Supports & Resistances [UAlgo]The "Supports & Resistances " indicator is designed to identify and visualize key support and resistance levels on the price chart. It utilizes the Average True Range (ATR) and Pivot Points to define the boundaries of S & R zones and considers historical price action to assess the strength of these zones.
🔶 How to Obtain Zones
The script continuously analyzes the price action and identifies potential support and resistance zones based on the following criteria:
Zone Creation: For swing highs, a zone is created with the high price at the zone length as the top and the top minus the Average True Range (ATR) as the bottom. Conversely, for swing lows, the zone is created with the low price at the zone length as the bottom and the low plus the ATR as the top.
Zone Strength Calculation: The script iterates through historical bars within the zone and counts how many times the price (low for support, high for resistance) touched but failed to break entirely through the zone. This count is assigned as the zone's "strength".
Zone Display and Removal: It identifying zones by assigning a "strength" value based on how many times the price has approached but failed to break the zone. This helps prioritize stronger potential support/resistance levels. Only zones exceeding the defined "strength threshold" are visually displayed on the chart. Weaker zones or those broken by price are automatically removed.
🔶 Parameters
Zone Length: Traders can adjust S & R detection sensitivity, length to be used to find pivot points.
Strength Threshold: Set the minimum number of times the price needs to touch but fail to break a zone for it to be considered "strong" and displayed.
Visual Settings: Tailor the appearance of the support/resistance zones by defining separate colors and text size for borders, backgrounds, and zone text.
🔶 Disclaimer
The "Supports & Resistances " indicator is provided for educational and informational purposes only.
It should not be considered as financial advice or a recommendation to buy or sell any financial instrument.
The use of this indicator involves inherent risks, and users should employ their own judgment and conduct their own research before making any trading decisions. Past performance is not indicative of future results.
🔷 Related Scripts
Support and Resistance with Signals
ATR Based Support and Resistance Zones
Análisis de tendencia
Zero Lag Exponential Moving Average ForLoop [InvestorUnknown]Overview
The Zero Lag Exponential Moving Average (ZLEMA) ForLoop indicator is designed for traders seeking a responsive and adaptive tool to identify trend changes. By leveraging a range of lengths and different moving average (MA) types, this indicator helps smooth out price data and provides timely signals for market entry and exit.
User Inputs
Start and End Lengths: Define the range of lengths over which the IIRF values are calculated.
Moving Average Type: Choose from EMA, SMA, WMA, VWMA, or TMA for trend smoothing.
Moving Average Length: Specify the length for the chosen MA type.
Calculation Source: Select the price data used for calculations.
Signal Calculation
Signal Mode (sigmode): Determines the type of signal generated by the indicator. Options are "Fast", "Slow", "Thresholds Crossing", and "Fast Threshold".
1. Slow: is a simple crossing of the midline (0).
2. Fast: positive signal depends if the current MA > MA or MA is above 0.99, negative signals comes if MA < MA or MA is below -0.99.
3. Thresholds Crossing: simple ta.crossover and ta.crossunder of the user defined threshold for Long and Short.
4. Fast Threshold: signal changes if the value of MA changes by more than user defined threshold against the current signal
col1 = MA > 0 ? colup : coldn
var color col2 = na
if MA > MA or MA > 0.99
col2 := colup
if MA < MA or MA < -0.99
col2 := coldn
var color col3 = na
if ta.crossover(MA,longth)
col3 := colup
if ta.crossunder(MA,shortth)
col3 := coldn
var color col4 = na
if (MA > MA + fastth)
col4 := colup
if (MA < MA - fastth)
col4 := coldn
color col = switch sigmode
"Slow" => col1
"Fast" => col2
"Thresholds Crossing" => col3
"Fast Threshold" => col4
Visualization Settings
Bull Color (colup): The color used to indicate bullish signals.
Bear Color (coldn): The color used to indicate bearish signals.
Color Bars (barcol): Option to color the bars based on the signal.
Custom function
// Function to calculate an array of ZLEMA values over a range of lengths
ZLEMAForLoop(a, b, c, s) =>
// Initialize an array to hold ZLEMA trend values
var Array = array.new_float(b - a + 1, 0.0)
// Loop through the range from 'a' to 'b'
for x = 0 to (b - a)
// Calculate the current length
len = a + x
// Calculate the lag based on the length
lag = math.floor((len - 1) / 2)
// Calculate the smoothing factor alpha
alpha = 2 / (len + 1)
// Initialize the ZLEMA variable
zlema = 0.0
// Compute the ZLEMA value
zlema := na(zlema ) ? (s + s - s ) : alpha * (s + s - s ) + (1 - alpha) * nz(zlema )
// Determine the trend based on ZLEMA value
trend = zlema > zlema ? 1 : -1
// Store the trend in the array
array.set(Array, x, trend)
// Calculate the average of the trend values
Avg = array.avg(Array)
// Apply the selected moving average type to the average trend value
float MA = switch maType
"EMA" => ta.ema(Avg, c) // Exponential Moving Average
"SMA" => ta.sma(Avg, c) // Simple Moving Average
"WMA" => ta.wma(Avg, c) // Weighted Moving Average
"VWMA" => ta.vwma(Avg, c) // Volume-Weighted Moving Average
"TMA" => ta.trima(Avg, c) // Triangular Moving Average
=>
runtime.error("No matching MA type found.") // Error handling for unsupported MA type
float(na)
// Return the array of trends, the average trend, and the moving average
Important Considerations
Speed vs. Stability: The ZLEMA ForLoop is designed for fast response times, making it ideal for short-term trading strategies. However, its sensitivity also means it may generate more signals, some of which could be false positives.
Use with Other Indicators: To improve the reliability of the signals, it is recommended to use the ZLEMA ForLoop in conjunction with other technical indicators.
Customization: Tailor the settings to match your trading style and risk tolerance. Adjusting the lengths, MA type, and thresholds can significantly impact the indicator's performance.
Conclusion
The ZLEMA ForLoop indicator offers a flexible tool for traders looking to capture trend changes quickly. By providing multiple modes and customization options, it allows traders to fine-tune their analysis and make informed decisions. For best results, use this indicator alongside other analytical tools to confirm signals and avoid potential false entries.
Infinite Impulse Response Filter ForLoop [InvestorUnknown]Overview
The Infinite Impulse Response Filter ForLoop indicator is designed for seeking quick and accurate trend identification. Leveraging the Infinite Impulse Response (IIR) filter technique, this indicator provides fast and responsive signals to aid in market timing and trend following.
User Inputs
Start and End Lengths: Define the range of lengths over which the IIRF values are calculated.
Moving Average Type: Choose from EMA, SMA, WMA, VWMA, or TMA for trend smoothing.
Moving Average Length: Specify the length for the chosen MA type.
Calculation Source: Select the price data used for calculations (default is close price).
Signal Calculation
Signal Mode (sigmode): Determines the type of signal generated by the indicator. Options are "Fast", "Slow", "Thresholds Crossing", and "Fast Threshold".
1. Slow: is a simple crossing of the midline (0).
2. Fast: positive signal depends if the current MA > MA or MA is above 0.99, negative signals comes if MA < MA or MA is below -0.99.
3. Thresholds Crossing: simple ta.crossover and ta.crossunder of the user defined threshold for Long and Short.
4. Fast Threshold: signal changes if the value of MA changes by more than user defined threshold against the current signal
col1 = MA > 0 ? colup : coldn
var color col2 = na
if MA > MA or MA > 0.99
col2 := colup
if MA < MA or MA < -0.99
col2 := coldn
var color col3 = na
if ta.crossover(MA,longth)
col3 := colup
if ta.crossunder(MA,shortth)
col3 := coldn
var color col4 = na
if (MA > MA + fastth)
col4 := colup
if (MA < MA - fastth)
col4 := coldn
color col = switch sigmode
"Slow" => col1
"Fast" => col2
"Thresholds Crossing" => col3
"Fast Threshold" => col4
Visualization Settings
Bull Color (colup): The color used to indicate bullish signals.
Bear Color (coldn): The color used to indicate bearish signals.
Color Bars (barcol): Option to color the bars based on the signal.
Custom function
// Function to calculate an array of IIRF values over a range of lengths
IIRFforLoop(a, b, c, s) =>
// Initialize an array to store IIRF values
var Array = array.new_float(b - a + 1, 0.0)
// Loop over the range from 'a' to 'b'
for x = 0 to (b - a)
// Calculate the length for the current iteration
len = a + x
// Calculate the IIRF alpha parameter
iirfAlpha = 2 / (len + 1)
// Calculate the lag for the IIRF calculation
iirfLag = math.round(1 / iirfAlpha - 1)
// Initialize the IIRF value
iirf = 0.0
// Update the IIRF value using the IIR filter formula
iirf := iirfAlpha * (s + ta.change(s, iirfLag)) + (1 - iirfAlpha) * nz(iirf )
// Determine the trend based on the current and previous IIRF values
trend = iirf > iirf ? 1 : -1
// Store the trend value in the array
array.set(Array, x, trend)
// Calculate the average of the IIRF values in the array
Avg = array.avg(Array)
// Calculate the moving average of the average IIRF values based on the selected MA type
float MA = switch maType
"EMA" => ta.ema(Avg, c) // Exponential Moving Average
"SMA" => ta.sma(Avg, c) // Simple Moving Average
"WMA" => ta.wma(Avg, c) // Weighted Moving Average
"VWMA" => ta.vwma(Avg, c) // Volume Weighted Moving Average
"TMA" => ta.trima(Avg, c) // Triangular Moving Average
=>
runtime.error("No matching MA type found.") // Error handling for invalid MA type
float(na)
// Return the array of IIRF values, their average, and the moving average
Important Considerations
Rapid Signal Response: The IIRF ForLoop is designed to provide very fast trend signals, making it suitable for short-term trading and quick decision-making.
Complementary Tool: While powerful, the IIRF ForLoop should be used in conjunction with other indicators and market analysis techniques to confirm signals and improve trading accuracy.
Conclusion
The Infinite Impulse Response Filter ForLoop indicator is a highly responsive and flexible tool that can significantly enhance your trading strategy. Its ability to quickly identify trends and generate signals based on various moving average types and customizable thresholds makes it invaluable for active traders. For the best results, use this indicator alongside other technical analysis tools to confirm signals and ensure robust trading decisions.
Moving Average Cross Probability [AlgoAlpha]Moving Average Cross Probability 📈✨
The Moving Average Cross Probability by AlgoAlpha calculates the probability of a cross-over or cross-under between the fast and slow values of a user defined Moving Average type before it happens, allowing users to benefit by front running the market.
✨ Key Features:
📊 Probability Histogram: Displays the Probability of MA cross in the form of a histogram.
🔄 Data Table: Displays forecast information for quick analysis.
🎨 Customizable MAs: Choose from various moving averages and customize their length.
🚀 How to Use:
🛠 Add Indicator: Add the indicator to favorites, and customize the settings to suite your trading style.
📊 Analyze Market: Watch the indicator to look for trend shifts early or for trend continuations.
🔔 Set Alerts: Get notified of bullish/bearish points.
✨ How It Works:
The Moving Average Cross Probability Indicator by AlgoAlpha determines the probability by looking at a probable range of values that the price can take in the next bar and finds out what percentage of those possibilities result in the user defined moving average crossing each other. This is done by first using the HMA to predict what the next price value will be, a standard deviation based range is then calculated. The range is divided by the user defined resolution and is split into multiple levels, each of these levels represent a possible value for price in the next bar. These possible predicted values are used to calculate the possible MA values for both the fast and slow MAs that may occur in the next bar and are then compared to see how many of those possible MA results end up crossing each other.
Stay ahead of the market with the Moving Average Cross Probability Indicator AlgoAlpha! 📈💡
Aroon ForLoop [InvestorUnknown]Overview
The Aroon ForLoop indicator is designed to calculate an array of Aroon values over a range of lengths, providing trend signals based on various moving averages. It offers flexibility with different signal modes and visual customizations.
User Input
Start Length (a) and End Length (b): Defines the range for calculating Aroon values.
MA Type (maType) and MA Length (c): Selects the moving average type (EMA, SMA, WMA, VWMA, TMA) and its length.
Calculation Source (s): Specifies the data source for calculations.
Signal Mode (sigmode): Offers options like Fast, Slow, Thresholds Crossing, and Fast Threshold to generate signals.
Thresholds: Configures long and short thresholds for signal generation.
Visualization Options: Customizes bull and bear colors, and enables/disables bar coloring.
Alert Settings: Chooses whether to wait for bar close for alert confirmation.
Signal Calculation
Signal Mode (sigmode): Determines the type of signal generated by the indicator. Options are "Fast", "Slow", "Thresholds Crossing", and "Fast Threshold".
1. Slow: is a simple crossing of the midline (0).
2. Fast: positive signal depends if the current MA > MA or MA is above 0.99, negative signals comes if MA < MA or MA is below -0.99.
3. Thresholds Crossing: simple ta.crossover and ta.crossunder of the user defined threshold for Long and Short.
4. Fast Threshold: signal changes if the value of Aroon MA changes by more than user defined threshold against the current signal
col1 = MA > 0 ? colup : coldn
var color col2 = na
if MA > MA or MA > 0.99
col2 := colup
if MA < MA or MA < -0.99
col2 := coldn
var color col3 = na
if ta.crossover(MA,longth)
col3 := colup
if ta.crossunder(MA,shortth)
col3 := coldn
var color col4 = na
if (MA > MA + fastth)
col4 := colup
if (MA < MA - fastth)
col4 := coldn
color col = na
if sigmode == "Slow"
col := col1
if sigmode == "Fast"
col := col2
if sigmode == "Thresholds Crossing"
col := col3
if sigmode == "Fast Threshold"
col := col4
else
na
Visualization Settings
Bull Color (colup): The color used to indicate bullish signals.
Bear Color (coldn): The color used to indicate bearish signals.
Color Bars (barcol): Option to color the bars based on the signal.
Custom Function
AroonForLoop: Calculates Aroon values over the specified range, determines the trend, and averages the results using the chosen moving average type.
AroonForLoop(a, b, c) =>
var SignalArray = array.new_float(b - a + 1, 0.0)
for x = 0 to (b - a)
len = a + x
upper = 100 * (ta.highestbars(high, len + 1) + len)/len
lower = 100 * (ta.lowestbars(low, len + 1) + len)/len
trend = upper > lower ? 1 : -1
array.set(SignalArray, x, trend)
Avg = array.avg(SignalArray)
float MA = switch maType
"EMA" => ta.ema(Avg, c)
"SMA" => ta.sma(Avg, c)
"WMA" => ta.wma(Avg, c)
"VWMA" => ta.vwma(Avg, c)
"TMA" => ta.trima(Avg, c)
=>
runtime.error("No matching MA type found.")
float(na)
Important Considerations
Fast Responses: The Aroon ForLoop indicator is designed for quick identification of trend changes, making it ideal for fast-paced trading environments.
Moving Average Types: Supports various MA types (EMA, SMA, WMA, VWMA, TMA) for adaptable smoothing of trend signals.
Combination with Other Indicators: For more reliable signals, use this indicator in conjunction with other technical indicators.
TSI w SuperTrend decision - Strategy [presentTrading]This strategy aims to improve upon the performance of Traidngview's newly published "Trend Strength Index" indicator by incorporating the SuperTrend for better trade execution and risk management. Enjoy :)
█ Introduction and How it is Different
The "TSI with SuperTrend Decision - Strategy" combines the Trend Strength Index (TSI) with SuperTrend indicators to determine entry and exit points. Unlike traditional strategies that rely solely on one indicator, this method leverages the strengths of both TSI and SuperTrend to provide a more nuanced and adaptive trading strategy.
This dual approach allows for capturing trends more effectively, especially in volatile markets.
BTCUSD 8h LS Performance
█ Strategy, How it Works: Detailed Explanation
🔶 Trend Strength Index (TSI)
The TSI is a momentum oscillator that shows both the direction and strength of a trend. It is calculated by comparing the price movement with the bar index over a specified period. The formula for TSI is as follows:
```
TSI = (PC / |PC|)
where:
PC = Change in price over the period
```
In this strategy, TSI is calculated using the closing prices and a default period of 64 bars. The TSI values help identify overbought and oversold conditions, providing signals for potential market reversals.
🔶 SuperTrend Indicator
The SuperTrend is a trend-following indicator based on the average true range (ATR). It helps in identifying the direction of the market trend. The SuperTrend calculation involves:
```
SuperTrend = HLC3 ± (Factor * ATR)
where:
HLC3 = (High + Low + Close) / 3
Factor = User-defined multiplier
ATR = Average True Range over a period
```
The SuperTrend settings in this strategy include a length of 10 bars and a factor of 3.0.
Last Bull Cycle of BTC
🔶 Entry and Exit Conditions
The strategy uses the TSI and SuperTrend together to determine entry and exit points:
- Long Entry: When the SuperTrend indicates a downward trend (st.d < 0) and the TSI is above the oversold level (-0.241).
- Long Exit: When the SuperTrend indicates an upward trend (st.d > 0) and the TSI is below the overbought level (0.241).
- Short Entry: When the SuperTrend indicates an upward trend (st.d > 0) and the TSI is below the overbought level (0.241).
- Short Exit: When the SuperTrend indicates a downward trend (st.d < 0) and the TSI is above the oversold level (-0.241).
█ Trade Direction
The strategy allows users to select the trade direction through the `tradeDirection` input. The options are:
- Both: Enables both long and short trades.
- Long: Enables only long trades.
- Short: Enables only short trades.
█ Default Settings
- TSI Length: 64
- SuperTrend Length: 10
- SuperTrend Factor: 3.0
- Trade Direction: Both
- Take Profit (%): 30.0
- Stop Loss (%): 20.0
Impact of Default Settings
- TSI Length: A longer TSI period smooths out noise but may lag in identifying trends. A shorter period is more responsive but can generate false signals.
- SuperTrend Length: A shorter length provides quicker signals but can be prone to whipsaws. A longer length is more reliable but may delay entries and exits.
- SuperTrend Factor: A higher factor increases the distance of the SuperTrend from the price, reducing sensitivity to minor price fluctuations.
- Trade Direction: Allows flexibility in trading strategies by enabling both long and short trades based on market conditions.
- Take Profit and Stop Loss: These settings manage risk by automatically closing trades at predefined profit or loss levels. Higher percentages provide larger potential gains but also higher risk.
Hindsight TrendNon-realtime but highly accurate trend analyzer with only one fundamental parameter ( period aka "minimum trend length")
Basically Hindsight Trend is pivot points on steroids (handles many cases much better). Plus it shows the trend line.
Period
I usually like periods of 10, 20 or 30.
The indicator's delay is identical to the chosen period.
You can actually try a low period like 4 or 5 to get something resembling a realtime indicator.
Uptrends are based on candle lows, downtrends are based on candle highs. So it is possible to have an uptrend and a downtrend at the same time.
Triangles
At trend start, a triangle is drawn. (Trendline isn't always there if the trend didn't last that long.)
Triangle size shows how long the high or low that started the trend remained unbroken. E.g. with period 20: Small triangle = 20+ candles, medium triangle = 40+ candles, big triangle = 80+ candles. So a big triangle marks an important reversal point.
How Hindsight Trend works
Whenever a candle completes, its high and low are saved as potentially "notable" points. A high or low is the more notable the longer it stays unbroken (= not touched again by price).
Now we simply take the notable highs and lows (as in, staying unbroken at least for the user-selected period)... and connect them together - if they are close enough to each other (less than "period" candles away). And decorate the first point in each trend with a triangle.
We only know whether a point is notable after "period" more candles have printed, so that's where the indicator's delay comes from.
Finally we divide the period by 2 and look at highs and lows which are unbroken for that shorter time. While they are not fully "notable" as defined above, we'll call them "semi-notable". Those points are only considered at the end of a trend, and help us extend the trend line a bit further.
Dynamic Support & Resistance Tracker with MTFDynamic Support & Resistance Tracker with Weekly, Monthly & Daily Levels
The Dynamic Support & Resistance Tracker is designed to help traders identify key support and resistance levels across multiple timeframes, enhancing market analysis and decision-making. This indicator calculates and plots support and resistance levels for daily, weekly, and monthly periods, along with extension lines that provide insights into potential price targets.
Key Features:
Multi-Timeframe Analysis:
Daily Levels: Identifies the high, low, and midpoint for each trading day. These levels help traders recognize important price points for short-term trading strategies.
Weekly Levels: Plots the high, low, and midpoint for each week. This feature is valuable for swing traders who need to understand broader market trends.
Monthly Levels: Displays the high, low, and midpoint for each month, which is essential for long-term investors.
Extension Lines:
Calculates extension lines beyond the standard support and resistance levels to help anticipate potential price targets and reversals. These extensions are based on the distance between the high/low and midpoint levels.
Real-Time Updates:
Automatically updates the levels based on the most recent market data, ensuring traders have the most current information for their analysis.
Clear Visuals:
The indicator provides clearly labeled and color-coded lines for easy identification of key levels, improving the visual clarity of market analysis.
How It Works:
Daily, Weekly, and Monthly Levels: The indicator calculates the high, low, and midpoint levels for daily, weekly, and monthly timeframes and plots them on the chart. These levels serve as potential areas of support and resistance where price action may react.
Extension Lines: The extension lines are calculated based on the distance between the high/low and midpoint levels, projecting potential areas where price may find support or resistance beyond the standard levels.
Automatic Updates: The indicator continuously updates the plotted levels based on the latest market data, providing real-time insights.
Benefits:
Improved Market Analysis: By providing a clear view of support and resistance levels across multiple timeframes, this indicator helps traders understand market trends and price movements more effectively.
Informed Trading Decisions: The detailed plotting of levels and extensions allows traders to make more informed decisions, enhancing their trading strategies.
Versatility: Suitable for various trading styles, including intraday trading, swing trading, and long-term investing.
Instructions for Use:
Analyze the Levels: Observe the plotted high, low, and mid-levels for daily, weekly, and monthly timeframes.
Plan Your Trades: Use the identified support and resistance levels to set your entry and exit points, stop-losses, and profit targets.
Monitor the Market: Stay updated with real-time adjustments of the levels, ensuring you always have the latest market information.
Note: This indicator is designed to enhance your trading analysis by providing clear and reliable support and resistance levels. However, it should be used as part of a comprehensive trading strategy and not as the sole basis for trading decisions.
Fisher ForLoop [InvestorUnknown]Overview
The Fisher ForLoop indicator is designed to apply the Fisher Transform over a range of lengths and signal modes. It calculates an array of Fisher values, averages them, and then applies an EMA to these values to derive a trend signal. This indicator can be customized with various settings to suit different trading strategies.
User Inputs
Start Length (a): The initial length for the Fisher Transform calculation (inclusive).
End Length (b): The final length for the Fisher Transform calculation (inclusive).
EMA Length (c): The length of the EMA applied to the average Fisher values.
Calculation Source (s): The price source used for calculations (e.g., ohlc4).
Signal Calculation
Signal Mode (sigmode): Determines the type of signal generated by the indicator. Options are "Fast", "Slow", "Thresholds Crossing", and "Fast Threshold".
1. Slow: is a simple crossing of the midline (0).
2. Fast: positive signal depends if the current Fisher EMA is above Fisher EMA or above 0.99, otherwise the signal is negative.
3. Thresholds Crossing: simple ta.crossover and ta.crossunder of the user defined threshold for Long and Short.
4. Fast Threshold: signal changes if the value of Fisher EMA changes by more than user defined threshold against the current signal
// Determine the color based on the EMA value
// If EMA is greater than 0, use the bullish color, otherwise use the bearish color
col1 = EMA > 0 ? colup : coldn
// Determine the color based on the EMA trend
// If the current EMA is greater than the previous EMA or greater than 0.99, use the bullish color, otherwise use the bearish color
col2 = EMA > EMA or EMA > 0.99 ? colup : coldn
// Initialize a variable for the color based on threshold crossings
var color col3 = na
// If the EMA crosses over the long threshold, set the color to bullish
if ta.crossover(EMA, longth)
col3 := colup
// If the EMA crosses under the short threshold, set the color to bearish
if ta.crossunder(EMA, shortth)
col3 := coldn
// Initialize a variable for the color based on fast threshold changes
var color col4 = na
// If the EMA increases by more than the fast threshold, set the color to bullish
if (EMA > EMA + fastth)
col4 := colup
// If the EMA decreases by more than the fast threshold, set the color to bearish
if (EMA < EMA - fastth)
col4 := coldn
// Initialize the final color variable
color col = na
// Set the color based on the selected signal mode
if sigmode == "Slow"
col := col1 // Use slow mode color
if sigmode == "Fast"
col := col2 // Use fast mode color
if sigmode == "Thresholds Crossing"
col := col3 // Use thresholds crossing color
if sigmode == "Fast Threshold"
col := col4 // Use fast threshold color
else
na // If no valid signal mode is selected, set color to na
Visualization Settings
Bull Color (colup): The color used to indicate bullish signals.
Bear Color (coldn): The color used to indicate bearish signals.
Color Bars (barcol): Option to color the bars based on the signal.
Custom Function: FisherForLoop
This function calculates an array of Fisher values over a specified range of lengths (from a to b). It then computes the average of these values and applies an EMA to derive the final trend signal.
// Function to calculate an array of Fisher values over a range of lengths
FisherForLoop(a, b, c, s) =>
// Initialize an array to store Fisher values for each length
var FisherArray = array.new_float(b - a + 1, 0.0)
// Loop through each length from 'a' to 'b'
for x = 0 to (b - a)
// Calculate the current length
len = a + x
// Calculate the highest and lowest values over the current length
high_ = ta.highest(s, len)
low_ = ta.lowest(s, len)
// Initialize the value variable
value = 0.0
// Update the value using the Fisher Transform formula
// The formula normalizes the price to a range between -0.5 and 0.5, then smooths it
value := .66 * ((s - low_) / (high_ - low_) - .5) + .67 * nz(value )
// Clamp the value to be within -0.999 to 0.999 to avoid math errors
val = value > .99 ? .999 : value < -.99 ? -.999 : value
// Initialize the fish1 variable
fish1 = 0.0
// Apply the Fisher Transform to the normalized value
// This converts the value to a Fisher value, which emphasizes extreme changes in price
fish1 := .5 * math.log((1 + val) / (1 - val)) + .5 * nz(fish1 )
// Store the previous Fisher value for comparison
fish2 = fish1
// Determine the trend based on the Fisher values
// If the current Fisher value is greater than the previous, the trend is up (1)
// Otherwise, the trend is down (-1)
trend = fish1 > fish2 ? 1 : -1
// Store the trend in the FisherArray at the current index
array.set(FisherArray, x, trend)
// Calculate the average of the FisherArray
Avg = array.avg(FisherArray)
// Apply an EMA to the average Fisher values to smooth the result
EMA = ta.ema(Avg, c)
// Return the FisherArray, the average, and the EMA
// Call the FisherForLoop function with the user-defined inputs
= FisherForLoop(a, b, c, s)
Important Considerations
Speed: This indicator is very fast and can provide rapid signals for potential entries. However, this speed also means it may generate false signals if used in isolation.
Complementary Use: It is recommended to use this indicator in conjunction with other indicators and analysis methods to confirm signals and enhance the reliability of your trading strategy.
Strength: The main strength of the Fisher ForLoop indicator is its ability to identify very fast entries and prevent entries against the current (short-term) market trend.
This indicator is useful for identifying trends and potential reversal points in the market, providing flexibility through its customizable settings. However, due to its sensitivity and speed, it should be used as part of a broader trading strategy rather than as a standalone tool.
Propulsion Blocks | Flux Charts💎 GENERAL OVERVIEW
Introducing our new Propulsion Blocks indicator! This new indicator can find & render ICT's propulsion blocks in the current ticker. It's highly customizable with detection, invalidation and style settings. For more information, please visit the "HOW DOES IT WORK ?" section.
Features of the new Propulsion Blocks indicator :
Render Bullish & Bearish Propulsion Blocks
Customizable Algorithm
Enable / Disable Historic Zones
Visual Customizability
📌 HOW DOES IT WORK ?
Order blocks occur when there is a high amount of market orders exist on a price range. It is possible to find order blocks using specific formations on the chart. One of which this indicator uses requires a large engulfing candlestick right after another one of the opposite direction. Then if the price comes back to retest the area that two candlesticks create, then it's an order block pattern.
Propulsion blocks are a specific type of order block used in the trading methodology. They build on the concept of order blocks and aim to identify potential areas for strong price movements. They are detected when a candlestick wicks to any existing order block, retesting it. Then a strong momentum in the direction of the order block is needed for the propulsion block to get created. Check this example :
You can use them as entry / exit points, or for confirmations for your trades. For example, a successful retest attempt to a bullish propulsion block might hint a strong bullish momentum. This indicator works best when used together with other ICT concepts.
🚩UNIQUENESS
Propulsion blocks can help traders identify key levels in a chart, and can be used mainly for confirmation. This indicator can identify and show them automatically in your chart, and provides customization settings for order & propulsion block detection and invalidation. Another capability of the indicator is that it combines overlapping order & propulsion blocks so you will have a clean look at the chart without any overlapping zones.
⚙️SETTINGS
1. General Configuration
Show Historic Zones -> This setting will hide invalidated propulsion blocks if enabled.
Max Distance To Last Bar -> This setting defines the maximum range that the indicator will find propulsion blocks to the past. Higher options will make older zones visible.
Zone Invalidation -> Select between Wick & Close price for Order Block & Propulsion Block Invalidation.
Swing Length -> Swing length is used when finding order block formations. Smaller values will result in finding smaller order blocks.
ADX with Donchian Channels
The "ADX with Donchian Channels" indicator combines the Average Directional Index (ADX) with Donchian Channels to provide traders with a powerful tool for identifying trends and potential breakouts.
Features:
Average Directional Index (ADX):
The ADX is used to quantify the strength of a trend. It helps traders determine whether a market is trending or ranging.
Adjustable parameters for ADX smoothing and DI length allow traders to fine-tune the sensitivity of the trend strength measurement.
Donchian Channels on ADX:
Donchian Channels are applied directly to the ADX values to highlight the highest high and lowest low of the ADX over a specified period.
The upper and lower Donchian Channels can signal potential trend breakouts when the ADX value moves outside these bounds.
The middle Donchian Channel provides a reference for the average trend strength.
Visualization:
The indicator plots the ADX line in red to clearly display the trend strength.
The upper and lower Donchian Channels are plotted in blue, with a green middle line to represent the average.
The area between the upper and lower Donchian Channels is filled with a blue shade to visually emphasize the range of ADX values.
Default Settings for Scalping:
Donchian Channel Length: 10
Standard Deviation Multiplier: 1.58
ADX Length: 2
ADX Smoothing Length: 2
These default settings are optimized for scalping, offering a quick response to changes in trend strength and potential breakout signals. However, traders can adjust these settings to suit different trading styles and market conditions.
How to Use:
Trend Strength Identification: Use the ADX line to identify the strength of the current trend. Higher ADX values indicate stronger trends.
Breakout Signals: Monitor the ADX value in relation to the Donchian Channels. A breakout above the upper channel or below the lower channel can signal a potential trend continuation or reversal.
Range Identification: The filled area between the Donchian Channels provides a visual representation of the ADX range, helping traders identify when the market is ranging or trending.
This indicator is designed to enhance your trading strategy by combining trend strength measurement with breakout signals, making it a versatile tool for various market conditions.
Fibonacci Period Range [UkutaLabs]█ OVERVIEW
The Fibonacci Period Range Indicator is a powerful trading tool that draws levels of support and resistance that are based on key Fibonacci levels. The script will identify the high and low of a range that is specified by the user, then draw several levels of support and resistance based on Fibonacci levels.
The script will also draw extension levels outside of the specified range that are also based on Fibonacci levels. These extension levels can be turned off in the indicator settings.
Each level is also labelled to help traders understand what each line represents. These labels can be turned off in the indicator settings.
The purpose of this script is to simplify the trading experience of users by giving them the ability to customize the time period that is identified, then draw levels of support and resistance that are based on the price action during this time.
█ USAGE
In the indicator settings, the user has access to a setting called Session Range. This gives users control over the range that will be used.
The script will then identify the high and low of the range that was specified and draw several levels of support and resistance based on Fibonacci levels between this range. The user can also choose to have extension levels that display more levels outside of the range.
These lines will extend until the end of the current trading day at 5:00 pm EST.
█ SETTINGS
Configuration
• Display Mode: Determines the number of days that will be displayed by the script.
• Show Labels: Determines whether or not identifying labels will be displayed on each line.
• Font Size: Determines the text size of labels.
• Label Position: Determines the justification of labels.
• Extension Levels: Determines whether or not extension levels will be drawn outside of the high and low of the specified range.
Session
• Session Range: Determines the time period that will be used for calculations.
• Timezone Offset (+/-): Determines how many hours the session should be offset by.
Gap Trend Lines by @eyemaginativeSummary:
The "Gap Trend Lines" script is designed to identify and visualize gaps between the close of one candle and the opening of the next on a TradingView chart. It draws extended trend lines to visually connect these gaps, helping traders to identify significant price movements between consecutive candles.
Functionality:
Indicator Setup:
The script is set as an overlay indicator on the main chart.
It includes settings for maximum line and label counts, ensuring efficient performance.
Parameter Customization:
Gap Threshold: Defines the minimum gap size considered significant.
Line Colors: Allows customization of colors for small and large gaps.
Line Thickness and Style: Provides options to adjust the thickness and style (solid, dotted, dashed) of the trend lines.
Drawing Extended Trend Lines:
For each bar (candlestick) on the chart, the script checks if there is a gap between the previous candle's close and the current candle's open.
If a gap is detected (i.e., close != open), it determines the size of the gap.
Depending on the size relative to the defined threshold, it selects the appropriate color (small or large gap).
It then draws an extended trend line that starts from the close of the previous candle (bar_index , close ) and extends to the open of the current candle (bar_index, open).
The trend line is drawn with the specified thickness, color, and style.
Dynamic Line Attribute Changes:
The script includes a function (changeLineAttributes()) that periodically changes the color and style of the trend lines.
By default, it changes the color every 4 hours (adjustable), alternating between green and the original color.
Enhanced Functionality:
Handles both small and large gaps with different visual cues (colors).
Supports extended trend lines that span both past and future directions (extend=extend.both), ensuring visibility across the entire chart.
Usage:
Traders can use the "Gap Trend Lines" script to:
Identify and analyze gaps between candlesticks.
Visualize significant price movements or breaks in continuity.
Customize the appearance of trend lines for better clarity and analysis.
By utilizing this script, traders can gain insights into price gap dynamics directly on TradingView charts, aiding in decision-making and strategy development.
DMI ForLoop [InvestorUnknown]Overview
This indicator utilizes the Directional Movement Index (DMI) combined with a for-loop to provide a robust trend analysis (ADX is not a part of this indicator).
Settings
DMI ForLoop Settings:
Start Length (a): The initial length for DMI calculation (inclusive).
End Length (b): The final length for DMI calculation (inclusive).
EMA Length (c): The length for the Exponential Moving Average applied to the DMI values, in order so smoothen the signal.
Signal Settings:
Signal Mode: Determines the mode of signal calculation. Options are "Fast", "Slow", "Thresholds Crossing", and "Fast Threshold". Default is "Fast".
1. Slow: is a simple crossing of the midline (0).
2. Fast: positive signal depends if the current "DMIema" is above "DMIema " or above 0.99, otherwise the signal is negative.
3. Thresholds Crossing: simple ta.crossover and ta.crossunder of the user defined threshold for Long and Short.
4. Fast Threshold: signal changes if the value of "DMIema" changes by more than user defined threshold against the current signal.
// Slow
dmicol1 = DMIema > 0 ? colup : coldn
// Fast
dmicol2 = DMIema > DMIema or DMIema > 0.99 ? colup : coldn
// Thresholds Crossing
var color dmicol3 = na
if ta.crossover(DMIema,longth)
dmicol3 := colup
if ta.crossunder(DMIema,shortth)
dmicol3 := coldn
// Fast Threshold
var color dmicol4 = na
if (DMIema > DMIema + fastth)
dmicol4 := colup
if (DMIema < DMIema - fastth)
dmicol4 := coldn
color dmicol = na
if sigmode == "Slow"
dmicol := dmicol1
if sigmode == "Fast"
dmicol := dmicol2
if sigmode == "Thresholds Crossing"
dmicol := dmicol3
if sigmode == "Fast Threshold"
dmicol := dmicol4
else
na
Functionality
The DMI ForLoop indicator calculates an array of DMI values over a specified range of lengths, then averages these values and applies an EMA for smoothing. The result is a dynamic trend indicator that adapts to market conditions.
DMI Calculation:
The indicator iterates through lengths from Start Length to End Length, calculating the positive and negative directional movement (DM) for each period and calculates the average of all the signals at the end. A custom function version of the DMI is used here in order to use DMI with "series" inputs.
// Function to calculate an array of DMI values over a range of lengths
DMIArray(a, b, c) =>
// Initialize an array to store DMI values, with size based on the range (b - a + 1)
var dmiArray = array.new_float(b - a + 1, 0.0)
// Loop through each length from a to b
for x = 0 to (b - a)
// Calculate the smoothing factor alpha for the current length
alpha = 1.0 / (a + x)
// Initialize variables for positive and negative DM
float plus = na
float minus = na
// Calculate the up and down movements
up = ta.change(high)
down = -ta.change(low)
// Determine the positive DM (plusDM)
plusDM = na(up) ? na : (up > down and up > 0 ? up : 0)
// Determine the negative DM (minusDM)
minusDM = na(down) ? na : (down > up and down > 0 ? down : 0)
// Calculate the smoothed positive DM using either SMA or EMA
plus := na(plus ) ? ta.sma(plusDM, (a + x)) : alpha * plusDM + (1 - alpha) * nz(plus )
// Calculate the smoothed negative DM using either SMA or EMA
minus := na(minus ) ? ta.sma(minusDM, (a + x)) : alpha * minusDM + (1 - alpha) * nz(minus )
// Determine the trend direction: 1 for positive trend, -1 for negative trend, 0 for no trend
trend = plus > minus ? 1 : plus < minus ? -1 : 0
// Store the trend value in the DMI array
array.set(dmiArray, x, trend)
// Calculate the average of the DMI array
dmiAvg = array.avg(dmiArray)
// Apply an EMA to the average DMI value
DMIema = ta.ema(dmiAvg, c)
// Return the DMI array, its average, and the EMA of the average
// Call the DMIArray function with the input parameters and assign the results to variables
= DMIArray(a, b, c)
This indicator is versatile and can be tailored to fit various trading/investing strategies by adjusting the input parameters and signal modes.
KillZones + ACD Fisher [TradingFinder] Sessions + Reversal Level🔵 Introduction
🟣 ACD Method
"The Logical Trader" opens with a thorough exploration of the ACD Methodology, which focuses on pinpointing particular price levels associated with the opening range.
This approach enables traders to establish reference points for their trades, using "A" and "C" points as entry markers. Additionally, the book covers the concept of the "Pivot Range" and how integrating it with the ACD method can help maximize position size while minimizing risk.
🟣 Session
The forex market is operational 24 hours a day, five days a week, closing only on Saturdays and Sundays. Typically, traders prefer to concentrate on one specific forex trading session rather than attempting to trade around the clock.
Trading sessions are defined time periods when a particular financial market is active, allowing for the execution of trades.
The most crucial trading sessions within the 24-hour cycle are the Asia, London, and New York sessions, as these are when substantial money flows and liquidity enter the market.
🟣 Kill Zone
Traders in financial markets earn profits by capitalizing on the difference between their buy/sell prices and the prevailing market prices.
Traders vary in their trading timelines.Some traders engage in daily or even hourly trading, necessitating activity during periods with optimal trading volumes and notable price movements.
Kill zones refer to parts of a session characterized by higher trading volumes and increased price volatility compared to the rest of the session.
🔵 How to Use
🟣 Session Times
The "Asia Session" comprises two parts: "Sydney" and "Tokyo." This session begins at 23:00 and ends at 06:00 UTC. The "Asia KillZone" starts at 23:00 and ends at 03:55 UTC.
The "London Session" includes "Frankfurt" and "London," starting at 07:00 and ending at 14:25 UTC. The "London KillZone" runs from 07:00 to 09:55 UTC.
The "New York" session starts at 14:30 and ends at 19:25 UTC, with the "New York am KillZone" beginning at 14:30 and ending at 22:55 UTC.
🟣 ACD Methodology
The ACD strategy is versatile, applicable to various markets such as stocks, commodities, and forex, providing clear buy and sell signals to set price targets and stop losses.
This strategy operates on the premise that the opening range of trades holds statistical significance daily, suggesting that initial market movements impact the market's behavior throughout the day.
Known as a breakout strategy, the ACD method thrives in volatile or strongly trending markets like crude oil and stocks.
Some key rules for employing the ACD strategy include :
Utilize points A and C as critical reference points, continually monitoring these during trades as they act as entry and exit markers.
Analyze daily and multi-day pivot ranges to understand market trends. Prices above the pivots indicate an upward trend, while prices below signal a downward trend.
In forex trading, the ACD strategy can be implemented using the ACD indicator, a technical tool that gauges the market's supply and demand balance. By evaluating trading volume and price, this indicator assists traders in identifying trend strength and optimal entry and exit points.
To effectively use the ACD indicator, consider the following :
Identifying robust trends: The ACD indicator can help pinpoint strong, consistent market trends.
Determining entry and exit points: ACD generates buy and sell signals to optimize trade timing.
Bullish Setup :
When the "A up" line is breached, it’s wise to wait briefly to confirm it’s not a "Fake Breakout" and that the price stabilizes above this line.
Upon entering the trade, the most effective stop loss is positioned below the "A down" line. It's advisable to backtest this to ensure the best outcomes. The recommended reward-to-risk ratio for this strategy is 1, which should also be verified through backtesting.
Bearish Setup :
When the "A down" line is breached, it’s prudent to wait briefly to ensure it’s not a "Fake Breakout" and that the price stabilizes below this line.
Upon entering the trade, the most effective stop loss is positioned above the "A up" line. Backtesting is recommended to confirm the best results. The recommended reward-to-risk ratio for this strategy is 1, which should also be validated through backtesting.
Advantages of Combining Kill Zone and ACD Method in Market Analysis :
Precise Trade Timing : Integrating the Kill Zone strategy with the ACD Method enhances precision in trade entries and exits. The ACD Method identifies key points for trading, while the Kill Zone focuses on high-activity periods, together ensuring optimal timing for trades.
Better Trend Identification : The ACD Method’s pivot ranges help spot market trends, and when combined with the Kill Zone’s emphasis on periods of significant price movement, traders can more effectively identify and follow strong market trends.
Maximized Profits and Minimized Risks : The ACD Method's structured approach to setting price targets and stop losses, coupled with the Kill Zone's high-volume trading periods, helps maximize profit potential while reducing risk.
Robust Risk Management : Combining these methods provides a comprehensive risk management strategy, strategically placing stop losses and protecting capital during volatile periods.
Versatility Across Markets : Both methods are applicable to various markets, including stocks, commodities, and forex, offering flexibility and adaptability in different trading environments.
Enhanced Confidence : Using the combined insights of the Kill Zone and ACD Method, traders gain confidence in their decision-making process, reducing emotional trading and improving consistency.
By merging the Kill Zone’s focus on trading volumes and the ACD Method’s structured breakout strategy, traders benefit from a synergistic approach that enhances precision, trend identification, and risk management across multiple markets.
Supply and Demand StrategyOverview
This strategy is designed to identify key supply (resistance) and demand (support) zones on a price chart. These zones represent areas where the price has historically shown a significant reaction, either bouncing up from a demand zone or dropping down from a supply zone. The strategy provides clear entry and exit points for trades based on these zones.
Key Components
Supply and Demand Zones:
Supply Zone: An area where the price has reversed from an uptrend to a downtrend. It represents a high concentration of sellers.
Demand Zone: An area where the price has reversed from a downtrend to an uptrend. It represents a high concentration of buyers.
Time Frames:
Use higher time frames (like daily or weekly) to identify key supply and demand zones.
Use lower time frames (like 1-hour or 4-hour) to pinpoint precise entry and exit points within these zones.
Confirmation:
Use price action and candlestick patterns (like pin bars or engulfing patterns) to confirm potential reversals in these zones.
ICT KillZones + Pivot Points [TradingFinder] Support/Resistance 🟣 Introduction
Pivot Points are critical levels on a price chart where trading activity is notably high. These points are derived from the prior day's price data and serve as key reference markers for traders' decision-making processes.
Types of Pivot Points :
Floor
Woodie
Camarilla
Fibonacci
🔵 Floor Pivot Points
Widely utilized in technical analysis, floor pivot points are essential in identifying support and resistance levels. The central pivot point (PP) acts as the primary level, suggesting the trend's likely direction.
The additional resistance levels (R1, R2, R3) and support levels (S1, S2, S3) offer further insight into potential trend reversals or continuations.
🔵 Camarilla Pivot Points
Featuring eight distinct levels, Camarilla pivot points closely correspond with support and resistance, making them highly effective for setting stop-loss orders and profit targets.
🔵 Woodie Pivot Points
Similar to floor pivot points, Woodie pivot points differ by placing greater emphasis on the closing price, often resulting in different pivot levels compared to the floor method.
🔵 Fibonacci Pivot Points
Fibonacci pivot points combine the standard floor pivot points with Fibonacci retracement levels applied to the previous trading period's range. Common retracement levels used are 38.2%, 61.8%, and 100%.
🟣 Sessions
Financial markets are divided into specific time segments, known as sessions, each with unique characteristics and activity levels. These sessions are active at different times throughout the day.
The primary sessions in financial markets include :
Asian Session
European Session
New York Session
The timing of these major sessions in UTC is as follows :
Asian Session: 23:00 to 06:00
European Session: 07:00 to 14:25
New York Session: 14:30 to 22:55
🟣 Kill Zones
Kill zones are periods within a session marked by heightened trading activity. During these times, trading volume surges and price movements become more pronounced.
The timing of the major kill zones in UTC is :
Asian Kill Zone: 23:00 to 03:55
European Kill Zone: 07:00 to 09:55
New York Kill Zone: 14:30 to 16:55
Combining kill zones and pivot points in financial market analysis provides several advantages :
Enhanced Market Sentiment Analysis : Aligns key price levels with high-activity periods for a clearer market sentiment.
Improved Timing for Trade Entries and Exits : Helps better time trades based on when price movements are most likely.
Higher Probability of Successful Trades : Increases the accuracy of predicting market movements and placing profitable trades.
Strategic Stop-Loss and Profit Target Placement : Allows for precise risk management by strategically setting stop-loss and profit targets.
Versatility Across Different Time Frames : Effective in both short and long time frames, suitable for various trading strategies.
Enhanced Trend Identification and Confirmation : Confirms trends using both pivot levels and high-activity periods, ensuring stronger trend validation.
In essence, this integrated approach enhances decision-making, optimizes trading performance, and improves risk management.
🟣 How to Use
🔵 Two Approaches to Trading Pivot Points
There are two main strategies for trading pivot points: utilizing "pivot point breakouts" and "price reversals."
🔵 Pivot Point Breakout
When the price breaks through pivot lines, it signals a shift in market sentiment to the trader. In the case of an upward breakout, where the price crosses these pivot lines, a trader might enter a long position, placing their stop-loss just below the pivot point (P).
Conversely, if the price breaks downward, a short position can be initiated below the pivot point. When using the pivot point breakout strategy, the first and second support levels can serve as profit targets in an upward trend. In a downward trend, these roles are filled by the first and second resistance levels.
🔵 Price Reversal
An alternative method involves waiting for the price to reverse at the support and resistance levels. To implement this strategy, traders should take positions opposite to the prevailing trend as the price rebounds from the pivot point.
While this tool is commonly used in higher time frames, it tends to produce better results in shorter time frames, such as 1-hour, 30-minute, and 15-minute intervals.
Three Strategies for Trading the Kill Zone
There are three principal strategies for trading within the kill zone :
Kill Zone Hunt
Breakout and Pullback to Kill Zone
Trading in the Trend of the Kill Zone
🔵 Kill Zone Hunt
This strategy involves waiting until the kill zone concludes and its high and low lines are established. If the price reaches one of these lines within the same session and is strongly rejected, a trade can be executed.
🔵 Breakout and Pullback to Kill Zone
In this approach, once the kill zone ends and its high and low lines stabilize, a trade can be made if the price breaks one of these lines decisively within the same session and then pulls back to that level.
🔵 Trading in the Trend of the Kill Zone
Kill zones are characterized by high trading volumes and strong trends. Therefore, trades can be placed in the direction of the prevailing trend. For instance, if an upward trend dominates this area, a buy trade can be entered when the price reaches a demand order block.
RV - Relative Strength Index Buy/SellIntroduction
The RV - RSI B/S V1.2 indicator leverages the RSI to identify overbought and oversold conditions in the market. The RSI line color changes according to bullish, bearish, oversold, and overbought zones, helping users identify direction and avoid false trades. By plotting the RSI along with user-defined moving averages and Bollinger Bands, it offers a multi-faceted approach to analyzing market momentum.
Indicator Overview
The indicator RSI line color changes as per the bullish, bearish, oversold, and overbought zones. This helps users find out the direction and the zones. The oversold and overbought zones are colored to help users avoid false trades.
Trading Strategy
Long Trades (Bullish Setup):
Entry: A long trade is initiated when the RSI crosses from 60 up to 80.
Exit: Long trades are generally exited when the RSI is between 80 and 90.
Condition: No long trades are taken if the RSI exceeds 80.
Short Trades (Bearish Setup):
Entry: A short trade is initiated when the RSI crosses from 40 down to 20.
Exit: Short trades are generally exited when the RSI is between 20 and 10.
Condition: No short trades are taken if the RSI falls below 20.
RSI Color Coding and Interpretation
The RV - RSI B/S V1.2 indicator uses color coding to provide a visual representation of RSI values, making it easier to identify critical levels at a glance:
Green (RSI 60-80): Indicates a bullish zone where long trades can be considered.
Red (RSI > 80): Signals an overbought condition where long trades should be avoided.
Orange (RSI 20-40): Indicates a bearish zone where short trades can be considered.
Pink (RSI < 20): Signals an oversold condition where short trades should be avoided.
RSI Settings and Their Importance
RSI Length: The default length is set to 12, which is the standard period for RSI calculation. This setting can be adjusted to increase or decrease sensitivity.
Source: The source of the data for the RSI calculation is typically the closing price.
MA Type: Various moving averages can be applied to the RSI, including SMA, EMA, SMMA (RMA), WMA, and VWMA. Each type offers different smoothing properties and can be selected based on
trading preferences.
MA Length: The default length is set to 20, aligning with the RSI length for consistency.
Bollinger Bands: When using Bollinger Bands, the standard deviation multiplier is set to 2.0 by default, but it can be adjusted to suit different volatility conditions.
Disclaimer
This indicator provides valuable signals for potential trading opportunities based on RSI levels and moving averages. However, it is crucial to incorporate directional price action analysis to confirm signals and improve trading accuracy. The RV - RSI B/S V1.2 should be used as part of a broader trading strategy, considering other technical and fundamental factors.
BTC outperform atrategy### Code Description
This Pine Script™ code implements a simple trading strategy based on the relative prices of Bitcoin (BTC) on a weekly and a three-month basis. The script plots the weekly and three-month closing prices of Bitcoin on the chart and generates trading signals based on the comparison of these prices. The code can also be applied to Ethereum (ETH) with similar effectiveness.
### Explanation
1. **Inputs and Variables**:
- The user selects the trading symbol (default is "BINANCE:BTCUSDT").
- `weeklyPrice` retrieves the closing price of the selected symbol on a weekly interval.
- `monthlyPrice` retrieves the closing price of the selected symbol on a three-month interval.
2. **Plotting Data**:
- The weekly price is plotted in blue.
- The three-month price is plotted in red.
3. **Trading Conditions**:
- A long position is suggested if the weekly price is greater than the three-month price.
- A short position is suggested if the three-month price is greater than the weekly price.
4. **Strategy Execution**:
- If the long condition is met, the strategy enters a long position.
- If the short condition is met, the strategy enters a short position.
This script works equally well for Ethereum (ETH) by changing the symbol input to "BINANCE:ETHUSDT" or any other desired Ethereum trading pair.
Cosine smoothed stochasticDescription
The "Cosine Smoothed Stochastic" indicator leverages advanced Fourier Transform techniques to smooth the traditional Stochastic Oscillator. This approach enhances the signal's reliability and reduces noise, providing traders with a more refined and actionable indicator.
The Stochastic Oscillator is a popular momentum indicator that measures the current price relative to the high-low range over a specified period. It helps identify overbought and oversold conditions, signaling potential trend reversals. By smoothing this indicator with Fourier Transform techniques, we aim to reduce false signals and improve its effectiveness.
The indicator comprises three main components:
Cosine Function: A custom function to compute the cosine of an input scaled by a frequency tuner.
Kernel Function: Utilizes the cosine function to create a smooth kernel, constrained to positive values within a specific range.
Kernel Regression and Multi Cosine: Perform kernel regression over a lookback period, with the multi cosine function summing these regressions at varying frequencies for a composite smooth signal.
Additionally, the indicator includes a volume oscillator to complement the smoothed stochastic signals, providing insights into market volume trends.
Features
Fourier Transform Smoothing: Advanced smoothing technique to reduce noise.
Volume Oscillator: Dynamic volume-based oscillator for additional market insights.
Customizable Inputs: Users can configure key parameters like regression lookback period, tuning coefficient, and smoothing length.
Visual Alerts: Buy and sell signals based on smoothed stochastic crossovers.
Usage
The indicator is designed for trend-following and momentum-based trading strategies . It helps identify overbought and oversold conditions, trend reversals, and potential entry and exit points based on smoothed stochastic values and volume trends.
Inputs
Cosine Kernel Setup:
varient: Choose between "Tuneable" and "Stepped" regression types.
lookbackR: Lookback period for regression.
tuning: Tuning coefficient for frequency adjustment.
Stochastic Calculation:
volshow: Toggle to show the volume oscillator.
emalength: Smoothing period for the Stochastic Oscillator.
lookback_period, m1, m2: Parameters for the Stochastic Oscillator lookback and moving averages.
How It Works
Stochastic Oscillator:
Computes the stochastic %K and smoothes it with an EMA.
Further smoothes %K using the multi cosine function.
Volume Oscillator:
Calculates short and long EMAs of volume and derives the oscillator as the percentage difference.
Plots volume oscillator columns with dynamic coloring based on the oscillator's value and change.
Visual Representation:
Plots smoothed stochastic lines with colors indicating bullish, bearish, overbought, and oversold conditions.
Uses plotchar to mark crossovers between current and previous values of d.
Displays overbought and oversold levels with filled regions between them.
Chart Example
To understand the indicator better, refer to the clean and annotated chart provided. The script is used without additional scripts to maintain clarity. The chart includes:
Smoothed Stochastic Lines: Colored according to trend conditions.
Volume Oscillator: Plotted as columns for visual volume trend analysis.
Overbought/Oversold Levels: Clearly marked levels with filled regions between them.
Alert Conditions
The indicator sets up alerts for buy and sell signals when the smoothed stochastic crosses over or under its previous value. These alerts can be used for automated trading systems or manual trading signals.
breakthrough of the indicators method :
Initialization and Inputs:
The indicator starts by defining necessary inputs, such as the lookback period for regression, tuning coefficient, and smoothing parameters for the Stochastic Oscillator and volume oscillator.
Cosine Function and Kernel Creation:
The cosine function is defined to compute the cosine of an input scaled by a frequency tuner.
The kernel function utilizes this cosine function to create a smoothing kernel, which is constrained to positive values within a specific range.
Kernel Regression:
The kernel regression function iterates over the lookback period, calculating weighted sums of the source values using the kernel function. This produces a smoothed value by dividing the accumulated weighted values by the total weights.
Multi Cosine Smoothing:
The multi cosine function combines multiple kernel regressions at different frequencies, summing these results and averaging them to achieve a composite smoothed value.
Stochastic Calculation and Smoothing:
The traditional Stochastic Oscillator is calculated, and its %K value is smoothed using an EMA.
The smoothed %K is further refined using the multi cosine function, resulting in a more reliable and less noisy signal.
Volume Oscillator Calculation:
The volume oscillator calculates short and long EMAs of the volume and derives the oscillator as the percentage difference between these EMAs. The result is plotted with dynamic coloring to indicate volume trends.
Plotting and Alerts:
The indicator plots the smoothed stochastic lines , overbought/oversold levels, and volume oscillator on the chart.
Buy and sell alerts are set up based on crossovers of the smoothed stochastic values, providing traders with actionable signals.
ICT Propulsion Block [LuxAlgo]The ICT Propulsion Block indicator is meant to detect and highlight propulsion blocks, which are specific price structures introduced by the Inner Circle Trader (ICT).
Propulsion Blocks are essentially blocks located where prices interact with preceding order blocks. Traders often utilize them when analyzing price movements to identify potential turning points and market behavior or areas of interest in the market.
🔶 USAGE
An order block is a significant area on a price chart where there was a notable accumulation or distribution of orders, often identified by a strong move in price followed by a consolidation or sideways movement. Traders use order blocks to identify potential support or resistance levels.
A Propulsion Block, on the other hand, is a concept taught by the Inner Circle Trader (ICT) and refers to a specific type of order block that interacts with the preceding order block. Traders often analyze propulsion blocks to identify potential turning points and areas of interest in the market.
A mitigated order block refers to an order block that has been invalidated or nullified due to subsequent market movements or developments. It no longer holds the same significance or relevance in the current market context.
Let's explore a bearish order block and propulsion block scenario commonly utilized by ICT traders in their trading strategies.
🔶 SETTINGS
🔹 Order & Propulsion Blocks
Swing Detection Length: Lookback period used to detect swing points for creating order blocks and/or propulsion blocks.
Mitigation Price: Allows users to choose between the closing price or the candle's wick for mitigation.
Highlight Propulsion Block Signals: Highlights the propulsion block and its sentiment for easier identification and analysis.
Remove Unassociated Order Blocks: Eliminate order blocks that are not associated with any propulsion block.
Remove Mitigated Blocks: Eliminates mitigated order blocks and propulsion blocks along with their associated order blocks, streamlining the visualization for clearer analysis.
Most Recent Blocks: Activates processing of the specified number of most recent blocks according to the option. If not enabled, the script defaults to processing the last 125 occurrences.
🔹 Order & Propulsion Blocks Style
Bullish Order & Propulsion Blocks: Toggles the visibility of bullish order and propulsion blocks, along with color customization options.
Bearish Order & Propulsion Blocks: Toggles the visibility of bearish order and propulsion blocks, along with color customization options.
Block Labels: Toggles the visibility of order and propulsion block labels, and label size customization option.
🔶 RELATED SCRIPTS
Order-Blocks-Breaker-Blocks .
Price & Moving Average + Financial IndicatorThis indicator displays:
Moving Average that can be set into SMA or EMA: Default setting is SMA 50
Label price for today's MA
Basic Financial Data:
Type of Sector
Type of Industry
P/E Ratio
Price to Book Ratio
ROE
Revenue (FQ)
Earnings (FQ)
Once again, I let the script open for you guys to custom it based on your own preferences. Hope you guys enjoy it!
Log Regression Channel [UAlgo]The "Log Regression Channel " channel is useful for analyzing price trends and volatility in a financial instrument over a specified period. By using logarithmic scaling, this indicator can more effectively handle the wide range of price movements seen in many financial markets, making it particularly valuable for assets with exponential growth characteristics.
The indicator plots the central regression line along with upper and lower deviation bands, providing a visual representation of potential support and resistance levels.
🔶 Key Features
Logarithmic Regression Line: The central line represents the logarithmic regression, which fits the price data over the specified length using a logarithmic scale. This helps in identifying the overall trend direction.
Deviation Bands: The upper and lower bands are plotted at a specified multiple of the standard deviation from the regression line, highlighting areas of potential overbought and oversold conditions.
Customizable Parameters: Users can adjust the length of the regression, the deviation multiplier, the color of the labels, and the size of the text labels to suit their preferences.
R-Squared Display: The R-squared value, which measures the goodness of fit of the regression model, is displayed on the chart. This helps traders assess the reliability of the regression line.
🔶 Calculations
The indicator performs several key calculations to plot the logarithmic regression channel:
Logarithmic Transformation: The prices and time indices are transformed using the natural logarithm to handle exponential growth in price data.
Regression Coefficients: The slope and intercept of the regression line are calculated using the least squares method on the transformed data.
Predicted Values: The regression equation is used to calculate predicted values for each data point.
Standard Deviation: The standard deviation of the residuals (differences between actual and predicted values) is computed to determine the width of the deviation bands.
Deviation Bands: Upper and lower bands are plotted at a specified multiple of the standard deviation above and below the regression line.
R-Squared Value: The R-squared value is calculated to measure how well the regression line fits the data. This value is displayed on the chart to inform the user of the model's reliability.
🔶 Disclaimer
The "Log Regression Channel " indicator is provided for educational and informational purposes only.
It is not intended as investment advice or a recommendation to buy or sell any financial instrument. Trading financial instruments involves substantial risk and may not be suitable for all investors.
Past performance is not indicative of future results. Users should conduct their own research.
