk to reward ratio when setting your first take profit point, so when the script looks back to get a pivot low based on the input you set, it will then set your first take profit at an equal ratio to the stop loss found from the pivot low.
The goal in optimizing this input is to give enough lookback to find real pivot points where price has reversed off of, but not to give too much lookback where its grabbing previous pivot points unrelated to the current move of momentum the script is giving a long signal from.
Consider the type of trades you're looking for in your strategy and what timeframe you are trying to trade on.
Longer swing trades which aim to catch bigger moves in the market, possibly on higher time frames, may require a further lookback in order to get your take profits in the correct positioning to catch the desired move, and not exit early before the trade has fully played out.
Shorter scalp trades may aim to catch smaller moves and therefore you don’t want to allow for too much risk by having a large stop loss and large take profits as a result.
Pivot Low 2
Pivot low 2 can be thought of as a backup lookback in order to get the correct pivot low.
In an input which will be discussed shortly called Pivot Low Minimum, you can set a minimum percentage for your pivot low to be, if the pivot low does not meet the minimum then the script will look to Pivot Low 2’s input to use as a bar lookback in order to get the correct pivot low.
This input is used because you might find a Pivot Low input that works well for the majority of the trades in your back tested strategy, however, there will always be outliers and when this Pivot Low input falls short of getting the correct level to put your stop losses at, Pivot Low 2 is used.
Pivot Low 2’s input should always be higher than Pivot Low’s input, that way you can allow the script to look back further in time to find the correct level when the minimum is not met.
Pivot High
This input is used to define the number of bars the script will look back to grab a pivot high when taking a short position.
This pivot high is then used to set the stop loss when entering a short position.
This input is very important and optimizing it correctly can be extremely crucial to your strategies success.
The Strategy Developer tool uses a 1:1 risk to reward ratio when setting your first take profit point, so when the script looks back to get a pivot high based on the input you set, it will then set your first take profit at an equal ratio to the stop loss found from the pivot high.
The goal in optimizing this input is to give enough lookback to find real pivot points where price has reversed off of, but not to give too much lookback where its grabbing previous pivot points unrelated to the current move of momentum the script is giving a short signal from.
Consider the type of trades you're looking for in your strategy and what timeframe you are trying to trade on.
Longer swing trades which aim to catch bigger moves in the market, possibly on higher time frames, may require a further lookback in order to get your take profits in the correct positioning to catch the desired move, and not exit early before the trade has fully played out.
Shorter scalp trades may aim to catch smaller moves and therefore you don’t want to allow for too much risk by having a large stop loss and large take profits as a result.
Pivot High 2
Pivot high 2 can be thought of as a backup lookback in order to get the correct pivot high.
In an input which will be discussed shortly called Pivot High Minimum, you can set a minimum percentage for your pivot high to be, if the pivot high does not meet the minimum then the script will look to Pivot High 2’s input to use as a bar lookback in order to get the correct pivot high.
This input is used because you might find a Pivot High input that works well for the majority of the trades in your back tested strategy, however, there will always be outliers and when this Pivot High input falls short of getting the correct level to put your stop losses at, Pivot High 2 is used.
Pivot High 2’s input should always be higher than Pivot High’s input, that way you can allow the script to look back further in time to find the correct level when the minimum is not met.
Pivot Low Risk Tolerance
This input is very important in managing the risk associated with your strategy.
Pivot Low Risk Tolerance is defining a maximum percentage the pivot low can be away from your entry.
Since the pivot low that’s found is assigned to your stop loss and directly affects the placement of your take profits when taking a long position, making sure the pivot low isn’t too far down is crucial.
Depending on the types of trades you're aiming to take, the timeframe you choose to trade on, and the leverage you use in your strategy, you may want to assign a higher risk tolerance or a lower one.
Example: Pivot Low Risk Tolerance input set to 3, this means that when all other conditions are met in order to take a long position, when searching for the pivot low in order to set a stop loss, if the script finds the pivot low is greater than 3% away from the entry point, it will not take the trade.
Pivot High Risk Tolerance
This input is very important in managing the risk associated with your strategy.
Pivot High Risk Tolerance is defining a maximum percentage the pivot high can be away from your entry.
Since the pivot high that’s found is assigned to your stop loss and directly affects the placement of your take profits when taking a short position, making sure the pivot high isn’t too far up is crucial.
Depending on the types of trades you're aiming to take, the timeframe you choose to trade on, and the leverage you use in your strategy, you may want to assign a higher risk tolerance or a lower one.
Example: Pivot High Risk Tolerance input set to 3, this means that when all other conditions are met in order to take a short position, when searching for the pivot high in order to set a stop loss, if the script finds the pivot high is greater than 3% away from the entry point, it will not take the trade.
Pivot Low Minimum
Sometimes when searching for the pivot low, the script's defined lookback may not be enough to find the proper pivot point.
This can cause improper placement of stop losses and take profits and may cause trades to be exited early before they can fully play out in your favor.
Pivot Low Minimum is an input used to combat this problem, when the script finds a pivot low that does not meet the minimum percentage away from the entry point, it will then turn to Pivot Low 2 input in order to gain a further lookback and grab the correct pivot point to set your stop loss and take profits with.
When reading and setting this input, understand that setting it to 1 means there is no minimum, setting it to 0.9 would mean the minimum is a 10% difference between the pivot low and your entry point.
Think of it in terms of decimals and their equivalent percentage, 0.1 is equal to 10%, 0.01 is equal to 1%.
Whatever percentage you want to set for a minimum, convert it to a decimal, then simply subtract it from 1.
Example: Say you desire a 1.5% minimum pivot low and as a result an equivalent stop loss of 1.5% below your long entry and furthermore a take profit 1.5% above your long entry since the script uses a 1:1 ratio. Converting 1.5% to a decimal would give you 0.015, then subtracting it from 1 would give you 0.985, this would be the input assigned to Pivot Low Minimum.
Pivot High Minimum
Sometimes when searching for the pivot high, the script's defined lookback may not be enough to find the proper pivot point.
This can cause improper placement of stop losses and take profits and may cause trades to be exited early before they can fully play out in your favor.
Pivot High Minimum is an input used to combat this problem, when the script finds a pivot high that does not meet the minimum percentage away from the entry point, it will then turn to Pivot High 2 input in order to gain a further lookback and grab the correct pivot point to set your stop loss and take profits with.
When reading and setting this input, understand that setting it to 1 means there is no minimum, setting it to 0.9 would mean the minimum is a 10% difference between the pivot high and your entry point.
Think of it in terms of decimals and their equivalent percentage, 0.1 is equal to 10%, 0.01 is equal to 1%.
Whatever percentage you want to set for a minimum, convert it to a decimal, then simply subtract it from 1.
Example: Say you desire a 1.5% minimum pivot high and as a result an equivalent stop loss of 1.5% above your short entry and furthermore a take profit 1.5% below your short entry since the script uses a 1:1 ratio. Converting 1.5% to a decimal would give you 0.015, then subtracting it from 1 would give you 0.985, this would be the input assigned to Pivot High Minimum.
Summary of Input Group: Pivot Low/High - Pivot Low/High 2 – Pivot Low/High Risk Tolerance – Pivot Low/High Minimum
The first key takeaway from all these inputs is that your stop losses and take profits will be directly affected through optimizing any of them. The second key takeaway is that these inputs are crucial in managing the risk in your strategy, and while this has been said many times throughout the guide for various inputs, when it comes to stop losses and take profits it is especially true. Having a stop loss which is too high opens up the possibility for much bigger losses, and as a result your take profits will also be too high, minimizing the chance of any of them being hit. Having a stop loss which is too low increases the chance that your trade will get stopped out preemptively, before the trade can mature and move in your favor because remember that trades will not always move immediately in the intended direction, a good amount of patience is often involved in creating consistent successful trades and a successful strategy as such. On the same note, too low of a stop loss could also mean you are missing out on unrealized profit since your take profits are a direct result of the stop loss which is found. When optimizing your pivot low/high risk tolerance, think not about how much you are willing to lose on a single trade, but how much your portfolio can actually afford to lose not just on a single trade but multiple trades, sometimes even in a row. Obviously, the goal in creating a strategy is that you avoid losing trades and especially multiple in a row, however, there are many things that can’t be accounted for. The only way to manage this unaccounted risk is to use proper risk management and not open yourself up to big losses even in the worst most unlikely scenarios. Even if you don’t lose multiple trades in a row, ask yourself, could I afford to lose multiple trades with the risk tolerance I have set if everything were to go to $hit, (hopefully it would not), but in the off chance it did, instead of beating yourself up over what you did wrong, you’ll be patting yourself on the back for what you did right.
TP2-4 Long Placement
The first thing to understand about the take profit placement is that our system of stop losses and take profits uses a 1:1 risk to reward ratio for the first stop loss and first take profit.
This means that if your stop loss falls 2% below your long entry, your first take profit will be 2% above your long entry, hence 1:1.
As for take profits 2-4, they are just extensions of that ratio. This means that if TP2 Long Placement is set to 1.5, the ratio for your second take profit is 1:1.5.
Using the same percentage from the second bullet point being 2%, we can now gather that with a 1:1.5 ratio our second take profit would be at 3% above our long entry.
The same applies for the rest of the take profits, meaning whatever the take profit is set at regardless of which one, apply that number to the second placeholder of the ratio.
Example: First stop loss falls 2% below long entry. TP2 Long Placement input set to 1.5; risk to reward ratio is 1:1.5; corresponding percentage would be a 3% gain. TP3 Long Placement input set to 2; risk to reward ratio is 1:2; corresponding percentage would be a 4% gain. TP4 Long Placement input set to 2.5; risk to reward ratio is 1:2.5; corresponding percentage would be a 5% gain.
The next key thing to understand about the trailing take profits system is the position size being sold at each take profit and therefore how the strategy tracker calculates your strategy's profit.
At the first take profit, 50% of your position is being calculated as sold, locking in good profits off the bat.
At TP2, 20% of your position is being calculated as sold, leaving a remaining 30% open to gain more profit.
At TP3, another 20% of your position is being calculated as sold, leaving 10% to collect any additional possible gains.
At TP4 the remaining 10% of your position is sold and the trade will be fully closed out.
SL2-4 Long Placement
Our system of trailing stop losses is completely similar to that of our trailing take profits.
Just like the trailing take profits, the inputs for stop losses 2-4 are also used as the second placeholders in the risk to reward ratio.
This may be confusing since generally stop losses are associated with a loss on your position, however, the only stop loss which results in a loss on your position is the first one, not stop losses 2-4.
This is because once your first take profit is hit on your long, your stop loss will automatically move up to the price equivalent to the ratio which you set using these inputs that lies in profit.
Example: Since your first take profit will always be at a 1:1 risk to reward ratio with your stop loss, your second take profit could be at a 1:0.8 ratio. So, to clarify, once your first take profit is hit at a 1:1, your original first stop loss will now be moved up in profits to just below your first take profit at a 1:0.8 risk to reward ratio. This only happens AFTER the first take profit is hit.
For stop losses 3 and 4, the same logic is true, once TP2 is hit, your second stop loss will now be moved up to the placement of SL3 which will fall somewhere below TP2. Once TP3 is hit, your third stop loss will now be moved up to the placement of SL4 which will fall somewhere below TP3. If stop loss 4 does not get hit, then the only thing left to happen is for TP4 to hit and the trade will fully close out.
The one major difference between our system of trailing stop losses and take profits is that no matter what stop loss is hit, the entire remainder of your position will be calculated as sold.
So, if your first take profit hits and sells 50% of your long position, but the trade does not continue upwards and moves down to your second stop loss, the remaining 50% of your position will be calculated as sold.
The same applies to SL3 and SL4, so at SL3 the remaining 30% of your position will be calculated as sold, and at SL4 the remaining 10% will be calculated as sold.
Your trailing stop loss placement is dependent on what types of trades you desire. For shorter scalps on smaller timeframes, it's recommended to place each stop loss just below each corresponding take profit for long trades.
This way you leave just enough room for the trade to continue upwards if there is enough momentum, but you don’t open yourself up to losing your unrealized profit if it does not make this continuation.
If you desire longer swing trades on higher timeframes, it might be a good idea to leave more room in between the take profit and corresponding stop loss.
This way you leave more room for the trade to mature and move in your favor since when trading longer moves, often they will not shoot straight up but rather have a series of small pullbacks throughout the more general upwards trend.
Note that when a long trade is first entered the only stop loss and take profit in play are your original stop loss found by the pivot low which would result in a loss, and the first take profit at a 1:1 risk to reward ratio from that pivot low.
TP2-4 Short Placement
The first thing to understand about the take profit placement is that our system of stop losses and take profits uses a 1:1 risk to reward ratio for the first stop loss and first take profit.
This means that if your stop loss falls 2% above your short entry, your first take profit will be 2% below your short entry, hence, 1:1.
As for take profits 2-4, they are just extensions of that ratio. This means that if TP2 Short Placement is set to 1.5, the ratio for your second take profit is 1:1.5.
Using the same percentage from the second bullet point being 2%, we can now gather that with a 1:1.5 ratio our second take profit would be at 3% below our short entry.
The same applies for the rest of the take profits, meaning whatever the take profit is set at regardless of which one, apply that number to the second placeholder of the ratio.
Example: First stop loss falls 2% above short entry. TP2 Short Placement input set to 1.5; risk to reward ratio is 1:1.5; corresponding percentage would be a 3% gain. TP3 Short Placement input set to 2; risk to reward ratio is 1:2; corresponding percentage would be a 4% gain. TP4 Short Placement input set to 2.5; risk to reward ratio is 1:2.5; corresponding percentage would be a 5% gain.
The next key thing to understand about the trailing take profits system is the position size being sold at each take profit and therefore how the strategy tracker calculates your strategy's profit.
At the first take profit, 50% of your position is being calculated as sold, locking in good profits off the bat.
At TP2, 20% of your position is being calculated as sold, leaving a remaining 30% open to gain more profit.
At TP3, another 20% of your position is being calculated as sold, leaving 10% to collect any additional possible gains.
At TP4 the remaining 10% of your position is sold and the trade will be fully closed out.
SL2-4 Short Placement
Our system of trailing stop losses is completely similar to that of our trailing take profits.
Just like the trailing take profits, the inputs for stop losses 2-4 are also used as the second placeholders in the risk to reward ratio.
This may be confusing since generally stop losses are associated with a loss on your position, however, the only stop loss which results in a loss on your position is the first one, not stop losses 2-4.
This is because once your first take profit is hit on your short, your stop loss will automatically move down to the price equivalent to the ratio which you set using these inputs that lies in profit.
Example: Since your first take profit will always be at a 1:1 risk to reward ratio with your stop loss, your second take profit could be at a 1:0.8 ratio. So, to clarify, once your first take profit is hit at a 1:1, your original first stop loss will now be moved down in profits to just below your first take profit at a 1:0.8 risk to reward ratio. This only happens AFTER the first take profit is hit.
For stop losses 3 and 4, the same logic is true, once TP2 is hit, your second stop loss will now be moved down to the placement of SL3 which will fall somewhere above TP2. Once TP3 is hit, your third stop loss will now be moved down to the placement of SL4 which will fall somewhere above TP3. If stop loss 4 does not get hit, then the only thing left to happen is for TP4 to hit and the trade will fully close out.
The one major difference between our system of trailing stop losses and take profits is that no matter what stop loss is hit, the entire remainder of your position will be calculated as sold.
So, if your first take profit hits and sells 50% of your short position, but the trade does not continue downwards and moves up to your second stop loss, the remaining 50% of your position will be calculated as sold.
The same applies to SL3 and SL4, so at SL3 the remaining 30% of your position will be calculated as sold, and at SL4 the remaining 10% will be calculated as sold.
Your trailing stop loss placement is dependent on what types of trades you desire. For shorter scalps on smaller timeframes, it's recommended to place each stop loss just above each corresponding take profit for short trades.
This way you leave just enough room for the trade to continue downwards if there is enough momentum, but you don’t open yourself up to losing your unrealized profit if it does not make this continuation.
If you desire longer swing trades on higher timeframes, it might be a good idea to leave more room in between the take profit and corresponding stop loss.
This way you leave more room for the trade to mature and move in your favor since when trading longer moves, often they will not shoot straight down but rather have a series of small bounces throughout the more general downwards trend.
Note that when a short trade is first entered the only stop loss and take profit in play are your original stop loss found by the pivot high which would result in a loss, and the first take profit at a 1:1 risk to reward ratio from that pivot high.
Summary of Take Profit/Stop Loss Placement:
Correctly placed take profits and stop losses are essential in having a successful strategy and proper risk management. With that being said there are also many ways in which to use this system. Deciding how to set them up is really just a matter of determining the trading style you aim to succeed with. Once this has been determined, the placement of take profits and stop losses should be easier to configure. However, if there is any confusion on either of these topics as the ratios and corresponding TP/SL can get confusing, please do not hesitate to ask further questions in our discord!
Leverage Long
Leverage Long input simply defines the leverage used in your long positions, and is used in calculating the profit in Strategy Tracker
A rundown of risk associated with using leverage will not be given here since it should assume that if you're using leverage, you should already understand the risks.
If you are not using any leverage, then set Leverage Long input to 1.
Long Position Size
This input defines the position size you are using in your long trades.
This input is also used in calculating profit in Strategy Tracker.
Long Hedge Position Size
This input is used to define the position size of long hedge positions.
This input is also used in calculating profit in Strategy Tracker.
Important: Your Long Hedge Position Size should always be half of your Long Position Size for accurate profit calculation.
Double Long Position Size
This input is used to define the position size when in a double long.
This input is also used in calculating profit in Strategy Tracker
Important: Your Double Long Position Size should always be double your Long Position Size for accurate profit calculation.
Short Position Size
This input defines the position size you are using in your short trades.
This input is also used in calculating profit in Strategy Tracker.
Short Hedge Position Size
This input is used to define the position size of short hedge positions.
This input is also used in calculating profit in Strategy Tracker.
Important: Your Short Hedge Position Size should always be half of your Short Position Size for accurate profit calculation.
Double Short Position Size
This input is used to define the position size when in a double short.
This input is also used in calculating profit in Strategy Tracker
Important: Your Double Short Position Size should always be double your Short Position Size for accurate profit calculation.
A Message From the Developer PLEASE READ!!!
If you have made it this far in the guide, I applaud you and thank you for sticking with it as I know there is a lot of information here! This is not an exaggeration when I say there are hundreds of millions of possible variations that could be applied throughout all the inputs which is why I much prefer to call this a tool rather than an algorithm. Algorithm is a loaded word in my opinion as it comes with an implication of guarantee in the trades being made. This is not meant to discourage anybody from taking trades based off the tool which is also why I provided the option for automated alerts which through third party software can turn into automated trades; if you have the confidence in your strategy by all means I encourage you to trade it, automated or not. Just please understand that it's highly recommended to also apply your own knowledge and analysis before taking a trade as historical back testing data has its limitations and cannot always account for current market conditions. The real applicability does not fall in what the back tester window is saying you would have made or how accurate your strategy would have been, it's within the sheer number of markets and scenarios this tool can be used in and the information you can get which a human just can’t comprehend all at once; its literally endless. I urge all of you to be creative and think outside the box about what you can do with such a powerful tool at your fingertips. After all this is the reason why so many inputs were provided. Another main goal of this project was to give users a better understanding of risk management. It can be hard to manage your risk when it’s all kept in your head, but when you can modify your strategy to better manage your risk by simply optimizing a few inputs, it’s a lot easier to comprehend and actually apply when trading. The last thing I want to say is have fun working through the possible learning curve in using this tool, it may be a process but enjoy it because the one thing I can guarantee is that you will come out the other side a better trader than before!
Cracking Cryptocurrency - Bottom Feeder Strategy TesterBottom Feeder - Strategy Tester
The Bottom Feeder is designed to algorithmically detect significantly oversold conditions in price that represent profitable buying opportunities. Combining this with it’s unique Stop and Target System, the Bottom Feeder is designed to return consistent return with minimal draw down. Whether used as a Market Bottom Detector or as a system for executing safe, profitable mean reversion trades, the Bottom Feeder is a powerful tool in any trader’s arsenal.
Bottom Feeder was designed to be used on BTCUSD, however it is also effective on other USD/USDT pairs. One will have to check the individual pair they wish to trade with the Strategy Tester to simulate performance.
Strategy displayed is from 2018-2021 on **Conservative Mode** with Percent of Equity (30%) enabled.
Options
Let’s go through the input options one by one, so that you are able to comfortably navigate all that this indicator has to offer. The link below will display a picture of the layout of the settings for your convenience.
For the sake of simplicity, let’s note now that all settings marked **Conservative Mode** will not work in Aggressive Mode.
Mode : Determines how aggressively Bottom Feeder generates a buy signal. In Conservative Mode, trades can only be opened once per candle and the stop and target will update as new signals appear. In Aggressive Mode, a separate trade is opened each time Bottom Feeder signals, which may be multiple times within one Daily candle.
Position Sizing Strategy : Determines what Risk Management system you will deploy when trading Bottom Feeder. Your options are “Percent of Equity” and “Distance to Stop Loss”. If Percent of Equity is selected, a trade size will be equal to a percentage of your equity, pursuant to the value in the ‘Percent of Equity’ box. If Distance to Stop Loss is selected, then your Position Size will be determined based off the distance to your stop loss and the value in the ‘Risk Percentage’ box.
Percent Of Equity : Determines what percentage of your equity will be allocated to each trade when ‘Position Sizing Strategy’ is enabled.
Risk Percentage : Determines the size of each trade if ‘Distance to Stop Loss’ strategy is enabled. This value reflects what percent of your account you will lose per trade if the trade hits your stop loss.
Plot Target and Stop Loss : Toggles on/off the visualized take profit and stop losses on the chart.
**Conservative Mode** TP Multiplier : This is an input box, it requires a float value. That is, it can accept either a whole number integer or a number with a decimal. This number will determine your Take Profit target. It will take whatever number is entered into this box and multiply the Average True Range against it to determine your Take Profit.
**Conservative Mode** SL Multiplier : See above - this will modify your Stop Loss Value.
**Conservative Mode** Average or Median True Range : This is a drop-down option, the two options are Average True Range or Median True Range. If Average True Range is selected, then this indicator will use the Average True Range calculation, that is, the average of a historical set of True Range values to determine the Average True Range value for Target and Stop Loss calculation. If Median True Range is selected, it will not take an average and will instead take the Median value of your historical look back period.
**Conservative Mode** True Range Length : This is an input that requires an integer. This will represent your historical lookback period for Average/Median True Range calculation.
**Conservative Mode** True Range Smoothing : This is a drop-down with the following options: Exponential Moving Average ( EMA ), Simple Moving Average ( SMA ), Weighted Moving Average ( WMA ), Relative Moving Average (RMA). This will determine the smoothing type for calculating the Average True Range if it is selected. Note: if Median True Range is selected above, this option will not have any effect as there is no smoothing for a Median value.
**Conservative Mode** Custom True Range Value? : This is a true/false option that is false by default. If enabled, it will override the Average/Median True Range calculation in favor of a users custom True Range value to be input below.
**Conservative Mode** Custom True Range Value : This is an input box that requires a float value. If Custom True Range is enabled this is where a user will input their desired custom True Range value for Target and Stop Loss calculation.
From Month/Day/Year to Month/Day/Year : This sets the Time Frame of your backtest for the Bottom Feeder Strategy. It will run FROM the date selected TO the date selected.
Stop and Target Description
Because Bottom Feeder is designed only to scalp the various market bottoms that can appear over time in the market and not to identify trends or to trade ranges, it’s imperative that the indicator notify us not just to when to enter our trades, but when to exit! In the service of that, CC Bottom Feeder has a built in Stop and Target system that tracks and displays the stop loss and take profit levels of each individual open trade, whether in Aggressive or Conservative Mode.
Conservative Mode Targeting: In Conservative Mode, Bottom Feeder signals are aggregated into a compound trade. The signal will appear as a green label pointing up below a candle, and will appear upon a candle close. If Bottom Feeder then generates another signal the stop loss and target price will be updated. The process will continue until the aggregated trade completes in either direction. On a trade with multiple signals, a larger position is slowly entered into upon each buy signal.
Aggressive Mode Targeting: In Aggressive Mode, Bottom Feeder signals are individually displayed as they are generated, regardless of how many signals are generated on any single candle. If Bottom Feeder continues to signal, each individual open trade will have their own stop loss and target that will be displayed on the chart until the individual trade completes in either direction. As opposed to a large compound position, aggressive mode represents a higher number of independent signals with their own stop and target levels.
Stop losses and targets are designed to be hard, not soft. That is, they are intended to be stop market orders, not mental stop losses. If price wicks through the target or stop, it will activate.
Recovery StrategyDescription:
The Recovery Strategy is a long-only trading system designed to capitalize on significant price drops from recent highs. It enters a position when the price falls 10% or more from the highest high over a 6-month lookback period and adds positions on further 2% drops, up to a maximum of 5 positions. Each trade is held for 6 months before exiting, regardless of profit or loss. The strategy uses margin to amplify position sizes, with a default leverage of 5:1 (20% margin requirement). All key parameters are customizable via inputs, allowing flexibility for different assets and timeframes. Visual markers indicate recent highs for reference.
How It Works:
Entry: Buys when the closing price drops 10% or more from the recent high (highest high in the lookback period, default 126 bars ~6 months). If already in a position, additional buys occur on further 2% drops (e.g., 12%, 14%, 16%, 18%), up to 5 positions (pyramiding).
Exit: Each trade exits after its own holding period (default 126 bars ~6 months), regardless of profit or loss. No stop loss or take-profit is used.
Margin: Uses leverage to control larger positions (default 20% margin, 5:1 leverage). The order size is a percentage of equity (default 100%), adjustable via inputs.
Visualization: Displays blue markers (without text) at new recent highs to highlight reference levels.
Inputs:
Lookback Period for High Peak (bars): Number of bars to look back for the recent high (default: 126, ~6 months on daily charts).
Initial Drop Percentage to Buy (%): Percentage drop from recent high to trigger the first buy (default: 10.0%).
Additional Drop Percentage to Buy (%): Further drop percentage to add positions (default: 2.0%).
Holding Period (bars): Number of bars to hold each position before selling (default: 126, ~6 months).
Order Size (% of Equity): Percentage of equity used per trade (default: 100%).
Margin for Long Positions (%): Percentage of position value covered by equity (default: 20%, equivalent to 5:1 leverage).
Usage:
Timeframe: Designed for daily charts (126 bars ~6 months). Adjust Lookback Period and Holding Period for other timeframes (e.g., 1008 hours for hourly charts, assuming 8 trading hours/day).
Assets: Suitable for stocks, ETFs, or other assets with significant price volatility. Test thoroughly on your chosen asset.
Settings: Customize inputs in the strategy settings to match your risk tolerance and market conditions. For example, lower Margin for Long Positions (e.g., to 10% for 10:1 leverage) to increase position sizes, but beware of higher risk.
Backtesting: Use TradingView’s Strategy Tester to evaluate performance. Check the “List of Trades” for skipped trades due to insufficient equity or margin requirements.
Risks and Considerations:
No Stop Loss: The strategy holds trades for the full 6 months without a stop loss, exposing it to significant drawdowns in prolonged downtrends.
Margin Risk: Leverage (default 5:1) amplifies both profits and losses. Ensure sufficient equity to cover margin requirements to avoid skipped trades or simulated margin calls.
Pyramiding: Up to 5 positions can be open simultaneously, increasing exposure. Adjust pyramiding in the code if fewer positions are desired (e.g., change to pyramiding=3).
Market Conditions: Performance depends on price drops and recoveries. Test on historical data to assess effectiveness in your market.
Broker Emulator: TradingView’s paper trading simulates margin but does not execute real margin trading. Results may differ in live trading due to broker-specific margin rules.
How to Use:
Add the strategy to your chart in TradingView.
Adjust input parameters in the settings panel to suit your asset, timeframe, and risk preferences.
Run a backtest in the Strategy Tester to evaluate performance.
Monitor open positions and margin levels in the Trading Panel to manage risk.
For live trading, consult your broker’s margin requirements and leverage policies, as TradingView’s simulation may not match real-world conditions.
Disclaimer:
This strategy is for educational purposes only and does not constitute financial advice. Trading involves significant risk, especially with leverage and no stop loss. Always backtest thoroughly and consult a financial advisor before using any strategy in live trading.
Game Theory Trading StrategyGame Theory Trading Strategy: Explanation and Working Logic
This Pine Script (version 5) code implements a trading strategy named "Game Theory Trading Strategy" in TradingView. Unlike the previous indicator, this is a full-fledged strategy with automated entry/exit rules, risk management, and backtesting capabilities. It uses Game Theory principles to analyze market behavior, focusing on herd behavior, institutional flows, liquidity traps, and Nash equilibrium to generate buy (long) and sell (short) signals. Below, I'll explain the strategy's purpose, working logic, key components, and usage tips in detail.
1. General Description
Purpose: The strategy identifies high-probability trading opportunities by combining Game Theory concepts (herd behavior, contrarian signals, Nash equilibrium) with technical analysis (RSI, volume, momentum). It aims to exploit market inefficiencies caused by retail herd behavior, institutional flows, and liquidity traps. The strategy is designed for automated trading with defined risk management (stop-loss/take-profit) and position sizing based on market conditions.
Key Features:
Herd Behavior Detection: Identifies retail panic buying/selling using RSI and volume spikes.
Liquidity Traps: Detects stop-loss hunting zones where price breaks recent highs/lows but reverses.
Institutional Flow Analysis: Tracks high-volume institutional activity via Accumulation/Distribution and volume spikes.
Nash Equilibrium: Uses statistical price bands to assess whether the market is in equilibrium or deviated (overbought/oversold).
Risk Management: Configurable stop-loss (SL) and take-profit (TP) percentages, dynamic position sizing based on Game Theory (minimax principle).
Visualization: Displays Nash bands, signals, background colors, and two tables (Game Theory status and backtest results).
Backtesting: Tracks performance metrics like win rate, profit factor, max drawdown, and Sharpe ratio.
Strategy Settings:
Initial capital: $10,000.
Pyramiding: Up to 3 positions.
Position size: 10% of equity (default_qty_value=10).
Configurable inputs for RSI, volume, liquidity, institutional flow, Nash equilibrium, and risk management.
Warning: This is a strategy, not just an indicator. It executes trades automatically in TradingView's Strategy Tester. Always backtest thoroughly and use proper risk management before live trading.
2. Working Logic (Step by Step)
The strategy processes each bar (candle) to generate signals, manage positions, and update performance metrics. Here's how it works:
a. Input Parameters
The inputs are grouped for clarity:
Herd Behavior (🐑):
RSI Period (14): For overbought/oversold detection.
Volume MA Period (20): To calculate average volume for spike detection.
Herd Threshold (2.0): Volume multiplier for detecting herd activity.
Liquidity Analysis (💧):
Liquidity Lookback (50): Bars to check for recent highs/lows.
Liquidity Sensitivity (1.5): Volume multiplier for trap detection.
Institutional Flow (🏦):
Institutional Volume Multiplier (2.5): For detecting large volume spikes.
Institutional MA Period (21): For Accumulation/Distribution smoothing.
Nash Equilibrium (⚖️):
Nash Period (100): For calculating price mean and standard deviation.
Nash Deviation (0.02): Multiplier for equilibrium bands.
Risk Management (🛡️):
Use Stop-Loss (true): Enables SL at 2% below/above entry price.
Use Take-Profit (true): Enables TP at 5% above/below entry price.
b. Herd Behavior Detection
RSI (14): Checks for extreme conditions:
Overbought: RSI > 70 (potential herd buying).
Oversold: RSI < 30 (potential herd selling).
Volume Spike: Volume > SMA(20) x 2.0 (herd_threshold).
Momentum: Price change over 10 bars (close - close ) compared to its SMA(20).
Herd Signals:
Herd Buying: RSI > 70 + volume spike + positive momentum = Retail buying frenzy (red background).
Herd Selling: RSI < 30 + volume spike + negative momentum = Retail selling panic (green background).
c. Liquidity Trap Detection
Recent Highs/Lows: Calculated over 50 bars (liquidity_lookback).
Psychological Levels: Nearest round numbers (e.g., $100, $110) as potential stop-loss zones.
Trap Conditions:
Up Trap: Price breaks recent high, closes below it, with a volume spike (volume > SMA x 1.5).
Down Trap: Price breaks recent low, closes above it, with a volume spike.
Visualization: Traps are marked with small red/green crosses above/below bars.
d. Institutional Flow Analysis
Volume Check: Volume > SMA(20) x 2.5 (inst_volume_mult) = Institutional activity.
Accumulation/Distribution (AD):
Formula: ((close - low) - (high - close)) / (high - low) * volume, cumulated over time.
Smoothed with SMA(21) (inst_ma_length).
Accumulation: AD > MA + high volume = Institutions buying.
Distribution: AD < MA + high volume = Institutions selling.
Smart Money Index: (close - open) / (high - low) * volume, smoothed with SMA(20). Positive = Smart money buying.
e. Nash Equilibrium
Calculation:
Price mean: SMA(100) (nash_period).
Standard deviation: stdev(100).
Upper Nash: Mean + StdDev x 0.02 (nash_deviation).
Lower Nash: Mean - StdDev x 0.02.
Conditions:
Near Equilibrium: Price between upper and lower Nash bands (stable market).
Above Nash: Price > upper band (overbought, sell potential).
Below Nash: Price < lower band (oversold, buy potential).
Visualization: Orange line (mean), red/green lines (upper/lower bands).
f. Game Theory Signals
The strategy generates three types of signals, combined into long/short triggers:
Contrarian Signals:
Buy: Herd selling + (accumulation or down trap) = Go against retail panic.
Sell: Herd buying + (distribution or up trap).
Momentum Signals:
Buy: Below Nash + positive smart money + no herd buying.
Sell: Above Nash + negative smart money + no herd selling.
Nash Reversion Signals:
Buy: Below Nash + rising close (close > close ) + volume > MA.
Sell: Above Nash + falling close + volume > MA.
Final Signals:
Long Signal: Contrarian buy OR momentum buy OR Nash reversion buy.
Short Signal: Contrarian sell OR momentum sell OR Nash reversion sell.
g. Position Management
Position Sizing (Minimax Principle):
Default: 1.0 (10% of equity).
In Nash equilibrium: Reduced to 0.5 (conservative).
During institutional volume: Increased to 1.5 (aggressive).
Entries:
Long: If long_signal is true and no existing long position (strategy.position_size <= 0).
Short: If short_signal is true and no existing short position (strategy.position_size >= 0).
Exits:
Stop-Loss: If use_sl=true, set at 2% below/above entry price.
Take-Profit: If use_tp=true, set at 5% above/below entry price.
Pyramiding: Up to 3 concurrent positions allowed.
h. Visualization
Nash Bands: Orange (mean), red (upper), green (lower).
Background Colors:
Herd buying: Red (90% transparency).
Herd selling: Green.
Institutional volume: Blue.
Signals:
Contrarian buy/sell: Green/red triangles below/above bars.
Liquidity traps: Red/green crosses above/below bars.
Tables:
Game Theory Table (Top-Right):
Herd Behavior: Buying frenzy, selling panic, or normal.
Institutional Flow: Accumulation, distribution, or neutral.
Nash Equilibrium: In equilibrium, above, or below.
Liquidity Status: Trap detected or safe.
Position Suggestion: Long (green), Short (red), or Wait (gray).
Backtest Table (Bottom-Right):
Total Trades: Number of closed trades.
Win Rate: Percentage of winning trades.
Net Profit/Loss: In USD, colored green/red.
Profit Factor: Gross profit / gross loss.
Max Drawdown: Peak-to-trough equity drop (%).
Win/Loss Trades: Number of winning/losing trades.
Risk/Reward Ratio: Simplified Sharpe ratio (returns / drawdown).
Avg Win/Loss Ratio: Average win per trade / average loss per trade.
Last Update: Current time.
i. Backtesting Metrics
Tracks:
Total trades, winning/losing trades.
Win rate (%).
Net profit ($).
Profit factor (gross profit / gross loss).
Max drawdown (%).
Simplified Sharpe ratio (returns / drawdown).
Average win/loss ratio.
Updates metrics on each closed trade.
Displays a label on the last bar with backtest period, total trades, win rate, and net profit.
j. Alerts
No explicit alertconditions defined, but you can add them for long_signal and short_signal (e.g., alertcondition(long_signal, "GT Long Entry", "Long Signal Detected!")).
Use TradingView's alert system with Strategy Tester outputs.
3. Usage Tips
Timeframe: Best for H1-D1 timeframes. Shorter frames (M1-M15) may produce noisy signals.
Settings:
Risk Management: Adjust sl_percent (e.g., 1% for volatile markets) and tp_percent (e.g., 3% for scalping).
Herd Threshold: Increase to 2.5 for stricter herd detection in choppy markets.
Liquidity Lookback: Reduce to 20 for faster markets (e.g., crypto).
Nash Period: Increase to 200 for longer-term analysis.
Backtesting:
Use TradingView's Strategy Tester to evaluate performance.
Check win rate (>50%), profit factor (>1.5), and max drawdown (<20%) for viability.
Test on different assets/timeframes to ensure robustness.
Live Trading:
Start with a demo account.
Combine with other indicators (e.g., EMAs, support/resistance) for confirmation.
Monitor liquidity traps and institutional flow for context.
Risk Management:
Always use SL/TP to limit losses.
Adjust position_size for risk tolerance (e.g., 5% of equity for conservative trading).
Avoid over-leveraging (pyramiding=3 can amplify risk).
Troubleshooting:
If no trades are executed, check signal conditions (e.g., lower herd_threshold or liquidity_sensitivity).
Ensure sufficient historical data for Nash and liquidity calculations.
If tables overlap, adjust position.top_right/bottom_right coordinates.
4. Key Differences from the Previous Indicator
Indicator vs. Strategy: The previous code was an indicator (VP + Game Theory Integrated Strategy) focused on visualization and alerts. This is a strategy with automated entries/exits and backtesting.
Volume Profile: Absent in this strategy, making it lighter but less focused on high-volume zones.
Wick Analysis: Not included here, unlike the previous indicator's heavy reliance on wick patterns.
Backtesting: This strategy includes detailed performance metrics and a backtest table, absent in the indicator.
Simpler Signals: Focuses on Game Theory signals (contrarian, momentum, Nash reversion) without the "Power/Ultra Power" hierarchy.
Risk Management: Explicit SL/TP and dynamic position sizing, not present in the indicator.
5. Conclusion
The "Game Theory Trading Strategy" is a sophisticated system leveraging herd behavior, institutional flows, liquidity traps, and Nash equilibrium to trade market inefficiencies. It’s designed for traders who understand Game Theory principles and want automated execution with robust risk management. However, it requires thorough backtesting and parameter optimization for specific markets (e.g., forex, crypto, stocks). The backtest table and visual aids make it easy to monitor performance, but always combine with other analysis tools and proper capital management.
If you need help with backtesting, adding alerts, or optimizing parameters, let me know!
Portfolio Tracker ARJO (V-01)Portfolio Tracker ARJO (V-01)
This indicator is a user-friendly portfolio tracking tool designed for TradingView charts. It overlays a customizable table on your chart to monitor up to 15 stocks or symbols in your portfolio. It calculates real-time metrics like current market price (CMP), gains/losses, and stoploss breaches, helping you stay on top of your investments without switching between multiple charts. The table uses color-coding for quick visual insights: green for profits, red for losses, and highlights breached stoplosses in red for alerts. It also shows portfolio-wide totals for overall performance.
Key Features
Supports up to 15 Symbols: Enter stock tickers (e.g., NSE:RELIANCE or BSE:TCS) with details like buy price, date, units, and stoploss.
Symbol: The stock ticker and description.
Buy Date: When you purchased it.
Units: Number of shares/units held.
Buy Price: Your entry price.
Stop Loss: Your set stoploss level (highlighted in red if breached by CMP).
CMP: Current market price (fetched from the chart's timeframe).
% Gain/Loss: Percentage change from buy price (color-coded: green for positive, red for negative).
Gain/Loss: Total monetary gain/loss based on units.
Optional Timeframe Columns: Toggle to show % change over 1 Week (1W), 1 Month (1M), 3 Months (3M), and 6 Months (6M) for historical performance.
Portfolio Summary: At the top of the table, see total % gain/loss and absolute gain/loss for your entire portfolio.
Visual Customizations: Adjust table position (e.g., Top Right), size, colors for positive/negative values, and intensity cutoff for gradients.
Benchmark Index-Based Header: The title row's background color reflects NIFTY's weekly trend (green if above 10-week SMA, red if below) for market context.
Benchmark Index-Based Header: The title row's background color reflects NIFTY's weekly trend (green if above 10-week SMA, red if below) for market context.
How to Use It: Step-by-Step Guide
Add the Indicator to Your Chart: Search for "Portfolio Tracker ARJO (V-01)" in TradingView's indicator library and add it to any chart (preferably Daily timeframe for accuracy).
Input Your Portfolio Symbols:
Open the indicator settings (gear icon).
In the "Symbol 1" to "Symbol 15" groups, fill in:
Symbol: Enter the ticker (e.g., NSE:INFY).
Year/Month/Day: Select your buy date (e.g., 2024-07-01).
Buy Price: Your purchase price per unit.
Stoploss: Your exit price if things go south.
Units: How many shares you own.
Only fill what you need—leave extras blank. The table auto-adjusts to show only entered symbols.
Customize the Table (Optional):
In "Table settings":
Choose position (e.g., Top Right) and size (% of chart).
Toggle "Show Timeframe Columns" to add 1W/1M/3M/6M performance.
In "Color settings":
Pick colors for positive (green) and negative (red) cells.
Set "Color intensity cutoff (%)" to control how strong the colors get (e.g., 10% means changes above 10% max out the color).
Interpret the Table on Your Chart:
The table appears overlaid—scan rows for each symbol's stats.
Look at colors: Greener = better gains; redder = bigger losses.
Check CMP cell: Red means stoploss breached—consider selling!
Portfolio Gain/Loss at the top gives a quick overall health check.
For Best Results:
Use on a Daily chart to avoid CMP errors (the script will warn if on Weekly/Monthly).
Refresh the chart or wait for a new bar if data doesn't update immediately.
For Indian stocks, prefix with NSE: or BSE: (e.g., BSE:RELIANCE).
This is for tracking only—not trading signals. Combine with your strategy.
If no symbols show, ensure inputs are valid (e.g., buy price > 0, valid date).
Finally, this tool makes it quite easy for beginners to track their portfolios, while also giving advanced traders powerful and customizable insights. I'd love to hear your feedback—happy trading!
Neuracap Gap AnalysisThe Neuracap Gap Analysis indicator is a comprehensive tool designed to identify and track price gaps, special candlestick patterns, and high-volume breakout signals. It combines multiple trading strategies into one powerful indicator for gap trading, pattern recognition, and momentum analysis.
🎯 What This Indicator Does
1. Gap Detection & Tracking
Automatically identifies price gaps (up and down)
Tracks gap fills with visual boxes that extend until closed
Manages gap history with customizable limits
Color-coded visualization (Green = Gap Up, Red = Gap Down)
2. Upside Tasuki Gap Pattern
Identifies the bullish continuation pattern
Colors candles yellow when pattern is detected
Confirms trend continuation signals
3. Episodic Pivot Detection
High-volume breakout identification
EMA filter ensures signals only in uptrends
Strong momentum confirmation
Fuchsia-colored candles with arrow markers
🔍 How to Use for Trading
📈 Gap Trading Strategy
Gap Up Trading:
Wait for gap up (green box appears)
Check volume - Higher volume = stronger signal
Entry options:
Aggressive: Enter at market open
Conservative: Wait for pullback to gap level
Stop loss: Below the gap fill level
Target: Previous resistance or 2:1 risk/reward
Gap Down Trading:
Identify gap down (red box appears)
Look for bounce opportunities
Entry: When price shows reversal signs
Stop: Below recent lows
Target: Gap fill level
💫 Tasuki Gap Strategy
Yellow candle indicates bullish continuation
Confirms uptrend is likely to continue
Entry: On next candle after pattern
Stop: Below the gap low
Target: Next resistance level
🚀 Episodic Pivot Strategy
Fuchsia candle + arrow = High probability breakout
All conditions met:
Price above EMA 20, 50, 200
High volume (2x+ average)
Strong price move (4%+)
Entry: At close or next open
Stop: Below EMA 20 or recent swing low
Target: Measured move or next resistance
📊 Reading the Visual Signals
Gap Boxes
🟢 Green Box: Gap up - potential bullish continuation
🔴 Red Box: Gap down - potential bounce or bearish continuation
Box extends until gap is filled
Box disappears when gap closes
Candle Colors
🟡 Yellow: Tasuki gap pattern (bullish continuation)
🟪 Fuchsia: Episodic pivot (high-volume breakout)
⬜ Normal: No special pattern detected
Arrows & Markers
⬆️ Triangle Arrow: Episodic pivot confirmation
💡 Trading Tips & Best Practices
✅ Do's
Combine with trend analysis - Trade gaps in direction of trend
Check volume - Higher volume = more reliable signals
Use multiple timeframes - Confirm on higher timeframes
Risk management - Always set stop losses
Wait for confirmation - Don't chase, let signals develop
❌ Don'ts
Don't trade all gaps - Focus on high-quality setups
Avoid low volume - Weak volume = unreliable signals
Don't ignore trend - Counter-trend trading is risky
Don't overtrade - Quality over quantity
Don't ignore context - Consider market conditions
⚠️ Risk Management
Position sizing: Risk 1-2% per trade
Stop losses: Always define before entry
Target levels: Set realistic profit targets
Market conditions: Avoid trading in choppy markets
📈 Performance Optimization
For Conservative Traders:
Increase minimum gap size to 1%
Set volume multiplier to 3.0x
Only trade episodic pivots in strong uptrends
Wait for gap fill confirmation
For Aggressive Traders:
Decrease minimum gap size to 0.3%
Set volume multiplier to 1.5x
Trade both gap types
Enter on pattern confirmation
🚨 Alert Setup
The indicator provides alerts for:
Gap Up Detected
Gap Down Detected
Upside Tasuki Gap
Episodic Pivot
Recommended: Enable all alerts and filter manually based on your strategy.
📝 Summary
This indicator excels at identifying high-probability trading opportunities through gap analysis, pattern recognition, and momentum confirmation. Use it as part of a complete trading system with proper risk management for best results.
EMA 12/26 With ATR Volatility StoplossThe EMA 12/26 With ATR Volatility Stoploss
The EMA 12/26 With ATR Volatility Stoploss strategy is a meticulously designed systematic trading approach tailored for navigating financial markets through technical analysis. By integrating the Exponential Moving Average (EMA) and Average True Range (ATR) indicators, the strategy aims to identify optimal entry and exit points for trades while prioritizing disciplined risk management. At its core, it is a trend-following system that seeks to capitalize on price momentum, employing volatility-adjusted stop-loss mechanisms and dynamic position sizing to align with predefined risk parameters. Additionally, it offers traders the flexibility to manage profits either by compounding returns or preserving initial capital, making it adaptable to diverse trading philosophies. This essay provides a comprehensive exploration of the strategy’s underlying concepts, key components, strengths, limitations, and practical applications, without delving into its technical code.
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Core Philosophy and Objectives
The EMA 12/26 With ATR Volatility Stoploss strategy is built on the premise of capturing short- to medium-term price trends with a high degree of automation and consistency. It leverages the crossover of two EMAs—a fast EMA (12-period) and a slow EMA (26-period)—to generate buy and sell signals, which indicate potential trend reversals or continuations. To mitigate the inherent risks of trading, the strategy incorporates the ATR indicator to set stop-loss levels that adapt to market volatility, ensuring that losses remain within acceptable bounds. Furthermore, it calculates position sizes based on a user-defined risk percentage, safeguarding capital while optimizing trade exposure.
A distinctive feature of the strategy is its dual profit management modes:
SnowBall (Compound Profit): Profits from successful trades are reinvested into the capital base, allowing for progressively larger position sizes and potential exponential portfolio growth.
ZeroRisk (Fixed Equity): Profits are withdrawn, and trades are executed using only the initial capital, prioritizing capital preservation and minimizing exposure to market downturns.
This duality caters to both aggressive traders seeking growth and conservative traders focused on stability, positioning the strategy as a versatile tool for various market environments.
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Key Components of the Strategy
1. EMA-Based Signal Generation
The strategy’s trend-following mechanism hinges on the interaction between the Fast EMA (12-period) and Slow EMA (26-period). EMAs are preferred over simple moving averages because they assign greater weight to recent price data, enabling quicker responses to market shifts. The key signals are:
Buy Signal: Triggered when the Fast EMA crosses above the Slow EMA, suggesting the onset of an uptrend or bullish momentum.
Sell Signal: Occurs when the Fast EMA crosses below the Slow EMA, indicating a potential downtrend or the end of a bullish phase.
To enhance signal reliability, the strategy employs an Anchor Point EMA (AP EMA), a short-period EMA (e.g., 2 days) that smooths the input price data before calculating the primary EMAs. This preprocessing reduces noise from short-term price fluctuations, improving the accuracy of trend detection. Additionally, users can opt for a Consolidated EMA (e.g., 18-period) to display a single trend line instead of both EMAs, simplifying chart analysis while retaining trend insights.
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2. Volatility-Adjusted Risk Management with ATR
Risk management is a cornerstone of the strategy, achieved through the use of the Average True Range (ATR), which quantifies market volatility by measuring the average price range over a specified period (e.g., 10 days). The ATR informs the placement of stop-loss levels, which are set at a multiple of the ATR (e.g., 2x ATR) below the entry price for long positions. This approach ensures that stop losses are proportionate to current market conditions—wider during high volatility to avoid premature exits, and narrower during low volatility to protect profits.
For example, if a stock’s ATR is $1 and the multiplier is 2, the stop loss for a buy at $100 would be set at $98. This dynamic adjustment enhances the strategy’s adaptability, preventing stop-outs from normal market noise while capping potential losses.
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3. Dynamic Position Sizing
The strategy calculates position sizes to align with a user-defined Risk Per Trade, typically expressed as a percentage of capital (e.g., 2%). The position size is determined by:
The available capital, which varies depending on whether SnowBall or ZeroRisk mode is selected.
The distance between the entry price and the ATR-based stop-loss level, which represents the per-unit risk.
The desired risk percentage, ensuring that the maximum loss per trade does not exceed the specified threshold.
For instance, with a $1,000 capital, a 2% risk per trade ($20), and a stop-loss distance equivalent to 5% of the entry price, the strategy computes the number of units (shares or contracts) to ensure the total loss, if the stop loss is hit, equals $20. To prevent over-leveraging, the strategy includes checks to ensure that the position’s dollar value does not exceed available capital. If it does, the position size is scaled down to fit within the capital constraints, maintaining financial discipline.
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4. Flexible Capital Management
The strategy’s dual profit management modes—SnowBall and ZeroRisk—offer traders strategic flexibility:
SnowBall Mode: By compounding profits, traders can increase their capital base, leading to larger position sizes over time. This is ideal for those with a long-term growth mindset, as it harnesses the power of exponential returns.
ZeroRisk Mode: By withdrawing profits and trading solely with the initial capital, traders protect their gains and limit exposure to market volatility. This conservative approach suits those prioritizing stability over aggressive growth.
These options allow traders to tailor the strategy to their risk tolerance, financial goals, and market outlook, enhancing its applicability across different trading styles.
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5. Time-Based Trade Filtering
To optimize performance and relevance, the strategy includes an option to restrict trading to a specific time range (e.g., from 2018 onward). This feature enables traders to focus on periods with favorable market conditions, avoid historically volatile or unreliable data, or align the strategy with their backtesting objectives. By confining trades to a defined timeframe, the strategy ensures that performance metrics reflect the intended market context.
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Strengths of the Strategy
The EMA 12/26 With ATR Volatility Stoploss strategy offers several compelling advantages:
Systematic and Objective: By adhering to predefined rules, the strategy eliminates emotional biases, ensuring consistent execution across market conditions.
Robust Risk Controls: The combination of ATR-based stop losses and risk-based position sizing caps losses at user-defined levels, fostering capital preservation.
Customizability: Traders can adjust parameters such as EMA periods, ATR multipliers, and risk percentages, tailoring the strategy to specific markets or preferences.
Volatility Adaptation: Stop losses that scale with market volatility enhance the strategy’s resilience, accommodating both calm and turbulent market phases.
Enhanced Visualization: The use of color-coded EMAs (green for bullish, red for bearish) and background shading provides intuitive visual cues, simplifying trend and trade status identification.
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Limitations and Considerations
Despite its strengths, the strategy has inherent limitations that traders must address:
False Signals in Range-Bound Markets: EMA crossovers may generate misleading signals in sideways or choppy markets, leading to whipsaws and unprofitable trades.
Signal Lag: As lagging indicators, EMAs may delay entry or exit signals, causing traders to miss rapid trend shifts or enter trades late.
Overfitting Risk: Excessive optimization of parameters to fit historical data can impair the strategy’s performance in live markets, as past patterns may not persist.
Impact of High Volatility: In extremely volatile markets, wider stop losses may result in larger losses than anticipated, challenging risk management assumptions.
Data Reliability: The strategy’s effectiveness depends on accurate, continuous price data, and discrepancies or gaps can undermine signal accuracy.
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Practical Applications
The EMA 12/26 With ATR Volatility Stoploss strategy is versatile, applicable to diverse markets such as stocks, forex, commodities, and cryptocurrencies, particularly in trending environments. To maximize its potential, traders should adopt a rigorous implementation process:
Backtesting: Evaluate the strategy’s historical performance across various market conditions to assess its robustness and identify optimal parameter settings.
Forward Testing: Deploy the strategy in a demo account to validate its real-time performance, ensuring it aligns with live market dynamics before risking capital.
Ongoing Monitoring: Continuously track trade outcomes, analyze performance metrics, and refine parameters to adapt to evolving market conditions.
Additionally, traders should consider market-specific factors, such as liquidity and volatility, when applying the strategy. For instance, highly liquid markets like forex may require tighter ATR multipliers, while less liquid markets like small-cap stocks may benefit from wider stop losses.
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Conclusion
The EMA 12/26 With ATR Volatility Stoploss strategy is a sophisticated, systematic trading framework that blends trend-following precision with disciplined risk management. By leveraging EMA crossovers for signal generation, ATR-based stop losses for volatility adjustment, and dynamic position sizing for risk control, it offers a balanced approach to capturing market trends while safeguarding capital. Its flexibility—evident in customizable parameters and dual profit management modes—makes it suitable for traders with varying risk appetites and objectives. However, its limitations, such as susceptibility to false signals and signal lag, necessitate thorough testing and prudent application. Through rigorous backtesting, forward testing, and continuous refinement, traders can harness this strategy to achieve consistent, risk-adjusted returns in trending markets, establishing it as a valuable tool in the arsenal of systematic trading.
Sideways Scalper Peak and BottomUnderstanding the Indicator
This indicator is designed to identify potential peaks (tops) and bottoms (bottoms) within a market, which can be particularly useful in a sideways or range-bound market where price oscillates between support and resistance levels without a clear trend. Here's how it works:
RSI (Relative Strength Index): Measures the speed and change of price movements to identify overbought (above 70) and oversold (below 30) conditions. In a sideways market, RSI can help signal when the price might be due for a reversal within its range.
Moving Averages (MAs): The Fast MA and Slow MA provide a sense of the short-term and longer-term average price movements. In a sideways market, these can help confirm if the price is at the upper or lower extremes of its range.
Volume Spike: Looks for significant increases in trading volume, which might indicate a stronger move or a potential reversal point when combined with other conditions.
Divergence: RSI divergence occurs when the price makes a new high or low, but the RSI does not, suggesting momentum is weakening, which can be a precursor to a reversal.
How to Use in a Sideways Market
Identify the Range: First, visually identify the upper resistance and lower support levels of the sideways market on your chart. This indicator can help you spot these levels more precisely by signaling potential peaks and bottoms.
Peak Signal :
When to Look: When the price approaches the upper part of the range.
Conditions: The indicator will give a 'Peak' signal when:
RSI is over 70, indicating overbought conditions.
There's bearish divergence (price makes a higher high, but RSI doesn't).
Volume spikes, suggesting strong selling interest.
Price is above both Fast MA and Slow MA, indicating it's at a potentially high point in the range.
Action: This signal suggests that the price might be at or near the top of its range and could reverse downwards. A trader might consider selling or shorting here, expecting the price to move towards the lower part of the range.
Bottom Signal:
When to Look: When the price approaches the lower part of the range.
Conditions: The indicator will give a 'Bottom' signal when:
RSI is below 30, indicating oversold conditions.
There's bullish divergence (price makes a lower low, but RSI doesn't).
Volume spikes, suggesting strong buying interest.
Price is below both Fast MA and Slow MA, indicating it's at a potentially low point in the range.
Action: This signal suggests that the price might be at or near the bottom of its range and could reverse upwards. A trader might consider buying here, expecting the price to move towards the upper part of the range.
Confirmation: In a sideways market, false signals can occur due to the lack of a strong trend. Always look for confirmation:
Volume Confirmation: A significant volume spike can add confidence to the signal.
Price Action: Look for price action like candlestick patterns (e.g., doji, engulfing patterns) that confirm the reversal.
Time Frame: Consider using this indicator on multiple time frames. A signal on a shorter time frame (like 15m or 1h) might be confirmed by similar conditions on a longer time frame (4h or daily).
Risk Management: Since this is designed for scalping in a sideways market:
Set Tight Stop-Losses: Due to the quick nature of reversals in range-bound markets, place stop-losses close to your entry to minimize loss.
Take Profit Levels: Set profit targets near the opposite end of the range or use a trailing stop to capture as much of the move as possible before it reverses again.
Practice: Before trading with real money, practice with this indicator on historical data or in a paper trading environment to understand how it behaves in different sideways market scenarios.
Key Points for New Traders
Patience: Wait for all conditions to align before taking a trade. Sideways markets require patience as the price might hover around these levels for a while.
Not All Signals Are Equal: Sometimes, even with all conditions met, the market might not reverse immediately. Look for additional context or confirmation.
Continuous Learning: Understand that this indicator, like any tool, isn't foolproof. Learn from each trade, whether it's a win or a loss, and adjust your strategy accordingly.
By following these guidelines
Strategy: Candlestick Wick Analysis with Volume Conditions
This strategy focuses on analyzing the wicks (or shadows) of candlesticks to identify potential trading opportunities based on candlestick structure and volume. Based on these criteria, it places stop orders at the extremities of the wicks when certain conditions are met, thus increasing the chances of capturing significant price movements.
Trading Criteria
Volume Conditions:
The strategy checks if the volume of the current candle is higher than that of the previous three candles. This ensures that the observed price movement is supported by significant volume, increasing the probability that the price will continue in the same direction.
Wick Analysis:
Upper Wick:
If the upper wick of a candle represents more than 90% of its body size and is longer than the lower wick, this indicates that the price tested a resistance level before pulling back.
Order Placement: In this case, a Buy Stop order is placed at the upper extremity of the wick. This means that if the price rises back to this level, the order will be triggered, and the trader will take a buy position.
SL Management: A stop-loss is then placed below the lowest point of the same candle. This protects the trader by limiting losses if the price falls back after the order is triggered.
Lower Wick:
If the lower wick of a candle is longer than the upper wick and represents more than 90% of its body size, this indicates that the price tested a support level before rising.
Order Placement: In this case, a Sell Stop order is placed at the lower extremity of the wick. Thus, if the price drops back to this level, the order will be triggered, and the trader will take a sell position.
SL Management: A stop-loss is then placed above the highest point of the same candle. This ensures risk management by limiting losses if the price rebounds upward after the order is triggered.
Strategy Advantages
Responsiveness to Price Movements: The strategy is designed to detect significant price movements based on the market's reaction around support and resistance levels. By placing stop orders directly at the wick extremities, it allows capturing strong movements in the direction indicated by the candles.
Securing Positions: Using stop-losses positioned just above or below key levels (wicks) provides better risk management. If the market doesn't move as expected, the position is automatically closed with a limited loss.
Clear Visual Indicators: Symbols are displayed on the chart at the points where orders have been placed, making it easier to understand trading decisions. This helps to quickly identify the support or resistance levels tested by the price, as well as potential entry points.
Conclusion
The strategy is based on the idea that large wicks signal areas where buyers or sellers have tested significant price levels before temporarily retreating. By placing stop orders at the extremities of these wicks, the strategy allows capturing price movements when they confirm, while limiting risks through strategically placed stop-losses. It thus offers a balanced approach between capturing potential profit and managing risk.
This description emphasizes the idea of capturing significant market movements with stop orders while providing a clear explanation of the logic and risk management. It’s tailored for publication on TradingView and highlights the robustness of the strategy.
Pro V3 [SMRT Algo]SMRT Algo Suite is a versatile toolkit featuring advanced features designed to deliver valuable signals and insights, catering to every trader's technical analysis requirements with precise data.
The SMRT Algo V3 represents a groundbreaking, comprehensive solution built from the ground up for traders.
While SMRT Algo can complement other technical analysis methods, it is also designed to function effectively as a standalone indicator adaptable to any trading style. Each feature is designed with the understanding that not all technical indicators suit every market condition.
The optimal approach to leveraging this indicator is to explore its diverse features gradually, select a few that best match your trading style, and use them consistently to develop a personalized SMRT Algo strategy.
Features:
Buy & Sell Signals: Clear buy and sell signals displayed on the chart, with ‘+’ indicating strong signals and normal signals without ‘+’.
Candle Coloring: Blue and red candle colors to signify bullish and bearish trends, respectively.
Signal Sensitivity: Adjust the frequency of signals to match your trading preferences.
MA Filter: Customizable moving average filter to ensure trades align with the prevailing trend.
Dashboard: Multi-timeframe analysis with information on various timeframes, offering quick decision-making capabilities and a customizable dashboard size.
Trailing Stop Loss: Suggestions for trailing stop losses to maximize profits while minimizing risk.
Power MA: A custom moving average that closely follows price, highlighting short-term market trends.
ChoCh/Bos: Displays internal market structure, including changes of character and breaks of structure.
Market Structure: Shows external market structure, detailing changes of character, breaks of structure, and pivot points.
Support & Resistance: Key support and resistance zones plotted on the chart.
Reversals: Highlights areas with a high likelihood of reversal using diamond markers.
Reversal Bands: Zones where price is likely to reverse or correct.
Trend Lines: Auto-plotted trendlines for quick and easy analysis.
Retest Zones: Ideal for break-and-retest traders, identifying key retest zones for entries and re-entries
Take Profit & Stop Loss: Customizable take profit and stop loss points.
Full Any Alert() Function Call Conditions: Create custom alerts directly to your TradingView device for timely notifications.
Additional features: A set of toggles turning on/off these indicators.
SMRT Algo Pro V3 offers a comprehensive set of features designed to enhance your trading experience by providing actionable insights and customizable tools for all trading styles.
SMRT Algo Pro V3 Confirmation Signals and Candle Coloring
The signals in SMRT Algo Pro V3 can generate both normal and strong labels, with strong signals marked by the "+" symbol. These signals are closely linked to the candle coloring, providing a visual representation of trend development to help navigate various market conditions effectively.
Candle Coloring:
Blue Candles: Indicate bullish trends.
Red Candles: Indicate bearish trends.
Candles will turn blue when there is a buy signal, and turn red when there is a sell signal.
The candle coloring is especially useful when interpreting signals. For instance, a consistent series of blue candles alongside buy signals suggests a strong uptrend, reducing the likelihood of a fake-out. Conversely, a series of red candles with sell signals indicates a strong downtrend.
Dashboard for Multi-Timeframe Analysis
The dashboard provides a consolidated view of multiple timeframes, helping traders make quick decisions based on comprehensive data. This feature reduces the need to switch between charts, streamlining the analysis process.
The dashboard will show the trend of higher timeframes, based on signal calculation and the trend filter.
Note on the dashboard: To reduce memory load, it will only display information from the current timeframe and up.
Trailing Stop Loss
This component workw to maximize profits and manage risk. The Trailing Stop Loss feature provides dynamic stop loss levels. Traders can use this feature to place their stop loss in profit while price goes in favor of your direction, so that less profit is left on the table, should the trade reverse against you.
Green trailing stop loss ranges are shown for buy trades, while red lines are shown for sell trades. This can be used together with the buy & sell signals to trail the stop loss for those trades.
Power MA
The Power MA follows the price closely, indicating short-term market trends and potential exit points. Traders can use the Power MA to determine when to enter a trade. For example, if the Pro V3 prints a buy signal, but the power MA is red (indicating that the market is short term bearish), it can act as a confirmation to stay out of that trade. Conversely, if the power MA is blue, then it can be an added confirmation to enter the buy trade based on the signals.
Market Structure
The inclusion of ChoCh/Bos (Change of Character and Break of Structure) helps traders understand internal and external market shifts. The ChoCh/Bos shows internal market structure, while the Market Structure feature shows the external market structure. This feature is crucial for identifying key turning points and potential trend continuations, as well as ICT traders.
We recommend traders to use this as an added confirmation, for example, once a buy signal is printed, wait for an internal or external Choch/BOS, possibly indicating that the market is now in control of the bulls. From there traders an either enter off another signal from the V3 or wait for the retest from the Retest Zones feature of the V3.
Support & Resistance, Reversals, and Reversal Bands
These features highlight critical market levels and areas where price is likely to reverse or correct. They are essential for traders looking to capitalize on key support and resistance zones or potential reversal points.
They can be used together with the buy & sell signals. An example is when a sell signal appears, we can look for potential trade exits either at the S/R zones, the reversal diamonds that are printed on the candle, or when price touches the reversal bands.
Trend Lines
Auto-plotted trend lines and the trend ribbon provide insights into longer-term trends. They can be used together with the buy sell features of the V3, e.g. if a sell signal is printed, but price is in the lower half of the trend lines, we can assume that price is in an area of premium for our short trade. Traders can choose whether to wait for price to retrace back into an area of discount (top half of the trend line), where they can look to short.
Retest Zones
The Retest Zones feature identifies optimal entry and re-entry points for break-and-retest strategies. As mentioned earlier, this feature can be used together with other features to act as a re-entry or further confirmation before entering a trade.
Traders can wait for a signal to be printed by the V3, and wait for further confrirmation from the retest zones to enter at a better price. This feature can be used together with the signals, and the market structure features to create a simple break & retest strategy.
Take Profit Modes:
SMRT Algo Pro V3 includes a versatile Take Profit Mode designed to help traders optimize their exits:
Hybrid Mode: Displays Take Profit, entry, and stop loss lines on the chart for the current position. Additionally, small circles labeled TP1, TP2, and TP3 indicate the points where take profit levels were hit.
Minimal Mode: Only displays the small circles labeled TP1, TP2, and TP3, providing a cleaner chart view while still indicating take profit hits.
Traditional Mode Only: Displays only the lines for Take Profit, entry, and stop loss, without the small circles.
Take profits are based off of 1:1, 1:2 and 1:3 risk to reward ratio with respect to the stop loss.
These modes offer flexibility for traders to choose their preferred level of detail on the chart, helping them to manage their trades effectively and track their take profit levels clearly.
The features of SMRT Algo Pro V3 can significantly strengthen your market analysis by providing additional confluences. These features allow traders to cross-verify signals and trends, making their strategies more robust and reliable. Here's how you can leverage these features:
SMRT Algo Pro V3 offers a comprehensive suite of tools and features that extend beyond the capabilities of standard or open-source indicators, providing significant additional value to users.
Integrated System: Unlike basic or open-source tools that may require multiple installations and configurations, SMRT Algo Pro V3 combines all necessary indicators into a cohesive system.
Advanced Customization: The toolkit offers extensive customization options, including signal sensitivity adjustments, customizable MA Filters, and various Take Profit Modes. These features allow traders to tailor the system to their specific trading styles and risk tolerance, providing a level of personalization that free tools often lack.
Real-Time Market Adaptation: SMRT Algo Pro V3 includes features like a deep learning dashboard and real-time market data integration, which continuously update and adapt to changing market conditions. This ensures that users receive the most current and relevant signals, enhancing decision-making accuracy.
Educational Support: Alongside the tools, SMRT Algo provides comprehensive educational resources and tutorials, helping traders understand how to effectively use the system and develop robust trading strategies. This educational aspect adds significant value, especially for beginners looking to deepen their knowledge.
Comprehensive Analysis Tools: The inclusion of multi-timeframe analysis, a detailed dashboard, and advanced market structure indicators help traders make more informed decisions by offering a complete picture of market dynamics.
Support and Community: Subscribers to SMRT Algo Pro V3 gain access to dedicated 24/7 support and an active trading community. This support network can be invaluable for troubleshooting, strategy development, and gaining insights from other experienced traders.
SMRT Algo believe that there is no magic indicator that is able to print money. Indicator toolkits provide value via their convinience, adaptibility and uniqueness. Combining these items can help a trader make more educated; less messy, more planned trades and in turn hopefully help them succeed.
RISK DISCLAIMER
Trading involves significant risk, and most day traders lose money. All content, tools, scripts, articles, and educational materials provided by SMRT Algo are intended solely for informational and educational purposes. Past performance is not indicative of future results. Always conduct your own research and consult with a licensed financial advisor before making any trading decisions.
Volume Candle bollinger band By Anil ChawraHow Users Can Make Profit Using This Script:
1.Volume Representation: Each candle on the chart represents a specific time period (e.g., 1 minute, 1 hour, 1 day) and includes information about both price movement and trading volume during that period.
2.Candlestick Anatomy: A volume candle has the same components as a regular candlestick: the body (which represents the opening and closing prices) and the wicks or shadows (which indicate the highest and lowest prices reached during the period).
3.Volume Bars: Instead of just the candlestick itself, volume candles also include a bar or histogram representing the trading volume during that period. The height or length of the volume bar indicates the amount of trading activity.
4.Interpreting Volume: High volume candles typically indicate increased market interest or activity during that period. This could be due to significant buying or selling pressure.
5.Confirmation: Traders often look for confirmation from other technical indicators or price action to validate the significance of a high volume candle. For example, a high volume candle breaking through a key support or resistance level may signal a strong market move.
6.Trend Strength: Volume candles can provide insights into the strength of a trend. A series of high volume candles in the direction of the trend suggests strong momentum, while decreasing volume may indicate weakening momentum or a potential reversal.
7.Volume Patterns: Traders also analyze volume patterns, such as volume spikes or divergences, to identify potential trading opportunities or reversals.
8.Combination with Price Action: Volume analysis is often used in conjunction with price action analysis and other technical indicators to make more informed trading decisions.
9.Confirmation and Validation: It's important to confirm the significance of volume candles with other indicators or price action signals to avoid false signals.
10.Risk Management: As with any trading strategy, proper risk management is crucial when using volume candles to make trading decisions. Set stop-loss orders and adhere to risk management principles to protect your capital.
How the Script Works:
1.Identify High Volume Candles: Look for candles with significantly higher volume compared to the surrounding candles. These can indicate increased market interest or activity.
2.Wait for Confirmation: Once you identify a high volume candle, wait for confirmation from subsequent candles to ensure the momentum is sustained.
3.Enter the Trade: After confirmation, consider entering a trade in the direction indicated by the high volume candle. For example, if it's a bullish candle, consider buying.
4.Set Stop Loss: Always set a stop loss to limit potential losses in case the trade goes against you.
5.Take Profit: Set a target for taking profits. This could be based on technical analysis, such as a resistance level or a certain percentage gain.
6.Monitor Volume: Continuously monitor volume to gauge the strength of the trend. Decreasing volume may signal weakening momentum and could be a sign to exit the trade.
7.Risk Management: Manage risk carefully by adjusting position sizes according to your risk tolerance and the size of your trading account.
8.Review and Adapt: Regularly review your trades and adapt your strategy based on what's working and what's not.
Remember, no trading strategy guarantees profits, and it's essential to practice proper risk management and have realistic expectations. Additionally, consider combining volume analysis with other technical indicators for a more comprehensive approach to trading.
How Users Can Make Profit Using this script :
Bollinger Bands are a technical analysis tool that helps traders identify potential trends and volatility in the market. Here's a simple strategy using Bollinger Bands with a 10-point range:
1. *Understanding Bollinger Bands*: Bollinger Bands consist of a simple moving average (typically 20 periods) and two standard deviations plotted above and below the moving average. The bands widen during periods of high volatility and contract during periods of low volatility.
2. *Identify Price Range*: Look for a stock or asset that has been trading within a relatively narrow range (around 10 points) for some time. This indicates low volatility.
3. *Wait for Squeeze*: When the Bollinger Bands contract, it suggests that volatility is low and a breakout may be imminent. This is often referred to as a "squeeze."
4. *Plan Entry and Exit Points*: When the price breaks out of the narrow range and closes above the upper Bollinger Band, consider entering a long position. Conversely, if the price breaks below the lower band, consider entering a short position.
5. *Set Stop-Loss and Take-Profit*: Set stop-loss orders to limit potential losses if the trade goes against you. Take-profit orders can be set at a predetermined level or based on the width of the Bollinger Bands.
6. *Monitor and Adjust*: Continuously monitor the trade and adjust your stop-loss and take-profit levels as the price moves.
7. *Risk Management*: Only risk a small percentage of your trading capital on each trade. This helps to mitigate potential losses.
8. *Practice and Refinement*: Practice this strategy on a demo account or with small position sizes until you are comfortable with it. Refine your approach based on your experience and market conditions.
Remember, no trading strategy guarantees profits, and it's essential to combine technical analysis with fundamental analysis and risk management principles for successful trading. Additionally, always stay informed about market news and events that could impact your trades.
How does script works:
Bollinger Bands work by providing a visual representation of the volatility and potential price movements of a financial instrument. Here's how they work with a 10-point range:
1. *Calculation of Bollinger Bands*: The bands consist of three lines: the middle line is a simple moving average (SMA) of the asset's price (typically calculated over 20 periods), and the upper and lower bands are calculated by adding and subtracting a multiple of the standard deviation (usually 2) from the SMA.
2. *Interpretation of the Bands*: The upper and lower bands represent the potential extremes of price movements. In a 10-point range scenario, these bands are positioned 10 points above and below the SMA.
3. *Volatility Measurement*: When the price is experiencing high volatility, the bands widen, indicating a wider potential range of price movement. Conversely, during periods of low volatility, the bands contract, suggesting a narrower potential range.
4. *Mean Reversion and Breakout Signals*: Traders often use Bollinger Bands to identify potential mean reversion or breakout opportunities. When the price touches or crosses the upper band, it may indicate overbought conditions, suggesting a potential reversal to the downside. Conversely, when the price touches or crosses the lower band, it may indicate oversold conditions and a potential reversal to the upside.
5. *10-Point Range Application*: In a scenario where the price range is limited to 10 points, traders can look for opportunities when the price approaches either the upper or lower band. If the price consistently bounces between the bands, traders may consider buying near the lower band and selling near the upper band.
6. *Confirmation and Risk Management*: Traders often use other technical indicators or price action patterns to confirm signals generated by Bollinger Bands. Additionally, it's crucial to implement proper risk management techniques, such as setting stop-loss orders, to protect against adverse price movements.
Overall, Bollinger Bands provide traders with valuable insights into market volatility and potential price movements, helping them make informed trading decisions. However, like any technical indicator, they are not foolproof and should be used in conjunction with other analysis methods.
Turtle Trading Strategy@lihexieThe full implementation of the Turtle Trading Rules (as distinct from the various truncated versions circulating within the community) is now ready.
This trading strategy script distinguishes itself from all currently publicly available Turtle trading systems on Tradingview by comprehensively embodying the rules for entries, exits, position management, and profit and loss controls.
Market Selection:
Trade in highly liquid markets such as forex, commodity futures, and stock index futures.
Entry Strategies:
Model 1: Buy when the price breaks above the highest point of the last 20 trading days; Sell when the price drops below the lowest point of the last 20 trading days. When an entry opportunity arises, if the previous trade was profitable, skip the current breakout opportunity and refrain from entering.
Model 2: Buy when the price breaks above the highest point of the last 55 trading days; Sell when the price drops below the lowest point of the last 55 trading days.
Position Sizing:
Determine the size of each position based on the price volatility (ATR) to ensure that the risk of each trade does not exceed 2% of the account balance.
Exit Strategies:
1. Use a fixed stop-loss point to limit losses: Close long positions when the price falls below the lowest point of the last 10 trading days.
2. Trailing stop-loss: Once a position is profitable, adjust the stop-loss point to protect profits.
Pyramiding Rules:
Unit Doubling: Increase position size by one unit every time the price moves forward by n (default is 0.5) units of ATR, up to a maximum of 4 units, while also raising the stop-loss point to below the ATR value at the level of additional entries.
海龟交易法则的完整实现（区别于当前社区各种有阉割海龟交易系统代码）
本策略脚本区别于Tradingview目前公开的所有的海龟交易系统，完整的实现了海龟交易法则中入场、出场、仓位管理，止盈止损的规则。
市场选择：
选择流动性高的市场进行交易，如外汇、商品期货和股指期货等。
入市策略：
模式1：当价格突破过去20个交易日的高点时，买入；当价格跌破过去20个交易日的低点时，卖出。当出现入场机会时，如果上一笔交易是盈利的，那么跳过当前突破的机会，不进行入场。
模式2：当价格突破过去55个交易日的高点时，买入；当价格跌破过去55个交易日的低点时，卖出。
头寸规模：
根据价格波动性（ATR）来确定每个头寸的大小, 使每笔交易的风险不超过账户余额的2%。
退出策略：
1. 使用一个固定的止损点来限制损失：当多头头寸的价格跌破过去10个交易日的低点时，平仓止损。
2. 跟踪止损：一旦头寸盈利，移动止损点以保护利润。
加仓规则：
单位加倍：每当价格向前n（默认是0.5）个单位的ATR移动时，就增加一个单位的头寸大小（默认最大头寸数量是4个），同时将止损点提升至加仓点位的ATR值以下。
Rate of Change StrategyRate of Change Strategy :
INTRODUCTION :
This strategy is based on the Rate of Change indicator. It compares the current price with that of a user-defined period of time ago. This makes it easy to spot trends and even speculative bubbles. The strategy is long term and very risky, which is why we've added a Stop Loss. There's also a money management method that allows you to reinvest part of your profits or reduce the size of your orders in the event of substantial losses.
RATE OF CHANGE (ROC) :
As explained above, the ROC is used to situate the current price compared to that of a certain period of time ago. The formula for calculating ROC in relation to the previous year is as follows :
ROC (365) = (close/close (365) - 1) * 100
With this formula we can find out how many percent the change in the current price is compared with 365 days ago, and thus assess the trend.
PARAMETERS :
ROC Length : Length of the ROC to be calculated. The current price is compared with that of the selected length ago.
ROC Bubble Signal : ROC value indicating that we are in a bubble. This value varies enormously depending on the financial product. For example, in the equity market, a bubble exists when ROC = 40, whereas in cryptocurrencies, a bubble exists when ROC = 150.
Stop Loss (in %) : Stop Loss value in percentage. This is the maximum trade value percentage that can be lost in a single trade.
Fixed Ratio : This is the amount of gain or loss at which the order quantity is changed. The default is 400, which means that for each $400 gain or loss, the order size is increased or decreased by an amount chosen by the user.
Increasing Order Amount : This is the amount to be added to or subtracted from orders when the fixed ratio is reached. The default is $200, which means that for every $400 gain, $200 is reinvested in the strategy. On the other hand, for every $400 loss, the order size is reduced by $200.
Initial capital : $1000
Fees : Interactive Broker fees apply to this strategy. They are set at 0.18% of the trade value.
Slippage : 3 ticks or $0.03 per trade. Corresponds to the latency time between the moment the signal is received and the moment the order is executed by the broker.
Important : A bot has been used to test the different parameters and determine which ones maximize return while limiting drawdown. This strategy is the most optimal on BITSTAMP:BTCUSD in 1D timeframe with the following parameters :
ROC Length = 365
ROC Bubble Signal = 180
Stop Loss (in %) = 6
LONG CONDITION :
We are in a LONG position if ROC (365) > 0 for at least two days. This allows us to limit noise and irrelevant signals to ensure that the ROC remains positive.
SHORT CONDITION :
We are in a SHORT position if ROC (365) < 0 for at least two days. We also open a SHORT position when the speculative bubble is about to burst. If ROC (365) > 180, we're in a bubble. If the bubble has been in existence for at least a week and the ROC falls back below this threshold, we can expect the asset to return to reasonable prices, and thus a downward trend. So we're opening a SHORT position to take advantage of this upcoming decline.
EXIT RULES FOR WINNING TRADE :
The strategy is self-regulating. We don't exit a LONG trade until a SHORT signal has arrived, and vice versa. So, to exit a winning position, you have to wait for the entry signal of the opposite position.
RISK MANAGEMENT :
This strategy is very risky, and we can easily end up on the wrong side of the trade. That's why we're going to manage our risk with a Stop Loss, limiting our losses as a percentage of the trade's value. By default, this percentage is set at 6%. Each trade will therefore take a maximum loss of 6%.
If the SL has been triggered, it probably means we were on the wrong side. This is why we change the direction of the trade when a SL is triggered. For example, if we were SHORT and lost 6% of the trade value, the strategy will close this losing trade and open a long position without taking into account the ROC value. This allows us to be in position all the time and not miss the best opportunities.
MONEY MANAGEMENT :
The fixed ratio method was used to manage our gains and losses. For each gain of an amount equal to the value of the fixed ratio, we increase the order size by a value defined by the user in the "Increasing order amount" parameter. Similarly, each time we lose an amount equal to the value of the fixed ratio, we decrease the order size by the same user-defined value. This strategy increases both performance and drawdown.
NOTE :
Please note that the strategy is backtested from 2017-01-01. As the timeframe is 1D, this strategy is a medium/long-term strategy. That's why only 34 trades were closed. Be careful, as the test sample is small and performance may not necessarily reflect what may happen in the future.
Enjoy the strategy and don't forget to take the trade :)
Cracking Cryptocurrency - Bottom FeederThe Bottom Feeder
The Bottom Feeder is designed to algorithmically detect significantly oversold conditions in price that represent profitable buying opportunities. Combining this with it’s unique Stop and Target System, the Bottom Feeder is designed to return consistent return with minimal draw down. Whether used as a Market Bottom Detector or as a system for executing safe, profitable mean reversion trades, the Bottom Feeder is a powerful tool in any trader’s arsenal.
Bottom Feeder was designed to be used on BTCUSD , however it is also effective on other USD/USDT pairs. One will have to check the individual pair they wish to trade with the Strategy Tester to simulate performance.
Options
Let’s go through the input options one by one, so that you are able to comfortably navigate all that this indicator has to offer. The link below will display a picture of the layout of the settings for your convenience.
For the sake of simplicity, let’s note now that all settings marked **Conservative Mode** will not work in Aggressive Mode.
Mode: Determines how aggressively Bottom Feeder generates a buy signal. In Conservative Mode, trades can only be opened once per candle and the stop and target will update as new signals appear. In Aggressive Mode, a separate trade is opened each time Bottom Feeder signals, which may be multiple times within one Daily candle.
Plot Target and Stop Loss: Toggles on/off the visualized take profit and stop losses on the chart.
**Conservative Mode** TP Multiplier: This is an input box, it requires a float value. That is, it can accept either a whole number integer or a number with a decimal. This number will determine your Take Profit target. It will take whatever number is entered into this box and multiply the Average True Range against it to determine your Take Profit.
**Conservative Mode** SL Multiplier: See above - this will modify your Stop Loss Value.
**Conservative Mode** Average or Median True Range: This is a drop-down option, the two options are Average True Range or Median True Range. If Average True Range is selected, then this indicator will use the Average True Range calculation, that is, the average of a historical set of True Range values to determine the Average True Range value for Target and Stop Loss calculation. If Median True Range is selected, it will not take an average and will instead take the Median value of your historical look back period.
**Conservative Mode** True Range Length: This is an input that requires an integer. This will represent your historical look back period for Average/Median True Range calculation.
**Conservative Mode** True Range Smoothing: This is a drop-down with the following options: Exponential Moving Average ( EMA ), Simple Moving Average ( SMA ), Weighted Moving Average ( WMA ), Relative Moving Average (RMA). This will determine the smoothing type for calculating the Average True Range if it is selected. Note: if Median True Range is selected above, this option will not have any effect as there is no smoothing for a Median value.
**Conservative Mode** Custom True Range Value?: This is a true/false option that is false by default. If enabled, it will override the Average/Median True Range calculation in favor of a users custom True Range value to be input below.
**Conservative Mode** Custom True Range Value: This is an input box that requires a float value. If Custom True Range is enabled this is where a user will input their desired custom True Range value for Target and Stop Loss calculation.
Stop and Target Description
Because Bottom Feeder is designed only to scalp the various market bottoms that can appear over time in the market and not to identify trends or to trade ranges, it’s imperative that the indicator notify us not just to when to enter our trades, but when to exit! In the service of that, CC Bottom Feeder has a built in Stop and Target system that tracks and displays the stop loss and take profit levels of each individual open trade, whether in Aggressive or Conservative Mode.
Conservative Mode Targeting: In Conservative Mode, Bottom Feeder signals are aggregated into a compound trade. The signal will appear as a green label pointing up below a candle, and will appear upon a candle close. If Bottom Feeder then generates another signal the stop loss and target price will be updated. The process will continue until the aggregated trade completes in either direction. On a trade with multiple signals, a larger position is slowly entered into upon each buy signal.
Aggressive Mode Targeting: In Aggressive Mode, Bottom Feeder signals are individually displayed as they are generated, regardless of how many signals are generated on any single candle. If Bottom Feeder continues to signal, each individual open trade will have their own stop loss and target that will be displayed on the chart until the individual trade completes in either direction. As opposed to a large compound position, aggressive mode represents a higher number of independent signals with their own stop and target levels.
Stop losses and targets are designed to be hard, not soft. That is, they are intended to be stop market orders, not mental stop losses. If price wicks through the target or stop, it will activate.
RSI Donchian Channel [DCAUT]█ RSI Donchian Channel
📊 ORIGINALITY & INNOVATION
The RSI Donchian Channel represents an important synthesis of two complementary analytical frameworks: momentum oscillators and breakout detection systems. This indicator addresses a common limitation in traditional RSI analysis by replacing fixed overbought/oversold thresholds with adaptive zones derived from historical RSI extremes.
Key Enhancement:
Traditional RSI analysis relies on static threshold levels (typically 30/70), which may not adequately reflect changing market volatility regimes. This indicator adapts the reference zones dynamically based on the actual RSI behavior over the lookback period, helping traders identify meaningful momentum extremes relative to recent price action rather than arbitrary fixed levels.
The implementation combines the proven momentum measurement capabilities of RSI with Donchian Channel's breakout detection methodology, creating a framework that identifies both momentum exhaustion points and potential continuation signals through the same analytical lens.
📐 MATHEMATICAL FOUNDATION
Core Calculation Process:
Step 1: RSI Calculation
The Relative Strength Index measures momentum by comparing the magnitude of recent gains to recent losses:
Calculate price changes between consecutive periods
Separate positive changes (gains) from negative changes (losses)
Apply selected smoothing method (RMA standard, also supports SMA, EMA, WMA) to both gain and loss series
Compute Relative Strength (RS) as the ratio of smoothed gains to smoothed losses
Transform RS into bounded 0-100 scale using the formula: RSI = 100 - (100 / (1 + RS))
Step 2: Donchian Channel Application
The Donchian Channel identifies the highest and lowest RSI values within the specified lookback period:
Upper Channel: Highest RSI value over the lookback period, represents the recent momentum peak
Lower Channel: Lowest RSI value over the lookback period, represents the recent momentum trough
Middle Channel (Basis): Average of upper and lower channels, serves as equilibrium reference
Channel Width Dynamics:
The distance between upper and lower channels reflects RSI volatility. Wide channels indicate high momentum variability, while narrow channels suggest momentum consolidation and potential breakout preparation. The indicator monitors channel width over a 100-period window to identify squeeze conditions that often precede significant momentum shifts.
📊 COMPREHENSIVE SIGNAL ANALYSIS
Primary Signal Categories:
Breakout Signals:
Upper Breakout: RSI crosses above the upper channel, indicates momentum reaching new relative highs and potential trend continuation, particularly significant when accompanied by price confirmation
Lower Breakout: RSI crosses below the lower channel, suggests momentum reaching new relative lows and potential trend exhaustion or reversal setup
Breakout strength is enhanced when the channel is narrow prior to the breakout, indicating a transition from consolidation to directional movement
Mean Reversion Signals:
Upper Touch Without Breakout: RSI reaches the upper channel but fails to break through, may indicate momentum exhaustion and potential reversal opportunity
Lower Touch Without Breakout: RSI reaches the lower channel without breakdown, suggests potential bounce as momentum reaches oversold extremes
Return to Basis: RSI moving back toward the middle channel after touching extremes signals momentum normalization
Trend Strength Assessment:
Sustained Upper Channel Riding: RSI consistently remains near or above the upper channel during strong uptrends, indicates persistent bullish momentum
Sustained Lower Channel Riding: RSI stays near or below the lower channel during strong downtrends, reflects persistent bearish pressure
Basis Line Position: RSI position relative to the middle channel helps identify the prevailing momentum bias
Channel Compression Patterns:
Squeeze Detection: Channel width narrowing to 100-period lows indicates momentum consolidation, often precedes significant directional moves
Expansion Phase: Channel widening after a squeeze confirms the initiation of a new momentum regime
Persistent Narrow Channels: Extended periods of tight channels suggest market indecision and accumulation/distribution phases
🎯 STRATEGIC APPLICATIONS
Trend Continuation Strategy:
This approach focuses on identifying and trading momentum breakouts that confirm established trends:
Identify the prevailing price trend using higher timeframe analysis or trend-following indicators
Wait for RSI to break above the upper channel in uptrends (or below the lower channel in downtrends)
Enter positions in the direction of the breakout when price action confirms the momentum shift
Place protective stops below the recent swing low (long positions) or above swing high (short positions)
Target profit levels based on prior swing extremes or use trailing stops to capture extended moves
Exit when RSI crosses back through the basis line in the opposite direction
Mean Reversion Strategy:
This method capitalizes on momentum extremes and subsequent corrections toward equilibrium:
Monitor for RSI reaching the upper or lower channel boundaries
Look for rejection signals (price reversal patterns, volume divergence) when RSI touches the channels
Enter counter-trend positions when RSI begins moving back toward the basis line
Use the basis line as the initial profit target for mean reversion trades
Implement tight stops beyond the channel extremes to limit risk on failed reversals
Scale out of positions as RSI approaches the basis line and closes the position when RSI crosses the basis
Breakout Preparation Strategy:
This approach positions traders ahead of potential volatility expansion from consolidation phases:
Identify squeeze conditions when channel width reaches 100-period lows
Monitor price action for consolidation patterns (triangles, rectangles, flags) during the squeeze
Prepare conditional orders for breakouts in both directions from the consolidation
Enter positions when RSI breaks out of the narrow channel with expanding width
Use the channel width expansion as a confirmation signal for the breakout's validity
Manage risk with stops just inside the opposite channel boundary
Multi-Timeframe Confluence Strategy:
Combining RSI Donchian Channel analysis across multiple timeframes can improve signal reliability:
Identify the primary trend direction using a higher timeframe RSI Donchian Channel (e.g., daily or weekly)
Use a lower timeframe (e.g., 4-hour or hourly) to time precise entry points
Enter long positions when both timeframes show RSI above their respective basis lines
Enter short positions when both timeframes show RSI below their respective basis lines
Avoid trades when timeframes provide conflicting signals (e.g., higher timeframe below basis, lower timeframe above)
Exit when the higher timeframe RSI crosses its basis line in the opposite direction
Risk Management Guidelines:
Effective risk management is essential for all RSI Donchian Channel strategies:
Position Sizing: Calculate position sizes based on the distance between entry point and stop loss, limiting risk to 1-2% of capital per trade
Stop Loss Placement: For breakout trades, place stops just inside the opposite channel boundary; for mean reversion trades, use stops beyond the channel extremes
Profit Targets: Use the basis line as a minimum target for mean reversion trades; for trend trades, target prior swing extremes or use trailing stops
Channel Width Context: Increase position sizes during narrow channels (lower volatility) and reduce sizes during wide channels (higher volatility)
Correlation Awareness: Monitor correlations between traded instruments to avoid over-concentration in similar setups
📋 DETAILED PARAMETER CONFIGURATION
RSI Source:
Defines the price data series used for RSI calculation:
Close (Default): Standard choice providing end-of-period momentum assessment, suitable for most trading styles and timeframes
High-Low Average (HL2): Reduces the impact of closing auction dynamics, useful for markets with significant end-of-day volatility
High-Low-Close Average (HLC3): Provides a more balanced view incorporating the entire period's range
Open-High-Low-Close Average (OHLC4): Offers the most comprehensive price representation, helpful for identifying overall period sentiment
Strategy Consideration: Use Close for end-of-period signals, HL2 or HLC3 for intraday volatility reduction, OHLC4 for capturing full period dynamics
RSI Length:
Controls the number of periods used for RSI calculation:
Short Periods (5-9): Highly responsive to recent price changes, produces more frequent signals with increased false signal risk, suitable for short-term trading and volatile markets
Standard Period (14): Widely accepted default balancing responsiveness with stability, appropriate for swing trading and intermediate-term analysis
Long Periods (21-28): Produces smoother RSI with fewer signals but more reliable trend identification, better for position trading and reducing noise in choppy markets
Optimization Approach: Test different lengths against historical data for your specific market and timeframe, consider using longer periods in ranging markets and shorter periods in trending markets
RSI MA Type:
Determines the smoothing method applied to price changes in RSI calculation:
RMA (Relative Moving Average - Default): Wilder's original smoothing method providing stable momentum measurement with gradual response to changes, maintains consistency with classical RSI interpretation
SMA (Simple Moving Average): Treats all periods equally, responds more quickly to changes than RMA but may produce more whipsaws in volatile conditions
EMA (Exponential Moving Average): Weights recent periods more heavily, increases responsiveness at the cost of potential noise, suitable for traders prioritizing early signal generation
WMA (Weighted Moving Average): Applies linear weighting favoring recent data, offers a middle ground between SMA and EMA responsiveness
Selection Guidance: Maintain RMA for consistency with traditional RSI analysis, use EMA or WMA for more responsive signals in fast-moving markets, apply SMA for maximum simplicity and transparency
DC Length:
Specifies the lookback period for Donchian Channel calculation on RSI values:
Short Periods (10-14): Creates tight channels that adapt quickly to changing momentum conditions, generates more frequent trading signals but increases sensitivity to short-term RSI fluctuations
Standard Period (20): Balances channel responsiveness with stability, aligns with traditional Bollinger Bands and moving average periods, suitable for most trading styles
Long Periods (30-50): Produces wider, more stable channels that better represent sustained momentum extremes, reduces signal frequency while improving reliability, appropriate for position traders and higher timeframes
Calibration Strategy: Match DC length to your trading timeframe (shorter for day trading, longer for swing trading), test channel width behavior during different market regimes, consider using adaptive periods that adjust to volatility conditions
Market Adaptation: Use shorter DC lengths in trending markets to capture momentum shifts earlier, apply longer periods in ranging markets to filter noise and focus on significant extremes
Parameter Combination Recommendations:
Scalping/Day Trading: RSI Length 5-9, DC Length 10-14, EMA or WMA smoothing for maximum responsiveness
Swing Trading: RSI Length 14, DC Length 20, RMA smoothing for balanced analysis (default configuration)
Position Trading: RSI Length 21-28, DC Length 30-50, RMA or SMA smoothing for stable signals
High Volatility Markets: Longer RSI periods (21+) with standard DC length (20) to reduce noise
Low Volatility Markets: Standard RSI length (14) with shorter DC length (10-14) to capture subtle momentum shifts
📈 PERFORMANCE ANALYSIS & COMPETITIVE ADVANTAGES
Adaptive Threshold Mechanism:
Unlike traditional RSI analysis with fixed 30/70 thresholds, this indicator's Donchian Channel approach provides several improvements:
Context-Aware Extremes: Overbought/oversold levels adjust automatically based on recent momentum behavior rather than arbitrary fixed values
Volatility Adaptation: In low volatility periods, channels narrow to reflect tighter momentum ranges; in high volatility, channels widen appropriately
Market Regime Recognition: The indicator implicitly adapts to different market conditions without manual threshold adjustments
False Signal Reduction: Adaptive channels help reduce premature reversal signals that often occur with fixed thresholds during strong trends
Signal Quality Characteristics:
The indicator's dual-purpose design provides distinct advantages for different trading objectives:
Breakout Trading: Channel boundaries offer clear, objective breakout levels that update dynamically, eliminating the ambiguity of when momentum becomes "too high" or "too low"
Mean Reversion: The basis line provides a natural profit target for reversion trades, representing the midpoint of recent momentum extremes
Trend Strength: Persistent channel boundary riding offers an objective measure of trend strength without additional indicators
Consolidation Detection: Channel width analysis provides early warning of potential volatility expansion from compression phases
Comparative Analysis:
When compared to traditional RSI implementations and other momentum frameworks:
vs. Fixed Threshold RSI: Provides market-adaptive reference levels rather than static values, helping to reduce false signals during trending markets where RSI can remain "overbought" or "oversold" for extended periods
vs. RSI Bollinger Bands: Offers clearer breakout signals and more intuitive extreme identification through actual high/low boundaries rather than statistical standard deviations
vs. Stochastic Oscillator: Maintains RSI's momentum measurement advantages (unbounded calculation avoiding scale compression) while adding the breakout detection capabilities of Donchian Channels
vs. Standard Donchian Channels: Applies breakout methodology to momentum space rather than price, providing earlier signals of potential trend changes before price breakouts occur
Performance Characteristics:
The indicator exhibits specific behavioral patterns across different market conditions:
Trending Markets: Excels at identifying momentum continuation through channel breakouts, RSI tends to ride one channel boundary during strong trends, providing trend confirmation
Ranging Markets: Channel width narrows during consolidation, offering early preparation signals for potential breakout trading opportunities
High Volatility: Channels widen to reflect increased momentum variability, automatically adjusting signal sensitivity to match market conditions
Low Volatility: Channels contract, making the indicator more sensitive to subtle momentum shifts that may be significant in calm market environments
Transition Periods: Channel squeezes often precede major trend changes, offering advance warning of potential regime shifts
Limitations and Considerations:
Users should be aware of certain operational characteristics:
Lookback Dependency: Channel boundaries depend entirely on the lookback period, meaning the indicator has no predictive element beyond identifying current momentum relative to recent history
Lag Characteristics: As with all moving average-based indicators, RSI calculation introduces lag, and channel boundaries update only as new extremes occur within the lookback window
Range-Bound Sensitivity: In extremely tight ranges, channels may become very narrow, potentially generating excessive signals from minor momentum fluctuations
Trending Persistence: During very strong trends, RSI may remain at channel extremes for extended periods, requiring patience for mean reversion setups or commitment to trend-following approaches
No Absolute Levels: Unlike traditional RSI, this indicator provides no fixed reference points (like 50), making it less suitable for strategies that depend on absolute momentum readings
USAGE NOTES
This indicator is designed for technical analysis and educational purposes to help traders understand momentum dynamics and identify potential trading opportunities. The RSI Donchian Channel has limitations and should not be used as the sole basis for trading decisions.
Important considerations:
Performance varies significantly across different market conditions, timeframes, and instruments
Historical signal patterns do not guarantee future results, as market behavior continuously evolves
Effective use requires understanding of both RSI momentum principles and Donchian Channel breakout concepts
Risk management practices (stop losses, position sizing, diversification) are essential for any trading application
Consider combining with additional analytical tools such as volume analysis, price action patterns, or trend indicators for confirmation
Backtest thoroughly on your specific instruments and timeframes before live trading implementation
Be aware that optimization on historical data may lead to curve-fitting and poor forward performance
The indicator performs best when used as part of a comprehensive trading methodology that incorporates multiple forms of market analysis, sound risk management, and realistic expectations about win rates and drawdowns.
Alpha - Combined BreakoutThis Pine Script indicator, "Alpha - Combined Breakout," is a combination between Smart Money Breakout Signals and UT Bot Alert, The UT Bot Alert indicator was initially developer by Yo_adriiiiaan
The idea of original code belongs HPotter.
This Indicator helps you identify potential trading opportunities by combining two distinct strategies: Smart Money Breakout and a modified UT Bot (likely a variation of the Ultimate Trend Bot). It provides visual signals, draws lines for potential take profit (TP) and stop loss (SL) levels, and includes a dashboard to track performance metrics.
Tutorial:
Understanding and Using the "Alpha - Combined Breakout" Indicator
This indicator is designed for traders looking for confirmation of market direction and potential entry/exit points by blending structural analysis with a trend-following oscillator.
How it Works (General Concept)
The indicator combines two main components:
Smart Money Breakout: This part identifies significant breaks in market structure, which "smart money" traders often use to gauge shifts in supply and demand. It looks for higher highs/lows or lower highs/lows and flags when these structural points are broken.
UT Bot: This is a trend-following component that generates buy and sell signals based on price action relative to an Average True Range (ATR) based trailing stop.
You can choose to use these signals independently or combined to generate trading alerts and visual cues on your chart. The dashboard provides a quick overview of how well the signals are performing based on your chosen settings and display mode.
Parameters and What They Do
Let's break down each input parameter:
1. Smart Money Inputs
These settings control how the indicator identifies market structure and breakouts.
swingSize (Market Structure Time-Horizon):
What it does: This integer value defines the number of candles used to identify significant "swing" (pivot) points—highs and lows.
Effect: A larger swingSize creates a smoother market structure, focusing on longer-term trends. This means signals might appear less frequently and with some delay but could be more reliable for higher timeframes or broader market movements. A smaller swingSize will pick up more minor market structure changes, leading to more frequent but potentially noisier signals, suitable for lower timeframes or scalping.
Analogy: Think of it like a zoom level on your market structure map. Higher values zoom out, showing only major mountain ranges. Lower values zoom in, showing every hill and bump.
bosConfType (BOS Confirmation Type):
What it does: This string input determines how a Break of Structure (BOS) is confirmed. You have two options:
'Candle Close': A breakout is confirmed only if a candle's closing price surpasses the previous swing high (for bullish) or swing low (for bearish).
'Wicks': A breakout is confirmed if any part of the candle (including its wick) surpasses the previous swing high or low.
Effect: 'Candle Close' provides stronger, more conservative confirmation, as it implies sustained price movement beyond the structure. 'Wicks' provides earlier, more aggressive signals, as it captures momentary breaches of the structure.
Analogy: Imagine a wall. 'Candle Close' means the whole person must get over the wall. 'Wicks' means even a finger touching over the top counts as a breach.
choch (Show CHoCH):
What it does: A boolean (true/false) input to enable or disable the display of "Change of Character" (CHoCH) labels. CHoCH indicates the first structural break against the current dominant trend.
Effect: When true, it helps identify early signs of a potential trend reversal, as it marks where the market's "character" (its tendency to make higher highs/lows or lower lows/highs) first changes.
BULL (Bullish Color) & BEAR (Bearish Color):
What they do: These color inputs allow you to customize the visual appearance of bullish and bearish signals and lines drawn by the Smart Money component.
Effect: Purely cosmetic, helps with visual identification on the chart.
sm_tp_sl_multiplier (SM TP/SL Multiplier (ATR)):
What it does: A float value that acts as a multiplier for the Average True Range (ATR) to calculate the Take Profit (TP) and Stop Loss (SL) levels specifically when you're in "Smart Money Only" mode. It uses the ATR calculated by the UT Bot's nLoss_ut as its base.
Effect: A higher multiplier creates wider TP/SL levels, potentially leading to fewer trades but larger wins/losses. A lower multiplier creates tighter TP/SL levels, potentially leading to more frequent but smaller wins/losses.
2. UT Bot Alerts Inputs
These parameters control the behavior and sensitivity of the UT Bot component.
a_ut (UT Key Value (Sensitivity)):
What it does: This integer value adjusts the sensitivity of the UT Bot.
Effect: A higher value makes the UT Bot less sensitive to price fluctuations, resulting in fewer and potentially more reliable signals. A lower value makes it more sensitive, generating more signals, which can include more false signals.
Analogy: Like a noise filter. Higher values filter out more noise, keeping only strong signals.
c_ut (UT ATR Period):
What it does: This integer sets the look-back period for the Average True Range (ATR) calculation used by the UT Bot. ATR measures market volatility.
Effect: This period directly influences the calculation of the nLoss_ut (which is a_ut * xATR_ut), thus defining the distance of the trailing stop loss and take profit levels. A longer period makes the ATR smoother and less reactive to sudden price spikes. A shorter period makes it more responsive.
h_ut (UT Signals from Heikin Ashi Candles):
What it does: A boolean (true/false) input to determine if the UT Bot calculations should use standard candlestick data or Heikin Ashi candlestick data.
Effect: Heikin Ashi candles smooth out price action, often making trends clearer and reducing noise. Using them for UT Bot signals can lead to smoother, potentially delayed signals that stay with a trend longer. Standard candles are more reactive to raw price changes.
3. Line Drawing Control Buttons
These crucial boolean inputs determine which type of signals will trigger the drawing of TP/SL/Entry lines and flags on your chart. They act as a priority system.
drawLinesUtOnly (Draw Lines: UT Only):
What it does: If checked (true), lines and flags will only be drawn when the UT Bot generates a buy/sell signal.
Effect: Isolates UT Bot signals for visual analysis.
drawLinesSmartMoneyOnly (Draw Lines: Smart Money Only):
What it does: If checked (true), lines and flags will only be drawn when the Smart Money Breakout logic generates a bullish/bearish breakout.
Effect: Overrides drawLinesUtOnly if both are checked. Isolates Smart Money signals.
drawLinesCombined (Draw Lines: UT & Smart Money (Combined)):
What it does: If checked (true), lines and flags will only be drawn when both a UT Bot signal AND a Smart Money Breakout signal occur on the same bar.
Effect: Overrides both drawLinesUtOnly and drawLinesSmartMoneyOnly if checked. Provides the strictest entry criteria for line drawing, looking for strong confluence.
Dashboard Metrics Explained
The dashboard provides performance statistics based on the lines drawing control button selected. For example, if "Draw Lines: UT Only" is active, the dashboard will show stats only for UT Bot signals.
Total Signals: The total number of buy or sell signals generated by the selected drawing mode.
TP1 Win Rate: The percentage of signals where the price reached Take Profit 1 (TP1) before hitting the Stop Loss.
TP2 Win Rate: The percentage of signals where the price reached Take Profit 2 (TP2) before hitting the Stop Loss.
TP3 Win Rate: The percentage of signals where the price reached Take Profit 3 (TP3) before hitting the Stop Loss. (Note: TP1, TP2, TP3 are in order of distance from entry, with TP3 being furthest.)
SL before any TP rate: This crucial metric shows the number of times the Stop Loss was hit / the percentage of total signals where the stop loss was triggered before any of the three Take Profit levels were reached. This gives you a clear picture of how often a trade resulted in a loss without ever moving into profit target territory.
Short Tutorial: How to Use the Indicator
Add to Chart: Open your TradingView chart, go to "Indicators," search for "Alpha - Combined Breakout," and add it to your chart.
Access Settings: Once added, click the gear icon next to the indicator name on your chart to open its settings.
Choose Your Signal Mode:
For UT Bot only: Uncheck "Draw Lines: Smart Money Only" and "Draw Lines: UT & Smart Money (Combined)". Ensure "Draw Lines: UT Only" is checked.
For Smart Money only: Uncheck "Draw Lines: UT Only" and "Draw Lines: UT & Smart Money (Combined)". Ensure "Draw Lines: Smart Money Only" is checked.
For Combined Signals: Check "Draw Lines: UT & Smart Money (Combined)". This will override the other two.
Adjust Parameters:
Start with default settings. Observe how the signals appear on your chosen asset and timeframe.
Refine Smart Money: If you see too many "noisy" market structure breaks, increase swingSize. If you want earlier breakouts, try "Wicks" for bosConfType.
Refine UT Bot: Adjust a_ut (Sensitivity) to get more or fewer UT Bot signals. Change c_ut (ATR Period) if you want larger or smaller TP/SL distances. Experiment with h_ut to see if Heikin Ashi smoothing suits your trading style.
Adjust TP/SL Multiplier: If using "Smart Money Only" mode, fine-tune sm_tp_sl_multiplier to set appropriate risk/reward levels.
Interpret Signals & Lines:
Buy/Sell Flags: These indicate the presence of a signal based on your selected drawing mode.
Entry Line (Blue Solid): This is where the signal was generated (usually the close price of the signal candle).
SL Line (Red/Green Solid): Your calculated stop loss level.
TP Lines (Dashed): Your three calculated take profit levels (TP1, TP2, TP3, where TP3 is the furthest target).
Smart Money Lines (BOS/CHoCH): These lines indicate horizontal levels where market structure breaks occurred. CHoCH labels might appear at the first structural break against the prior trend.
Monitor Dashboard: Pay attention to the dashboard in the top right corner. This dynamically updates to show the win rates for each TP and, crucially, the "SL before any TP rate." Use these statistics to evaluate the effectiveness of the indicator's signals under your current settings and chosen mode.
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Set Alerts (Optional): You can set up alerts for any of the specific signals (UT Bot Long/Short, Smart Money Bullish/Bearish, or the "Line Draw" combined signals) to notify you when they occur, even if you're not actively watching the chart.
By following this tutorial, you'll be able to effectively use and customize the "Alpha - Combined Breakout" indicator to suit your trading strategy.
SMA + RSI + Volume + ATR StrategySMA + RSI + Volume + ATR Strategy
1. Indicators Used:
SMA (Simple Moving Average): This is a trend-following indicator that calculates the average price of a security over a specified period (50 periods in this case). It's used to identify the overall trend of the market.
RSI (Relative Strength Index): This measures the speed and change of price movements. It tells us if the market is overbought (too high) or oversold (too low). Overbought is above 70 and oversold is below 30.
Volume: This is the amount of trading activity. A higher volume often indicates strong interest in a particular price move.
ATR (Average True Range): This measures volatility, or how much the price is moving in a given period. It helps us adjust stop losses and take profits based on market volatility.
2. Conditions for Entering Trades:
Buy Signal (Green Up Arrow):
Price is above the 50-period SMA (indicating an uptrend).
RSI is below 30 (indicating the market might be oversold or undervalued, signaling a potential reversal).
Current volume is higher than average volume (indicating strong interest in the move).
ATR is increasing (indicating higher volatility, suggesting that the market might be ready for a move).
Sell Signal (Red Down Arrow):
Price is below the 50-period SMA (indicating a downtrend).
RSI is above 70 (indicating the market might be overbought or overvalued, signaling a potential reversal).
Current volume is higher than average volume (indicating strong interest in the move).
ATR is increasing (indicating higher volatility, suggesting that the market might be ready for a move).
3. Take Profit & Stop Loss:
Take Profit: When a trade is made, the strategy will set a target price at a certain percentage above or below the entry price (1.5% in this case) to automatically exit the trade once that target is hit.
Stop Loss: If the price goes against the position, a stop loss is set at a percentage below or above the entry price (0.5% in this case) to limit losses.
4. Execution of Trades:
When the buy condition is met, the strategy will enter a long position (buying).
When the sell condition is met, the strategy will enter a short position (selling).
5. Visual Representation:
Green Up Arrow: Appears on the chart when the buy condition is met.
Red Down Arrow: Appears on the chart when the sell condition is met.
These arrows help you see at a glance when the strategy suggests you should buy or sell.
In Summary:
This strategy uses a combination of trend-following (SMA), momentum (RSI), volume, and volatility (ATR) to decide when to buy or sell a stock. It looks for opportunities when the market is either oversold (buy signal) or overbought (sell signal) and makes sure there’s enough volume and volatility to back up the move. It also includes take-profit and stop-loss levels to manage risk.
Martingale with MACD+KDJ opening conditionsStrategy Overview:
This strategy is based on a Martingale trading approach, incorporating MACD and KDJ indicators. It features pyramiding, trailing stops, and dynamic profit-taking mechanisms, suitable for both long and short trades. The strategy increases position size progressively using a Multiplier, a key feature of Martingale systems.
Key Concepts:
Martingale Strategy: A trading system where positions are doubled or increased after a loss to recover previous losses with a single successful trade. In this script, the position size is incremented using a Multiplier for each addition.
Pyramiding: Allows adding to existing trades when market conditions are favorable, enhancing profitability during trends.
Settings:
Basic Inputs:
Initial Order: Defines the starting size of the position.
Default: 150.0
MACD Settings: Customize the fast, slow, and signal smoothing lengths.
Default: Fast Length: 9, Slow Length: 26, Signal Smoothing: 9
KDJ Settings: Customize the length and smoothing parameters for KDJ.
Default: Length: 14, Smooth K: 3, Smooth D: 3
Max Additions: Sets the number of additional positions (pyramiding).
Default: 5 (Min: 1, Max: 10)
Position Sizing: Percent to add to positions on favorable conditions.
Default: 1.0%
Martingale Multiplier:
Add Multiplier: This value controls the scaling of additional positions according to the Martingale principle. After each loss, a new position is added, and its size is increased by the Multiplier factor. For example, with a multiplier of 2, each new addition will be twice as large as the previous one, accelerating recovery if the price moves favorably.
Default: 1.0 (no multiplication)
Can be adjusted up to 10x to aggressively increase position size after losses.
Trade Execution:
Long Trades:
Entry Condition: A long position is opened when the MACD line crosses over the signal line, and the KDJ’s %K crosses above %D.
Additions (Martingale): After the initial long position, new positions are added if the price drops by the defined percentage, and each new addition is increased using the Multiplier. This continues up to the set Max Additions.
Short Trades:
Entry Condition: A short position is opened when the MACD line crosses under the signal line, and the KDJ’s %K crosses below %D.
Additions (Martingale): After the initial short position, new positions are added if the price rises by the defined percentage, and each new addition is increased using the Multiplier.
Exit Conditions:
Take Profit: Exits are triggered when the price reaches the take-profit threshold.
Stop Loss: If the price moves unfavorably, the position will be closed at the set stop-loss level.
Trailing Stop: Adjusts dynamically as the price moves in favor of the trade to lock in profits.
On-Chart Visuals:
Long Signals: Blue triangles below the bars indicate long entries, and green triangles mark additional long positions.
Short Signals: Red triangles above the bars indicate short entries, and orange triangles mark additional short positions.
Information Table:
The strategy displays a table with key metrics:
Open Price: The entry price of the trade.
Average Price: The average price of the current position.
Additions: The number of additional positions taken.
Next Add Price: The price level for the next position.
Take Profit: The price at which profits will be taken.
Stop Loss: The stop-loss level to minimize risk.
Usage Instructions:
Adjust the parameters to your trading style using the input settings.
The Multiplier amplifies your position size after each addition, so use it cautiously, especially in volatile markets.
Monitor the signals and table on the chart for entry/exit decisions and trade management.
Larry Connors %b Strategy (Bollinger Band)Larry Connors’ %b Strategy is a mean-reversion trading approach that uses Bollinger Bands to identify buy and sell signals based on the %b indicator. This strategy was developed by Larry Connors, a renowned trader and author known for his systematic, data-driven trading methods, particularly those focusing on short-term mean reversion.
The %b indicator measures the position of the current price relative to the Bollinger Bands, which are volatility bands placed above and below a moving average. The strategy specifically targets times when prices are oversold within a long-term uptrend and aims to capture rebounds by buying at relatively low points and selling at relatively high points.
Strategy Rules
The basic rules of the %b Strategy are:
1. Trend Confirmation: The closing price must be above the 200-day moving average. This filter ensures that trades are made in alignment with a longer-term uptrend, thereby avoiding trades against the primary market trend.
2. Oversold Conditions: The %b indicator must be below 0.2 for three consecutive days. The %b value below 0.2 indicates that the price is near the lower Bollinger Band, suggesting an oversold condition.
3. Entry Signal: Enter a long position at the close when conditions 1 and 2 are met.
4. Exit Signal: Exit the position when the %b value closes above 0.8, signaling an overbought condition where the price is near the upper Bollinger Band.
How the Strategy Works
This strategy operates on the premise of mean reversion, which suggests that extreme price movements will revert to the mean over time. By entering positions when the %b value indicates an oversold condition (below 0.2) in a confirmed uptrend, the strategy attempts to capture short-term price rebounds. The exit rule (when %b is above 0.8) aims to lock in profits once the price reaches an overbought condition, often near the upper Bollinger Band.
Who Was Larry Connors?
Larry Connors is a well-known figure in the world of financial markets and trading. He co-authored several influential trading books, including “Short-Term Trading Strategies That Work” and “High Probability ETF Trading.” Connors is recognized for his quantitative approach, focusing on systematic, rules-based strategies that leverage historical data to validate trading edges.
His work primarily revolves around short-term trading strategies, often using technical indicators like RSI (Relative Strength Index), Bollinger Bands, and moving averages. Connors’ methodologies have been widely adopted by traders seeking structured approaches to exploit short-term inefficiencies in the market.
Risks of the Strategy
While the %b Strategy can be effective, particularly in mean-reverting markets, it is not without risks:
1. Mean Reversion Assumption: The strategy is based on the assumption that prices will revert to the mean. In trending or sharply falling markets, this reversion may not occur, leading to sustained losses.
2. False Signals in Choppy Markets: In volatile or sideways markets, the strategy may generate multiple false signals, resulting in whipsaw trades that can erode capital through frequent small losses.
3. No Stop Loss: The basic implementation of the strategy does not include a stop loss, which increases the risk of holding losing trades longer than intended, especially if the market continues to move against the position.
4. Performance During Market Crashes: During major market downturns, the strategy’s buy signals could be triggered frequently as prices decline, compounding losses without the presence of a risk management mechanism.
Scientific References and Theoretical Basis
The %b Strategy relies on the concept of mean reversion, which has been extensively studied in finance literature. Studies by Avellaneda and Lee (2010) and Bouchaud et al. (2018) have demonstrated that mean-reverting strategies can be profitable in specific market environments, particularly when combined with volatility filters like Bollinger Bands. However, the same studies caution that such strategies are highly sensitive to market conditions and often perform poorly during periods of prolonged trends.
Bollinger Bands themselves were popularized by John Bollinger and are widely used to assess price volatility and detect potential overbought and oversold conditions. The %b value is a critical part of this analysis, as it standardizes the position of price relative to the bands, making it easier to compare conditions across different securities and time frames.
Conclusion
Larry Connors’ %b Strategy is a well-known mean-reversion technique that leverages Bollinger Bands to identify buying opportunities in uptrending markets when prices are temporarily oversold. While the strategy can be effective under the right conditions, traders should be aware of its limitations and risks, particularly in trending or highly volatile markets. Incorporating risk management techniques, such as stop losses, could help mitigate some of these risks, making the strategy more robust against adverse market conditions.
Futures Risk CalculatorFutures Risk Calculator Script - Description
The Futures Risk Calculator (FRC) is a comprehensive tool designed to help traders effectively manage risk when trading futures contracts. This script allows users to calculate risk/reward ratios directly on the chart by specifying their entry price and stop loss. It's an ideal tool for futures traders who want to quantify their potential losses and gains with precision, based on their trading account size and the number of contracts they trade.
What the Script Does:
1. Risk and Reward Calculation:
The script calculates your total risk in dollars and as a percentage of your account size based on the entry and stop-loss prices you input.
It also calculates two key levels where potential reward (Take Profit 1 and Take Profit 2) can be expected, helping you assess the reward-to-risk ratio for any trade.
2. Customizable Settings:
You can specify the size of your trading account (available $ for Futures trading) and the number of futures contracts you're trading. This allows for tailored risk management that reflects your exact trading conditions.
3. Live Chart Integration:
You add the script to your chart after opening a futures chart in TradingView. Simply click on the chart to set your Entry Price and Stop Loss. The script will instantly calculate and display the risk and reward levels based on the points you set.
Adjusting the entry and stop-loss points later is just as easy: drag and drop the levels directly on the chart, and the risk and reward calculations update automatically.
4. Futures Contract Support:
The script is pre-configured with a list of popular futures symbols (like ES, NQ, CL, GC, and more). If your preferred futures contract isn’t in the list, you can easily add it by modifying the script.
The script uses each symbol’s point value to ensure precise risk calculations, providing you with an accurate dollar risk and potential reward based on the specific contract you're trading.
How to Use the Script:
1. Apply the Script to a Futures Chart:
Open a futures contract chart in TradingView.
Add the Futures Risk Calculator (FRC) script as an indicator.
2. Set Entry and Stop Loss:
Upon applying the script, it will prompt you to select your entry price by clicking the chart where you plan to enter the market.
Next, click on the chart to set your stop-loss level.
The script will then calculate your total risk in dollars and as a percentage of your account size.
3. View Risk, Reward, and (Take Profit):
You can immediately see visual lines representing your entry, stop loss, and the calculated reward-to-risk ratio levels (Take Profit 1 and Take Profit 2).
If you want to adjust the entry or stop loss after plotting them, simply move the points on
the chart, and the script will recalculate everything for you.
4. Configure Account and Contracts:
In the script settings, you can enter your account size and adjust the number of contracts you are trading. These inputs allow the script to calculate risk in monetary terms and as a percentage, making it easier to manage your risk effectively.
5. Understand the Information in the Table:
Once you apply the script, a table will appear in the top-right corner of your chart, providing you with key information about your futures contract and the trade setup. Here's what each field represents:
Account Size: Displays your total account value, which you can set in the script's settings.
Future: Shows the selected futures symbol, along with key details such as its tick size and point value. This gives you a clear understanding of how much one point or tick is worth in dollar terms.
Entry Price: The exact price at which you plan to enter the trade, displayed in green.
Stop Loss Price: The price level where you plan to exit the trade if the market moves against you, shown in red.
Contracts: The number of futures contracts you are trading, which you can adjust in the settings.
Risk: Highlighted in orange, this field shows your total risk in dollars, as well as the percentage risk based on your account size. This is a crucial value to help you stay within your risk tolerance and manage your trades effectively.
GKD-C RSI of Fast Discrete Cosine Transform [Loxx]Giga Kaleidoscope GKD-C RSI of Fast Discrete Cosine Transform is a Confirmation module included in Loxx's "Giga Kaleidoscope Modularized Trading System".
█ Giga Kaleidoscope Modularized Trading System
What is Loxx's "Giga Kaleidoscope Modularized Trading System"?
The Giga Kaleidoscope Modularized Trading System is a trading system built on the philosophy of the NNFX (No Nonsense Forex) algorithmic trading.
What is the NNFX algorithmic trading strategy?
The NNFX (No-Nonsense Forex) trading system is a comprehensive approach to Forex trading that is designed to simplify the process and remove the confusion and complexity that often surrounds trading. The system was developed by a Forex trader who goes by the pseudonym "VP" and has gained a significant following in the Forex community.
The NNFX trading system is based on a set of rules and guidelines that help traders make objective and informed decisions. These rules cover all aspects of trading, including market analysis, trade entry, stop loss placement, and trade management.
Here are the main components of the NNFX trading system:
1. Trading Philosophy: The NNFX trading system is based on the idea that successful trading requires a comprehensive understanding of the market, objective analysis, and strict risk management. The system aims to remove subjective elements from trading and focuses on objective rules and guidelines.
2. Technical Analysis: The NNFX trading system relies heavily on technical analysis and uses a range of indicators to identify high-probability trading opportunities. The system uses a combination of trend-following and mean-reverting strategies to identify trades.
3. Market Structure: The NNFX trading system emphasizes the importance of understanding the market structure, including price action, support and resistance levels, and market cycles. The system uses a range of tools to identify the market structure, including trend lines, channels, and moving averages.
4. Trade Entry: The NNFX trading system has strict rules for trade entry. The system uses a combination of technical indicators to identify high-probability trades, and traders must meet specific criteria to enter a trade.
5. Stop Loss Placement: The NNFX trading system places a significant emphasis on risk management and requires traders to place a stop loss order on every trade. The system uses a combination of technical analysis and market structure to determine the appropriate stop loss level.
6. Trade Management: The NNFX trading system has specific rules for managing open trades. The system aims to minimize risk and maximize profit by using a combination of trailing stops, take profit levels, and position sizing.
Overall, the NNFX trading system is designed to be a straightforward and easy-to-follow approach to Forex trading that can be applied by traders of all skill levels.
Core components of an NNFX algorithmic trading strategy
The NNFX algorithm is built on the principles of trend, momentum, and volatility. There are six core components in the NNFX trading algorithm:
1. Volatility - price volatility; e.g., Average True Range, True Range Double, Close-to-Close, etc.
2. Baseline - a moving average to identify price trend
3. Confirmation 1 - a technical indicator used to identify trends
4. Confirmation 2 - a technical indicator used to identify trends
5. Continuation - a technical indicator used to identify trends
6. Volatility/Volume - a technical indicator used to identify volatility/volume breakouts/breakdown
7. Exit - a technical indicator used to determine when a trend is exhausted
What is Volatility in the NNFX trading system?
In the NNFX (No Nonsense Forex) trading system, ATR (Average True Range) is typically used to measure the volatility of an asset. It is used as a part of the system to help determine the appropriate stop loss and take profit levels for a trade. ATR is calculated by taking the average of the true range values over a specified period.
True range is calculated as the maximum of the following values:
-Current high minus the current low
-Absolute value of the current high minus the previous close
-Absolute value of the current low minus the previous close
ATR is a dynamic indicator that changes with changes in volatility. As volatility increases, the value of ATR increases, and as volatility decreases, the value of ATR decreases. By using ATR in NNFX system, traders can adjust their stop loss and take profit levels according to the volatility of the asset being traded. This helps to ensure that the trade is given enough room to move, while also minimizing potential losses.
Other types of volatility include True Range Double (TRD), Close-to-Close, and Garman-Klass
What is a Baseline indicator?
The baseline is essentially a moving average, and is used to determine the overall direction of the market.
The baseline in the NNFX system is used to filter out trades that are not in line with the long-term trend of the market. The baseline is plotted on the chart along with other indicators, such as the Moving Average (MA), the Relative Strength Index (RSI), and the Average True Range (ATR).
Trades are only taken when the price is in the same direction as the baseline. For example, if the baseline is sloping upwards, only long trades are taken, and if the baseline is sloping downwards, only short trades are taken. This approach helps to ensure that trades are in line with the overall trend of the market, and reduces the risk of entering trades that are likely to fail.
By using a baseline in the NNFX system, traders can have a clear reference point for determining the overall trend of the market, and can make more informed trading decisions. The baseline helps to filter out noise and false signals, and ensures that trades are taken in the direction of the long-term trend.
What is a Confirmation indicator?
Confirmation indicators are technical indicators that are used to confirm the signals generated by primary indicators. Primary indicators are the core indicators used in the NNFX system, such as the Average True Range (ATR), the Moving Average (MA), and the Relative Strength Index (RSI).
The purpose of the confirmation indicators is to reduce false signals and improve the accuracy of the trading system. They are designed to confirm the signals generated by the primary indicators by providing additional information about the strength and direction of the trend.
Some examples of confirmation indicators that may be used in the NNFX system include the Bollinger Bands, the MACD (Moving Average Convergence Divergence), and the Stochastic Oscillator. These indicators can provide information about the volatility, momentum, and trend strength of the market, and can be used to confirm the signals generated by the primary indicators.
In the NNFX system, confirmation indicators are used in combination with primary indicators and other filters to create a trading system that is robust and reliable. By using multiple indicators to confirm trading signals, the system aims to reduce the risk of false signals and improve the overall profitability of the trades.
What is a Continuation indicator?
In the NNFX (No Nonsense Forex) trading system, a continuation indicator is a technical indicator that is used to confirm a current trend and predict that the trend is likely to continue in the same direction. A continuation indicator is typically used in conjunction with other indicators in the system, such as a baseline indicator, to provide a comprehensive trading strategy.
What is a Volatility/Volume indicator?
Volume indicators, such as the On Balance Volume (OBV), the Chaikin Money Flow (CMF), or the Volume Price Trend (VPT), are used to measure the amount of buying and selling activity in a market. They are based on the trading volume of the market, and can provide information about the strength of the trend. In the NNFX system, volume indicators are used to confirm trading signals generated by the Moving Average and the Relative Strength Index. Volatility indicators include Average Direction Index, Waddah Attar, and Volatility Ratio. In the NNFX trading system, volatility is a proxy for volume and vice versa.
By using volume indicators as confirmation tools, the NNFX trading system aims to reduce the risk of false signals and improve the overall profitability of trades. These indicators can provide additional information about the market that is not captured by the primary indicators, and can help traders to make more informed trading decisions. In addition, volume indicators can be used to identify potential changes in market trends and to confirm the strength of price movements.
What is an Exit indicator?
The exit indicator is used in conjunction with other indicators in the system, such as the Moving Average (MA), the Relative Strength Index (RSI), and the Average True Range (ATR), to provide a comprehensive trading strategy.
The exit indicator in the NNFX system can be any technical indicator that is deemed effective at identifying optimal exit points. Examples of exit indicators that are commonly used include the Parabolic SAR, the Average Directional Index (ADX), and the Chandelier Exit.
The purpose of the exit indicator is to identify when a trend is likely to reverse or when the market conditions have changed, signaling the need to exit a trade. By using an exit indicator, traders can manage their risk and prevent significant losses.
In the NNFX system, the exit indicator is used in conjunction with a stop loss and a take profit order to maximize profits and minimize losses. The stop loss order is used to limit the amount of loss that can be incurred if the trade goes against the trader, while the take profit order is used to lock in profits when the trade is moving in the trader's favor.
Overall, the use of an exit indicator in the NNFX trading system is an important component of a comprehensive trading strategy. It allows traders to manage their risk effectively and improve the profitability of their trades by exiting at the right time.
How does Loxx's GKD (Giga Kaleidoscope Modularized Trading System) implement the NNFX algorithm outlined above?
Loxx's GKD v1.0 system has five types of modules (indicators/strategies). These modules are:
1. GKD-BT - Backtesting module (Volatility, Number 1 in the NNFX algorithm)
2. GKD-B - Baseline module (Baseline and Volatility/Volume, Numbers 1 and 2 in the NNFX algorithm)
3. GKD-C - Confirmation 1/2 and Continuation module (Confirmation 1/2 and Continuation, Numbers 3, 4, and 5 in the NNFX algorithm)
4. GKD-V - Volatility/Volume module (Confirmation 1/2, Number 6 in the NNFX algorithm)
5. GKD-E - Exit module (Exit, Number 7 in the NNFX algorithm)
(additional module types will added in future releases)
Each module interacts with every module by passing data between modules. Data is passed between each module as described below:
GKD-B => GKD-V => GKD-C(1) => GKD-C(2) => GKD-C(Continuation) => GKD-E => GKD-BT
That is, the Baseline indicator passes its data to Volatility/Volume. The Volatility/Volume indicator passes its values to the Confirmation 1 indicator. The Confirmation 1 indicator passes its values to the Confirmation 2 indicator. The Confirmation 2 indicator passes its values to the Continuation indicator. The Continuation indicator passes its values to the Exit indicator, and finally, the Exit indicator passes its values to the Backtest strategy.
This chaining of indicators requires that each module conform to Loxx's GKD protocol, therefore allowing for the testing of every possible combination of technical indicators that make up the six components of the NNFX algorithm.
What does the application of the GKD trading system look like?
Example trading system:
Backtest: Strategy with 1-3 take profits, trailing stop loss, multiple types of PnL volatility, and 2 backtesting styles
Baseline: Hull Moving Average
Volatility/Volume: Hurst Exponent
Confirmation 1: RSI of Fast Discrete Cosine Transform as shown on the chart above
Confirmation 2: Williams Percent Range
Continuation: Fisher Transform
Exit: Rex Oscillator
Each GKD indicator is denoted with a module identifier of either: GKD-BT, GKD-B, GKD-C, GKD-V, or GKD-E. This allows traders to understand to which module each indicator belongs and where each indicator fits into the GKD protocol chain.
Giga Kaleidoscope Modularized Trading System Signals (based on the NNFX algorithm)
Standard Entry
1. GKD-C Confirmation 1 Signal
2. GKD-B Baseline agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume agrees
Baseline Entry
1. GKD-B Baseline signal
2. GKD-C Confirmation 1 agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume agrees
6. GKD-C Confirmation 1 signal was less than 7 candles prior
Continuation Entry
1. Standard Entry, Baseline Entry, or Pullback; entry triggered previously
2. GKD-B Baseline hasn't crossed since entry signal trigger
3. GKD-C Confirmation Continuation Indicator signals
4. GKD-C Confirmation 1 agrees
5. GKD-B Baseline agrees
6. GKD-C Confirmation 2 agrees
1-Candle Rule Standard Entry
1. GKD-C Confirmation 1 signal
2. GKD-B Baseline agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
Next Candle:
1. Price retraced (Long: close < close or Short: close > close )
2. GKD-B Baseline agrees
3. GKD-C Confirmation 1 agrees
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume agrees
1-Candle Rule Baseline Entry
1. GKD-B Baseline signal
2. GKD-C Confirmation 1 agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 1 signal was less than 7 candles prior
Next Candle:
1. Price retraced (Long: close < close or Short: close > close )
2. GKD-B Baseline agrees
3. GKD-C Confirmation 1 agrees
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume Agrees
PullBack Entry
1. GKD-B Baseline signal
2. GKD-C Confirmation 1 agrees
3. Price is beyond 1.0x Volatility of Baseline
Next Candle:
1. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
3. GKD-C Confirmation 1 agrees
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume Agrees
█ Fast Discrete Cosine Transform
What is the Fast Discrete Cosine Transform?
Algolib is a C++ library for algorithmic trading that provides various algorithms for processing and analyzing financial data. The library includes a Fast Discrete Cosine Transform (FDCT) implementation, which is a fast version of the Discrete Cosine Transform (DCT) algorithm used for signal processing and data compression.
The FDCT implementation in Algolib is based on the FFT (Fast Fourier Transform) algorithm, which is a widely used method for computing the DCT. The implementation is optimized for performance and can handle large datasets efficiently. It uses the standard divide-and-conquer approach to compute the DCT recursively and combines the resulting coefficients to obtain the final DCT of the input signal.
The input to the FDCT algorithm in Algolib is a one-dimensional array of real numbers, which represents a time series or a financial signal. The algorithm then computes the DCT of the input sequence and returns a one-dimensional array of DCT coefficients, which represent the frequency components of the signal.
The implementation of the FDCT algorithm in Algolib uses C++ templates to provide a generic implementation that can work with different data types. It also includes various optimizations, such as loop unrolling, to improve the performance of the algorithm.
The steps involved in the FDCT algorithm in Algolib are:
-Divide the input sequence into even and odd parts.
-Compute the DCT of the even and odd parts recursively.
-Combine the DCT coefficients of the even and odd parts to obtain the final DCT coefficients.
-The implementation of the FDCT algorithm in Algolib uses the FFTW (Fastest Fourier Transform in the West) library to perform the FFT computations, which is a highly optimized library for computing Fourier transforms.
In summary, the Fast Discrete Cosine Transform implementation in Algolib is a fast and efficient implementation of the DCT algorithm, which is used for processing financial signals and time series data. The implementation is optimized for performance and uses the FFT algorithm for fast computation. The implementation is generic and can work with different data types, and includes optimizations such as loop unrolling to improve the performance of the algorithm.
What is the Fast Discrete Cosine Transform in terms of Forex trading?
The Fast Discrete Cosine Transform (FDCT) is an algorithm used for signal processing and data compression that can also be applied in trading forex. The FDCT is used to transform financial data into a set of coefficients that represent the data in terms of cosine functions of different frequencies. These coefficients can be used to analyze the frequency components of financial signals and to develop trading strategies based on these components.
In trading forex, the FDCT can be applied to various financial signals, such as price data, volume data, and technical indicators. By applying the FDCT to these signals, traders can identify the dominant frequency components of the signals and use this information to develop trading strategies.
For example, traders can use the FDCT to identify cycles in the market and use this information to develop trend-following strategies. The FDCT can also be used to identify short-term fluctuations in the market and develop mean-reversion strategies based on these fluctuations.
The FDCT can also be used in combination with other technical analysis tools, such as moving averages, to improve the accuracy of trading signals. For example, traders can apply the FDCT to the moving average of a financial signal to identify the dominant frequency components of the moving average and use this information to develop trading signals.
The FDCT can also be used in conjunction with machine learning algorithms to develop predictive models for financial markets. By applying the FDCT to financial data and using the resulting coefficients as inputs to a machine learning algorithm, traders can develop models that predict future price movements and identify profitable trading opportunities.
In summary, the FDCT can be applied in trading forex to analyze the frequency components of financial signals and develop trading strategies based on these components. The FDCT can be used in conjunction with other technical analysis tools and machine learning algorithms to improve the accuracy of trading signals and develop predictive models for financial markets.
What is the Fast Discrete Cosine Transform in terms of Forex trading?
The Fast Discrete Cosine Transform (FDCT) is an algorithm used for signal processing and data compression that can also be applied in trading forex. The FDCT is used to transform financial data into a set of coefficients that represent the data in terms of cosine functions of different frequencies. These coefficients can be used to analyze the frequency components of financial signals and to develop trading strategies based on these components.
In trading forex, the FDCT can be applied to various financial signals, such as price data, volume data, and technical indicators. By applying the FDCT to these signals, traders can identify the dominant frequency components of the signals and use this information to develop trading strategies.
For example, traders can use the FDCT to identify cycles in the market and use this information to develop trend-following strategies. The FDCT can also be used to identify short-term fluctuations in the market and develop mean-reversion strategies based on these fluctuations.
The FDCT can also be used in combination with other technical analysis tools, such as moving averages, to improve the accuracy of trading signals. For example, traders can apply the FDCT to the moving average of a financial signal to identify the dominant frequency components of the moving average and use this information to develop trading signals.
The FDCT can also be used in conjunction with machine learning algorithms to develop predictive models for financial markets. By applying the FDCT to financial data and using the resulting coefficients as inputs to a machine learning algorithm, traders can develop models that predict future price movements and identify profitable trading opportunities.
In summary, the FDCT can be applied in trading forex to analyze the frequency components of financial signals and develop trading strategies based on these components. The FDCT can be used in conjunction with other technical analysis tools and machine learning algorithms to improve the accuracy of trading signals and develop predictive models for financial markets.
█ Relative Strength Index (RSI)
This indicator contains 7 different types of RSI .
RSX
Regular
Slow
Rapid
Harris
Cuttler
Ehlers Smoothed
What is RSI?
RSI stands for Relative Strength Index . It is a technical indicator used to measure the strength or weakness of a financial instrument's price action.
The RSI is calculated based on the price movement of an asset over a specified period of time, typically 14 days, and is expressed on a scale of 0 to 100. The RSI is considered overbought when it is above 70 and oversold when it is below 30.
Traders and investors use the RSI to identify potential buy and sell signals. When the RSI indicates that an asset is oversold, it may be considered a buying opportunity, while an overbought RSI may signal that it is time to sell or take profits.
It's important to note that the RSI should not be used in isolation and should be used in conjunction with other technical and fundamental analysis tools to make informed trading decisions.
What is RSX?
Jurik RSX is a technical analysis indicator that is a variation of the Relative Strength Index Smoothed ( RSX ) indicator. It was developed by Mark Jurik and is designed to help traders identify trends and momentum in the market.
The Jurik RSX uses a combination of the RSX indicator and an adaptive moving average (AMA) to smooth out the price data and reduce the number of false signals. The adaptive moving average is designed to adjust the smoothing period based on the current market conditions, which makes the indicator more responsive to changes in price.
The Jurik RSX can be used to identify potential trend reversals and momentum shifts in the market. It oscillates between 0 and 100, with values above 50 indicating a bullish trend and values below 50 indicating a bearish trend . Traders can use these levels to make trading decisions, such as buying when the indicator crosses above 50 and selling when it crosses below 50.
The Jurik RSX is a more advanced version of the RSX indicator, and while it can be useful in identifying potential trade opportunities, it should not be used in isolation. It is best used in conjunction with other technical and fundamental analysis tools to make informed trading decisions.
What is Slow RSI?
Slow RSI is a variation of the traditional Relative Strength Index ( RSI ) indicator. It is a more smoothed version of the RSI and is designed to filter out some of the noise and short-term price fluctuations that can occur with the standard RSI .
The Slow RSI uses a longer period of time than the traditional RSI , typically 21 periods instead of 14. This longer period helps to smooth out the price data and makes the indicator less reactive to short-term price fluctuations.
Like the traditional RSI , the Slow RSI is used to identify potential overbought and oversold conditions in the market. It oscillates between 0 and 100, with values above 70 indicating overbought conditions and values below 30 indicating oversold conditions. Traders often use these levels as potential buy and sell signals.
The Slow RSI is a more conservative version of the RSI and can be useful in identifying longer-term trends in the market. However, it can also be slower to respond to changes in price, which may result in missed trading opportunities. Traders may choose to use a combination of both the Slow RSI and the traditional RSI to make informed trading decisions.
What is Rapid RSI?
Same as regular RSI but with a faster calculation method
What is Harris RSI?
Harris RSI is a technical analysis indicator that is a variation of the Relative Strength Index ( RSI ). It was developed by Larry Harris and is designed to help traders identify potential trend changes and momentum shifts in the market.
The Harris RSI uses a different calculation formula compared to the traditional RSI . It takes into account both the opening and closing prices of a financial instrument, as well as the high and low prices. The Harris RSI is also normalized to a range of 0 to 100, with values above 50 indicating a bullish trend and values below 50 indicating a bearish trend .
Like the traditional RSI , the Harris RSI is used to identify potential overbought and oversold conditions in the market. It oscillates between 0 and 100, with values above 70 indicating overbought conditions and values below 30 indicating oversold conditions. Traders often use these levels as potential buy and sell signals.
The Harris RSI is a more advanced version of the RSI and can be useful in identifying longer-term trends in the market. However, it can also generate more false signals than the standard RSI . Traders may choose to use a combination of both the Harris RSI and the traditional RSI to make informed trading decisions.
What is Cuttler RSI?
Cuttler RSI is a technical analysis indicator that is a variation of the Relative Strength Index ( RSI ). It was developed by Curt Cuttler and is designed to help traders identify potential trend changes and momentum shifts in the market.
The Cuttler RSI uses a different calculation formula compared to the traditional RSI . It takes into account the difference between the closing price of a financial instrument and the average of the high and low prices over a specified period of time. This difference is then normalized to a range of 0 to 100, with values above 50 indicating a bullish trend and values below 50 indicating a bearish trend .
Like the traditional RSI , the Cuttler RSI is used to identify potential overbought and oversold conditions in the market. It oscillates between 0 and 100, with values above 70 indicating overbought conditions and values below 30 indicating oversold conditions. Traders often use these levels as potential buy and sell signals.
The Cuttler RSI is a more advanced version of the RSI and can be useful in identifying longer-term trends in the market. However, it can also generate more false signals than the standard RSI . Traders may choose to use a combination of both the Cuttler RSI and the traditional RSI to make informed trading decisions.
What is Ehlers Smoothed RSI?
Ehlers smoothed RSI is a technical analysis indicator that is a variation of the Relative Strength Index ( RSI ). It was developed by John Ehlers and is designed to help traders identify potential trend changes and momentum shifts in the market.
The Ehlers smoothed RSI uses a different calculation formula compared to the traditional RSI . It uses a smoothing algorithm that is designed to reduce the noise and random fluctuations that can occur with the standard RSI . The smoothing algorithm is based on a concept called "digital signal processing" and is intended to improve the accuracy of the indicator.
Like the traditional RSI , the Ehlers smoothed RSI is used to identify potential overbought and oversold conditions in the market. It oscillates between 0 and 100, with values above 70 indicating overbought conditions and values below 30 indicating oversold conditions. Traders often use these levels as potential buy and sell signals.
The Ehlers smoothed RSI can be useful in identifying longer-term trends and momentum shifts in the market. However, it can also generate more false signals than the standard RSI . Traders may choose to use a combination of both the Ehlers smoothed RSI and the traditional RSI to make informed trading decisions.
█ GKD-C RSI of Fast Discrete Cosine Transform
What is the RSI of Fast Discrete Cosine Transform in terms of Forex trading?
The Relative Strength Index (RSI) is a popular technical indicator used in trading forex to measure the strength of a trend and identify potential trend reversals. While the Fast Discrete Cosine Transform (FDCT) is not directly related to the RSI, it can be used to analyze the frequency components of the price data used to calculate the RSI and improve its accuracy.
The RSI is calculated by comparing the average gains and losses of a financial instrument over a given period of time. The RSI value ranges from 0 to 100, with values above 70 indicating an overbought market and values below 30 indicating an oversold market.
One limitation of the RSI is that it only considers the average gains and losses over a fixed period of time, which may not capture the complex patterns and dynamics of financial markets. This is where the FDCT can be useful.
By applying the FDCT to the price data used to calculate the RSI, traders can identify the dominant frequency components of the price data and use this information to adjust the RSI calculation. For example, traders can weight the gains and losses based on the frequency components identified by the FDCT, giving more weight to the dominant frequencies and less weight to the lower frequencies.
This approach can improve the accuracy of the RSI calculation and provide traders with more reliable signals for identifying trends and potential trend reversals. Traders can also use the frequency components identified by the FDCT to develop more advanced trading strategies, such as identifying cycles in the market and using this information to develop trend-following strategies.
In summary, while the FDCT is not directly related to the RSI, it can be used to analyze the frequency components of the price data used to calculate the RSI and improve its accuracy. Traders can use the FDCT to identify dominant frequency components and adjust the RSI calculation accordingly, providing more reliable signals for identifying trends and potential trend reversals.
This indicator has period lengths that are powers of powers of 2. There is also a features to increase the resolution of the FDCT.
Requirements
Inputs
Confirmation 1 and Solo Confirmation: GKD-V Volatility / Volume indicator
Confirmation 2: GKD-C Confirmation indicator
Outputs
Confirmation 2 and Solo Confirmation Complex: GKD-E Exit indicator
Confirmation 1: GKD-C Confirmation indicator
Continuation: GKD-E Exit indicator
Solo Confirmation Simple: GKD-BT Backtest strategy
Additional features will be added in future releases.
