KNN Regression [SS]Another indicator release, I know.
But note, this isn't intended to be a stand-alone indicator, this is just a functional addition for those who program Machine Learning algorithms in Pinescript! There isn't enough content here to merit creating a library for (it's only 1 function), but it's a really useful function for those who like machine learning and Nearest Known Neighbour Algos (or KNN).
About the indicator:
This indicator creates a function to perform KNN-based regression.
In contrast to traditional linear regression, KNN-based regression has the following advantages over linear regression:
Advantages of KNN Regression vs. Linear Regression:
🎯 Non-linearity: KNN is a non-parametric method, meaning it makes no assumptions about the underlying data distribution. This allows it to capture non-linear relationships between features and the target variable.
🎯Simple Implementation: KNN is conceptually simple and easy to understand. It doesn't require the estimation of parameters, making it straightforward to implement.
🎯Robust to Outliers: KNN is less sensitive to outliers compared to linear regression. Outliers can have a significant impact on linear regression models, but KNN tends to be less affected.
Disadvantages of KNN Regression vs. Linear Regression:
🎯 Resource Intensive for Computation: Because KNN operates on identifying the nearest neighbors in a dataset, each new instance has to be searched for and identified within the dataset, vs. linear regression which can create a coefficient-based model and draw from the coefficient for each new data point.
🎯Curse of Dimensionality: KNN performance can degrade with an increasing number of features, leading to a "curse of dimensionality." This is because, in high-dimensional spaces, the concept of proximity becomes less meaningful.
🎯Sensitive to Noise: KNN can be sensitive to noisy data, as it relies on the local neighborhood for predictions. Noisy or irrelevant features may affect its performance.
Which is better?
I am very biased, coming from a statistics background. I will always love linear regression and will always prefer it over KNN. But depending on what you want to accomplish, KNN makes sense. If you are using highly skewed data or data that you cannot identify linearity in, KNN is probably preferable.
However, if you require precise estimations of ranges and outliers, such as creating co-integration models, I would advise sticking with linear regression. However, out of curiosity, I exported the function into a separate dummy indicator and pulled in data from QQQ to predict SPY close, and the results are actually very admirable:
And plotted with showing the standard error variance:
Pretty impressive, I must say I was a little shocked, it's really giving linear regression a run for its money. In school I was taught LinReg is the gold standard for modeling, nothing else compares. So as with most things in trading, this is challenging some biases of mine ;).
Functionality of the function
I have permitted 3 types of KNN regression. Traditional KNN regression, as I understand it, revolves around clustering. ( Clustering refers to identifying a cluster, normally 3, of identical cases and averaging out the Dependent variable in each of those cases) . Clustering is great, but when you are working with a finite dataset, identifying exact matches for 2 or 3 clusters can be challenging when you are only looking back at 500 candles or 1000 candles, etc.
So to accommodate this, I have added a functionality to clustering called "Tolerance". And it allows you to set a tolerance level for your Euclidean distance parameters. As a default, I have tested this with a default of 0.5 and it has worked great and no need to change even when working with large numbers such as NQ and ES1!.
However, I have added 2 additional regression types that can be done with KNN.
#1 One is a regression by the last IDENTICAL instance, which will find the most recent instance of a similar Independent variable and pull the Dependent variable from that instance. Or
#2 Average from all IDENTICAL instances.
Using the function
The code has the instructions for integrating the function into your own code, the parameters, and such, so I won't exhaust you with the boring details about that here.
But essentially, it exports 3, float variables, the Result, the Correlation, and the simplified R2.
As this is KNN regression, there are no coefficients, slopes, or intercepts and you do not need to test for linearity before applying it.
Also, the output can be a bit choppy, so I tend to like to throw in a bit of smoothing using the ta.sma function at a deault of 14.
For example, here is SPY from QQQ smoothed as a 14 SMA:
And it is unsmoothed:
It seems relatively similar but it does make a bit of an aesthetic difference. And if you are doing it over 14, there is no data loss and it is still quite reactive to changes in data.
And that's it! Hopefully you enjoy and find some interesting uses for this function in your own scripts :-).
Safe trades everyone!
Buscar en scripts para "ha溢价率"
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 :)
hamster-bot MRS 2 (simplified version) MRS - Mean Reversion Strategy (Countertrend) (Envelope strategy)
This script does not claim to be unique and does not mislead anyone. Even the unattractive backtest result is attached. The source code is open. The idea has been described many times in various sources. But at the same time, their collection in one place provides unique opportunities.
Published by popular demand and for ease of use. so that users can track the development of the script and can offer their ideas in the comments. Otherwise, you have to communicate in several telegram chats.
Representative of the family of counter-trend strategies. The basis of the strategy is Mean reversion . You can also read about the Envelope strategy .
Mean reversion , or reversion to the mean, is a theory used in finance that suggests that asset price volatility and historical returns eventually will revert to the long-run mean or average level of the entire dataset.
The strategy is very simple. Has very few settings. Good for beginners to get acquainted with algorithmic trading. A simple adjustment will help avoid overfitting. There are many variations of this strategy, but for understanding it is better to start with this implementation.
Principle of operation.
1)
A conventional MA is being built. (fuchsia line). A limit order is placed on this line to close the position.
2)
(green line) A limit order is placed on this line to open a long position
3)
(red line) A limit order is placed on this line to open a short position
Attention!
Please note that a limit order is used. Conclude that the strategy has a limited capacity. And the results obtained on low-liquid instruments will be too high in the tester. On real auctions there will be a different result.
Note for testing the strategy in the spot market:
When testing in the spot market, do not include both long and short at the same time. It is recommended to test only the long mode on the spot. Short mode for more advanced users.
Settings:
Available types of moving averages:
SMA
EMA
TEMA - triple exponential moving average
DEMA - Double Exponential Moving Average
ZLEMA - Zero lag exponential moving average
WMA - weighted moving average
Hma - Hull Moving Average
Thma - Triple Exponential Hull Moving Average
Ehma - Exponential Hull Moving Average
H - MA built based on highs for n candles | ta.highest(len)
L - MA built based on lows for n candles | ta.lowest(len)
DMA - Donchian Moving Average
A Kalman filter can be applied to all MA
The peculiarity of the strategy is a large selection of MA and the possibility of shifting lines. You can set up a reverse trending strategy on the Donchian channel for example.
Use Long - enable/disable opening a Long position
Use Short - enable/disable opening a Short position
Lot Long, % - % allocated from the deposit for opening a Long position. In the spot market, do not use % greater than 100%
Lot Short, % - allocated % of the deposit for opening a Short position
Start date - the beginning of the testing period
End date - the end of the testing period (Example: only August 2020 can be tested)
Mul - multiplier. Used to offset lines. Example:
Mul = 0.99 is shift -1%
Mul = 1.01 is shift +1%
Non-strict recommendations:
1) Test the SPOT market on crypto exchanges. (The countertrend strategy has liquidation risk on futures)
2) Symbols altcoin/bitcoin or altcoin/altcoin. Example: ETH/BTC or DOGE/ETH
3) Timeframe is usually 1 hour
If the script passes moderation, I will supplement it by adding separate settings for closing long and short positions according to their MA
OTT CollectionIf you are not yet familiar with OTT, this script could provide an introduction to help you get started.
"Optimized Trend Tracker" (OTT) is an effective trend-following indicator created by Anıl Özekşi . It aims to detect the current trend direction based on an elegant mathematical construct. The key defining characteristic of OTT is its reliance on a trailing-stop mechanism. This enables OTT to identify price movements and follow the price until a reversal occurs. The widespread adoption of OTT in various algo-trading platforms has fostered the development of diverse applications of the indicator over time. Examining its history, eight distinct applications emerge.
1) OTT - Optimized Trend Tracker
2) TOTT - Twin Ott
3) OTT Channel - Half Channel & Fibonacci Channel
4) RISOTTO - Rsi Ott
5) SOTT - Stochastic Ott
6) HOTT & LOTT - Highest-Lowest Ott + Sum Option
7) ROTT - Relative Ott
8) FT - "Fırsatçı" Trend
BONUS: RTR - Relative True Range
Each system functions as an independent indicator and the "OTT Collection" is intended to present all of them in a single script.
ORIGINALITY
Primarily, this script introduces previously unreleased OTT applications on Tradingview (RISOTTO, ROTT, FT). In contrast to previously published examples that treat OTT as a variable, this script portrays OTT as a function, rendering it adaptable for more intricate computations. Consequently, OTT has evolved into a versatile tool capable of facilitating complex analyses. Furthermore, this script offers an innovative feature that permits the blocking of consecutive signals in the same direction, catering to user preferences. (This feature is crucial for all indicators utilizing band structures such as TOTT and HOTT-LOTT).
USAGE
It is simple to use. The settings section of the indicator groups the parameters. In first group, the System parameter allows you to select the OTT system you want to display on the chart. Activating the Pyramiding parameter enables the display of consecutive signals in the same direction (for TOTT and HOTT-LOTT). In the second group you can change the display options with the Barcolor, Signal and Bars parameters. The OTT system you select is configured with the parameters in the group with the corresponding system heading. (For example, suppose you select OTT CHANNEL in the system parameter. The parameters defining the channels are grouped under the heading "OTT CHANNELS" in the settings section.) Also the parameters you chose are displayed in table form on the chart screen. The table also presents the total number of bars on the chart and the number of signals generated by the selected system.
MECHANICS
Let's take a look at how the indicator works. This indicator incorporates eight distinct OTT systems, each characterized by unique parameters, lines, and signals. (Exception: OTT Channel does not include any referenced signals.)
1) WHAT IS "OTT"?
OTT comprises two lines: Support and Target. There's an up-trending market when the Support is superior to the Target, and a down-trending market when the Support is inferior to the Target. It is governed by two parameters. The Support (moving average) is determined by the Length parameter, while the Multiplier parameter is employed for percentage calculations. Lower values are adept at capturing short-term fluctuations, whereas higher values are more adept at identifying long-term trends. These principles apply to all parameters within the indicator.
DETAILED INFO : The OTT function in the script automatically performs the calculation process described in this section. So, if you know how OTT works you can skip the details. To comprehend its functioning, it's essential to grasp the "MOST" indicator, also devised by Anıl Özekşi. The fundamental principle of MOST involves creating bands that function akin to a trailing stop-loss. Initially, a moving average, referred to as the 'Support,' is established. (Anıl Özekşi employs VAR/VIDYA as the moving average type in all his systems.) Subsequently, the Support line is adjusted both upward and downward by a percentage multiplier to establish a band system. In the context of the trailing stop-loss concept, when the Support line approaches either the lower or upper band, the respective band ceases to move in parallel with the Support line and becomes horizontal. Consequently, the Support always intersects the band at some point. The values of the upper or lower bands, determined by this intersection, are referred to as the MOST line. OTT is generated by consolidating the values of MOST shifted upwards and downwards by half the coefficient percentage into a single line using the same method as above, and calculating the value of this line from two bars ago. Support is the data series of OTT and it serves as a source in OTT function. The OTT line is named as "Target" in this scipt. Support and Target will automatically vary according to the OTT application selected in the "System" parameter.
2) WHAT IS "TOTT"?
Twin OTT , also known as the "OTT Band," involves three parameters: Length, Multiplier, and Band Multiplier. It consists of three lines: Support, Upper Line, and Lower Line. OTT is determined by the Length and Multiplier parameters, while TOTT is calculated by adjusting OTT upwards and downwards as per the Band Multiplier parameter. The indicator generates signals based on the intersections of the Support and these two new OTT levels.
3) WHAT IS "OTT CHANNEL"?
Similar to TOTT, the OTT CHANNEL is also based on shifted OTT levels, employing a similar calculation method. The primary distinction lies in the fact that TOTT has a single Band Multiplier, whereas OTT CHANNEL incorporates two line multipliers for the band. It encompasses four parameters: Length, Multiplier, Upper Line Multiplier, and Lower Line Multiplier. OTT is defined by the Length and Multiplier parameters. The Upper Line Multiplier and Lower Line Multiplier parameters establish the channel boundaries by shifting the OTT line. Subsequently, levels are drawn between the upper and lower lines. The additional Channel Type parameter determines which levels are displayed on the chart. The "Half Channel" option draws channels shifted by half the coefficient. The "Fibonacci Channel" option draws channels shifted by 0.382 and 0.618 coefficients. The "Both" option plots all levels.
4) WHAT IS "RISOTTO"?
OTT also has application examples in momentum oscillators. RISOTTO utilizes the RSI indicator and operates with three parameters. The RSI is defined by the Length 1 parameter, while the Support is determined by the Length 2 parameter. The Multiplier parameter is utilized for percentage calculations. RISOTTO comprises two lines: Support and Target. To ensure more stable calculations, a constant (+1000) is added to the oscillator average when applying OTT to momentum oscillators. This approach eradicates nonsensical results stemming from percentage calculations when the oscillator reaches a value of 0. The indicator generates signals based on the intersection of these two lines.
5) WHAT IS "SOTT"?
Stochastic OTT is an another example of application on oscillator. Its working principle is akin to that of RISOTTO. It operates with three parameters. The Stochastic %k is defined by the Length 1 parameter, while the Stochastic %d is determined by the Length 2 parameter. The Multiplier parameter is utilized for percentage calculations. SOTT comprises two lines: Support and Target. The indicator generates signals based on the intersection of these two lines.
6) WHAT IS "HOTT-LOTT"?
OTT can be applied to the highest and lowest series as well. HOTT-LOTT operates with three parameters: Length, Multiplier, and Sum N Bars. The highest and lowest series are defined by the Length parameter. The Multiplier parameter is utilized for percentage calculations. It encompasses two lines: Upper Line and Lower Line, where HOTT employs the highest series and LOTT uses the lowest series. If the 'High' price surpasses HOTT, the indicator generates Long signals. Similarly, if the 'Low' price falls below LOTT, the indicator generates Short signals. When the Sum N Bars option is activated, signals are generated based on the confirmation concept for N bars.
7) WHAT IS "ROTT"?
Relative OTT serves as a valuable tool for long-period filters. ROTT operates with two parameters. The Support is determined by the length parameter and equals twice the moving average. The Multiplier parameter is utilized for percentage calculations. The indicator generates signals based on the intersection of these two lines.
8) WHAT IS "FT"?
"Fırsatçı" (opportunistic) Trend is a system that revolves around two levels, namely major and minor OTT. It operates with three parameters: Length, Major Multiplier, and Minor Multiplier. FT comprises two lines, Support and Target. The indicator generates signals based on the intersection of these two lines.
9) WHAT IS "RTR"?
Relative True Range is not an OTT system; however, it serves as a complementary feature. It does not have any referenced signals. RTR is devised to obtain a normalized result of the current market volatility. It operates with two parameters: ATR, which is determined by the Length 1 parameter, and RTR, defined by the Length 2 parameter.
A TIP
If any indicator is defined in function form instead of the OTT function, the applications can also be adapted for different indicators. E.g. Supertrend, PMAX, AlphaTrend, etc.
UPDATE
Anıl Özekşi is a competent algotrader who shares his work with open sources. I will update the indicator as new applications are released.
DISCLEIMER
This is just an indicator, nothing more. The script is for informational and educational purposes only. The use of the script does not constitute professional and/or financial advice. The responsibility for risks associated with the use of the script is solely owned by the user. Do not forget to manage your risk. And trade as safely as possible. Good luck!
Smooth Trail V2Please, enjoy your new game-changing tradingview indicator, may I present to you: the Smooth Trail (second version), with an updated script and open source script to let anyone use it freely.
The Smooth Trail is an indicator that works just like a super trend, but it has a completely different usage and potential.
The super trend works by following the price and displaying a line that uses the ATR to determine how far it has to be from the actual price, and many new traders like to use the indicator thanks to its easy readability and the buy-sell signals that it shows, unfortunately, this is not the best usage of the indicator and it often leads to losing money on the markets.
The main characteristic that this indicator has is that, not like the normal super trend, it follows the trend better adapting itself in the retracement phases.
The second feature that dictates the best usage of this indicator, is that it shows a zone in which to buy or sell to have the best risk-to-reward ratio.
The indicator also works as the dynamic level of support and resistance and can be used best for trend-following strategies to maximize profits.
The first input, the multiplier, is used to determine how many times the ATR has to be added or subtracted in order to plot the indicator.
The second input, the length, is used to determine how many candles the indicator and the ATR have to consider for the calculation.
The third and last input, the zone width, is used to calculate the width of the zone displayed by the indicator, and is the factor that will be multiplied by the ATR, this means that if you leave the settings as default, the zone will be 1 ATR or 34 candle width.
This indicator is great to use in confluence with other indicators or with various candlestick patterns.
Volume and Price Z-Score [Multi-Asset] - By LeviathanThis script offers in-depth Z-Score analytics on price and volume for 200 symbols. Utilizing visualizations such as scatter plots, histograms, and heatmaps, it enables traders to uncover potential trade opportunities, discern market dynamics, pinpoint outliers, delve into the relationship between price and volume, and much more.
A Z-Score is a statistical measurement indicating the number of standard deviations a data point deviates from the dataset's mean. Essentially, it provides insight into a value's relative position within a group of values (mean).
- A Z-Score of zero means the data point is exactly at the mean.
- A positive Z-Score indicates the data point is above the mean.
- A negative Z-Score indicates the data point is below the mean.
For instance, a Z-Score of 1 indicates that the data point is 1 standard deviation above the mean, while a Z-Score of -1 indicates that the data point is 1 standard deviation below the mean. In simple terms, the more extreme the Z-Score of a data point, the more “unusual” it is within a larger context.
If data is normally distributed, the following properties can be observed:
- About 68% of the data will lie within ±1 standard deviation (z-score between -1 and 1).
- About 95% will lie within ±2 standard deviations (z-score between -2 and 2).
- About 99.7% will lie within ±3 standard deviations (z-score between -3 and 3).
Datasets like price and volume (in this context) are most often not normally distributed. While the interpretation in terms of percentage of data lying within certain ranges of z-scores (like the ones mentioned above) won't hold, the z-score can still be a useful measure of how "unusual" a data point is relative to the mean.
The aim of this indicator is to offer a unique way of screening the market for trading opportunities by conveniently visualizing where current volume and price activity stands in relation to the average. It also offers features to observe the convergent/divergent relationships between asset’s price movement and volume, observe a single symbol’s activity compared to the wider market activity and much more.
Here is an overview of a few important settings.
Z-SCORE TYPE
◽️ Z-Score Type: Current Z-Score
Calculates the z-score by comparing current bar’s price and volume data to the mean (moving average with any custom length, default is 20 bars). This indicates how much the current bar’s price and volume data deviates from the average over the specified period. A positive z-score suggests that the current bar's price or volume is above the mean of the last 20 bars (or the custom length set by the user), while a negative z-score means it's below that mean.
Example: Consider an asset whose current price and volume both show deviations from their 20-bar averages. If the price's Z-Score is +1.5 and the volume's Z-Score is +2.0, it means the asset's price is 1.5 standard deviations above its average, and its trading volume is 2 standard deviations above its average. This might suggest a significant upward move with strong trading activity.
◽️ Z-Score Type: Average Z-Score
Calculates the custom-length average of symbol's z-score. Think of it as a smoothed version of the Current Z-Score. Instead of just looking at the z-score calculated on the latest bar, it considers the average behavior over the last few bars. By doing this, it helps reduce sudden jumps and gives a clearer, steadier view of the market.
Example: Instead of a single bar, imagine the average price and volume of an asset over the last 5 bars. If the price's 5-bar average Z-Score is +1.0 and the volume's is +1.5, it tells us that, over these recent bars, both the price and volume have been consistently above their longer-term averages, indicating sustained increase.
◽️ Z-Score Type: Relative Z-Score
Calculates a relative z-score by comparing symbol’s current bar z-score to the mean (average z-score of all symbols in the group). This is essentially a z-score of a z-score, and it helps in understanding how a particular symbol's activity stands out not just in its own historical context, but also in relation to the broader set of symbols being analyzed. In other words, while the primary z-score tells you how unusual a bar's activity is for that specific symbol, the relative z-score informs you how that "unusualness" ranks when compared to the entire group's deviations. This can be particularly useful in identifying symbols that are outliers even among outliers, indicating exceptionally unique behaviors or opportunities.
Example: If one asset's price Z-Score is +2.5 and volume Z-Score is +3.0, but the group's average Z-Scores are +0.5 for price and +1.0 for volume, this asset’s Relative Z-Score would be high and therefore stand out. This means that asset's price and volume activities are notably high, not just by its own standards, but also when compared to other symbols in the group.
DISPLAY TYPE
◽️ Display Type: Scatter Plot
The Scatter Plot is a visual tool designed to represent values for two variables, in this case the Z-Scores of price and volume for multiple symbols. Each symbol has it's own dot with x and y coordinates:
X-Axis: Represents the Z-Score of price. A symbol further to the right indicates a higher positive deviation in its price from its average, while a symbol to the left indicates a negative deviation.
Y-Axis: Represents the Z-Score of volume. A symbol positioned higher up on the plot suggests a higher positive deviation in its trading volume from its average, while one lower down indicates a negative deviation.
Here are some guideline insights of plot positioning:
- Top-Right Quadrant (High Volume-High Price): Symbols in this quadrant indicate a scenario where both the trading volume and price are higher than their respective mean.
- Top-Left Quadrant (High Volume-Low Price): Symbols here reflect high trading volumes but prices lower than the mean.
- Bottom-Left Quadrant (Low Volume-Low Price): Assets in this quadrant have both low trading volume and price compared to their mean.
- Bottom-Right Quadrant (Low Volume-High Price): Symbols positioned here have prices that are higher than their mean, but the trading volume is low compared to the mean.
The plot also integrates a set of concentric squares which serve as visual guides:
- 1st Square (1SD): Encapsulates symbols that have Z-Scores within ±1 standard deviation for both price and volume. Symbols within this square are typically considered to be displaying normal behavior or within expected range.
- 2nd Square (2SD): Encapsulates those with Z-Scores within ±2 standard deviations. Symbols within this boundary, but outside the 1 SD square, indicate a moderate deviation from the norm.
- 3rd Square (3SD): Represents symbols with Z-Scores within ±3 standard deviations. Any symbol outside this square is deemed to be a significant outlier, exhibiting extreme behavior in terms of either its price, its volume, or both.
By assessing the position of symbols relative to these squares, traders can swiftly identify which assets are behaving typically and which are showing unusual activity. This visualization simplifies the process of spotting potential outliers or unique trading opportunities within the market. The farther a symbol is from the center, the more it deviates from its typical behavior.
◽️ Display Type: Columns
In this visualization, z-scores are represented using columns, where each symbol is presented horizontally. Each symbol has two distinct nodes:
- Left Node: Represents the z-score of volume.
- Right Node: Represents the z-score of price.
The height of these nodes can vary along the y-axis between -4 and 4, based on the z-score value:
- Large Positive Columns: Signify a high or positive z-score, indicating that the price or volume is significantly above its average.
- Large Negative Columns: Represent a low or negative z-score, suggesting that the price or volume is considerably below its average.
- Short Columns Near 0: Indicate that the price or volume is close to its mean, showcasing minimal deviation.
This columnar representation provides a clear, intuitive view of how each symbol's price and volume deviate from their respective averages.
◽️ Display Type: Circles
In this visualization style, z-scores are depicted using circles. Each symbol is horizontally aligned and represented by:
- Solid Circle: Represents the z-score of price.
- Transparent Circle: Represents the z-score of volume.
The vertical position of these circles on the y-axis ranges between -4 and 4, reflecting the z-score value:
- Circles Near the Top: Indicate a high or positive z-score, suggesting the price or volume is well above its average.
- Circles Near the Bottom: Represent a low or negative z-score, pointing to the price or volume being notably below its average.
- Circles Around the Midline (0): Highlight that the price or volume is close to its mean, with minimal deviation.
◽️ Display Type: Delta Columns
There's also an option to utilize Z-Score Delta Columns. For each symbol, a single column is presented, depicting the difference between the z-score of price and the z-score of volume.
The z-score delta essentially captures the disparity between how much the price and volume deviate from their respective mean:
- Positive Delta: Indicates that the z-score of price is greater than the z-score of volume. This suggests that the price has deviated more from its average than the volume has from its own average. Such a scenario could point to price movements being more significant or pronounced compared to the changes in volume.
- Negative Delta: Represents that the z-score of volume is higher than the z-score of price. This might mean that there are substantial volume changes, yet the price hasn't moved as dramatically. This can be indicative of potential build-up in trading interest without an equivalent impact on price.
- Delta Close to 0: Means that the z-scores for price and volume are almost equal, indicating their deviations from the average are in sync.
◽️ Display Type: Z-Volume/Z-Price Heatmap
This visualization offers a heatmap either for volume z-scores or price z-scores across all symbols. Here's how it's presented:
Each symbol is allocated its own horizontal row. Within this row, bar-by-bar data is displayed using a color gradient to represent the z-score values. The heatmap employs a user-defined gradient scale, where a chosen "cold" color represents low z-scores and a chosen "hot" color signifies high z-scores. As the z-score increases or decreases, the colors transition smoothly along this gradient, providing an intuitive visual indication of the z-score's magnitude.
- Cold Colors: Indicate values significantly below the mean (negative z-score)
- Mild Colors: Represent values close to the mean, suggesting minimal deviation.
- Hot Colors: Indicate values significantly above the mean (positive z-score)
This heatmap format provides a rapid, visually impactful means to discern how each symbol's price or volume is behaving relative to its average. The color-coded rows allow you to quickly spot outliers.
VOLUME TYPE
The "Volume Type" input allows you to choose the nature of volume data that will be factored into the volume z-score calculation. The interpretation of indicator’s data changes based on this input. You can opt between:
- Volume (Regular Volume): This is the classic measure of trading volume, which represents the volume traded in a given time period - bar.
- OBV (On-Balance Volume): OBV is a momentum indicator that accumulates volume on up bars and subtracts it on down bars, making it a cumulative indicator that sort of measures buying and selling pressure.
Interpretation Implications:
- For Volume Type: Regular Volume:
Positive Z-Score: Indicates that the trading volume is above its average, meaning there's unusually high trading activity .
Negative Z-Score: Suggests that the trading volume is below its average, signifying unusually low trading activity.
- For Volume Type: OBV:
Positive Z-Score: Signifies that “buying pressure” is above its average.
Negative Z-Score: Signifies that “selling pressure” is above its average.
When comparing Z-Score of OBV to Z-Score of price, we can observe several scenarios. If Z-Price and Z-Volume are convergent (have similar z-scores), we can say that the directional price movement is supported by volume. If Z-Price and Z-Volume are divergent (have very different z-scores or one of them being zero), it suggests a potential misalignment between price movement and volume support, which might hint at possible reversals or weakness.
Fractals 5/7/9/11/13 ModifiedDescription:
The Modified Fractals Indicator is designed to help traders identify specific fractal patterns on a chart. Unlike traditional Williams Fractals, this indicator focuses on highlighting two distinct types of fractals:
- UpFractals: These fractals are identified when each preceding candle has a higher high than the one before it, and each succeeding candle has a higher high than the one following it.
- DownFractals: Conversely, DownFractals are detected when each preceding candle has a lower low than the one before it, and each succeeding candle has a lower low than the one following it.
This unique approach sets it apart from standard Fractal indicators.
Features:
1. Originality and Uniqueness: This indicator employs a distinctive algorithm to detect and display modified fractals, providing a fresh perspective on price reversals.
2. Customizable Parameters: Users can fine-tune the indicator to their trading strategy by adjusting the candle count and arrow size.
3. Easy-to-Understand Chart: The Modified Fractals Indicator is designed to provide clear and easily identifiable signals on your chart, enhancing your trading experience.
4. User-Friendly Interface: This indicator is user-friendly and can be easily integrated into your TradingView setup.
How it Works:
The Modified Fractals Indicator scans the price action on your chart and identifies specific fractal patterns based on the criteria mentioned above for both UpFractals and DownFractals.
Usage:
- Add the Modified Fractals Indicator to your TradingView chart.
- Customize the settings, including the candle count and arrow size, to align with your trading strategy.
- Observe the chart for the appearance of UpFractals and DownFractals as marked by the indicator's arrows.
- Use the signals provided by the indicator to inform your trading decisions, such as potential entry or exit points.
Please note that this Modified Fractals Indicator offers a unique approach to fractal analysis, focusing on specific price patterns that differ from traditional Williams Fractals. It provides traders with an additional tool for identifying potential trend reversals and market opportunities.
Market Open - Relative VolumeThe indicator calculates the Pre-market volume percentage of the current day, relative to the average volume being traded in the trading session (14 days), displayed in Table Row 1, Table Cell 1, as V%. Pre-market volume between 15% & 30% has a orange background color. Pre-market volume percentage above 30% has a green background color.
The indicator calculates the relative volume per candle relative to the average volume being traded in that time period (14 days) (e.g., "1M," "2M," up to "5M"), displayed in a table. Relative volume between 250% & 350% has a orange background color. Relative volume above 350% has a green background color.
FYI >> Indicator calculations are per candle, not time unit (due to pine script restrictions). Meaning, the indicator current table data is only accurate in the 1M chart. If you are using the indicator in a higher timeframe, e.g., on the 5M chart, then the values in table cells >> (1M value == relative volume of the first 5-minute candle) (5M value = relative volume of the first five 5-minute candles) and so on. (Future versions will have a dynamic table).
SMC Structures and FVGThe SMC Structures and FVG indicator allows the user to easily identify trend continuations (Break Of Structure) or trend changes (CHange Of CHaracter) on any time frame. In addition, it display all FVG areas, whether they are bullish, bearish, or even mitigated.
Fair Value Gap :
The FVG process shows every bullish, bearish or even mitigated FVG liquidity area. When a FVG is fully mitigated it will directly be removed of the chart.
There is an history of FVG to show. By selecting specific number of FVG to show in the chart, the user can focus its analysis on lasts liquidity area.
Here's the rules for FVG color :
Green when it's a bullish FVG and has not been mitigated
Red when it's a bearish FVG and has not been mitigated
Gray when the bullish / bearish FVG has been mitigated
Removed when the FVG has been fully mitigated
Structures analysis:
The Structure process show BOS in grey lines and CHoCH in yellow lines. It shows to the user the lasts price action pattern.
The blue lines are the high value and the low value of the current structure.
ICT Institutional Order Flow (fadi)ICT Institutional Order Flow indicator is intended to provide wholistic view to better analyze order flow and where price may go to next. The concept follows ICT principles.
ICT Market Structure
ICT breaks down Pivot points into three categories:
Short Term High/Low (STH/STL) is a 3 candle pattern with a low with higher low on each side (STL), or a high with lower high on each side (STH)
Intermediate Term High/Low (ITH/ITL) uses the calculated STH/STL and marks any STH that has lower or STH on each side, and STL that has higher STL on each side
Long Term High/Low (LTH/LTL) uses the calculated ITH/ITL and marks any ITH that has lower or ITH on each side, and ITL that has higher ITL on each side
Note: ICT also states that if a STH wicks into and closes (almost?) a FVG, he marks it as ITH even if it does not have STH on reach side. This scenario is not covered by this indicator
Liquidity
liquidity is usually present under pivot points. The more prominent the pivot point, the more likely higher values liquidity pools reside under/above it. Liquidity under ITL and LTL as an example, will have better indication of which liquidity the price may seek next.
Displacement
Displacement registers above average move in the price resulting in strong visible move. If requiring a FVG is enabled (in settings), then the displacement could possibly (but never guaranteed) be used to visually recognize a move as it develops.
Full Credit: The calculation for Displacement is derived from TFO's Visualizing Displacement
Imbalances
Imbalances can come in different forms. This indicator identifies three type of imbalances:
1. FVG
2. Volume Imbalance
3. Open Gaps
Imbalances completes the picture by help visualize strong moves, where possible pivot points may develop, and how to enter or manage a trade.
Support and Resistance Backtester [SS]Hey everyone,
Excited to release this indicator I have been working on.
I conceptualized it as an idea a while ago and had to nail down the execution part of it. I think I got it to where I am happy with it, so let me tell you about it!
What it does?
This provides the user with the ability to quantify support and resistance levels. There are plenty of back-test strategies for RSI, stochastics, MFI, any type of technical based indicator. However, in terms of day traders and many swing traders, many of the day traders I know personally do not use or rely on things like RSI, stochastics or MFI. They actually just play the support and resistance levels without attention to anything else. However, there are no tools available to these people who want to, in a way, objectively test their identified support and resistance levels.
For me personally, I use support and resistance levels that are mathematically calculated and I am always curious to see which levels:
a) Have the most touches,
b) Have provided the most support,
c) Have provided the most resistance; and,
d) Are most effective as support/resistance.
And, well, this indicator answers all four of those questions for you! It also attempts to provide some way to support and resistance traders to quantify their levels and back-test the reliability and efficacy of those levels.
How to use:
So this indicator provides a lot of functionality and I think its important to break it down part by part. We can do this as we go over the explanation of how to use it. Here is the step by step guide of how to use it, which will also provide you an opportunity to see the options and functionality.
Step 1: Input your support and resistance levels:
When we open up the settings menu, we will see the section called "Support and Resistance Levels". Here, you have the ability to input up to 5 support and resistance levels. If you have less, no problem, simply leave the S/R level as 0 and the indicator will automatically omit this from the chart and data inclusion.
Step 2: Identify your threshold value:
The threshold parameter extends the range of your support and resistance level by a desired amount. The value you input here should be the value in which you would likely stop out of your position. So, if you are willing to let the stock travel $1 past your support and resistance level, input $1 into this variable. This will extend the range for the assessment and permit the stock to travel +/- your threshold amount before it counts it as a fail or pass.
Step 3: Select your source:
The source will tell the indicator what you want to assess. If you want to assess close, it will look at where the ticker closes in relation to your support and resistance levels. If you want to see how the highs and lows behave around the S/R levels, then change the source to High or Low.
It is recommended to leave at close for optimal results and reliability however.
Step 4: Determine your lookback length:
The lookback length will be the number of candles you want the indicator to lookback to assess the support and resistance level. This is key to get your backtest results.
The recommendation is on timeframes 1 hour or less, to look back 300 candles.
On the daily, 500 candles is recommended.
Step 5: Plot your levels
You will see you have various plot settings available to you. The default settings are to plot your support and resistance levels with labels. This will look as follows:
This will plot your basic support and resistance levels for you, so you do not have to manually plot them.
However, if you want to extend the plotted support and resistance level to visually match your threshold values, you can select the "Plot Threshold Limits" option. This will extend your support and resistance areas to match the designated threshold limits.
In this case on MSFT, I have the threshold limit set at $1. When I select "Plot Threshold Limits", this is the result:
Plotting Passes and Fails:
You will notice at the bottom of the settings menu is an option to plot passes and plot fails. This will identify, via a label overlaid on the chart, where the support and resistance failures and passes resulted. I recommend only selecting one at a time as the screen can get kind of crowded with both on. here is an example on the MSFT chart:
And on the larger timeframe:
The chart
The chart displays all of the results and counts of your support and resistance results. Some things to pay attention to use the chart are:
a) The general success rate as support vs resistance
Rationale: Support levels may act as resistance more often than they do support or vice versa. Let's take a look at MSFT as an example:
The chart above shows the 334.07 level has acted as very strong support. It has been successful as support almost 82% of the time. However, as resistance, it has only been successful 33% of the time. So we could say that 334 is a strong key support level and an area we would be comfortable longing at.
b) The number of touches:
Above you will see the number of touches pointed out by the blue arrow.
Rationale: The number of touches differs from support and resistance. It counts how many times and how frequently a ticker approaches your support and/or resistance area and the duration of time spent in that area. Whereas support and resistance is determined by a candle being either above or below a s/r area, then approaching that area and then either failing or bouncing up/down, the number of touches simply assesses the time spent (in candles) around a support or resistance level. This is key to help you identify if a level has frequent touches/consolidation vs other levels and can help you filter out s/r levels that may not have a lot of touches or are infrequently touched.
Closing comments:
So this is pretty much the indicator in a nutshell. Hopefully you find it helpful and useful and enjoy it.
As always let me know your questions/comments and suggestions below.
As always I appreciate all of you who check out, try out and read about my indicators and ideas. I wish you all the safest trades and good luck!
Lower timeframe chartHi all!
I've made this script to help with my laziness (and to help me (and now you) with efficiency). It's purpose is to, without having to change the chart timeframe, being able to view the lower timeframe bars (and trend) within the last chart bar. The defaults are just my settings (It's based on daily bars), so feel free to change them and maybe share yours! It's also based on stocks, which have limited trading hours, but if you want to view this for forex trading I suggest changing the 'lower time frame' to a higher value since it has more trading hours.
The script prints a label chart (ASCII) based on your chosen timeframe and the trend, based on @KivancOzbilgic script SuperTrend The printed ASCII chart has rows (slots) that are based on ATR (14 bars) and empty gaps are removed. The current trend is decided by a percentage of bars (user defined but defaults to 80%, which is really big but let's you be very conservative in defining a trend to be bullish. Set to 50% to have the trend being decided equally or lower to be more conservative in defining a trend to be bearish) that must have a bullish SuperTrend, it's considered to be bearish otherwise. Big price range (based on the ATR for 14 bars) and big volume (true if the volume is bigger than a user defined simple moving average (defaults to 20 bars)) can be disabled for faster execution.
The chart displayed will consist of bars and thicker bars that has a higher volume than the defined simple moving average. The bars that has a 'big range' (user defined value of ATR (14 days) factor that defaults to 0.5) will also have a wick. The characters used are the following:
Green bar = ┼
Green bar with large volume = ╪
Green bar wick = │
Red bar = ╋
Red bar with large volume = ╬
Red bar wick = ┃
Bar with no range = ─
Bar with no range and high volume = ═
Best of trading!
Modern Portfolio Management IndicatorAfter weeks of grueling over this indicator, I am excited to be releasing it!
Intro:
This is not a sexy, technical or math based indicator that will give you buy and sell signals or anything fancy, but it is an indicator that I created in hopes to bridge a gap I have noticed. That gap is the lack of indicators and technical resources for those who also like to plan their investments. This indicator is tailored to those who are either established investors and to those who are looking to get into investing but don't really know where to start.
The premise of this indicator is based on Modern Portfolio Theory (MPT). Before we get into the indicator itself, I think its important to provide a quick synopsis of MPT.
About MPT:
Modern Portfolio Theory (MPT) is an investment framework that was developed by Harry Markowitz in the 1950s. It is based on the idea that an investor can optimize their investment portfolio by considering the trade-off between risk and return. MPT emphasizes diversification and holds that the risk of an individual asset should be assessed in the context of its contribution to the overall portfolio's risk. The theory suggests that by diversifying investments across different asset classes with varying levels of risk, an investor can achieve a more efficient portfolio that maximizes returns for a given level of risk or minimizes risk for a desired level of return. MPT also introduced the concept of the efficient frontier, which represents the set of portfolios that offer the highest expected return for a given level of risk. MPT has been widely adopted and used by investors, financial advisors, and portfolio managers to construct and manage portfolios.
So how does this indicator help with MPT?
The thinking and theory that went behind this indicator was this: I wanted an indicator, or really just a "way" to test and back-test ticker performance over time and under various circumstances and help manage risk.
Over the last 3 years we have seen a massive bull market, followed by a pretty huge bear market, followed by a very unexpected bull market. We have been and continue to be plagued with economic and political uncertainty that seems to constantly be looming over everyone with each waking day. Some people have liquidated their retirement investments, while others are fomoing in to catch this current bull run. But which tickers are sound and how tickers and funds have compared amongst each other remains somewhat difficult to ascertain, absent manually reviewing and calculating each ticker individually.
That is where this indicator comes in. This indicator permits the user to define up to 5 equities that they are potentially interested in investing in, or are already invested in. The user can then select a specific period in time, say from the beginning of 2022 till now. The user can then define how much they want to invest in each company by number of shares, so if they want to buy 1 share a week, or 2 shares a month, they can input these variables into the indicator to draw conclusions. As many brokers are also now permitting fractional share trading, this ability is also integrated into the indicator. So for shares, you can put in, say, 0.25 shares of SPY and the indicator will accept this and account for this fractional share.
The indicator will then show you a portfolio summary of what your earnings and returns would be for the defined period. It will provide a percent return as well as the projected P&L based on your desired investment amount and frequency.
But it goes beyond just that, you can also have the indicator display a simple forecasting projection of the portfolio. It will show the projected P&L and % Return over various periods in time on each of the ticker (see image below):
The indicator will also break down your portfolio allocation, it will show where the majority of your holdings are and where the majority of your P&L in coming from (best performers will show a green fill and worst will show a red fill, see image below):
This colour coding also extends to the portfolio breakdown itself.
Dollar cost averaging (DCA) is incorporated into the indicator itself, by assuming ongoing contributions. If you want to stop contributions at a certain point, you just select your end time for contributions at the point in which you would stop contributing.
The indicator also provides some basic fundamental information about the company tickers (if applicable). Simply select the "Fundamental" chart and it will display a breakdown of the fundamentals, including dividends paid, market cap and earnings yield:
The indicator also provides a correlation assessment of each holding against each other holding. This emphasizes the profound role of diversification on portfolios. The less correlation you have in your portfolio among your holdings, the better diversified you are. As well, if you have holdings that are perfectly inverse other holdings, you have a pseudo hedge against the downturn of one of your holdings. This is even more helpful if the inverse is a company with solid fundamentals.
In the below example you will see NASDAQ:IRDM in the portfolio. You will be able to see that NASDAQ:IRDM has a slight inverse relationship to SPY:
Yet IRDM has solid fundamentals and is performing well fundamentally. Thus, this makes IRDIM a solid addition to your portfolio as it can potentially hedge against a downturn for SPY and is less risky than simply holding an inverse leveraged share on SPY which is most likely just going to cost you money than make you money.
Concluding remarks:
There are many fun and interesting things you can do with this indicator and I encourage you to try it out and have fun with it! The overall objective with the indicator is to help you plan for your portfolio and not necessarily to manage your portfolio. If you have a few stocks you are looking at and contemplating investing in, this will help you run some theoretical scenarios with this stock based on historical performance and also help give you a feel of how it will perform in the future based on past behaviour.
It is important to remember that past behaviour does not indicate future behaviour, but the indicator provides you with tools to get a feel for how a stock has performed under various circumstances and get a general feel of the fundamentals of the company you could potentially be investing in.
Please note, this indicator is not meant to replace full, fundamental analyses of individual companies. It is simply meant to give you a "gist" of how companies are fundamentally and how they have performed historically.
I hope you enjoy it!
Safe trades everyone!
Price & Volume Profile (Expo)█ Overview
The Price & Volume Profile provides a holistic perspective on market dynamics by simultaneously tracking price action and trading volume across a range of price levels. So it is not only a volume-based indicator but also a price-based one. In addition to illustrating volume distribution, it quantifies how frequently the price has fallen within a particular range, thus offering a holistic perspective on market dynamics.
This unique and comprehensive approach to market analysis by considering both price action and trading volume, two crucial dimensions of market activity. Its distinctive methodology offers several advantages:
Holistic Market View: By simultaneously tracking the frequency of specific price ranges (Price Profile) and the volume traded at those ranges (Volume Profile), this indicator provides a more complete picture of market behavior. It shows not only where the market is trading but also how much it's trading, reflecting both price acceptance levels and market participation intensity.
Point of Control (POC): The POC, as highlighted by this indicator, serves as a significant reference point for traders. It identifies the price level with the highest trading activity, thus indicating a strong consensus among market participants about the asset's fair value. Observing how price interacts with the POC can offer valuable insights into market sentiment and potential trend reversals.
Support and Resistance Levels: Price levels with high trading activity often act as support or resistance in future price movements. The indicator visually represents these levels, enabling traders to anticipate potential price reactions.
Price Profile
Price and Volume Profile
█ Calculations
The algorithm analyzes both trade frequency and volume across different price levels. It identifies these levels within the visible chart range, then examines each bar to determine if the selected price falls within these levels. If so, it increases a counter and adds the trading volume. This process repeats across the visible range and is visualized as a horizontal histogram, each bar representing a price level and the bar length reflecting trade frequency and volume. Additionally, it calculates the Point of Control (POC), signifying the price level with the highest activity.
In summary: The histogram presents a dual perspective - not only the traded volume at each price level but also the frequency of the price hitting each range. The longer the bar, the more times the price has frequented that specific range, revealing key insights into price behavior and acceptance levels. These frequently visited areas often emerge as strong support or resistance zones, helping traders navigate market movements.
Please note that the indicator adjusts to the visible price range, making it adaptable to changing market conditions. This dynamic analysis can provide more relevant and timely information than static indicators.
█ How to use
This indicator is beneficial for traders as it offers insights into the distribution of trading activity across different price levels. It helps identify key areas of support and resistance and gives a visual representation of market sentiment and liquidity.
The point of control (POC) , which is the price level with the highest traded volume or frequency count, becomes even more crucial in this context. It marks the price at which the most trading activity occurred, signaling a strong consensus among market participants about the asset's fair value. If the market price deviates significantly from the POC, it could suggest an overbought or oversold condition, potentially leading to a price reversion.
Fair Price Areas/gaps are specific price levels or zones where an asset has spent limited time in the past. These areas are considered interesting or significant because they may have an impact on future price action.
Similar to the concept of fair value gaps, which refers to discrepancies between an asset's market price and its estimated intrinsic value, Fair Price Areas/gaps focus on price levels that have been relatively underutilized in terms of trading activity. When an asset's price reaches a Fair Price Area/gap, traders and investors pay attention because they expect the price to react in some way. The rationale behind this concept is that price tends to gravitate towards areas where it has spent less time in the past, as the market perceives them as significant levels.
█ Settings
The indicator is customizable, allowing users to define the number of price levels (rows), the offset, the data source, and whether to display volume or frequency count. It also adjusts dynamically to the visible price range on the chart, ensuring that the analysis remains relevant and timely with changing market conditions.
Source: The price to use for the calculation. Typically, this is the closing price. By considering the user-selected Source (typically the closing price), the indicator determines the frequency with which the price lands within each designated price level (row) over the selected period. In essence, the indicator provides a count of bars where the Source price falls within each range, essentially creating a "Price Profile."
Row Size: The number of price levels (rows) to divide the visible price range into.
Display: Choose whether to display the number of bars ("Counter") or the total volume ("Volume") for each price level.
Offset: The distance of the histogram from the price chart.
Point of Control (POC): If enabled, the indicator will highlight the price level with the most activity.
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Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
Multi Kernel Regression [ChartPrime]The "Multi Kernel Regression" is a versatile trading indicator that provides graphical interpretations of market trends by using different kernel regression methods. It's beneficial because it smoothes out price data, creating a clearer picture of price movements, and can be tailored according to the user's preference with various options.
What makes this indicator uniquely versatile is the 'Kernel Select' feature, which allows you to choose from a variety of regression kernel types, such as Gaussian, Logistic, Cosine, and many more. In fact, you have 17 options in total, making this an adaptable tool for diverse market contexts.
The bandwidth input parameter directly affects the smoothness of the regression line. While a lower value will make the line more sensitive to price changes by sticking closely to the actual prices, a higher value will smooth out the line even further by placing more emphasis on distant prices.
It's worth noting that the indicator's 'Repaint' function, which re-estimates work according to the most recent data, is not a deficiency or a flaw. Instead, it’s a crucial part of its functionality, updating the regression line with the most recent data, ensuring the indicator measurements remain as accurate as possible. We have however included a non-repaint feature that provides fixed calculations, creating a steady line that does not change once it has been plotted, for a different perspective on market trends.
This indicator also allows you to customize the line color, style, and width, allowing you to seamlessly integrate it into your existing chart setup. With labels indicating potential market turn points, you can stay on top of significant price movements.
Repaint : Enabling this allows the estimator to repaint to maintain accuracy as new data comes in.
Kernel Select : This option allows you to select from an array of kernel types such as Triangular, Gaussian, Logistic, etc. Each kernel has a unique weight function which influences how the regression line is calculated.
Bandwidth : This input, a scalar value, controls the regression line's sensitivity towards the price changes. A lower value makes the regression line more sensitive (closer to price) and higher value makes it smoother.
Source : Here you denote which price the indicator should consider for calculation. Traditionally, this is set as the close price.
Deviation : Adjust this to change the distance of the channel from the regression line. Higher values widen the channel, lower values make it smaller.
Line Style : This provides options to adjust the visual style of the regression lines. Options include Solid, Dotted, and Dashed.
Labels : Enabling this introduces markers at points where the market direction switches. Adjust the label size to suit your preference.
Colors : Customize color schemes for bullish and bearish trends along with the text color to match your chart setup.
Kernel regression, the technique behind the Multi Kernel Regression Indicator, has a rich history rooted in the world of statistical analysis and machine learning.
The origins of kernel regression are linked to the work of Emanuel Parzen in the 1960s. He was a pioneer in the development of nonparametric statistics, a domain where kernel regression plays a critical role. Although originally developed for the field of probability, these methods quickly found application in various other scientific disciplines, notably in econometrics and finance.
Kernel regression became really popular in the 1980s and 1990s along with the rise of other nonparametric techniques, like local regression and spline smoothing. It was during this time that kernel regression methods were extensively studied and widely applied in the fields of machine learning and data science.
What makes the kernel regression ideal for various statistical tasks, including financial market analysis, is its flexibility. Unlike linear regression, which assumes a specific functional form for the relationship between the independent and dependent variables, kernel regression makes no such assumptions. It creates a smooth curve fit to the data, which makes it extremely useful in capturing complex relationships in data.
In the context of stock market analysis, kernel regression techniques came into use in the late 20th century as computational power improved and these techniques could be more easily applied. Since then, they have played a fundamental role in financial market modeling, market prediction, and the development of trading indicators, like the Multi Kernel Regression Indicator.
Today, the use of kernel regression has solidified its place in the world of trading and market analysis, being widely recognized as one of the most effective methods for capturing and visualizing market trends.
The Multi Kernel Regression Indicator is built upon kernel regression, a versatile statistical method pioneered by Emanuel Parzen in the 1960s and subsequently refined for financial market analysis. It provides a robust and flexible approach to capturing complex market data relationships.
This indicator is more than just a charting tool; it reflects the power of computational trading methods, combining statistical robustness with visual versatility. It's an invaluable asset for traders, capturing and interpreting complex market trends while integrating seamlessly into diverse trading scenarios.
In summary, the Multi Kernel Regression Indicator stands as a testament to kernel regression's historic legacy, modern computational power, and contemporary trading insight.
Trend Correlation HeatmapHello everyone!
I am excited to release my trend correlation heatmap, or trend heatmap for short.
Per usual, I think its important to explain the theory before we get into the use of the indicator, so let's get into the theory!
The theory:
So what is a correlation?
Correlation is the relationship one variable has to another. Correlations are the basis of everything I do as a quantitative trader. From the correlation between the same variables (i.e. autocorrelation), the correlation between other variables (i.e. VIX and SPY, SPY High and SPY Low, DXY and ES1! close, etc.) and, as well, the correlation between price and time (time series correlation).
This may sound very familiar to you, especially if you are a user, observer or follower of my ideas and/or indicators. Ninety-five percent of my indicators are a function of one of those three things. Whether it be a time series based indicator (i.e.my time series indicator), whether it be autocorrelation (my autoregressive cloud indicator or my autocorrelation oscillator) or whether it be regressive in nature (i.e. my SPY Volume weighted close, or even my expected move which uses averages in lieu of regressive approaches but is foundational in regression principles. Or even my VIX oscillator which relies on the premise of correlations between tickers.) So correlation is extremely important to me and while its true I am more of a regression trader than anything, I would argue that I am more of a correlation trader, because correlations are the backbone of how I develop math models of stocks.
What I am trying to stress here is the importance of correlations. They really truly are foundational to any type of quantitative analysis for stocks. And as such, understanding the current relationship a stock has to time is pivotal for any meaningful analysis to be conducted.
So what is correlation to time and what does it tell us?
Correlation to time, otherwise known and commonly referred to as "Time Series", is the relationship a ticker's price has to the passing of time. It is displayed in the traditional Pearson Correlation Coefficient or R value and can be any value from -1 (strong negative relationship, i.e. a strong downtrend) to + 1 (i.e. a strong positive relationship, i.e. a strong uptrend). The higher or lower the value the stronger the up or downtrend is.
As such, correlation to time tells us two very important things. These are:
a) The direction of the stock; and
b) The strength of the trend.
Let's take a look at an example:
Above we have a chart of QQQ. We can see a trendline that seems to fit well. The questions we ask as traders are:
1. What is the likelihood QQQ breaks down from this trendline?
2. What is the likelihood QQQ continues up?
3. What is the likelihood QQQ does a false breakdown?
There are numerous mathematical approaches we can take to answer these questions. For example, 1 and 2 can be answered by use of a Cumulative Distribution Density analysis (CDDA) or even a linear or loglinear regression analysis and 3 can be answered, more or less, with a linear regression analysis and standard error ascertainment, or even just a general comparison using a data science approach (such as cosine similarity or Manhattan distance).
But, the reality is, all 3 of these questions can be visualized, at least in some way, by simply looking at the correlation to time. Let's look at this chart again, this time with the correlation heatmap applied:
If we look at the indicator we can see some pivotal things. These are:
1. We have 4, very strong uptrends that span both higher AND lower timeframes. We have a strong uptrend of 0.96 on the 5 minute, 50 candle period. We have a strong uptrend at the 300 candle lookback period on the 1 minute, we have a strong uptrend on the 100 day lookback on the daily timeframe period and we have a strong uptrend on the 5 minute on the 500 candle lookback period.
2. By comparison, we have 3 downtrends, all of which have correlations less than the 4 uptrends. All of the downtrends have a correlation above -0.8 (which we would want lower than -0.8 to be very strong), and all of the uptrends are greater than + 0.80.
3. We can also see that the uptrends are not confined to the smaller timeframes. We have multiple uptrends on multiple timeframes and both short term (50 to 100 candles) and long term (up to 500 candles).
4. The overall trend is strengthening to the upside manifested by a positive Max Change and a Positive Min change (to be discussed later more in-depth).
With this, we can see that QQQ is actually very strong and likely will continue at least some upside. If we let this play out:
We continued up, had one test and then bounced.
Now, I want to specify, this indicator is not a panacea for all trading. And in relation to the 3 questions posed, they are best answered, at least quantitatively, not only by correlation but also by the aforementioned methods (CDDA, etc.) but correlation will help you get a feel for the strength or weakness present with a stock.
What are some tangible applications of the indicator?
For me, this indicator is used in many ways. Let me outline some ways I generally apply this indicator in my day and swing trading:
1. Gauging the strength of the stock: The indictor tells you the most prevalent behavior of the stock. Are there more downtrends than uptrends present? Are the downtrends present on the larger timeframes vs uptrends on the shorter indicating a possible bullish reversal? or vice versa? Are the trends strengthening or weakening? All of these things can be visualized with the indicator.
2. Setting parameters for other indicators: If you trade EMAs or SMAs, you may have a "one size fits all" approach. However, its actually better to adjust your EMA or SMA length to the actual trend itself. Take a look at this:
This is QQQ on the 1 hour with the 200 EMA with 200 standard deviation bands added. If we look at the heatmap, we can see, yes indeed 200 has a fairly strong uptrend correlation of 0.70. But the strongest hourly uptrend is actually at 400 candles, with a correlation of 0.91. So what happens if we change the EMA length and standard deviation to 400? This:
The exact areas are circled and colour coded. You can see, the 400 offers more of a better reference point of supports and resistances as well as a better overall trend fit. And this is why I never advocate for getting married to a specific EMA. If you are an EMA 200 lover or 21 or 51, know that these are not always the best depending on the trend and situation.
Components of the indicator:
Ah okay, now for the boring stuff. Let's go over the functionality of the indicator. I tried to keep it simple, so it is pretty straight forward. If we open the menu here are our options:
We have the ability to toggle whichever timeframes we want. We also have the ability to toggle on or off the legend that displays the colour codes and the Max and Min highest change.
Max and Min highest change: The max and min highest change simply display the change in correlation over the previous 14 candles. An increasing Max change means that the Max trend is strengthening. If we see an increasing Max change and an increasing Min change (the Min correlation is moving up), this means the stock is bullish. Why? Because the min (i.e. ideally a big negative number) is going up closer to the positives. Therefore, the downtrend is weakening.
If we see both the Max and Min declining (red), that means the uptrend is weakening and downtrend is strengthening. Here are some examples:
Final Thoughts:
And that is the indicator and the theory behind the indicator.
In a nutshell, to summarize, the indicator simply tracks the correlation of a ticker to time on multiple timeframes. This will allow you to make judgements about strength, sentiment and also help you adjust which tools and timeframes you are using to perform your analyses.
As well, to make the indicator more user friendly, I tried to make the colours distinctively different. I was going to do different shades but it was a little difficult to visualize. As such, I have included a toggle-able legend with a breakdown of the colour codes!
That's it my friends, I hope you find it useful!
Safe trades and leave your questions, comments and feedback below!
Swing Volume Profiles [LuxAlgo]The Swing Volume Profiles indicator aims to calculate and highlight trading activity at specific price levels between two swing points; allowing traders to reveal dominant and/or significant price levels based on volume.
By measuring traded volume at all price levels in the market over a specified time period, the script can also be used to detect some key analysis generally such as supply & demand, buy-side & sell-side liquidity levels, unfilled liquidity voids, and imbalances that can highlight on the chart.
🔶 USAGE
A volume profile is an advanced charting tool that displays the traded volume at different price levels over a specific period. It helps you visualize where the majority of trading activity has occurred.
Key Levels are the areas where the volume is concentrated or where there are significant volume spikes. These levels are known as key support and resistance levels. High-volume nodes indicate areas of high activity and are likely to act as support or resistance in the future.
Volume profile also helps identify value areas, which represent the price levels where the most trading activity has taken place. These levels can act as areas of support or resistance as traders perceive them as fair value.
The Point of Control describes the price level where the most volume was traded. A Naked Point of Control (also called a Virgin Point of Control) is a previous POC that has not been traded. Extending PoC options 'Until Bar Cross' or 'Until Bar Touch' helps in identifying Naked Point of Control Lines.
Previous PoC levels can serve as support and resistance for future price movements. Extending PoC Level 'Until Last Bar' option will help to identify such levels.
🔶 DETAILS
One of the unique features of the script is its ability to detect some other key levels such as levels of acceptance and rejection.
Levels of rejection we may summarize as supply and demand levels, these are also referred to as buy-side and sell-side liquidity levels. They usually occur at extreme highs or lows, where prices may be too high for buyers (high supply, low demand) or too low for sellers (low supply, high demand)
Levels of acceptance are the levels where Liquidity Voids occur, these are also referred to imbalances. Liquidity voids are sudden changes in price when the price jumps from one level to another. The peculiar thing about liquidity voids is that they almost always fill up, so we call them levels of acceptance.
🔶 ALERTS
When an alert is configured, the user will have the ability to be notified in case:
Point Of Control Line is touched/crossed
Value Area High Line is touched/crossed
Value Area Low Line is touched/crossed
🔶 SETTINGS
🔹 Display Options
Mode: Controls the lookback length of detection and visualization, where Present assumes last X bars specifid in '# Bars' option and Historical assumes all data available to the user as well as allowed limits of visiual objects (boxs, lines, labels etc)
# Bars: Controls the lookback length.
🔹 Swing Volume Profiles
The script takes into account user-defined parameters and plots volume profiles. Due to Pine Script™ drwaing objects limit only total volume profiles are presented.
Swing Detection Length: Lookback period
Swing Volume Profiles: Toggles the visibility of the Volume Profiles, with color options to differentiate the Value Area within a profile.
Profile Range Background Fill: Toggles the visibility of the Volume Profiles Range
🔹 Point of Control (PoC)
Point of Control (POC) – The price level for the time period with the highest traded volume
Point of Control (PoC): Toggles the visibility of the Point of Control
Developing PoC: Toggles the visibility of the Developing PoC
Extend PoC: Option that allows detecting virgin PoC levels. Virgin Point of Control (VPoC) is defined as a Point of Control that has never been revisited or touched. The option also allows PoC levels to extend till the last bar aiming to present levels from history where the levels were traded significantly and those levels can be used as support and resistance levels.
🔹 Value Area (VA)
Value Area (VA) – The range of price levels in which the specified percentage of all volume was traded during the time period.
Value Area Volume %: Specifies percentage of the Value Area
Value Area High (VAH): Toggles the visibility of the Value Area High, the highest price level within the Value Area
Value Area Low (VAL): Toggles the visibility of the Value Area Low, the lowest price level within the Value Area
Value Area (VA) Background Fill: Toggles the visibility of the Value Area Range
🔹 Liquidity Levels / Voids
Unfilled Liquidity, Thresh: Enable display of the Unfilled Liquidity Levels and Liquidity Voids, where threshold value defines the significance of the level.
🔹 Profile Stats
Position, Size: Specifies the position and the size of the label presenting Profile Stats, the tooltip of the label includes all related info for each profile.
Price, Price Change, and Cumulative Volume: Enable display of the given options on the chart.
🔹 Volume Profile Others
Number of Rows: Specify how many rows each histogram will have. Caution, having it set to high values will quickly hit Pine Script™ drawing objects limit and may cause fewer historical profiles to be displayed.
Placement: Place profile either left or right.
Profile Width %: Alters the width of the rows in the histogram, relative to the calculated profile length.
🔶 RELATED SCRIPTS
Alternative Liquidity Void Detection script, Buyside-Sellside-Liquidity
5EMA BollingerBand Nifty Stock Scanner
What ?
We all heard about (well: over-heard) 5-EMA strategy. Which falls into the broader category of mean reversal type of trading setup.
What is mean reversal?
Price (or any time series, in fact) tries to follow a mean . Whenever price diverges from the mean it tries to meet it back.
It is empirically observed by some traders (I honestly don't know who first time observed it) that in Indian context specially, 5 Exponential Moving Average (5-EMA) works pretty good as that mean.
So whenever price moves away from that 5-EMA, it ultimately comes back and attain total nirvana :) Means: if price moved way higher than the 5EMA without touching it, then price will correct to meet it's 5-EMA and if price moved way lower, it will be uplifted to meet it's 5-EMA. Funny - but it works !
Now there are already enough social media coverage on this 5-EMA strategy/setup. Even TradingView has some excellent work done on these setups. Kudos to all those great souls.
So when we came to know about this, we were thinking what we should do for the community. Because it is well cover topic (specially in Indian context). Also, there are public indicators.
Then we thought why not come up with a scanner which will scan all the Nifty-50 constituent stocks and find out on the fly, real-time which all stocks are matching this 5-EMA setup and causing a Buy/Sell trade recommendation.
Hence here we are with the first version of our first scanner on the 5EMA setup (well it has some more masala than merely a 5-EMA setup).
Why?
Parts of why is already covered up.
Now instead of blindly following 5-EMA setup, we added the Bollinger band as well. Again: it's also not new. There are enough coverage in social media about the 5-EMA+BB strategy/setup. We mercilessly borrowed from all of these.
Suppose you have an indicator.
Now you apply the indicator in your chart. And then you need to (rock) and roll through your watchlist of Nifty-50 stocks (note: TradingView has no default watchlist of Nifty-50 stock by default - you have to create one custom watchlist to list all manually) to find out which all are matching the setup, need to take a note about the trade recomendations (entry, SL, target) and other stuffs like VWAP, Volume, volatility (Bollinger Band Width).
Not any more.
This scanner will track all the Nifty-50 stocks (technically: 40 stocks other than Banking stocks) and provide which one to Buy or Sell (if any), what's the entry, SL, target, where is the VWAP of the day, what's the picture in volume (high, low, rising, falling) and the implied volatility (using Bolling band width). Also it has a naive alerting mechanism as well.
In fact the code is there to monitor the (Future) OI also and all the OI drama (OI vs price and all the 4 stuffs like long build up, long unwinding, short covering, short buildup). But unfortunately, due to some limitations of the TradingView (that one can not monitor more than 40 `ta.security` call) we have to comment out the code. If you wish you can monitor only 20 stocks and enable the OI monitoring also (20 for stocks + 20 for their OI monitoring .. total 40 `ta.security` call).
How?
To know the divergence from 5-EMA we just check if the high of the candle (on closing) is below the 5-EMA. Then we check if the closing is inside the Bollinger Band (BB). That's a Buy signal. SL: low of the candle, T: middle and higher BB.
Just opposite for selling. 5-EMA low should be above 5-EMA and closing should be inside BB (lesser than BB higher level). That's a Sell signal. SL: high of the candle, T: middle and lower BB.
Along with we compare the current bar's volume with the last-20 bar VWMA (volume weighted moving average) to determine if the volume is high or low.
Present bar's volume is compared with the previous bar's volume to know if it's rising or falling.
VWAP is also determined using `ta.vwap` built-in support of TradingView.
The Bolling Band width is also notified, along with whether it is rising or falling (comparing with previous candle).
Simple, but effective.
Customization
As usual the EMA setup (5 default), the BB setup (20 SMA with 1.5 standard deviation), we provided option wherther to include or exclude BB role in the 5-EMA setup (as we found out there are two schools of thought .. some people use BB some don't. Lets make all happy :))
We also provide options to choose other symbols using Settings if they wish so. We have the default 40 non banking Nifty stocks (why non-banking? - Bank Nifty is in ATH :) .. enough :)). But if user wishes can monitor others too (provided the symbol is there in TradingView).
Although we strongly recommend the timeframe as 30 minutes , you can choose what's fit you most.
The output of the scanner is a table. By default the table is placed in the right-bottom (as we are most comfortable with that). However you can change per your wish. We have the option to choose that.
What is unique in it ?
This is more of an indicator. This is a scanner (of Nifty-50 stocks). So you can apply (our recommendation is in 30m timeframe) it to any chart (does not matter which chart it is) and it will show every 30 mins (which is also configurable) which all stocks (along with trade levels) to Buy and Sell according to the setup.
It will ease your trading activity.
You can concentrate only on the execution, the filtering you can leave it to this one.
Limitations
There is a build in limitation of the TradingView platform is that one can call only upto 40 securities API. Not beyond that. So naturally we are constraint by that. Otherwise we could monitor 190 Nifty F&O stocks itself.
30m is the recommended timeframe. In very lower (say 5m) this script tends to go out of heap (out of memory). Please note that also.
How to trade using this?
Put any chart in 30m (recommended) timeframe.
Apply this screener from Indicators (shortcut to launch indicators is just type / in your keyboard).
This will provide the Buy (shown in green color) or Sell (shown in red color) recommendations in a table, at every 30m candle closing.
Note the volume and BB width as well.
Wait for at least 2 5-minutes candles to close above/below the recommended level .
Take the trade with the SL and target mentioned.
Mentions
@QuantNomad. The whole implementation concept we mercilessly borrowed from him, even some of his code snippet we took it (after asking him through one of his videos comment section and seeking explicit permission which he readily granted within an hour). Thank You sir @QuantNomad. Indebted to you.
Monika (Rawat) ji: for reviewing, correcting, providing real time examples during live market hours, often compromising her own trading activities, about the effectiveness and usefulness of this setup. Thank You madam ji. Indebted to you.
There are innumerable contents in social media about this. Don't even know whom all we checked. Thanks to all of them.
Happy Trading (in stocks - isn't enough of Indices already?)
Disclaimer
This piece of software does not come up with any warrantee or any rights of not changing it over the future course of time.
We are not responsible for any trading/investment decision you are taking out of the outcome of this indicator.
loggerLibrary "logger"
◼ Overview
A dual logging library for developers. Tradingview lacks logging capability. This library provides logging while developing your scripts and is to be used by developers when developing and debugging their scripts.
Using this library would potentially slow down you scripts. Hence, use this for debugging only. Once your code is as you would like it to be, remove the logging code.
◼︎ Usage (Console):
Console = A sleek single cell logging with a limit of 4096 characters. When you dont need a large logging capability.
//@version=5
indicator("demo.Console", overlay=true)
plot(na)
import GETpacman/logger/1 as logger
var console = logger.log.new()
console.init() // init() should be called as first line after variable declaration
console.FrameColor:=color.green
console.log('\n')
console.log('\n')
console.log('Hello World')
console.log('\n')
console.log('\n')
console.ShowStatusBar:=true
console.StatusBarAtBottom:=true
console.FrameColor:=color.blue //settings can be changed anytime before show method is called. Even twice. The last call will set the final value
console.ShowHeader:=false //this wont throw error but is not used for console
console.show(position=position.bottom_right) //this should be the last line of your code, after all methods and settings have been dealt with.
◼︎ Usage (Logx):
Logx = Multiple columns logging with a limit of 4096 characters each message. When you need to log large number of messages.
//@version=5
indicator("demo.Logx", overlay=true)
plot(na)
import GETpacman/logger/1 as logger
var logx = logger.log.new()
logx.init() // init() should be called as first line after variable declaration
logx.FrameColor:=color.green
logx.log('\n')
logx.log('\n')
logx.log('Hello World')
logx.log('\n')
logx.log('\n')
logx.ShowStatusBar:=true
logx.StatusBarAtBottom:=true
logx.ShowQ3:=false
logx.ShowQ4:=false
logx.ShowQ5:=false
logx.ShowQ6:=false
logx.FrameColor:=color.olive //settings can be changed anytime before show method is called. Even twice. The last call will set the final value
logx.show(position=position.top_right) //this should be the last line of your code, after all methods and settings have been dealt with.
◼︎ Fields (with default settings)
▶︎ IsConsole = True Log will act as Console if true, otherwise it will act as Logx
▶︎ ShowHeader = True (Log only) Will show a header at top or bottom of logx.
▶︎ HeaderAtTop = True (Log only) Will show the header at the top, or bottom if false, if ShowHeader is true.
▶︎ ShowStatusBar = True Will show a status bar at the bottom
▶︎ StatusBarAtBottom = True Will show the status bar at the bottom, or top if false, if ShowHeader is true.
▶︎ ShowMetaStatus = True Will show the meta info within status bar (Current Bar, characters left in console, Paging On Every Bar, Console dumped data etc)
▶︎ ShowBarIndex = True Logx will show column for Bar Index when the message was logged. Console will add Bar index at the front of logged messages
▶︎ ShowDateTime = True Logx will show column for Date/Time passed with the logged message logged. Console will add Date/Time at the front of logged messages
▶︎ ShowLogLevels = True Logx will show column for Log levels corresponding to error codes. Console will log levels in the status bar
▶︎ ReplaceWithErrorCodes = True (Log only) Logx will show error codes instead of log levels, if ShowLogLevels is switched on
▶︎ RestrictLevelsToKey7 = True Log levels will be restricted to Ley 7 codes - TRACE, DEBUG, INFO, WARNING, ERROR, CRITICAL, FATAL
▶︎ ShowQ1 = True (Log only) Show the column for Q1
▶︎ ShowQ2 = True (Log only) Show the column for Q2
▶︎ ShowQ3 = True (Log only) Show the column for Q3
▶︎ ShowQ4 = True (Log only) Show the column for Q4
▶︎ ShowQ5 = True (Log only) Show the column for Q5
▶︎ ShowQ6 = True (Log only) Show the column for Q6
▶︎ ColorText = True Log/Console will color text as per error codes
▶︎ HighlightText = True Log/Console will highlight text (like denoting) as per error codes
▶︎ AutoMerge = True (Log only) Merge the queues towards the right if there is no data in those queues.
▶︎ PageOnEveryBar = True Clear data from previous bars on each new bar, in conjuction with PageHistory setting.
▶︎ MoveLogUp = True Move log in up direction. Setting to false will push logs down.
▶︎ MarkNewBar = True On each change of bar, add a marker to show the bar has changed
▶︎ PrefixLogLevel = True (Console only) Prefix all messages with the log level corresponding to error code.
▶︎ MinWidth = 40 Set the minimum width needed to be seen. Prevents logx/console shrinking below these number of characters.
▶︎ TabSizeQ1 = 0 If set to more than one, the messages on Q1 or Console messages will indent by this size based on error code (Max 4 used)
▶︎ TabSizeQ2 = 0 If set to more than one, the messages on Q2 will indent by this size based on error code (Max 4 used)
▶︎ TabSizeQ3 = 0 If set to more than one, the messages on Q2 will indent by this size based on error code (Max 4 used)
▶︎ TabSizeQ4 = 0 If set to more than one, the messages on Q2 will indent by this size based on error code (Max 4 used)
▶︎ TabSizeQ5 = 0 If set to more than one, the messages on Q2 will indent by this size based on error code (Max 4 used)
▶︎ TabSizeQ6 = 0 If set to more than one, the messages on Q2 will indent by this size based on error code (Max 4 used)
▶︎ PageHistory = 0 Used with PageOnEveryBar. Determines how many historial pages to keep.
▶︎ HeaderQbarIndex = 'Bar#' (Logx only) The header to show for Bar Index
▶︎ HeaderQdateTime = 'Date' (Logx only) The header to show for Date/Time
▶︎ HeaderQerrorCode = 'eCode' (Logx only) The header to show for Error Codes
▶︎ HeaderQlogLevel = 'State' (Logx only) The header to show for Log Level
▶︎ HeaderQ1 = 'h.Q1' (Logx only) The header to show for Q1
▶︎ HeaderQ2 = 'h.Q2' (Logx only) The header to show for Q2
▶︎ HeaderQ3 = 'h.Q3' (Logx only) The header to show for Q3
▶︎ HeaderQ4 = 'h.Q4' (Logx only) The header to show for Q4
▶︎ HeaderQ5 = 'h.Q5' (Logx only) The header to show for Q5
▶︎ HeaderQ6 = 'h.Q6' (Logx only) The header to show for Q6
▶︎ Status = '' Set the status to this text.
▶︎ HeaderColor Set the color for the header
▶︎ HeaderColorBG Set the background color for the header
▶︎ StatusColor Set the color for the status bar
▶︎ StatusColorBG Set the background color for the status bar
▶︎ TextColor Set the color for the text used without error code or code 0.
▶︎ TextColorBG Set the background color for the text used without error code or code 0.
▶︎ FrameColor Set the color for the frame around Logx/Console
▶︎ FrameSize = 1 Set the size of the frame around Logx/Console
▶︎ CellBorderSize = 0 Set the size of the border around cells.
▶︎ CellBorderColor Set the color for the border around cells within Logx/Console
▶︎ SeparatorColor = gray Set the color of separate in between Console/Logx Attachment
◼︎ Methods (summary)
● init ▶︎ Initialise the log
● log ▶︎ Log the messages. Use method show to display the messages
● page ▶︎ Clear messages from previous bar while logging messages on this bar.
● show ▶︎ Shows a table displaying the logged messages
● clear ▶︎ Clears the log of all messages
● resize ▶︎ Resizes the log. If size is for reduction then oldest messages are lost first.
● turnPage ▶︎ When called, all messages marked with previous page, or from start are cleared
● dateTimeFormat ▶︎ Sets the date time format to be used when displaying date/time info.
● resetTextColor ▶︎ Reset Text Color to library default
● resetTextBGcolor ▶︎ Reset Text BG Color to library default
● resetHeaderColor ▶︎ Reset Header Color to library default
● resetHeaderBGcolor ▶︎ Reset Header BG Color to library default
● resetStatusColor ▶︎ Reset Status Color to library default
● resetStatusBGcolor ▶︎ Reset Status BG Color to library default
● setColors ▶︎ Sets the colors to be used for corresponding error codes
● setColorsBG ▶︎ Sets the background colors to be used for corresponding error codes. If not match of error code, then text color used.
● setColorsHC ▶︎ Sets the highlight colors to be used for corresponding error codes.If not match of error code, then text bg color used.
● resetColors ▶︎ Reset the colors to library default (Total 36, not including error code 0)
● resetColorsBG ▶︎ Reset the background colors to library default
● resetColorsHC ▶︎ Reset the highlight colors to library default
● setLevelNames ▶︎ Set the log level names to be used for corresponding error codes. If not match of error code, then empty string used.
● resetLevelNames ▶︎ Reset the log level names to library default. (Total 36) 1=TRACE, 2=DEBUG, 3=INFO, 4=WARNING, 5=ERROR, 6=CRITICAL, 7=FATAL
● attach ▶︎ Attaches a console to an existing Logx, allowing to have dual logging system independent of each other
● detach ▶︎ Detaches an already attached console from Logx
method clear(this)
Clears all the queue, including bar_index and time queues, of existing messages
Namespace types: log
Parameters:
this (log)
method resize(this, rows)
Resizes the message queues. If size is decreased then removes the oldest messages
Namespace types: log
Parameters:
this (log)
rows (int) : The new size needed for the queues. Default value is 40.
method dateTimeFormat(this, format)
Re/set the date time format used for displaying date and time. Default resets to dd.MMM.yy HH:mm
Namespace types: log
Parameters:
this (log)
format (string)
method resetTextColor(this)
Resets the text color of the log to library default.
Namespace types: log
Parameters:
this (log)
method resetTextColorBG(this)
Resets the background color of the log to library default.
Namespace types: log
Parameters:
this (log)
method resetHeaderColor(this)
Resets the color used for Headers, to library default.
Namespace types: log
Parameters:
this (log)
method resetHeaderColorBG(this)
Resets the background color used for Headers, to library default.
Namespace types: log
Parameters:
this (log)
method resetStatusColor(this)
Resets the text color of the status row, to library default.
Namespace types: log
Parameters:
this (log)
method resetStatusColorBG(this)
Resets the background color of the status row, to library default.
Namespace types: log
Parameters:
this (log)
method resetFrameColor(this)
Resets the color used for the frame around the log table, to library default.
Namespace types: log
Parameters:
this (log)
method resetColorsHC(this)
Resets the color used for the highlighting when Highlight Text option is used, to library default
Namespace types: log
Parameters:
this (log)
method resetColorsBG(this)
Resets the background color used for setting the background color, when the Color Text option is used, to library default
Namespace types: log
Parameters:
this (log)
method resetColors(this)
Resets the color used for respective error codes, when the Color Text option is used, to library default
Namespace types: log
Parameters:
this (log)
method setColors(this, c)
Sets the colors corresponding to error codes
Index 0 of input array c is color is reserved for future use.
Index 1 of input array c is color for debug code 1.
Index 2 of input array c is color for debug code 2.
There are 2 modes of coloring
1 . Using the Foreground color
2 . Using the Foreground color as background color and a white/black/gray color as foreground color
This is denoting or highlighting. Which effectively puts the foreground color as background color
Namespace types: log
Parameters:
this (log)
c (color ) : Array of colors to be used for corresponding error codes. If the corresponding code is not found, then text color is used
method setColorsHC(this, c)
Sets the highlight colors corresponding to error codes
Index 0 of input array c is color is reserved for future use.
Index 1 of input array c is color for debug code 1.
Index 2 of input array c is color for debug code 2.
There are 2 modes of coloring
1 . Using the Foreground color
2 . Using the Foreground color as background color and a white/black/gray color as foreground color
This is denoting or highlighting. Which effectively puts the foreground color as background color
Namespace types: log
Parameters:
this (log)
c (color ) : Array of highlight colors to be used for corresponding error codes. If the corresponding code is not found, then text color BG is used
method setColorsBG(this, c)
Sets the highlight colors corresponding to debug codes
Index 0 of input array c is color is reserved for future use.
Index 1 of input array c is color for debug code 1.
Index 2 of input array c is color for debug code 2.
There are 2 modes of coloring
1 . Using the Foreground color
2 . Using the Foreground color as background color and a white/black/gray color as foreground color
This is denoting or highlighting. Which effectively puts the foreground color as background color
Namespace types: log
Parameters:
this (log)
c (color ) : Array of background colors to be used for corresponding error codes. If the corresponding code is not found, then text color BG is used
method resetLevelNames(this, prefix, suffix)
Resets the log level names used for corresponding error codes
With prefix/suffix, the default Level name will be like => prefix + Code + suffix
Namespace types: log
Parameters:
this (log)
prefix (string) : Prefix to use when resetting level names
suffix (string) : Suffix to use when resetting level names
method setLevelNames(this, names)
Resets the log level names used for corresponding error codes
Index 0 of input array names is reserved for future use.
Index 1 of input array names is name used for error code 1.
Index 2 of input array names is name used for error code 2.
Namespace types: log
Parameters:
this (log)
names (string ) : Array of log level names be used for corresponding error codes. If the corresponding code is not found, then an empty string is used
method init(this, rows, isConsole)
Sets up data for logging. It consists of 6 separate message queues, and 3 additional queues for bar index, time and log level/error code. Do not directly alter the contents, as library could break.
Namespace types: log
Parameters:
this (log)
rows (int) : Log size, excluding the header/status. Default value is 50.
isConsole (bool) : Whether to init the log as console or logx. True= as console, False = as Logx. Default is true, hence init as console.
method log(this, ec, m1, m2, m3, m4, m5, m6, tv, log)
Logs messages to the queues , including, time/date, bar_index, and error code
Namespace types: log
Parameters:
this (log)
ec (int) : Error/Code to be assigned.
m1 (string) : Message needed to be logged to Q1, or for console.
m2 (string) : Message needed to be logged to Q2. Not used/ignored when in console mode
m3 (string) : Message needed to be logged to Q3. Not used/ignored when in console mode
m4 (string) : Message needed to be logged to Q4. Not used/ignored when in console mode
m5 (string) : Message needed to be logged to Q5. Not used/ignored when in console mode
m6 (string) : Message needed to be logged to Q6. Not used/ignored when in console mode
tv (int) : Time to be used. Default value is time, which logs the start time of bar.
log (bool) : Whether to log the message or not. Default is true.
method page(this, ec, m1, m2, m3, m4, m5, m6, tv, page)
Logs messages to the queues , including, time/date, bar_index, and error code. All messages from previous bars are cleared
Namespace types: log
Parameters:
this (log)
ec (int) : Error/Code to be assigned.
m1 (string) : Message needed to be logged to Q1, or for console.
m2 (string) : Message needed to be logged to Q2. Not used/ignored when in console mode
m3 (string) : Message needed to be logged to Q3. Not used/ignored when in console mode
m4 (string) : Message needed to be logged to Q4. Not used/ignored when in console mode
m5 (string) : Message needed to be logged to Q5. Not used/ignored when in console mode
m6 (string) : Message needed to be logged to Q6. Not used/ignored when in console mode
tv (int) : Time to be used. Default value is time, which logs the start time of bar.
page (bool) : Whether to log the message or not. Default is true.
method turnPage(this, turn)
Set the messages to be on a new page, clearing messages from previous page.
This is not dependent on PageHisotry option, as this method simply just clears all the messages, like turning old pages to a new page.
Namespace types: log
Parameters:
this (log)
turn (bool)
method show(this, position, hhalign, hvalign, hsize, thalign, tvalign, tsize, show, attach)
Display Message Q, Index Q, Time Q, and Log Levels
All options for postion/alignment accept TV values, such as position.bottom_right, text.align_left, size.auto etc.
Namespace types: log
Parameters:
this (log)
position (string) : Position of the table used for displaying the messages. Default is Bottom Right.
hhalign (string) : Horizontal alignment of Header columns
hvalign (string) : Vertical alignment of Header columns
hsize (string) : Size of Header text Options
thalign (string) : Horizontal alignment of all messages
tvalign (string) : Vertical alignment of all messages
tsize (string) : Size of text across the table
show (bool) : Whether to display the logs or not. Default is true.
attach (log) : Console that has been attached via attach method. If na then console will not be shown
method attach(this, attach, position)
Attaches a console to Logx, or moves already attached console around Logx
All options for position/alignment accept TV values, such as position.bottom_right, text.align_left, size.auto etc.
Namespace types: log
Parameters:
this (log)
attach (log) : Console object that has been previously attached.
position (string) : Position of Console in relation to Logx. Can be Top, Right, Bottom, Left. Default is Bottom. If unknown specified then defaults to bottom.
method detach(this, attach)
Detaches the attached console from Logx.
All options for position/alignment accept TV values, such as position.bottom_right, text.align_left, size.auto etc.
Namespace types: log
Parameters:
this (log)
attach (log) : Console object that has been previously attached.
Daily Gaps & Trapped PositionsThis script builds substantially upon the default Gaps script provided by Tradingview. Functionality was added to allow users to decide what price from the previous session is used to determine a daily gap, added support for showing gaps across all timeframes up to the daily time frame, and also allow gaps to be shown even with ETH enabled on the chart. This script provides support across normal securities, futures, and also crypto.
Users can decide between the following selections to determine if a daily gap has formed:
- Previous Session Close
- Previous Session High/Low
- Last RTH Candle High/Low
The other larger piece that was added is something called trapped positions or what some folks familiar with Market Profile would call "single prints". They could also be considered FVGs but they are a specific subset of FVGs as these must from above or below the current session's high/low.
Single prints form above or below a current session's high/low and can be considered an area where price has moved too fast in that area and price will most likely return to these areas at a later point in time. In some teachings, these are also looked at as "trapped shorts" (lighter blue box color) or "trapped supply" (yellow orange box color) which creates an area where there will be potential support (trapped shorts) or resistance (trapped supply) when this area is revisited in the future. Adding these to your chart will simply provide additional areas of interest where you may see buying or selling.
Both gaps and trapped positions have the following options:
- Show only active gaps/trapped positions. Selecting this will only show areas where price has not completely traded through the box.
- Close gaps/trapped positions partially. If this is selected, it will reduce the box size as price is traded through the area. If it is not selected, the box will only disappear once price has traded through the entire box completely.
There are some additional settings that allow you to tailor how many boxes show up on the chart. These settings are as follows:
- Max number of boxes. This setting will only plot up to this number of gaps/trapped positions.
- Minimum Deviation. This will prevent gaps/trapped positions from showing if they are too small relative to average across that last 14 periods.
- Limit Max Box Trail Length (bars). If checkbox is selected, the box will stop being extended after X number of bars given in this input.
Multi Time Frame Normalized PriceEnhance Your Trading Experience with the Multi Time Frame Normalized Price Indicator
Introduction
As a trader, having a clear and informative chart is crucial for making informed decisions. In this post, we will introduce the Multi Time Frame Normalized Price (MTFNP) Indicator, an innovative trading tool that offers an insightful perspective on price action. The script creates a symmetric chart, with the time axis going from top to bottom, making it easier to identify potential tops and bottoms in various ranges. Let's dive deeper into this powerful tool to understand how it works and how it can improve your trading experience.
The Multi Time Frame Normalized Price Indicator
The MTFNP Indicator is designed to provide a comprehensive view of price action across multiple time frames. By plotting the normalized price levels for each time frame, traders can easily identify areas of support and resistance, as well as potential tops and bottoms in various ranges.
One of the key features of this indicator is the symmetry of the chart. Instead of the traditional horizontal time axis, the MTFNP Indicator plots the time axis vertically from top to bottom. This innovative approach makes it easier for traders to visualize the price action across different time frames, enabling them to make more informed decisions.
Benefits of a Symmetric Chart
There are several advantages to using a symmetric chart with a vertical time axis, such as:
Easier to read: The unique layout of the chart makes it easier to analyze price action across multiple time frames. The clear separation between each time frame helps traders avoid confusion and identify important price levels more effectively.
Identifying tops and bottoms: The symmetric presentation of price action enables traders to quickly spot potential tops and bottoms in various ranges. This can be particularly useful for identifying potential reversal points or areas of support and resistance.
Improved decision-making: By offering a comprehensive view of price action, the MTFNP Indicator helps traders make better-informed decisions. This can lead to improved trading strategies and ultimately, better results.
The MTFNP Indicator Script
The MTFNP Indicator script leverages several custom functions, including the Chebyshev Type I Moving Average, to provide a smooth and responsive signal. Additionally, the indicator uses the Spider Plot function to create a symmetric chart with the time axis going from top to bottom.
To customize the MTFNP Indicator to your preferences, you can adjust the input parameters, such as the standard deviation length, multiplier, axes color, bottom color, and top color. You can also change the scale to fit your desired chart size.
Exploring the Relationship between Min, Max Values and Time Frames
In the Multi Time Frame Normalized Price (MTFNP) script, it is crucial to understand the relationship between the min and max values across different time frames. By analyzing how these values relate to each other, traders can make more informed decisions about market trends and potential reversals. In this section, we will dive deep into the relationship between the current time frame's min and max values and those of the further-out time frames.
Interpreting Min and Max Values Across Time Frames
When analyzing the min and max values of the current time frame in relation to the further-out time frames, it is essential to keep in mind the following points:
All min values: If the current time frame and all further-out time frames have min values, this is a strong indication that the current price level is not just a local minimum. Instead, it is likely a more significant support level. In such cases, there is a higher probability that the price will bounce back upwards, making it a potentially favorable entry point for a long position.
All max values: Conversely, if the current time frame and all further-out time frames have max values, this suggests that the current price level is not just a local maximum. Instead, it is likely a more significant resistance level. In these situations, there is a higher probability that the price will reverse downwards, making it a potentially favorable entry point for a short position.
Neutral values with high current time frame: If the current time frame has a high value while the further-out time frames are more neutral, it could indicate that the trend may continue. This is because the high value in the current time frame may signify momentum in the market, whereas the neutral values in the further-out time frames suggest that the trend has not yet reached an extreme level. In this case, traders might consider following the trend and entering a position in the direction of the current movement.
Neutral values with low current time frame: If the current time frame has a low value while the further-out time frames are more neutral, it could indicate that the trend may reverse. This is because the low value in the current time frame may suggest a potential reversal point, whereas the neutral values in the further-out time frames imply that the trend has not yet reached an extreme level. In this case, traders might consider entering a counter-trend position, anticipating a potential reversal.
Balancing Different Time Frames for Optimal Decision Making
It is essential to remember that relying solely on min and max values across different time frames can lead to potential pitfalls. The market is influenced by a wide array of factors, and no single indicator or data point can provide a complete picture. To make the most informed decisions, traders should consider incorporating additional technical analysis tools and evaluating the overall market context.
Moreover, it is crucial to maintain a balance between the current time frame and the further-out time frames. While the current time frame provides information about the most recent market movements, the further-out time frames offer a broader perspective on the market's historical behavior. By combining insights from both types of time frames, traders can make more comprehensive assessments of potential opportunities and risks.
Conclusion
In conclusion, the Multi Time Frame Normalized Price (MTFNP) script offers traders valuable insights by analyzing the relationship between the current time frame and further-out time frames. By identifying potential trend reversals and continuations, traders can make better-informed decisions about market entry and exit points.
Understanding the relationship between min and max values across different time frames is an essential component of using the MTFNP script effectively. By carefully analyzing these relationships and incorporating additional technical analysis tools, traders can improve their decision-making process and enhance their overall trading strategy.
However, it is important to remember that relying solely on the MTFNP script or any single indicator can lead to potential pitfalls. The market is influenced by a wide array of factors, and no single indicator or data point can provide a complete picture. To make the most informed decisions, traders should consider using a combination of technical analysis tools, evaluating the overall market context, and maintaining a balance between the current time frame and the further-out time frames for a comprehensive understanding of the market's behavior. By doing so, they can increase their chances of success in the ever-changing and complex world of trading.
Volume-based Support & Resistance Zones-V1 By Trade Mastership™ The all-new Support & Resistance Zones indicator, which has been upgraded to offer traders more powerful features and functionality. This innovative indicator identifies high-volume fractal lows or highs to create zones based on the size of the wick for that timeframe's candle. This makes it easy for traders to visualize which price levels are the most significant for either a trend continuation or a reversal when zones are broken and retested.
The original script for this indicator was created by Trade Mastership, with additional modifications by L N Behera. Credit goes to both of them for the majority of the logic behind this script. Since then, the script has been improved with several changes, including:
Changing the default S/R lines from plots to lines, and giving users the option to change between solid, dashed, or dotted lines for both S/R lines
Adding additional timeframes and more options for TF1, beyond the current TF. Now, users have four timeframes to plot S/R zones from
Giving users the option to easily change the line thickness for all S/R lines
Making it easier to change the colors of S/R lines and zones by consolidating the options under settings (rather than under style)
Adding extensions to active SR Zones to extend all the way right
Adding the option to extend or not extend the previous S/R zones up to the next S/R zone
Adding optional timeframe labels to active S/R zones, with left and right options, as well as the option to adjust how far to the right the label is set
Fixing an issue where the higher timeframe S/R zone was not properly starting from the high/low of fractal. Now, any higher timeframe S/R will begin exactly at the High/Low points. Note that this may not work perfectly on stocks, and if a fractal high/low is too many bars in the past, it will revert to a default max bars back to avoid script errors.
Adding a function to prevent S/R zones from lower timeframes displaying while on a higher timeframe. This helps clean up the chart quite a bit.
Creating arrays for each timeframe's boxes and lines so that the number of S/R zones can be controlled for each timeframe and limit memory consumption.
Adding new alert options and customized alert messages
Here's how this indicator works: it looks for fractal highs or fractal lows with volume that pierces above the volume's Moving Average. This moving average value can be modified in the settings for each timeframe. The fractal highs will be confirmed with three successive higher highs followed by two successive lower highs and vice versa for the fractal lows. The zone is created from the fractal high/low and the close of the candle for whatever timeframe you selected. The bigger the zone, the more significant that zone is.
Traders can disable any zone, change the zones to show lines only, and modify all the colors, transparencies, and thickness of lines for all the zones. To create alerts, traders can enable the types of alerts they want for each timeframe in the indicator's settings. After applying changes, right-click on one of the zones on the chart, and click "Add Alert on Vol S/R Zones." You do not need to add a title, as the correct alert messages are already built-in.
The latest update has migrated the script to Pine Script Version 5 and added a higher number of total boxes/lines to show on the chart. It has also increased the max bars count to the maximum Pine Script allows, enabling traders to utilize as many bars as possible when drawing the left side of SR zones that are very far back on the chart. Additionally, the update fixed issues where the indicator would not load on 1 minute and 3-minute charts unless higher timeframe SR zones
Bearish 5-0 Harmonic Patterns [theEccentricTrader]█ OVERVIEW
This indicator automatically draws bearish 5-0 harmonic patterns and price projections derived from the ranges that constitute the patterns.
█ CONCEPTS
Green and Red Candles
• A green candle is one that closes with a close price equal to or above the price it opened.
• A red candle is one that closes with a close price that is lower than the price it opened.
Swing Highs and Swing Lows
• A swing high is a green candle or series of consecutive green candles followed by a single red candle to complete the swing and form the peak.
• A swing low is a red candle or series of consecutive red candles followed by a single green candle to complete the swing and form the trough.
Peak and Trough Prices (Basic)
• The peak price of a complete swing high is the high price of either the red candle that completes the swing high or the high price of the preceding green candle, depending on which is higher.
• The trough price of a complete swing low is the low price of either the green candle that completes the swing low or the low price of the preceding red candle, depending on which is lower.
Historic Peaks and Troughs
The current, or most recent, peak and trough occurrences are referred to as occurrence zero. Previous peak and trough occurrences are referred to as historic and ordered numerically from right to left, with the most recent historic peak and trough occurrences being occurrence one.
Range
The range is simply the difference between the current peak and current trough prices, generally expressed in terms of points or pips.
Support and Resistance
• Support refers to a price level where the demand for an asset is strong enough to prevent the price from falling further.
• Resistance refers to a price level where the supply of an asset is strong enough to prevent the price from rising further.
Support and resistance levels are important because they can help traders identify where the price of an asset might pause or reverse its direction, offering potential entry and exit points. For example, a trader might look to buy an asset when it approaches a support level , with the expectation that the price will bounce back up. Alternatively, a trader might look to sell an asset when it approaches a resistance level , with the expectation that the price will drop back down.
It's important to note that support and resistance levels are not always relevant, and the price of an asset can also break through these levels and continue moving in the same direction.
Upper Trends
• A return line uptrend is formed when the current peak price is higher than the preceding peak price.
• A downtrend is formed when the current peak price is lower than the preceding peak price.
• A double-top is formed when the current peak price is equal to the preceding peak price.
Lower Trends
• An uptrend is formed when the current trough price is higher than the preceding trough price.
• A return line downtrend is formed when the current trough price is lower than the preceding trough price.
• A double-bottom is formed when the current trough price is equal to the preceding trough price.
Muti-Part Upper and Lower Trends
• A multi-part return line uptrend begins with the formation of a new return line uptrend, or higher peak, and continues until a new downtrend, or lower peak, completes the trend.
• A multi-part downtrend begins with the formation of a new downtrend, or lower peak, and continues until a new return line uptrend, or higher peak, completes the trend.
• A multi-part uptrend begins with the formation of a new uptrend, or higher trough, and continues until a new return line downtrend, or lower trough, completes the trend.
• A multi-part return line downtrend begins with the formation of a new return line downtrend, or lower trough, and continues until a new uptrend, or higher trough, completes the trend.
Wave Cycles
A wave cycle is here defined as a complete two-part move between a swing high and a swing low, or a swing low and a swing high. The first swing high or swing low will set the course for the sequence of wave cycles that follow; for example a chart that begins with a swing low will form its first complete wave cycle upon the formation of the first complete swing high and vice versa.
Figure 1.
Fibonacci Retracement and Extension Ratios
The Fibonacci sequence is a series of numbers in which each number is the sum of the two preceding numbers, starting with 0 and 1. For example 0 + 1 = 1, 1 + 1 = 2, 1 + 2 = 3, and so on. Ultimately, we could go on forever but the first few numbers in the sequence are as follows: 0 , 1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89, 144.
The extension ratios are calculated by dividing each number in the sequence by the number preceding it. For example 0/1 = 0, 1/1 = 1, 2/1 = 2, 3/2 = 1.5, 5/3 = 1.6666..., 8/5 = 1.6, 13/8 = 1.625, 21/13 = 1.6153..., 34/21 = 1.6190..., 55/34 = 1.6176..., 89/55 = 1.6181..., 144/89 = 1.6179..., and so on. The retracement ratios are calculated by inverting this process and dividing each number in the sequence by the number proceeding it. For example 0/1 = 0, 1/1 = 1, 1/2 = 0.5, 2/3 = 0.666..., 3/5 = 0.6, 5/8 = 0.625, 8/13 = 0.6153..., 13/21 = 0.6190..., 21/34 = 0.6176..., 34/55 = 0.6181..., 55/89 = 0.6179..., 89/144 = 0.6180..., and so on.
1.618 is considered to be the 'golden ratio', found in many natural phenomena such as the growth of seashells and the branching of trees. Some now speculate the universe oscillates at a frequency of 0,618 Hz, which could help to explain such phenomena, but this theory has yet to be proven.
Traders and analysts use Fibonacci retracement and extension indicators, consisting of horizontal lines representing different Fibonacci ratios, for identifying potential levels of support and resistance. Fibonacci ranges are typically drawn from left to right, with retracement levels representing ratios inside of the current range and extension levels representing ratios extended outside of the current range. If the current wave cycle ends on a swing low, the Fibonacci range is drawn from peak to trough. If the current wave cycle ends on a swing high the Fibonacci range is drawn from trough to peak.
Harmonic Patterns
The concept of harmonic patterns in trading was first introduced by H.M. Gartley in his book "Profits in the Stock Market", published in 1935. Gartley observed that markets have a tendency to move in repetitive patterns, and he identified several specific patterns that he believed could be used to predict future price movements.
Since then, many other traders and analysts have built upon Gartley's work and developed their own variations of harmonic patterns. One such contributor is Larry Pesavento, who developed his own methods for measuring harmonic patterns using Fibonacci ratios. Pesavento has written several books on the subject of harmonic patterns and Fibonacci ratios in trading. Another notable contributor to harmonic patterns is Scott Carney, who developed his own approach to harmonic trading in the late 1990s and also popularised the use of Fibonacci ratios to measure harmonic patterns. Carney expanded on Gartley's work and also introduced several new harmonic patterns, such as the Shark pattern and the 5-0 pattern.
The bullish and bearish Gartley patterns are the oldest recognized harmonic patterns in trading and all the other harmonic patterns are ultimately modifications of the original Gartley patterns. Gartley patterns are fundamentally composed of 5 points, or 4 waves.
Bullish and Bearish 5-0 Patterns
• Bullish 5-0 patterns are fundamentally composed of three peaks and three troughs, with the second peak being lower than the first peak and the third peak being higher than the first peak. And similarly, the second trough being lower than the first trough and the third trough being higher than both the first and second troughs.
• Bearish 5-0 patterns are fundamentally composed of three troughs and three peaks, with the second trough being higher than the first trough and the third trough being lower than the first trough. And similarly, the second peak being higher than the first peak and the third peak being lower than both the first and second peaks.
The ratio measurements recommended by Scott Carney, who originated the pattern, are as follows:
• Wave 1 of the pattern, referred to as OX, has no specific ratio requirements.
• Wave 2 of the pattern, referred to as XA, has no specific ratio requirements.
• Wave 3 of the pattern, referred to as AB, should extend to at least 113%, but no further than 161.8% of the range set by wave 2.
• Wave 4 of the pattern, referred to as BC, should extend to at least 161.8%, but no further than 224% of the range set by wave 3.
• Wave 5 of the pattern, referred to as CD, should retrace to 50.0% of the range set by wave 4.
Measurement Tolerances
In general, tolerance in measurements refers to the allowable variation or deviation from a specific value or dimension. It is the range within which a particular measurement is considered to be acceptable or accurate. In this script I have applied this concept to the measurement of harmonic pattern ratios to increase to the frequency of pattern occurrences.
For example, the AB measurement of Gartley patterns is generally set at around 61.8%, but with such specificity in the measuring requirements the patterns are very rare. We can increase the frequency of pattern occurrences by setting a tolerance. A tolerance of 10% to both downside and upside, which is the default setting for all tolerances, means we would have a tolerable measurement range between 51.8-71.8%, thus increasing the frequency of occurrence.
█ FEATURES
Inputs
• AB Lower Tolerance
• AB Upper Tolerance
• BC Lower Tolerance
• BC Upper Tolerance
• CD Lower Tolerance
• CD Upper Tolerance
• Pattern Color
• Label Color
• Show Projections
• Extend Current Projection Lines
█ LIMITATIONS
All green and red candle calculations are based on differences between open and close prices, as such I have made no attempt to account for green candles that gap lower and close below the close price of the preceding candle, or red candles that gap higher and close above the close price of the preceding candle. This may cause some unexpected behaviour on some markets and timeframes. I can only recommend using 24-hour markets, if and where possible, as there are far fewer gaps and, generally, more data to work with.
█ NOTES
Here is a link to Scott's harmonic patterns webpage for those who may be interested: harmonictrader.com
