Buy The Deep Final Version V3Buy The Deep Final Version V3
This script implements a buy-the-dip strategy based on market volatility, featuring multi-level additional buy logic and performance visualization tools for traders.
Key Features Dynamic Position Sizing:
Dynamically calculates position size based on the trader's initial capital, current profit, and leverage settings. Offers options to reinvest profits or maintain fixed position sizes.
Volatility-Based Entry:
Identifies buy opportunities based on a calculated volatility percentage (val).
Automated Take Profit and Stop Loss:
Automatically sets take profit (tp) and stop-loss (tp22) levels using predefined percentages to ensure effective risk management.
SMA-Based Conditions:
Uses a Simple Moving Average (SMA) to determine whether to enter long positions.
Support for Additional Buy Levels:
Supports dollar-cost averaging (DCA) with additional buy levels (so1, so2, etc.).
Leverage and Commission Customization:
Allows users to set desired leverage and trading fees, which are incorporated into calculations for precise execution.
Performance Tracking:
Displays the following key metrics: Total profit and percentage Monthly and annual profit percentages Maximum drawdown (MDD) Win rate Includes a performance table and data window for real-time insights.
Time-Limited Testing:
Enables users to test the strategy over specific time periods for refinement and validation.
How It Works: Entry Conditions: Identifies opportunities when the price crosses above the SMA or meets specific volatility thresholds. Position Sizing: Dynamically calculates optimal position sizes using leverage and capital allocation. Exit Points: Automated take profit and stop-loss orders minimize manual intervention.
Input Descriptions
This strategy offers customizable input parameters to accommodate various trading needs. Each input is described below:
Initial Settings Profit Reinvest (reinvest):
Options: True or False Determines whether to reinvest profits to increase the size of subsequent trades.
Long Buy % (longper):
Default: 6 Sets the percentage of initial capital allocated for the first long position.
Leverage (lev):
Default: 3 Sets the leverage multiplier for trades. For example, 3 means 3x leverage is used.
Fee % (commission_value):
Default: 0.044 Input the trading fee as a percentage, which is factored into profit calculations.
Decimal Places (num):
Default: 2 Determines the number of decimal places considered in calculations.
Table Font Size (texts):
Default: Normal Sets the font size for the performance table. Options include Tiny, Small, Normal, and Large.
Volatility and Additional Buy Settings Volatility % (val):
Default: -1.5 Specifies the volatility percentage used to determine entry points.
Additional Buy % (so):
Default: -3 Defines the percentage drop at which additional buy orders are executed.
Take Profit % (tp):
Default: 0.5 Specifies the percentage increase at which take profit orders are executed.
Candle Count (sl):
Default: 1 Sets the number of candles to hold a position before closing it.
Take Profit Stop-Loss % (tp22):
Default: 0.1 Defines the stop-loss threshold as a percentage below the average entry price.
SMA Length (len):
Default: 48 Determines the period for calculating the Simple Moving Average (SMA).
Position Multipliers Position Multiplier Longline 4 (long2_qty):
Default: 1 Sets the size of the first additional buy position.
Position Multiplier Longline 5 (long3_qty):
Default: 2 Sets the size of the second additional buy position.
Position Multiplier Longline 4 (long4_qty):
Default: 4 Sets the size of the third additional buy position.
Position Multiplier Longline 5 (long5_qty):
Default: 8 Sets the size of the fourth additional buy position.
التقلب
ADR Table BY @ICT_YEROADR Table BY @ICT_YERO
Created by: @ICT_YERO
This custom indicator is designed to provide the Average Daily Range (ADR) for multiple timeframes, including Daily, 4-Hour, and 1-Hour. The indicator is tailored to assist traders in understanding price volatility and making informed trading decisions.
Key Features
Multi-Timeframe ADR Calculation:
Automatically calculates and displays the ADR for Daily, 4-Hour, and 1-Hour timeframes.
Helps traders identify potential price movement ranges for different trading sessions.
Dynamic Range Visualization:
Clear visual representation of the ADR on the chart, making it easy to spot price extremes.
Real-time updates to reflect changes in price movement.
Custom Alerts:
Option to set alerts when the price approaches the ADR high or low.
Useful for identifying potential reversal zones or breakout opportunities.
User-Friendly Interface:
Simple and intuitive settings to customize colors, levels, and display preferences.
Seamlessly integrates with your existing TradingView setup.
ICT-Inspired Methodology:
Designed for traders who follow ICT concepts, focusing on precision and high-probability setups.
Applications
Range Trading: Helps determine the high and low boundaries for scalping or intraday setups.
Volatility Analysis: Understand market behavior during different times of the day or week.
Reversal Zones: Identify areas where price is likely to reverse, based on ADR extremes.
Whether you're a scalper, day trader, or swing trader, this indicator provides a comprehensive overview of price volatility across multiple timeframes, making it an essential tool for your trading arsenal.
Medium Risk Strategy with OrdersJust a first Hello World. I am just messing around with pine scripting and portfolios.
It is medium risk with some safeguards to maintain portfolio value.
EMA VelocityThe EMA Velocity strategy is a revised version of the original High-Frequency EMA Scalper strategy. Designed for active traders looking to capture short-term trends using Fast and Slow EMA crossovers, this version addresses previous concerns such as redrawing issues and excessive trade frequency in short time periods.
Key Features:
EMA Crossover Signals: The strategy enters long when the Fast EMA crosses above the Slow EMA and short when the Fast EMA crosses below, designed to capture quick price movements.
Static Stop Loss & Take Profit:
The stop-loss is set to 1 * ATR below the entry price for long trades and above for short trades.
The take-profit is set based on a Risk-to-Reward ratio (default: 1.5x).
Dynamic Position Sizing: The position size is dynamically calculated based on ATR and account equity, or you can use a fixed contract size.
Heikin-Ashi Candles Recommended: To achieve optimal results, Heikin-Ashi candles are highly recommended. These candles smooth out price action and help avoid false signals, which is critical for this strategy’s success. Without Heikin-Ashi candles, the strategy may not perform profitably.
Changes Made Based on Feedback:
Removed Redrawing Issues: Previous versions used trailing stops that led to redrawing, making backtesting unreliable. These have now been replaced with static stop-loss and take-profit levels based on ATR.
Optimized for Higher Timeframes: The strategy was previously triggering trades too frequently on lower timeframes (such as the 1-minute chart). The current version is now optimized for timeframes above 1 minute to avoid excessive trade signals and provide more reliable results.
Real-Time Testing Advised: As noted in feedback from the community, it is crucial to test this strategy in real-time to ensure it fits the market conditions and trading style you're using. The strategy has shown good profit-to-loss ratios, but live market conditions can differ.
How to Use:
Timeframe: Best applied on 1-minute or higher timeframes for better trade quality and fewer false signals.
Real-Time Testing: We strongly recommend performing real-time testing on this strategy. While it has shown a favorable profit/loss ratio in backtests, live market conditions may behave differently.
Adjust Parameters: Fine-tune the EMA lengths, ATR settings, and Risk-to-Reward ratio to suit the specific asset or market conditions you're trading.
Disclaimer: Past performance is not indicative of future results. Always test the strategy thoroughly in a simulated environment before applying it to live trading.
Average ATR & Average Volume TableProvides a comparison (above or below average) of the current Average True Range (ATR) with the ATR values from the previous 13 periods at the same point in time, offering insight into the average range over the past 13 sessions. Additionally, it includes the current trading volume alongside the average volume for the previous 13 periods during the same time frame offering insight into the average volume over the past 13 sessions.
rohith buying multi-timeframe EMA AlertsThis indicator makes use of EMA and Bollinger Bands along with CCI and mul;ti timeframe EMAs to handle scalping or option buying trades on Indian indices.
Monday Candles with Percentage Difference
The code selects Mondays and indicates the percentage change at which the market closed on those days.
Pamplona Enhanced TP/SL ToggleableName: Pamplona Enhanced TP/SL Toggleable
Type: Strategy
Description:
This strategy introduces flexibility and innovation in managing Take Profit (TP) and Stop Loss (SL) levels, making it a valuable tool for traders. It offers three configurable modes: Tick-Based, Dollar-Based, and Risk-Reward Ratio-Based, allowing users to toggle between them based on trading preferences. The strategy combines robust technical indicators to identify optimal trade opportunities and improves reliability by entering trades only on the second signal.
Key Features:
TP/SL Modes:
Tick-Based: Uses a fixed number of ticks to calculate TP/SL.
Dollar-Based: Uses fixed dollar amounts for TP/SL.
Risk-Reward Ratio-Based: Calculates TP/SL based on a user-defined ratio.
The user can toggle one mode at a time for precise control.
Trade Logic:
Long Trades: Triggered when price trends above the 200 EMA, the Madrid Ribbon turns bullish, and price exceeds the Donchian Channel high. The trade is confirmed only after the second valid signal.
Short Trades: Triggered when price trends below the 200 EMA, the Madrid Ribbon turns bearish, and price breaks the Donchian Channel low. The trade is confirmed only after the second valid signal.
Dynamic Configuration:
Adjustable ticks, dollar amounts, and risk-reward ratios in the settings.
Allows users to define contract size and Donchian Channel length.
Originality and Usefulness:
This strategy enhances common trading methodologies by:
Offering a configurable multi-mode TP/SL system that adapts to diverse trading styles.
Using a confirmation-based entry system, which reduces false signals and increases reliability.
Combining widely used indicators (EMA, Madrid Ribbon, Donchian Channel) into a practical framework for trend-following strategies.
How to Use:
Set TP/SL Mode:
In the settings, enable only one mode (Tick-Based, Dollar-Based, or Risk-Reward).
Adjust relevant parameters for the selected mode (e.g., ticks, dollar values, or risk-reward ratio).
Customize Trade Settings:
Define the contract size and Donchian Channel period.
The default configuration is suited for swing trading but can be adapted to other timeframes.
Understand Trade Logic:
The background highlights potential long (green) and short (red) zones.
Long entries occur when all conditions align bullishly, confirmed on the second signal.
Short entries occur when all conditions align bearishly, confirmed on the second signal.
Review Backtesting Results:
Use realistic commission, slippage, and risk values.
Ensure settings align with your trading style and risk management rules.
Notes:
No repainting: The script operates entirely on historical and current data without lookahead bias.
Backtesting: Test the strategy across multiple assets and timeframes to ensure robustness.
Customizability: The toggling system and configurable parameters make this strategy highly adaptable.
🚀
Pamplona Enhanced TP/SL ToggleableName: Pamplona Enhanced TP/SL Toggleable
Type: Strategy
Description:
This strategy introduces flexibility and innovation in managing Take Profit (TP) and Stop Loss (SL) levels, making it a valuable tool for traders. It offers three configurable modes: Tick-Based, Dollar-Based, and Risk-Reward Ratio-Based, allowing users to toggle between them based on trading preferences. The strategy combines robust technical indicators to identify optimal trade opportunities and improves reliability by entering trades only on the second signal.
Key Features:
TP/SL Modes:
Tick-Based: Uses a fixed number of ticks to calculate TP/SL.
Dollar-Based: Uses fixed dollar amounts for TP/SL.
Risk-Reward Ratio-Based: Calculates TP/SL based on a user-defined ratio.
The user can toggle one mode at a time for precise control.
Trade Logic:
Long Trades: Triggered when price trends above the 200 EMA, the Madrid Ribbon turns bullish, and price exceeds the Donchian Channel high. The trade is confirmed only after the second valid signal.
Short Trades: Triggered when price trends below the 200 EMA, the Madrid Ribbon turns bearish, and price breaks the Donchian Channel low. The trade is confirmed only after the second valid signal.
Dynamic Configuration:
Adjustable ticks, dollar amounts, and risk-reward ratios in the settings.
Allows users to define contract size and Donchian Channel length.
Originality and Usefulness:
This strategy enhances common trading methodologies by:
Offering a configurable multi-mode TP/SL system that adapts to diverse trading styles.
Using a confirmation-based entry system, which reduces false signals and increases reliability.
Combining widely used indicators (EMA, Madrid Ribbon, Donchian Channel) into a practical framework for trend-following strategies.
How to Use:
Set TP/SL Mode:
In the settings, enable only one mode (Tick-Based, Dollar-Based, or Risk-Reward).
Adjust relevant parameters for the selected mode (e.g., ticks, dollar values, or risk-reward ratio).
Customize Trade Settings:
Define the contract size and Donchian Channel period.
The default configuration is suited for swing trading but can be adapted to other timeframes.
Understand Trade Logic:
The background highlights potential long (green) and short (red) zones.
Long entries occur when all conditions align bullishly, confirmed on the second signal.
Short entries occur when all conditions align bearishly, confirmed on the second signal.
Review Backtesting Results:
Use realistic commission, slippage, and risk values.
Ensure settings align with your trading style and risk management rules.
Notes:No repainting: The script operates entirely on historical and current data without lookahead bias.
Backtesting: Test the strategy across multiple assets and timeframes to ensure robustness.
Customizability: The toggling system and configurable parameters make this strategy highly adaptable.
🚀
ATR Only-{Jebri}Displays the ATR, a key volatility measure. Use it to gauge market swings, set stops, and manage risk. Higher readings indicate bigger moves; lower readings suggest calmer phases. Adjust the ATR length to suit your timeframe. Combine with other tools for robust decision-making.
Monday JumpThe "Monday Candles with Percentage Difference" indicator calculates the percentage difference between the opening and closing prices for each Monday and displays this difference. This indicator visually shows the user whether the price movement on Mondays is positive or negative.
Adaptive Momentum Reversion StrategyThe Adaptive Momentum Reversion Strategy: An Empirical Approach to Market Behavior
The Adaptive Momentum Reversion Strategy seeks to capitalize on market price dynamics by combining concepts from momentum and mean reversion theories. This hybrid approach leverages a Rate of Change (ROC) indicator along with Bollinger Bands to identify overbought and oversold conditions, triggering trades based on the crossing of specific thresholds. The strategy aims to detect momentum shifts and exploit price reversions to their mean.
Theoretical Framework
Momentum and Mean Reversion: Momentum trading assumes that assets with a recent history of strong performance will continue in that direction, while mean reversion suggests that assets tend to return to their historical average over time (Fama & French, 1988; Poterba & Summers, 1988). This strategy incorporates elements of both, looking for periods when momentum is either overextended (and likely to revert) or when the asset’s price is temporarily underpriced relative to its historical trend.
Rate of Change (ROC): The ROC is a straightforward momentum indicator that measures the percentage change in price over a specified period (Wilder, 1978). The strategy calculates the ROC over a 2-period window, making it responsive to short-term price changes. By using ROC, the strategy aims to detect price acceleration and deceleration.
Bollinger Bands: Bollinger Bands are used to identify volatility and potential price extremes, often signaling overbought or oversold conditions. The bands consist of a moving average and two standard deviation bounds that adjust dynamically with price volatility (Bollinger, 2002).
The strategy employs two sets of Bollinger Bands: one for short-term volatility (lower band) and another for longer-term trends (upper band), with different lengths and standard deviation multipliers.
Strategy Construction
Indicator Inputs:
ROC Period: The rate of change is computed over a 2-period window, which provides sensitivity to short-term price fluctuations.
Bollinger Bands:
Lower Band: Calculated with a 18-period length and a standard deviation of 1.7.
Upper Band: Calculated with a 21-period length and a standard deviation of 2.1.
Calculations:
ROC Calculation: The ROC is computed by comparing the current close price to the close price from rocPeriod days ago, expressing it as a percentage.
Bollinger Bands: The strategy calculates both upper and lower Bollinger Bands around the ROC, using a simple moving average as the central basis. The lower Bollinger Band is used as a reference for identifying potential long entry points when the ROC crosses above it, while the upper Bollinger Band serves as a reference for exits, when the ROC crosses below it.
Trading Conditions:
Long Entry: A long position is initiated when the ROC crosses above the lower Bollinger Band, signaling a potential shift from a period of low momentum to an increase in price movement.
Exit Condition: A position is closed when the ROC crosses under the upper Bollinger Band, or when the ROC drops below the lower band again, indicating a reversal or weakening of momentum.
Visual Indicators:
ROC Plot: The ROC is plotted as a line to visualize the momentum direction.
Bollinger Bands: The upper and lower bands, along with their basis (simple moving averages), are plotted to delineate the expected range for the ROC.
Background Color: To enhance decision-making, the strategy colors the background when extreme conditions are detected—green for oversold (ROC below the lower band) and red for overbought (ROC above the upper band), indicating potential reversal zones.
Strategy Performance Considerations
The use of Bollinger Bands in this strategy provides an adaptive framework that adjusts to changing market volatility. When volatility increases, the bands widen, allowing for larger price movements, while during quieter periods, the bands contract, reducing trade signals. This adaptiveness is critical in maintaining strategy effectiveness across different market conditions.
The strategy’s pyramiding setting is disabled (pyramiding=0), ensuring that only one position is taken at a time, which is a conservative risk management approach. Additionally, the strategy includes transaction costs and slippage parameters to account for real-world trading conditions.
Empirical Evidence and Relevance
The combination of momentum and mean reversion has been widely studied and shown to provide profitable opportunities under certain market conditions. Studies such as Jegadeesh and Titman (1993) confirm that momentum strategies tend to work well in trending markets, while mean reversion strategies have been effective during periods of high volatility or after sharp price movements (De Bondt & Thaler, 1985). By integrating both strategies into one system, the Adaptive Momentum Reversion Strategy may be able to capitalize on both trending and reverting market behavior.
Furthermore, research by Chan (1996) on momentum-based trading systems demonstrates that adaptive strategies, which adjust to changes in market volatility, often outperform static strategies, providing a compelling rationale for the use of Bollinger Bands in this context.
Conclusion
The Adaptive Momentum Reversion Strategy provides a robust framework for trading based on the dual concepts of momentum and mean reversion. By using ROC in combination with Bollinger Bands, the strategy is capable of identifying overbought and oversold conditions while adapting to changing market conditions. The use of adaptive indicators ensures that the strategy remains flexible and can perform across different market environments, potentially offering a competitive edge for traders who seek to balance risk and reward in their trading approaches.
References
Bollinger, J. (2002). Bollinger on Bollinger Bands. McGraw-Hill Professional.
Chan, L. K. C. (1996). Momentum, Mean Reversion, and the Cross-Section of Stock Returns. Journal of Finance, 51(5), 1681-1713.
De Bondt, W. F., & Thaler, R. H. (1985). Does the Stock Market Overreact? Journal of Finance, 40(3), 793-805.
Fama, E. F., & French, K. R. (1988). Permanent and Temporary Components of Stock Prices. Journal of Political Economy, 96(2), 246-273.
Jegadeesh, N., & Titman, S. (1993). Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency. Journal of Finance, 48(1), 65-91.
Poterba, J. M., & Summers, L. H. (1988). Mean Reversion in Stock Prices: Evidence and Implications. Journal of Financial Economics, 22(1), 27-59.
Wilder, J. W. (1978). New Concepts in Technical Trading Systems. Trend Research.
SMA 20 and 50 with ATR VolatilityThis indicator combines the analysis of two SMAs (20 and 50) with a volatility filter using ATR (Average True Range). It identifies long and short entry signals based on SMA crossovers while filtering out sideways markets using ATR. Volatility levels are categorized into low, medium, and high, with each level color-coded on the chart for easy identification (green for low, yellow for medium, and red for high). The indicator also visualizes entry points with triangles and dynamically adjusts price levels based on ATR. It helps traders make decisions based on trend direction and market volatility.
TEY CandlesL'indicateur TEY Candles colore les bougies selon le momentum directionnel basé sur le DMI.
Vert : Momentum haussier.
Rouge : Momentum baissier.
Violet : Phase neutre, ralentissement de la volatilité, permettant ainsi de détecter les phases d'accumulation et de distribution.
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The TEY Candles indicator colors the candles based on directional momentum derived from the DMI.
Green: Bullish momentum.
Red: Bearish momentum.
Purple: Neutral phase, indicating a slowdown in volatility, which helps identify accumulation and distribution phases.
Enhanced HMA 5D standard Deviation - RickSimple hull moving average enhanced with standard deviation bands calculated over a 5 day period to account for volatility in ranging periods.
Possibility to choose the source of the hull calculation, as well as the source to use as threshold for long and short signal.
Two different types of visualization: candle coloring or moving average.
Prime Bands [ChartPrime]The Prime Standard Deviation Bands indicator uses custom-calculated bands based on highest and lowest price values over specific period to analyze price volatility and trend direction. Traders can set the bands to 1, 2, or 3 standard deviations from a central base, providing a dynamic view of price behavior in relation to volatility. The indicator also includes color-coded trend signals, standard deviation labels, and mean reversion signals, offering insights into trend strength and potential reversal points.
⯁ KEY FEATURES AND HOW TO USE
⯌ Standard Deviation Bands :
The indicator plots upper and lower bands based on standard deviation settings (1, 2, or 3 SDs) from a central base, allowing traders to visualize volatility and price extremes. These bands can be used to identify overbought and oversold conditions, as well as potential trend reversals.
Example of 3-standard-deviation bands around price:
⯌ Dynamic Trend Indicator :
The midline of the bands changes color based on trend direction. If the midline is rising, it turns green, indicating an uptrend. When the midline is falling, it turns orange, suggesting a downtrend. This color coding provides a quick visual reference to the current trend.
Trend color examples for rising and falling midlines:
⯌ Standard Deviation Labels :
At the end of the bands, the indicator displays labels with price levels for each standard deviation level (+3, 0, -3, etc.), helping traders quickly reference where price is relative to its statistical boundaries.
Price labels at each standard deviation level on the chart:
⯌ Mean Reversion Signals :
When price moves beyond the upper or lower bands and then reverts back inside, the indicator plots mean reversion signals with diamond icons. These signals indicate potential reversal points where the price may return to the mean after extreme moves.
Example of mean reversion signals near bands:
⯌ Standard Deviation Scale on Chart :
A visual scale on the right side of the chart shows the current price position in relation to the bands, expressed in standard deviations. This scale provides an at-a-glance view of how far price has deviated from the mean, helping traders assess risk and volatility.
⯁ USER INPUTS
Length : Sets the number of bars used in the calculation of the bands.
Standard Deviation Level : Allows selection of 1, 2, or 3 standard deviations for upper and lower bands.
Colors : Customize colors for the uptrend and downtrend midline indicators.
⯁ CONCLUSION
The Prime Standard Deviation Bands indicator provides a comprehensive view of price volatility and trend direction. Its customizable bands, trend coloring, and mean reversion signals allow traders to effectively gauge price behavior, identify extreme conditions, and make informed trading decisions based on statistical boundaries.
Samet-AL SAT SinyaL// This Pine Script™ code is subject to the terms of the Mozilla Public License 2.0 at mozilla.org
// © Samce
//@version=5
indicator(title='Samet-AL SAT SinyaL', shorttitle='Samet-AL SAT SinyaL', overlay=true)
pSARbeginningValue = input.int(2, minval=0, maxval=10, title='PSAR başlangıç değeri')
pSARendValue = input.int(2, minval=1, maxval=10, title='PSAR bitiş değeri')
pSARmultiplierValue = input.int(2, minval=0, maxval=10, title=' PSAR katsayi değeri')
pSARbeginningMethod = pSARbeginningValue * .01
pSARendMethod = pSARendValue * .10
pSARmultiplierMethod = pSARmultiplierValue * .01
pSAR_UpValue = ta.sar(pSARbeginningMethod, pSARmultiplierMethod, pSARendMethod)
pSAR_DownValue = ta.sar(pSARbeginningMethod, pSARmultiplierMethod, pSARendMethod)
pSAR_UpColor = close >= pSAR_DownValue ? color.green : na
pSAR_DownColor = close <= pSAR_UpValue ? color.red : na
plot(pSAR_UpValue ? pSAR_UpValue : na, style=plot.style_columns, color=pSAR_UpColor, linewidth=0, title='PSAR yukarı', transp=85)
plot(pSAR_DownValue ? pSAR_DownValue : na, style=plot.style_columns, color=pSAR_DownColor, linewidth=1, title='PSAR aşağı', transp=85)
//Zone Identification - This is once again ATR based method to identify the zone based on its strength
zoneSource = input(hl2, title='Kaynak')
src = input(hl2, title='Kaynak')
zoneLength = input(defval=10, title='ATR Alan Uzunluğu')
zoneMultiplier = input.float(defval=3.0, step=0.1, title='ATR Alan Katsayısı')
zoneATR = ta.atr(zoneLength)
downZone = zoneSource + zoneMultiplier * zoneATR
downZoneNew = nz(downZone , downZone)
downZone := close < downZoneNew ? math.min(downZone, downZoneNew) : downZone
upZone = zoneSource - zoneMultiplier * zoneATR
upZoneNew = nz(upZone , upZone)
upZone := close > upZoneNew ? math.max(upZone, upZoneNew) : upZone
zoneDecider = 1
zoneDecider := nz(zoneDecider , zoneDecider)
zoneDecider := zoneDecider == -1 and close > downZoneNew ? 1 : zoneDecider == 1 and close < upZoneNew ? -1 : zoneDecider
redZone = zoneDecider == -1 and zoneDecider == 1
greenZone = zoneDecider == 1 and zoneDecider == -1
downZoneColor = zoneDecider == -1 ? color.red : color.gray
upZoneColor = zoneDecider == 1 ? color.green : color.gray
downZonePlot = plot(zoneDecider == 1 ? na : downZone, style=plot.style_linebr, linewidth=2, color=color.new(color.red, 0), title='Düşüş Bölgesi')
plotshape(redZone ? downZone : na, location=location.absolute, style=shape.diamond, size=size.tiny, color=color.new(color.red, 0), title='Düşüş Bölgesi Başlangıçı')
plotshape(redZone ? downZone : na, location=location.absolute, style=shape.labeldown, size=size.tiny, color=color.new(color.red, 0), textcolor=color.new(color.white, 0), title='SAT', text='Samet/ SAT(short)')
upZonePlot = plot(zoneDecider == 1 ? upZone : na, style=plot.style_linebr, linewidth=2, color=color.new(color.green, 0), title='Yükseliş Bölgesi')
plotshape(greenZone ? upZone : na, location=location.absolute, style=shape.diamond, size=size.tiny, color=color.new(color.green, 0), title='Yükseliş Bölgesi Başlangıçı')
plotshape(greenZone ? upZone : na, location=location.belowbar, style=shape.labelup, size=size.tiny, color=color.new(color.green, 0), textcolor=color.new(color.white, 0), title='AL', text='Samet/ AL(long)')
aldigimfiyat = str.tostring(ta.valuewhen(greenZone, zoneSource, 0))
sattigimfiyat = str.tostring(ta.valuewhen(redZone, zoneSource, 0))
Buy = greenZone
Sell = redZone
if greenZone == 1
l = label.new(bar_index, na)
label.set_text(l, aldigimfiyat)
label.set_color(l, color.green)
label.set_yloc(l, yloc.belowbar)
label.set_style(l, label.style_label_up)
if redZone == 1
l = label.new(bar_index, na)
label.set_text(l, sattigimfiyat)
label.set_color(l, color.red)
label.set_yloc(l, yloc.abovebar)
label.set_style(l, label.style_label_down)
neutralZonePlot = plot(ohlc4, style=plot.style_circles, linewidth=0, title='Alan Stili')
fill(neutralZonePlot, downZonePlot, color=downZoneColor, title='Düşüş Rengi', transp=90)
fill(neutralZonePlot, upZonePlot, color=upZoneColor, title='Yükseliş Rengi', transp=90)
emaLowerPeriod = input.int(9, minval=1, title='EMA Düşük Periyotlar için')
emaLower = ta.ema(input(close), emaLowerPeriod)
plot(emaLower, color=color.new(color.fuchsia, 0), linewidth=2, title='EMA Düşük Periyot')
showEMA2 = input(false, title='EMA - Orta Periyotlar için')
emaMediumPeriod = input.int(27, minval=1, title='EMA Orta Periyotlar için')
emaMedium = ta.ema(input(close), emaMediumPeriod)
plot(showEMA2 and emaMedium ? emaMedium : na, color=color.new(color.aqua, 0), linewidth=2, title='EMA Orta Periyotlar için')
hmaLongPeriod = input.int(200, minval=1, title='HMA Uzun Periyotlar için')
hmaLong = ta.hma(input(close), hmaLongPeriod)
plot(hmaLong, color=color.new(color.gray, 0), linewidth=2, title='HMA Uzun Periyotlar için')
isCloseAbove = close > emaLower and close > hmaLong
isCloseBelow = close < emaLower and close < hmaLong
isCloseBetween = close > emaLower and close < hmaLong or close < emaLower and close > hmaLong
isNeutral = close > pSAR_DownValue and isCloseBelow or close < pSAR_DownValue and isCloseAbove
barcolor(isNeutral or isCloseBetween ? color.yellow : isCloseBelow ? color.red : isCloseAbove ? color.green : color.black)
position = input(500)
h = ta.highest(position)
info_label_off = input(50, title='Bilgilendirme paneli gösterilsin mi?')
info_label_size = input.string(size.normal, options= , title='Info panel label size')
info_panel_x = timenow + math.round(ta.change(time) * 10)
info_panel_y = h
info_current_close = ' SON KAPANIŞ : ' + str.tostring(close)
disp_panels1 = input(true, title='ALIŞ BİLGİLENDİRME PANELİ İSTİYORMUSUNUZ?')
disp_panels2 = input(true, title='SATIŞ BİLGİLENDİRME PANELİ İSTİYORMUSUNUZ?')
Long = '-=-=-ALIŞ DETAY-=-=- '
Short = '-=-=-SATIŞ DETAY-=-=- '
pp1 = ' Aldıktan sonra geçen BAR : ' + str.tostring(ta.barssince(Buy), '##.##')
pp2 = ' Sattıktan sonra geçen BAR : ' + str.tostring(ta.barssince(Sell), '##.##')
Buyprice = ' Satın aldığımız fiyat : ' + str.tostring(ta.valuewhen(Buy, src, 0), '##.##') + ''
ProfitLong = ' KAR : ' + '(' + str.tostring(100 * ((src - ta.valuewhen(Buy, src, 0)) / ta.valuewhen(Buy, src, 0)), '##.##') + '%' + ')'
Sellprice = ' Satın aldığımız fiyat : ' + str.tostring(ta.valuewhen(Sell, src, 0), '##.##') + ''
ProfitShort = ' KAR : ' + '(' + str.tostring(100 * ((ta.valuewhen(Sell, src, 0) - src) / ta.valuewhen(Sell, src, 0)), '##.##') + '%' + ')'
info_textlongbuy = Long + info_current_close + pp1 + Buyprice + ProfitLong
info_textlongsell = Short + info_current_close + pp2 + Sellprice + ProfitShort
info_panellongbuy = zoneDecider == 1 and disp_panels1 ? label.new(x=info_panel_x, y=info_panel_y, text=info_textlongbuy, xloc=xloc.bar_time, yloc=yloc.price, color=color.green, style=label.style_label_up, textcolor=color.black, size=info_label_size) : na
info_panellongsell = zoneDecider == -1 and disp_panels2 ? label.new(x=info_panel_x, y=info_panel_y, text=info_textlongsell, xloc=xloc.bar_time, yloc=yloc.price, color=color.red, style=label.style_label_up, textcolor=color.black, size=info_label_size) : na
label.delete(info_panellongbuy )
label.delete(info_panellongsell )
Samet-AL SAT SinyaL // This Pine Script™ code is subject to the terms of the Mozilla Public License 2.0 at mozilla.org
// © Samce
//@version=5
indicator(title='Samet-AL SAT SinyaL', shorttitle='Samet-AL SAT SinyaL', overlay=true)
pSARbeginningValue = input.int(2, minval=0, maxval=10, title='PSAR başlangıç değeri')
pSARendValue = input.int(2, minval=1, maxval=10, title='PSAR bitiş değeri')
pSARmultiplierValue = input.int(2, minval=0, maxval=10, title=' PSAR katsayi değeri')
pSARbeginningMethod = pSARbeginningValue * .01
pSARendMethod = pSARendValue * .10
pSARmultiplierMethod = pSARmultiplierValue * .01
pSAR_UpValue = ta.sar(pSARbeginningMethod, pSARmultiplierMethod, pSARendMethod)
pSAR_DownValue = ta.sar(pSARbeginningMethod, pSARmultiplierMethod, pSARendMethod)
pSAR_UpColor = close >= pSAR_DownValue ? color.green : na
pSAR_DownColor = close <= pSAR_UpValue ? color.red : na
plot(pSAR_UpValue ? pSAR_UpValue : na, style=plot.style_columns, color=pSAR_UpColor, linewidth=0, title='PSAR yukarı', transp=85)
plot(pSAR_DownValue ? pSAR_DownValue : na, style=plot.style_columns, color=pSAR_DownColor, linewidth=1, title='PSAR aşağı', transp=85)
//Zone Identification - This is once again ATR based method to identify the zone based on its strength
zoneSource = input(hl2, title='Kaynak')
src = input(hl2, title='Kaynak')
zoneLength = input(defval=10, title='ATR Alan Uzunluğu')
zoneMultiplier = input.float(defval=3.0, step=0.1, title='ATR Alan Katsayısı')
zoneATR = ta.atr(zoneLength)
downZone = zoneSource + zoneMultiplier * zoneATR
downZoneNew = nz(downZone , downZone)
downZone := close < downZoneNew ? math.min(downZone, downZoneNew) : downZone
upZone = zoneSource - zoneMultiplier * zoneATR
upZoneNew = nz(upZone , upZone)
upZone := close > upZoneNew ? math.max(upZone, upZoneNew) : upZone
zoneDecider = 1
zoneDecider := nz(zoneDecider , zoneDecider)
zoneDecider := zoneDecider == -1 and close > downZoneNew ? 1 : zoneDecider == 1 and close < upZoneNew ? -1 : zoneDecider
redZone = zoneDecider == -1 and zoneDecider == 1
greenZone = zoneDecider == 1 and zoneDecider == -1
downZoneColor = zoneDecider == -1 ? color.red : color.gray
upZoneColor = zoneDecider == 1 ? color.green : color.gray
downZonePlot = plot(zoneDecider == 1 ? na : downZone, style=plot.style_linebr, linewidth=2, color=color.new(color.red, 0), title='Düşüş Bölgesi')
plotshape(redZone ? downZone : na, location=location.absolute, style=shape.diamond, size=size.tiny, color=color.new(color.red, 0), title='Düşüş Bölgesi Başlangıçı')
plotshape(redZone ? downZone : na, location=location.absolute, style=shape.labeldown, size=size.tiny, color=color.new(color.red, 0), textcolor=color.new(color.white, 0), title='SAT', text='Samet/ SAT(short)')
upZonePlot = plot(zoneDecider == 1 ? upZone : na, style=plot.style_linebr, linewidth=2, color=color.new(color.green, 0), title='Yükseliş Bölgesi')
plotshape(greenZone ? upZone : na, location=location.absolute, style=shape.diamond, size=size.tiny, color=color.new(color.green, 0), title='Yükseliş Bölgesi Başlangıçı')
plotshape(greenZone ? upZone : na, location=location.belowbar, style=shape.labelup, size=size.tiny, color=color.new(color.green, 0), textcolor=color.new(color.white, 0), title='AL', text='Samet/ AL(long)')
aldigimfiyat = str.tostring(ta.valuewhen(greenZone, zoneSource, 0))
sattigimfiyat = str.tostring(ta.valuewhen(redZone, zoneSource, 0))
Buy = greenZone
Sell = redZone
if greenZone == 1
l = label.new(bar_index, na)
label.set_text(l, aldigimfiyat)
label.set_color(l, color.green)
label.set_yloc(l, yloc.belowbar)
label.set_style(l, label.style_label_up)
if redZone == 1
l = label.new(bar_index, na)
label.set_text(l, sattigimfiyat)
label.set_color(l, color.red)
label.set_yloc(l, yloc.abovebar)
label.set_style(l, label.style_label_down)
neutralZonePlot = plot(ohlc4, style=plot.style_circles, linewidth=0, title='Alan Stili')
fill(neutralZonePlot, downZonePlot, color=downZoneColor, title='Düşüş Rengi', transp=90)
fill(neutralZonePlot, upZonePlot, color=upZoneColor, title='Yükseliş Rengi', transp=90)
emaLowerPeriod = input.int(9, minval=1, title='EMA Düşük Periyotlar için')
emaLower = ta.ema(input(close), emaLowerPeriod)
plot(emaLower, color=color.new(color.fuchsia, 0), linewidth=2, title='EMA Düşük Periyot')
showEMA2 = input(false, title='EMA - Orta Periyotlar için')
emaMediumPeriod = input.int(27, minval=1, title='EMA Orta Periyotlar için')
emaMedium = ta.ema(input(close), emaMediumPeriod)
plot(showEMA2 and emaMedium ? emaMedium : na, color=color.new(color.aqua, 0), linewidth=2, title='EMA Orta Periyotlar için')
hmaLongPeriod = input.int(200, minval=1, title='HMA Uzun Periyotlar için')
hmaLong = ta.hma(input(close), hmaLongPeriod)
plot(hmaLong, color=color.new(color.gray, 0), linewidth=2, title='HMA Uzun Periyotlar için')
isCloseAbove = close > emaLower and close > hmaLong
isCloseBelow = close < emaLower and close < hmaLong
isCloseBetween = close > emaLower and close < hmaLong or close < emaLower and close > hmaLong
isNeutral = close > pSAR_DownValue and isCloseBelow or close < pSAR_DownValue and isCloseAbove
barcolor(isNeutral or isCloseBetween ? color.yellow : isCloseBelow ? color.red : isCloseAbove ? color.green : color.black)
position = input(500)
h = ta.highest(position)
info_label_off = input(50, title='Bilgilendirme paneli gösterilsin mi?')
info_label_size = input.string(size.normal, options= , title='Info panel label size')
info_panel_x = timenow + math.round(ta.change(time) * 10)
info_panel_y = h
info_current_close = ' SON KAPANIŞ : ' + str.tostring(close)
disp_panels1 = input(true, title='ALIŞ BİLGİLENDİRME PANELİ İSTİYORMUSUNUZ?')
disp_panels2 = input(true, title='SATIŞ BİLGİLENDİRME PANELİ İSTİYORMUSUNUZ?')
Long = '-=-=-ALIŞ DETAY-=-=- '
Short = '-=-=-SATIŞ DETAY-=-=- '
pp1 = ' Aldıktan sonra geçen BAR : ' + str.tostring(ta.barssince(Buy), '##.##')
pp2 = ' Sattıktan sonra geçen BAR : ' + str.tostring(ta.barssince(Sell), '##.##')
Buyprice = ' Satın aldığımız fiyat : ' + str.tostring(ta.valuewhen(Buy, src, 0), '##.##') + ''
ProfitLong = ' KAR : ' + '(' + str.tostring(100 * ((src - ta.valuewhen(Buy, src, 0)) / ta.valuewhen(Buy, src, 0)), '##.##') + '%' + ')'
Sellprice = ' Satın aldığımız fiyat : ' + str.tostring(ta.valuewhen(Sell, src, 0), '##.##') + ''
ProfitShort = ' KAR : ' + '(' + str.tostring(100 * ((ta.valuewhen(Sell, src, 0) - src) / ta.valuewhen(Sell, src, 0)), '##.##') + '%' + ')'
info_textlongbuy = Long + info_current_close + pp1 + Buyprice + ProfitLong
info_textlongsell = Short + info_current_close + pp2 + Sellprice + ProfitShort
info_panellongbuy = zoneDecider == 1 and disp_panels1 ? label.new(x=info_panel_x, y=info_panel_y, text=info_textlongbuy, xloc=xloc.bar_time, yloc=yloc.price, color=color.green, style=label.style_label_up, textcolor=color.black, size=info_label_size) : na
info_panellongsell = zoneDecider == -1 and disp_panels2 ? label.new(x=info_panel_x, y=info_panel_y, text=info_textlongsell, xloc=xloc.bar_time, yloc=yloc.price, color=color.red, style=label.style_label_up, textcolor=color.black, size=info_label_size) : na
label.delete(info_panellongbuy )
label.delete(info_panellongsell )
Aura Vibes EMA Ribbon + VStop + SAR + Bollinger BandsThe combination of Exponential Moving Averages (EMA), Volatility Stop (VStop), Parabolic SAR (PSAR), and Bollinger Bands (BB) offers a comprehensive approach to technical analysis, each serving a distinct purpose:
Exponential Moving Averages (EMA): EMAs are used to identify the direction of the trend by smoothing price data. Shorter-period EMAs react more quickly to price changes, while longer-period EMAs provide a broader view of the trend.
Volatility Stop (VStop): VStop is a dynamic stop-loss mechanism that adjusts based on market volatility, typically using the Average True Range (ATR). This allows traders to set stop-loss levels that accommodate market fluctuations, potentially reducing the likelihood of premature stop-outs.
Parabolic SAR (PSAR): PSAR is a trend-following indicator that provides potential entry and exit points by plotting dots above or below the price chart. When the dots are below the price, it suggests an uptrend; when above, a downtrend.
Bollinger Bands (BB): BB consists of a middle band (typically a 20-period simple moving average) and two outer bands set at standard deviations above and below the middle band. These bands expand and contract based on market volatility, helping traders identify overbought or oversold conditions.
Integrating these indicators can enhance trading strategies:
Trend Identification: Use EMAs to determine the prevailing market trend. For instance, a short-term EMA crossing above a long-term EMA may signal an uptrend.
Entry and Exit Points: Combine PSAR and BB to pinpoint potential entry and exit points. For example, a PSAR dot appearing below the price during an uptrend, coinciding with the price touching the lower Bollinger Band, might indicate a buying opportunity.
Risk Management: Implement VStop to set adaptive stop-loss levels that adjust with market volatility, providing a buffer against market noise.
By thoughtfully combining these indicators, traders can develop a robust trading system that adapts to various market conditions.
Rango de 5% y RSI - Señales de Compra/VentaEl indicador da señales de compra cuando la vela tiene un rango de 5% o más y el RSI está sobrevendido en gráfica de 4h o superior (viceversa para las ventas).
AI InfinityAI Infinity – Multidimensional Market Analysis
Overview
The AI Infinity indicator combines multiple analysis tools into a single solution. Alongside dynamic candle coloring based on MACD and Stochastic signals, it features Alligator lines, several RSI lines (including glow effects), and optionally enabled EMAs (20/50, 100, and 200). Every module is individually configurable, allowing traders to tailor the indicator to their personal style and strategy.
Important Note (Disclaimer)
This indicator is provided for educational and informational purposes only.
It does not constitute financial or investment advice and offers no guarantee of profit.
Each trader is responsible for their own trading decisions.
Past performance does not guarantee future results.
Please review the settings thoroughly and adjust them to your personal risk profile; consider supplementary analyses or professional guidance where appropriate.
Functionality & Components
1. Candle Coloring (MACD & Stochastic)
Objective: Provide an immediate visual snapshot of the market’s condition.
Details:
MACD Signal: Used to identify bullish and bearish momentum.
Stochastic: Detects overbought and oversold zones.
Color Modes: Offers both a simple (two-color) mode and a gradient mode.
2. Alligator Lines
Objective: Assist with trend analysis and determining the market’s current phase.
Details:
Dynamic SMMA Lines (Jaw, Teeth, Lips) that adjust based on volatility and market conditions.
Multiple Lengths: Each element uses a separate smoothing period (13, 8, 5).
Transparency: You can show or hide each line independently.
3. RSI Lines & Glow Effects
Objective: Display the RSI values directly on the price chart so critical levels (e.g., 20, 50, 80) remain visible at a glance.
Details:
RSI Scaling: The RSI is plotted in the chart window, eliminating the need to switch panels.
Dynamic Transparency: A pulse effect indicates when the RSI is near critical thresholds.
Glow Mode: Choose between “Direct Glow” or “Dynamic Transparency” (based on ATR distance).
Custom RSI Length: Freely adjustable (default is 14).
4. Optional EMAs (20/50, 100, 200)
Objective: Utilize moving averages for trend assessment and identifying potential support/resistance areas.
Details:
20/50 EMA: Select which one to display via a dropdown menu.
100 EMA & 200 EMA: Independently enabled.
Color Logic: Automatically green (price > EMA) or red (price < EMA). Each EMA’s up/down color is customizable.
Configuration Options
Candle Coloring:
Choose between Gradient or Simple mode.
Adjust the color scheme for bullish/bearish candles.
Transparency is dynamically based on candle body size and Stochastic state.
Alligator Lines:
Toggle each line (Jaw/Teeth/Lips) on or off.
Select individual colors for each line.
RSI Section:
RSI Length can be set as desired.
RSI lines (0, 20, 50, 80, 100) with user-defined colors and transparency (pulse effect).
Additional lines (e.g., RSI 40/60) are also available.
Glow Effects:
Switch between “Dynamic Transparency” (ATR-based) and “Direct Glow”.
Independently applied to the RSI 100 and RSI 0 lines.
EMAs (20/50, 100, 200):
Activate each one as needed.
Each EMA’s up/down color can be customized.
Example Use Cases
Trend Identification:
Enable Alligator lines to gauge general trend direction through SMMA signals.
Timing:
Watch the Candle Colors to spot potential overbought or oversold conditions.
Fine-Tuning:
Utilize the RSI lines to closely monitor important thresholds (50 as a trend barometer, 80/20 as possible reversal zones).
Filtering:
Enable a 50 EMA to quickly see if the market is trading above (bullish) or below (bearish) it.
StdDev of VWAP/MAStdDev Indicator (MA, Smoothed VWAP & Rolling VWAP) v5
Overview: The StdDev Indicator is a comprehensive tool designed to provide traders with multi-term deviation analysis by integrating various Moving Averages (MA) and Volume Weighted Average Price (VWAP) methodologies. This indicator combines different MA types and VWAP calculations across multiple timeframes to offer a nuanced view of market volatility and trend strength.
Key Features:
Multiple Moving Average Types:
Simple Moving Average (SMA): Calculates the average price over a specified period, providing a straightforward trend indicator.
Exponential Moving Average (EMA): Gives more weight to recent prices, making it more responsive to new information.
Weighted Moving Average (WMA): Assigns different weights to each price point, emphasizing specific periods.
Smoothed VWAP: Enhances the traditional VWAP by applying additional smoothing techniques (SMA, EMA, WMA) to reduce volatility.
Rolling VWAP: Continuously recalculates VWAP over a rolling window, offering dynamic support and resistance levels.
Multi-Term Deviation Analysis:
Extra Short Term (30 periods)
Short Term (50 periods)
Medium Term (110 periods)
Long Term (125 periods)
Extra-Long Term (190 periods)
Extremely-Long Term (245 periods)
Each term calculates the deviation of the selected price source (default: Low) from its corresponding MA or VWAP, normalized by the standard deviation. This multi-term approach allows traders to assess volatility and trend consistency across different time horizons.
Composite Upper and Lower Bounds:
Aggregates the upper and lower deviations from all terms to form composite boundaries. These bounds serve as dynamic support and resistance levels, helping traders identify potential reversal points or breakout zones.
Timeframe Customization:
Visibility Settings: Customize which deviation terms are visible on specific timeframes (15m, 1h, 4h, 1d, 1w). This flexibility ensures that the indicator aligns with your trading strategy, whether you're a scalper, day trader, or long-term investor.
Bar Coloring (Optional):
Visual Cues: When enabled, bars are color-coded based on the deviation levels, providing immediate visual feedback on market conditions. For example, bars may turn red when short-term deviations exceed the upper bound, indicating potential overbought conditions.
How It Works:
Deviation Calculation:
For each selected MA or VWAP type and term length, the indicator calculates the deviation of the current price source from the MA/VWAP. This deviation is normalized by the standard deviation to account for volatility.
Channel Offset:
Applies a linear regression and standard deviation to the deviation series to establish upper and lower channels. These channels are adjustable via multipliers, allowing traders to set their sensitivity levels.
Composite Boundaries:
Averages the upper and lower channels across all deviation terms to form composite upper and lower bounds. These bounds provide a holistic view of market volatility and trend strength.
Visualization:
Plots individual deviation lines for each term, along with the composite bounds. Optional bar coloring enhances visual interpretation, making it easier to spot significant market movements.
Usage Instructions:
Setup:
Add the StdDev Indicator to your TradingView chart. By default, it uses the Low price as the source, but this can be customized.
Configuration:
Moving Average Type: Select your preferred MA or VWAP type from the dropdown menu.
Term Lengths: Adjust the lengths for each deviation term as per your trading strategy.
StdDev Multipliers: Set the multipliers for the upper and lower bounds to control sensitivity.
Timeframe Visibility: Choose which deviation terms are visible on specific timeframes to tailor the indicator to your trading style.
Bar Coloring: Enable or disable bar coloring based on deviation thresholds for enhanced visual cues.
Interpretation:
Deviations: Monitor the deviation lines to assess overbought or oversold conditions across different terms.
Composite Bounds: Use the upper and lower bounds as dynamic support and resistance levels.
Bar Colors: Quickly identify significant market movements through color-coded bars.
Why Choose StdDev Indicator?
Comprehensive Analysis: By integrating multiple MA and VWAP types across various terms, the indicator offers a multifaceted view of market conditions.
Customization: Highly configurable settings allow traders to adapt the indicator to their specific strategies and timeframes.
Visual Clarity: Clear plotting and optional bar coloring provide intuitive insights, reducing the need for complex analysis.
Conclusion: The StdDev Indicator (MA, Smoothed VWAP & Rolling VWAP) v5 is a versatile tool that combines advanced moving average and VWAP methodologies to deliver a robust deviation analysis framework. Whether you're looking to fine-tune your scalping strategy or gain a deeper understanding of long-term market trends, this indicator equips you with the necessary tools to make informed trading decisions.
Support & Feedback: If you have any questions or need assistance with the indicator, feel free to reach out through the TradingView community or contact the script author directly.
