02 SMC + BB Breakout (Improved)This strategy combines Smart Money Concepts (SMC) with Bollinger Band breakouts to identify potential trading opportunities. SMC focuses on identifying key price levels and market structure shifts, while Bollinger Bands help pinpoint overbought/oversold conditions and potential breakout points. The strategy also incorporates higher timeframe trend confirmation to filter out trades that go against the prevailing trend.
Key Components:
Bollinger Bands:
Calculated using a Simple Moving Average (SMA) of the closing price and a standard deviation multiplier.
The strategy uses the upper and lower bands to identify potential breakout points.
The SMA (basis) acts as a centerline and potential support/resistance level.
The fill between the upper and lower bands can be toggled by the user.
Higher Timeframe Trend Confirmation:
The strategy allows for optional confirmation of the current trend using a higher timeframe (e.g., daily).
It calculates the SMA of the higher timeframe's closing prices.
A bullish trend is confirmed if the higher timeframe's closing price is above its SMA.
This helps filter out trades that go against the prevailing long-term trend.
Smart Money Concepts (SMC):
Order Blocks:
Simplified as recent price clusters, identified by the highest high and lowest low over a specified lookback period.
These levels are considered potential areas of support or resistance.
Liquidity Zones (Swing Highs/Lows):
Identified by recent swing highs and lows, indicating areas where liquidity may be present.
The Swing highs and lows are calculated based on user defined lookback periods.
Market Structure Shift (MSS):
Identifies potential changes in market structure.
A bullish MSS occurs when the closing price breaks above a previous swing high.
A bearish MSS occurs when the closing price breaks below a previous swing low.
The swing high and low values used for the MSS are calculated based on the user defined swing length.
Entry Conditions:
Long Entry:
The closing price crosses above the upper Bollinger Band.
If higher timeframe confirmation is enabled, the higher timeframe trend must be bullish.
A bullish MSS must have occurred.
Short Entry:
The closing price crosses below the lower Bollinger Band.
If higher timeframe confirmation is enabled, the higher timeframe trend must be bearish.
A bearish MSS must have occurred.
Exit Conditions:
Long Exit:
The closing price crosses below the Bollinger Band basis.
Or the Closing price falls below 99% of the order block low.
Short Exit:
The closing price crosses above the Bollinger Band basis.
Or the closing price rises above 101% of the order block high.
Position Sizing:
The strategy calculates the position size based on a fixed percentage (5%) of the strategy's equity.
This helps manage risk by limiting the potential loss per trade.
Visualizations:
Bollinger Bands (upper, lower, and basis) are plotted on the chart.
SMC elements (order blocks, swing highs/lows) are plotted as lines, with user-adjustable visibility.
Entry and exit signals are plotted as shapes on the chart.
The Bollinger band fill opacity is adjustable by the user.
Trading Logic:
The strategy aims to capitalize on Bollinger Band breakouts that are confirmed by SMC signals and higher timeframe trend. It looks for breakouts that align with potential market structure shifts and key price levels (order blocks, swing highs/lows). The higher timeframe filter helps avoid trades that go against the overall trend.
In essence, the strategy attempts to identify high-probability breakout trades by combining momentum (Bollinger Bands) with structural analysis (SMC) and trend confirmation.
Key User-Adjustable Parameters:
Bollinger Bands Length
Standard Deviation Multiplier
Higher Timeframe
Higher Timeframe Confirmation (on/off)
SMC Elements Visibility (on/off)
Order block lookback length.
Swing lookback length.
Bollinger band fill opacity.
This detailed description should provide a comprehensive understanding of the strategy's logic and components.
***DISCLAIMER: This strategy is for educational purposes only. It is not financial advice. Past performance is not indicative of future results. Use at your own risk. Always perform thorough backtesting and forward testing before using any strategy in live trading.***
在腳本中搜尋"entry"
Auto TrendLines [TradingFinder] Support Resistance Signal Alerts🔵 Introduction
The trendline is one of the most essential tools in technical analysis, widely used in financial markets such as Forex, cryptocurrency, and stocks. A trendline is a straight line that connects swing highs or swing lows and visually indicates the market’s trend direction.
Traders use trendlines to identify price structure, the strength of buyers and sellers, dynamic support and resistance zones, and optimal entry and exit points.
In technical analysis, trendlines are typically classified into three categories: uptrend lines (drawn by connecting higher lows), downtrend lines (formed by connecting lower highs), and sideways trends (moving horizontally). A valid trendline usually requires at least three confirmed touchpoints to be considered reliable for trading decisions.
Trendlines can serve as the foundation for a variety of trading strategies, such as the trendline bounce strategy, valid breakout setups, and confluence-based analysis with other tools like candlestick patterns, divergences, moving averages, and Fibonacci levels.
Additionally, trendlines are categorized into internal and external, and further into major and minor levels, each serving unique roles in market structure analysis.
🔵 How to Use
Trendlines are a key component in technical analysis, used to identify market direction, define dynamic support and resistance zones, highlight strategic entry and exit points, and manage risk. For a trendline to be reliable, it must be drawn based on structural principles—not by simply connecting two arbitrary points.
🟣 Selecting Pivot Types Based on Trend Direction
The first step is to determine the market trend: uptrend, downtrend, or sideways.
Then, choose pivot points that match the trend type :
In an uptrend, trendlines are drawn by connecting low pivots, especially higher lows.
In a downtrend, trendlines are formed by connecting high pivots, specifically lower highs.
It is crucial to connect pivots of the same type and structure to ensure the trendline is valid and analytically sound.
🟣 Pivot Classification
This indicator automatically classifies pivot points into two categories :
Major Pivots :
MLL : Major Lower Low
MHL : Major Higher Low
MHH : Major Higher High
MLH : Major Lower High
These define the primary structure of the market and are typically used in broader structural analysis.
Minor Pivots :
mLL: minor Lower Low
mHL: minor Higher Low
mHH: minor Higher High
mLH: minor Lower High
These are used for drawing more precise trendlines within corrective waves or internal price movements.
Example : In a downtrend, drawing a trendline from an MHH to an mHH creates structural inconsistency and introduces noise. Instead, connect points like MHL to MHL or mLH to mLH for a valid trendline.
🟣 Drawing High-Precision Trendlines
To ensure a reliable trendline :
Use pivots of the same classification (Major with Major or Minor with Minor).
Ensure at least three valid contact points (three touches = structural confirmation).
Draw through candles with the least deviation (choose wicks or bodies based on confluence).
Preferably draw from right to left for better alignment with current market behavior.
Use parallel lines to turn a single trendline into a trendline zone, if needed.
🟣 Using Trendlines for Trade Entries
Bounce Entry: When price approaches the trendline and shows signs of reversal (e.g., a reversal candle, divergence, or support/resistance), enter in the direction of the trend with a logical stop-loss.
Breakout Entry: When price breaks through the trendline with strong momentum and a confirmation (such as a retest or break of structure), consider trading in the direction of the breakout.
🟣 Trendline-Based Risk Management
For bounce entries, the stop-loss is placed below the trendline or the last pivot low (in an uptrend).
For breakout entries, the stop-loss is set behind the breakout candle or the last structural level.
A broken trendline can also act as an exit signal from a trade.
🟣 Combining Trendlines with Other Tools (Confluence)
Trendlines gain much more strength when used alongside other analytical tools :
Horizontal support and resistance levels
Moving averages (such as EMA 50 or EMA 200)
Fibonacci retracement zones
Candlestick patterns (e.g., Engulfing, Pin Bar)
RSI or MACD divergences
Market structure breaks (BoS / ChoCH)
🔵 Settings
Pivot Period : This defines how sensitive the pivot detection is. A higher number means the algorithm will identify more significant pivot points, resulting in longer-term trendlines.
Alerts
Alert :
Enable or disable the entire alert system
Set a custom alert name
Choose how often alerts trigger (every time, once per bar, or on bar close)
Select the time zone for alert timestamps (e.g., UTC)
Each trendline type supports two alert types :
Break Alert : Triggered when price breaks the trendline
React Alert : Triggered when price reacts or bounces off the trendline
These alerts can be independently enabled or disabled for all trendline categories (Major/Minor, Internal/External, Up/Down).
Display :
For each of the eight trendline types, you can control :
Whether to show or hide the line
Whether to delete the previous line when a new one is drawn
Color, line style (solid, dashed, dotted), extension direction (e.g., right only), and width
Major lines are typically thicker and more opaque, while minor lines appear thinner and more transparent.
All settings are designed to give the user full control over the appearance, behavior, and alert system of the indicator, without requiring manual drawing or adjustments.
🔵 Conclusion
A trendline is more than just a line on the chart—it is a structural, strategic, and flexible tool in technical analysis that can serve as the foundation for understanding price behavior and making trading decisions. Whether in trending markets or during corrections, trendlines help traders identify market direction, key zones, and high-potential entry and exit points with precision.
The accuracy and effectiveness of a trendline depend on using structurally valid pivot points and adhering to proper market logic, rather than relying on guesswork or personal bias.
This indicator is built to solve that exact problem. It automatically detects and draws multiple types of trendlines based on actual price structure, separating them into Major/Minor and Internal/External categories, and respecting professional analytical principles such as pivot type, trend direction, and structural location.
Gold Scalping BOS & CHoCHThis strategy is designed for scalping gold (XAU/USD) on the 3-minute timeframe, utilizing Break of Structure (BOS) and Change of Character (CHoCH) to identify high-probability trade setups. Unlike traditional SMA crossover strategies, this method focuses purely on price action and market structure shifts, allowing for early entries and better risk management.
Core Concepts:
Break of Structure (BOS) – Confirms a continuation of the trend when price breaks the last swing high (bullish) or last swing low (bearish).
Change of Character (CHoCH) – Detects possible trend reversals by identifying a shift in market momentum.
Dynamic Support & Resistance – Uses the last 10-bar highs and lows to determine adaptive stop-loss (SL) and take-profit (TP) levels.
Risk-to-Reward Ratio (1:2 RR) – Ensures trades are executed with a favorable risk/reward ratio.
Entry Conditions:
Buy Entry:
BOS (Bullish) confirmed (price breaks the previous swing high).
CHoCH (Bullish) confirms trend shift.
Price crosses back above the last swing low (confirmation of support).
Sell Entry:
BOS (Bearish) confirmed (price breaks the previous swing low).
CHoCH (Bearish) confirms trend shift.
Price crosses back below the last swing high (confirmation of resistance).
Exit Conditions:
Stop Loss (SL): Set at the most recent dynamic support (for buys) or resistance (for sells).
Take Profit (TP): 2x the risk (1:2 risk-reward ratio).
Advantages of This Strategy:
✅ No lagging indicators – Uses price action for real-time entries.
✅ High probability setups – Focuses only on strong structural breaks.
✅ Adaptive SL/TP – Uses real market structure instead of fixed values.
✅ Optimized for Scalping – Best suited for quick in-and-out trades.
Best Time to Trade:
🔹 London & New York Sessions (High volatility for gold).
Rally Base Drop SND Pivots Strategy [LuxAlgo X PineIndicators]This strategy is based on the Rally Base Drop (RBD) SND Pivots indicator developed by LuxAlgo. Full credit for the concept and original indicator goes to LuxAlgo.
The Rally Base Drop SND Pivots Strategy is a non-repainting supply and demand trading system that detects pivot points based on Rally, Base, and Drop (RBD) candles. This strategy automatically identifies key market structure levels, allowing traders to:
Identify pivot-based supply and demand (SND) zones.
Use fixed criteria for trend continuation or reversals.
Filter out market noise by requiring structured price formations.
Enter trades based on breakouts of key SND pivot levels.
How the Rally Base Drop SND Pivots Strategy Works
1. Pivot Point Detection Using RBD Candles
The strategy follows a rigid market structure methodology, where pivots are detected only when:
A Rally (R) consists of multiple consecutive bullish candles.
A Drop (D) consists of multiple consecutive bearish candles.
A Base (B) is identified as a transition between Rallies and Drops, acting as a pivot point.
The pivot level is confirmed when the formation is complete.
Unlike traditional fractal-based pivots, RBD Pivots enforce stricter structural rules, ensuring that each pivot:
Has a well-defined bullish or bearish price movement.
Reduces false signals caused by single-bar fluctuations.
Provides clear supply and demand levels based on structured price movements.
These pivot levels are drawn on the chart using color-coded boxes:
Green zones represent bullish pivot levels (Rally Base formations).
Red zones represent bearish pivot levels (Drop Base formations).
Once a pivot is confirmed, the high or low of the base candle is used as the reference level for future trades.
2. Trade Entry Conditions
The strategy allows traders to select from three trading modes:
Long Only – Only takes long trades when bullish pivot breakouts occur.
Short Only – Only takes short trades when bearish pivot breakouts occur.
Long & Short – Trades in both directions based on pivot breakouts.
Trade entry signals are triggered when price breaks through a confirmed pivot level:
Long Entry:
A bullish pivot level is formed.
Price breaks above the bullish pivot level.
The strategy enters a long position.
Short Entry:
A bearish pivot level is formed.
Price breaks below the bearish pivot level.
The strategy enters a short position.
The strategy includes an optional mode to reverse long and short conditions, allowing traders to experiment with contrarian entries.
3. Exit Conditions Using ATR-Based Risk Management
This strategy uses the Average True Range (ATR) to calculate dynamic stop-loss and take-profit levels:
Stop-Loss (SL): Placed 1 ATR below entry for long trades and 1 ATR above entry for short trades.
Take-Profit (TP): Set using a Risk-Reward Ratio (RR) multiplier (default = 6x ATR).
When a trade is opened:
The entry price is recorded.
ATR is calculated at the time of entry to determine stop-loss and take-profit levels.
Trades exit automatically when either SL or TP is reached.
If reverse conditions mode is enabled, stop-loss and take-profit placements are flipped.
Visualization & Dynamic Support/Resistance Levels
1. Pivot Boxes for Market Structure
Each pivot is marked with a colored box:
Green boxes indicate bullish demand zones.
Red boxes indicate bearish supply zones.
These boxes remain on the chart to act as dynamic support and resistance levels, helping traders identify key price reaction zones.
2. Horizontal Entry, Stop-Loss, and Take-Profit Lines
When a trade is active, the strategy plots:
White line → Entry price.
Red line → Stop-loss level.
Green line → Take-profit level.
Labels display the exact entry, SL, and TP values, updating dynamically as price moves.
Customization Options
This strategy offers multiple adjustable settings to optimize performance for different market conditions:
Trade Mode Selection → Choose between Long Only, Short Only, or Long & Short.
Pivot Length → Defines the number of required Rally & Drop candles for a pivot.
ATR Exit Multiplier → Adjusts stop-loss distance based on ATR.
Risk-Reward Ratio (RR) → Modifies take-profit level relative to risk.
Historical Lookback → Limits how far back pivot zones are displayed.
Color Settings → Customize pivot box colors for bullish and bearish setups.
Considerations & Limitations
Pivot Breakouts Do Not Guarantee Reversals. Some pivot breaks may lead to continuation moves instead of trend reversals.
Not Optimized for Low Volatility Conditions. This strategy works best in trending markets with strong momentum.
ATR-Based Stop-Loss & Take-Profit May Require Optimization. Different assets may require different ATR multipliers and RR settings.
Market Noise May Still Influence Pivots. While this method filters some noise, fake breakouts can still occur.
Conclusion
The Rally Base Drop SND Pivots Strategy is a non-repainting supply and demand system that combines:
Pivot-based market structure analysis (using Rally, Base, and Drop candles).
Breakout-based trade entries at confirmed SND levels.
ATR-based dynamic risk management for stop-loss and take-profit calculation.
This strategy helps traders:
Identify high-probability supply and demand levels.
Trade based on structured market pivots.
Use a systematic approach to price action analysis.
Automatically manage risk with ATR-based exits.
The strict pivot detection rules and built-in breakout validation make this strategy ideal for traders looking to:
Trade based on market structure.
Use defined support & resistance levels.
Reduce noise compared to traditional fractals.
Implement a structured supply & demand trading model.
This strategy is fully customizable, allowing traders to adjust parameters to fit their market and trading style.
Full credit for the original concept and indicator goes to LuxAlgo.
Liquidity Sweep Filter Strategy [AlgoAlpha X PineIndicators]This strategy is based on the Liquidity Sweep Filter developed by AlgoAlpha. Full credit for the concept and original indicator goes to AlgoAlpha.
The Liquidity Sweep Filter Strategy is a non-repainting trading system designed to identify liquidity sweeps, trend shifts, and high-impact price levels. It incorporates volume-based liquidation analysis, trend confirmation, and dynamic support/resistance detection to optimize trade entries and exits.
This strategy helps traders:
Detect liquidity sweeps where major market participants trigger stop losses and liquidations.
Identify trend shifts using a volatility-based moving average system.
Analyze volume distribution with a built-in volume profile visualization.
Filter noise by differentiating between major and minor liquidity sweeps.
How the Liquidity Sweep Filter Strategy Works
1. Trend Detection Using Volatility-Based Filtering
The strategy applies a volatility-adjusted moving average system to determine trend direction:
A central trend line is calculated using an EMA smoothed over a user-defined length.
Upper and lower deviation bands are created based on the average price deviation over multiple periods.
If price closes above the upper band, the strategy signals an uptrend.
If price closes below the lower band, the strategy signals a downtrend.
This approach ensures that trend shifts are confirmed only when price significantly moves beyond normal market fluctuations.
2. Liquidity Sweep Detection
Liquidity sweeps occur when price temporarily breaks key levels, triggering stop-loss liquidations or margin call events. The strategy tracks swing highs and lows, marking potential liquidity grabs:
Bearish Liquidity Sweeps – Price breaks a recent high, then reverses downward.
Bullish Liquidity Sweeps – Price breaks a recent low, then reverses upward.
Volume Integration – The strategy analyzes trading volume at each sweep to differentiate between major and minor sweeps.
Key levels where liquidity sweeps occur are plotted as color-coded horizontal lines:
Red lines indicate bearish liquidity sweeps.
Green lines indicate bullish liquidity sweeps.
Labels are displayed at each sweep, showing the volume of liquidated positions at that level.
3. Volume Profile Analysis
The strategy includes an optional volume profile visualization, displaying how trading volume is distributed across different price levels.
Features of the volume profile:
Point of Control (POC) – The price level with the highest traded volume is marked as a key area of interest.
Bounding Box – The profile is enclosed within a transparent box, helping traders visualize the price range of high trading activity.
Customizable Resolution & Scale – Traders can adjust the granularity of the profile to match their preferred time frame.
The volume profile helps identify zones of strong support and resistance, making it easier to anticipate price reactions at key levels.
Trade Entry & Exit Conditions
The strategy allows traders to configure trade direction:
Long Only – Only takes long trades.
Short Only – Only takes short trades.
Long & Short – Trades in both directions.
Entry Conditions
Long Entry:
A bullish trend shift is confirmed.
A bullish liquidity sweep occurs (price sweeps below a key level and reverses).
The trade direction setting allows long trades.
Short Entry:
A bearish trend shift is confirmed.
A bearish liquidity sweep occurs (price sweeps above a key level and reverses).
The trade direction setting allows short trades.
Exit Conditions
Closing a Long Position:
A bearish trend shift occurs.
The position is liquidated at a predefined liquidity sweep level.
Closing a Short Position:
A bullish trend shift occurs.
The position is liquidated at a predefined liquidity sweep level.
Customization Options
The strategy offers multiple adjustable settings:
Trade Mode: Choose between Long Only, Short Only, or Long & Short.
Trend Calculation Length & Multiplier: Adjust how trend signals are calculated.
Liquidity Sweep Sensitivity: Customize how aggressively the strategy identifies sweeps.
Volume Profile Display: Enable or disable the volume profile visualization.
Bounding Box & Scaling: Control the size and position of the volume profile.
Color Customization: Adjust colors for bullish and bearish signals.
Considerations & Limitations
Liquidity sweeps do not always result in reversals. Some price sweeps may continue in the same direction.
Works best in volatile markets. In low-volatility environments, liquidity sweeps may be less reliable.
Trend confirmation adds a slight delay. The strategy ensures valid signals, but this may result in slightly later entries.
Large volume imbalances may distort the volume profile. Adjusting the scale settings can help improve visualization.
Conclusion
The Liquidity Sweep Filter Strategy is a volume-integrated trading system that combines liquidity sweeps, trend analysis, and volume profile data to optimize trade execution.
By identifying key price levels where liquidations occur, this strategy provides valuable insight into market behavior, helping traders make better-informed trading decisions.
Key use cases for this strategy:
Liquidity-Based Trading – Capturing moves triggered by stop hunts and liquidations.
Volume Analysis – Using volume profile data to confirm high-activity price zones.
Trend Following – Entering trades based on confirmed trend shifts.
Support & Resistance Trading – Using liquidity sweep levels as dynamic price zones.
This strategy is fully customizable, allowing traders to adapt it to different market conditions, timeframes, and risk preferences.
Full credit for the original concept and indicator goes to AlgoAlpha.
Market Trend Levels Non-Repainting [BigBeluga X PineIndicators]This strategy is based on the Market Trend Levels Detector developed by BigBeluga. Full credit for the concept and original indicator goes to BigBeluga.
The Market Trend Levels Detector Strategy is a non-repainting trend-following strategy that identifies market trend shifts using two Exponential Moving Averages (EMA). It also detects key price levels and allows traders to apply multiple filters to refine trade entries and exits.
This strategy is designed for trend trading and enables traders to:
Identify trend direction based on EMA crossovers.
Detect significant market levels using labeled trend lines.
Use multiple filter conditions to improve trade accuracy.
Avoid false signals through non-repainting calculations.
How the Market Trend Levels Detector Strategy Works
1. Core Trend Detection Using EMA Crossovers
The strategy detects trend shifts using two EMAs:
Fast EMA (default: 12 periods) – Reacts quickly to price movements.
Slow EMA (default: 25 periods) – Provides a smoother trend confirmation.
A bullish crossover (Fast EMA crosses above Slow EMA) signals an uptrend , while a bearish crossover (Fast EMA crosses below Slow EMA) signals a downtrend .
2. Market Level Detection & Visualization
Each time an EMA crossover occurs, a trend level line is drawn:
Bullish crossover → A green line is drawn at the low of the crossover candle.
Bearish crossover → A purple line is drawn at the high of the crossover candle.
Lines can be extended to act as support and resistance zones for future price action.
Additionally, a small label (●) appears at each crossover to mark the event on the chart.
3. Trade Entry & Exit Conditions
The strategy allows users to choose between three trading modes:
Long Only – Only enters long trades.
Short Only – Only enters short trades.
Long & Short – Trades in both directions.
Entry Conditions
Long Entry:
A bullish EMA crossover occurs.
The trade direction setting allows long trades.
Filter conditions (if enabled) confirm a valid long signal.
Short Entry:
A bearish EMA crossover occurs.
The trade direction setting allows short trades.
Filter conditions (if enabled) confirm a valid short signal.
Exit Conditions
Long Exit:
A bearish EMA crossover occurs.
Exit filters (if enabled) indicate an invalid long position.
Short Exit:
A bullish EMA crossover occurs.
Exit filters (if enabled) indicate an invalid short position.
Additional Trade Filters
To improve trade accuracy, the strategy allows traders to apply up to 7 additional filters:
RSI Filter: Only trades when RSI confirms a valid trend.
MACD Filter: Ensures MACD histogram supports the trade direction.
Stochastic Filter: Requires %K line to be above/below threshold values.
Bollinger Bands Filter: Confirms price position relative to the middle BB line.
ADX Filter: Ensures the trend strength is above a set threshold.
CCI Filter: Requires CCI to indicate momentum in the right direction.
Williams %R Filter: Ensures price momentum supports the trade.
Filters can be enabled or disabled individually based on trader preference.
Dynamic Level Extension Feature
The strategy provides an optional feature to extend trend lines until price interacts with them again:
Bullish support lines extend until price revisits them.
Bearish resistance lines extend until price revisits them.
If price breaks a line, the line turns into a dotted style , indicating it has been breached.
This helps traders identify key levels where trend shifts previously occurred, providing useful support and resistance insights.
Customization Options
The strategy includes several adjustable settings :
Trade Direction: Choose between Long Only, Short Only, or Long & Short.
Trend Lengths: Adjust the Fast & Slow EMA lengths.
Market Level Extension: Decide whether to extend support/resistance lines.
Filters for Trade Confirmation: Enable/disable individual filters.
Color Settings: Customize line colors for bullish and bearish trend shifts.
Maximum Displayed Lines: Limit the number of drawn support/resistance lines.
Considerations & Limitations
Trend Lag: As with any EMA-based strategy, signals may be slightly delayed compared to price action.
Sideways Markets: This strategy works best in trending conditions; frequent crossovers in sideways markets can produce false signals.
Filter Usage: Enabling multiple filters may reduce trade frequency, but can also improve trade quality.
Line Overlap: If many crossovers occur in a short period, the chart may become cluttered with multiple trend levels. Adjusting the "Display Last" setting can help.
Conclusion
The Market Trend Levels Detector Strategy is a non-repainting trend-following system that combines EMA crossovers, market level detection, and customizable filters to improve trade accuracy.
By identifying trend shifts and key price levels, this strategy can be used for:
Trend Confirmation – Using EMA crossovers and filters to confirm trend direction.
Support & Resistance Trading – Identifying dynamic levels where price reacts.
Momentum-Based Trading – Combining EMA crossovers with additional momentum filters.
This strategy is fully customizable and can be adapted to different trading styles, timeframes, and market conditions.
Full credit for the original concept and indicator goes to BigBeluga.
Gradient Trend Filter STRATEGY [ChartPrime/PineIndicators]This strategy is based on the Gradient Trend Filter indicator developed by ChartPrime. Full credit for the concept and indicator goes to ChartPrime.
The Gradient Trend Filter Strategy is designed to execute trades based on the trend analysis and filtering system provided by the Gradient Trend Filter indicator. It integrates a noise-filtered trend detection system with a color-gradient visualization, helping traders identify trend strength, momentum shifts, and potential reversals.
How the Gradient Trend Filter Strategy Works
1. Noise Filtering for Smoother Trends
To reduce false signals caused by market noise, the strategy applies a three-stage smoothing function to the source price. This function ensures that trend shifts are detected more accurately, minimizing unnecessary trade entries and exits.
The filter is based on an Exponential Moving Average (EMA)-style smoothing technique.
It processes price data in three successive passes, refining the trend signal before generating trade entries.
This filtering technique helps eliminate minor fluctuations and highlights the true underlying trend.
2. Multi-Layered Trend Bands & Color-Based Trend Visualization
The Gradient Trend Filter constructs multiple trend bands around the filtered trend line, acting as dynamic support and resistance zones.
The mid-line changes color based on the trend direction:
Green for uptrends
Red for downtrends
A gradient cloud is formed around the trend line, dynamically shifting colors to provide early warning signals of trend reversals.
The outer bands function as potential support and resistance, helping traders determine stop-loss and take-profit zones.
Visualization elements used in this strategy:
Trend Filter Line → Changes color between green (bullish) and red (bearish).
Trend Cloud → Dynamically adjusts color based on trend strength.
Orange Markers → Appear when a trend shift is confirmed.
Trade Entry & Exit Conditions
This strategy automatically enters trades based on confirmed trend shifts detected by the Gradient Trend Filter.
1. Trade Entry Rules
Long Entry:
A bullish trend shift is detected (trend direction changes to green).
The filtered trend value crosses above zero, confirming upward momentum.
The strategy enters a long position.
Short Entry:
A bearish trend shift is detected (trend direction changes to red).
The filtered trend value crosses below zero, confirming downward momentum.
The strategy enters a short position.
2. Trade Exit Rules
Closing a Long Position:
If a bearish trend shift occurs, the strategy closes the long position.
Closing a Short Position:
If a bullish trend shift occurs, the strategy closes the short position.
The trend shift markers (orange diamonds) act as a confirmation signal, reinforcing the validity of trade entries and exits.
Customization Options
This strategy allows traders to adjust key parameters for flexibility in different market conditions:
Trade Direction: Choose between Long Only, Short Only, or Long & Short .
Trend Length: Modify the length of the smoothing function to adapt to different timeframes.
Line Width & Colors: Customize the visual appearance of trend lines and cloud colors.
Performance Table: Enable or disable the equity performance table that tracks historical trade results.
Performance Tracking & Reporting
A built-in performance table is included to monitor monthly and yearly trading performance.
The table calculates monthly percentage returns, displaying them in a structured format.
Color-coded values highlight profitable months (blue) and losing months (red).
Tracks yearly cumulative performance to assess long-term strategy effectiveness.
Traders can use this feature to evaluate historical performance trends and optimize their strategy settings accordingly.
How to Use This Strategy
Identify Trend Strength & Reversals:
Use the trend line and cloud color changes to assess trend strength and detect potential reversals.
Monitor Momentum Shifts:
Pay attention to gradient cloud color shifts, as they often appear before the trend line changes color.
This can indicate early momentum weakening or strengthening.
Act on Trend Shift Markers:
Use orange diamonds as confirmation signals for trend shifts and trade entry/exit points.
Utilize Cloud Bands as Support/Resistance:
The outer bands of the cloud serve as dynamic support and resistance, helping with stop-loss and take-profit placement.
Considerations & Limitations
Trend Lag: Since the strategy applies a smoothing function, entries may be slightly delayed compared to raw price action.
Volatile Market Conditions: In high-volatility markets, trend shifts may occur more frequently, leading to higher trade frequency.
Optimized for Trend Trading: This strategy is best suited for trending markets and may produce false signals in sideways (ranging) conditions.
Conclusion
The Gradient Trend Filter Strategy is a trend-following system based on the Gradient Trend Filter indicator by ChartPrime. It integrates noise filtering, trend visualization, and gradient-based color shifts to help traders identify strong market trends and potential reversals.
By combining trend filtering with a multi-layered cloud system, the strategy provides clear trade signals while minimizing noise. Traders can use this strategy for long-term trend trading, momentum shifts, and support/resistance-based decision-making.
This strategy is a fully automated system that allows traders to execute long, short, or both directions, with customizable settings to adapt to different market conditions.
Credit for the original concept and indicator goes to ChartPrime.
MACD Crossover Strategy MACD Crossover Strategy:
This strategy is based on the Moving Average Convergence Divergence (MACD) indicator, a popular tool used in technical analysis to identify potential trend changes and momentum in price movements. The strategy focuses on MACD crossovers within a specific "important zone" to generate trading signals.
Key Components:
1. MACD Calculation: The strategy uses customizable parameters for fast length (default 12), slow length (default 26), and signal length (default 9) to calculate the MACD line and signal line.
2. Important Zone: Defined by upper and lower thresholds (default 0.5 and -0.5), this zone helps filter out potentially less significant crossovers.
3. Entry Conditions:
- Long (Buy) Entry: When the MACD line crosses above the signal line within the important zone.
- Short (Sell) Entry: When the MACD line crosses below the signal line within the important zone.
4. Exit Conditions: The strategy closes positions on opposite crossover signals. Long positions are closed on bearish crossovers, and short positions on bullish crossovers.
5. Visualization:
- MACD line (blue) and signal line (orange) are plotted.
- The zero line, upper threshold, and lower threshold are displayed for reference.
- Buy signals are represented by green triangles at the bottom of the chart.
- Sell signals are shown as red triangles at the top of the chart.
This strategy aims to capture trend changes while filtering out potentially false signals that occur when the MACD is at extreme values. By focusing on crossovers within the important zone, the strategy attempts to identify more reliable trading opportunities.
Traders can adjust the MACD parameters and the important zone thresholds to fine-tune the strategy for different assets or timeframes. As with any trading strategy, it's crucial to thoroughly backtest and consider risk management before using it in live trading.
Dual SuperTrend w VIX Filter - Strategy [presentTrading]Hey everyone! Haven't been here for a long time. Been so busy again in the past 2 months. I recently started working on analyzing the combination of trend strategy and VIX, but didn't get outstanding results after a few tries. Sharing this tool with all of you in case you have better insights.
█ Introduction and How it is Different
The Dual SuperTrend with VIX Filter Strategy combines traditional trend following with market volatility analysis. Unlike conventional SuperTrend strategies that focus solely on price action, this experimental system incorporates VIX (Volatility Index) as an adaptive filter to create a more context-aware trading approach. By analyzing where current volatility stands relative to historical norms, the strategy adjusts to different market environments rather than applying uniform logic across all conditions.
BTCUSD 6hr Long Short Performance
█ Strategy, How it Works: Detailed Explanation
🔶 Dual SuperTrend Core
The strategy uses two SuperTrend indicators with different sensitivity settings:
- SuperTrend 1: Length = 13, Multiplier = 3.5
- SuperTrend 2: Length = 8, Multiplier = 5.0
The SuperTrend calculation follows this process:
1. ATR = Average of max(High-Low, |High-PreviousClose|, |Low-PreviousClose|) over 'length' periods
2. UpperBand = (High+Low)/2 - (Multiplier * ATR)
3. LowerBand = (High+Low)/2 + (Multiplier * ATR)
Trend direction is determined by:
- If Close > previous LowerBand, Trend = Bullish (1)
- If Close < previous UpperBand, Trend = Bearish (-1)
- Otherwise, Trend = previous Trend
🔶 VIX Analysis Framework
The core innovation lies in the VIX analysis system:
1. Statistical Analysis:
- VIX Mean = SMA(VIX, 252)
- VIX Standard Deviation = StdDev(VIX, 252)
- VIX Z-Score = (Current VIX - VIX Mean) / VIX StdDev
2. **Volatility Bands:
- Upper Band 1 = VIX Mean + (2 * VIX StdDev)
- Upper Band 2 = VIX Mean + (3 * VIX StdDev)
- Lower Band 1 = VIX Mean - (2 * VIX StdDev)
- Lower Band 2 = VIX Mean - (3 * VIX StdDev)
3. Volatility Regimes:
- "Very Low Volatility": VIX < Lower Band 1
- "Low Volatility": Lower Band 1 ≤ VIX < Mean
- "Normal Volatility": Mean ≤ VIX < Upper Band 1
- "High Volatility": Upper Band 1 ≤ VIX < Upper Band 2
- "Extreme Volatility": VIX ≥ Upper Band 2
4. VIX Trend Detection:
- VIX EMA = EMA(VIX, 10)
- VIX Rising = VIX > VIX EMA
- VIX Falling = VIX < VIX EMA
Local performance:
🔶 Entry Logic Integration
The strategy combines trend signals with volatility filtering:
Long Entry Condition:
- Both SuperTrend 1 AND SuperTrend 2 must be bullish (trend = 1)
- AND selected VIX filter condition must be satisfied
Short Entry Condition:
- Both SuperTrend 1 AND SuperTrend 2 must be bearish (trend = -1)
- AND selected VIX filter condition must be satisfied
Available VIX filter rules include:
- "Below Mean + SD": VIX < Lower Band 1
- "Below Mean": VIX < VIX Mean
- "Above Mean": VIX > VIX Mean
- "Above Mean + SD": VIX > Upper Band 1
- "Falling VIX": VIX < VIX EMA
- "Rising VIX": VIX > VIX EMA
- "Any": No VIX filtering
█ Trade Direction
The strategy allows testing in three modes:
1. **Long Only:** Test volatility effects on uptrends only
2. **Short Only:** Examine volatility's impact on downtrends only
3. **Both (Default):** Compare how volatility affects both trend directions
This enables comparative analysis of how volatility regimes impact bullish versus bearish markets differently.
█ Usage
Use this strategy as an experimental framework:
1. Form a hypothesis about how volatility affects trend reliability
2. Configure VIX filters to test your specific hypothesis
3. Analyze performance across different volatility regimes
4. Compare results between uptrends and downtrends
5. Refine your volatility filtering approach based on results
6. Share your findings with the trading community
This framework allows you to investigate questions like:
- Are uptrends more reliable during rising or falling volatility?
- Do downtrends perform better when volatility is above or below its historical average?
- Should different volatility filters be applied to long vs. short positions?
█ Default Settings
The default settings serve as a starting point for exploration:
SuperTrend Parameters:
- SuperTrend 1 (Length=13, Multiplier=3.5): More responsive to trend changes
- SuperTrend 2 (Length=8, Multiplier=5.0): More selective filter requiring stronger trends
VIX Analysis Settings:
- Lookback Period = 252: Establishes a full market cycle for volatility context
- Standard Deviation Bands = 2 and 3 SD: Creates statistically significant regime boundaries
- VIX Trend Period = 10: Balances responsiveness with noise reduction
Default VIX Filter Selection:
- Long Entry: "Above Mean" - Tests if uptrends perform better during above-average volatility
- Short Entry: "Rising VIX" - Tests if downtrends accelerate when volatility is increasing
Feel Free to share your insight below!!!
[3Commas] Turtle StrategyTurtle Strategy
🔷 What it does: This indicator implements a modernized version of the Turtle Trading Strategy, designed for trend-following and automated trading with webhook integration. It identifies breakout opportunities using Donchian channels, providing entry and exit signals.
Channel 1: Detects short-term breakouts using the highest highs and lowest lows over a set period (default 20).
Channel 2: Acts as a confirmation filter by applying an offset to the same period, reducing false signals.
Exit Channel: Functions as a dynamic stop-loss (wait for candle close), adjusting based on market structure (default 10 periods).
Additionally, traders can enable a fixed Take Profit level, ensuring a systematic approach to profit-taking.
🔷 Who is it for:
Trend Traders: Those looking to capture long-term market moves.
Bot Users: Traders seeking to automate entries and exits with bot integration.
Rule-Based Traders: Operators who prefer a structured, systematic trading approach.
🔷 How does it work: The strategy generates buy and sell signals using a dual-channel confirmation system.
Long Entry: A buy signal is generated when the close price crosses above the previous high of Channel 1 and is confirmed by Channel 2.
Short Entry: A sell signal occurs when the close price falls below the previous low of Channel 1, with confirmation from Channel 2.
Exit Management: The Exit Channel acts as a trailing stop, dynamically adjusting to price movements. To exit the trade, wait for a full bar close.
Optional Take Profit (%): Closes trades at a predefined %.
🔷 Why it’s unique:
Modern Adaptation: Updates the classic Turtle Trading Strategy, with the possibility of using a second channel with an offset to filter the signals.
Dynamic Risk Management: Utilizes a trailing Exit Channel to help protect gains as trades move favorably.
Bot Integration: Automates trade execution through direct JSON signal communication with your DCA Bots.
🔷 Considerations Before Using the Indicator:
Market & Timeframe: Best suited for trending markets; higher timeframes (e.g., H4, D1) are recommended to minimize noise.
Sideways Markets: In choppy conditions, breakouts may lead to false signals—consider using additional filters.
Backtesting & Demo Testing: It is crucial to thoroughly backtest the strategy and run it on a demo account before risking real capital.
Parameter Adjustments: Ensure that commissions, slippage, and position sizes are set accurately to reflect real trading conditions.
🔷 STRATEGY PROPERTIES
Symbol: BINANCE:ETHUSDT (Spot).
Timeframe: 4h.
Test Period: All historical data available.
Initial Capital: 10000 USDT.
Order Size per Trade: 1% of Capital, you can use a higher value e.g. 5%, be cautious that the Max Drawdown does not exceed 10%, as it would indicate a very risky trading approach.
Commission: Binance commission 0.1%, adjust according to the exchange being used, lower numbers will generate unrealistic results. By using low values e.g. 5%, it allows us to adapt over time and check the functioning of the strategy.
Slippage: 5 ticks, for pairs with low liquidity or very large orders, this number should be increased as the order may not be filled at the desired level.
Margin for Long and Short Positions: 100%.
Indicator Settings: Default Configuration.
Period Channel 1: 20.
Period Channel 2: 20.
Period Channel 2 Offset: 20.
Period Exit: 10.
Take Profit %: Disable.
Strategy: Long & Short.
🔷 STRATEGY RESULTS
⚠️Remember, past results do not guarantee future performance.
Net Profit: +516.87 USDT (+5.17%).
Max Drawdown: -100.28 USDT (-0.95%).
Total Closed Trades: 281.
Percent Profitable: 40.21%.
Profit Factor: 1.704.
Average Trade: +1.84 USDT (+1.80%).
Average # Bars in Trades: 29.
🔷 How to Use It:
🔸 Adjust Settings:
Select your asset and timeframe suited for trend trading.
Adjust the periods for Channel 1, Channel 2, and the Exit Channel to align with the asset’s historical behavior. You can visualize these channels by going to the Style tab and enabling them.
For example, if you set Channel 2 to 40 with an offset of 40, signals will take longer to appear but will aim for a more defined trend.
Experiment with different values, a possible exit configuration is using 20 as well. Compare the results and adjust accordingly.
Enable the Take Profit (%) option if needed.
🔸Results Review:
It is important to check the Max Drawdown. This value should ideally not exceed 10% of your capital. Consider adjusting the trade size to ensure this threshold is not surpassed.
Remember to include the correct values for commission and slippage according to the symbol and exchange where you are conducting the tests. Otherwise, the results will not be realistic.
If you are satisfied with the results, you may consider automating your trades. However, it is strongly recommended to use a small amount of capital or a demo account to test proper execution before committing real funds.
🔸Create alerts to trigger the DCA Bot:
Verify Messages: Ensure the message matches the one specified by the DCA Bot.
Multi-Pair Configuration: For multi-pair setups, enable the option to add the symbol in the correct format.
Signal Settings: Enable the option to receive long or short signals (Entry | TP | SL), copy and paste the messages for the DCA Bots configured.
Alert Setup:
When creating an alert, set the condition to the indicator and choose "alert() function call only".
Enter any desired Alert Name.
Open the Notifications tab, enable Webhook URL, and paste the Webhook URL.
For more details, refer to the section: "How to use TradingView Custom Signals".
Finalize Alerts: Click Create, you're done! Alerts will now be sent automatically in the correct format.
🔷 INDICATOR SETTINGS
Period Channel 1: Period of highs and lows to trigger signals
Period Channel 2: Period of highs and lows to filter signals
Offset: Move Channel 2 to the right x bars to try to filter out the favorable signals.
Period Exit: It is the period of the Donchian channel that is used as trailing for the exits.
Strategy: Order Type direction in which trades are executed.
Take Profit %: When activated, the entered value will be used as the Take Profit in percentage from the entry price level.
Use Custom Test Period: When enabled signals only works in the selected time window. If disabled it will use all historical data available on the chart.
Test Start and End: Once the Custom Test Period is enabled, here you select the start and end date that you want to analyze.
Check Messages: Check Messages: Enable this option to review the messages that will be sent to the bot.
Entry | TP | SL: Enable this options to send Buy Entry, Take Profit (TP), and Stop Loss (SL) signals.
Deal Entry and Deal Exit: Copy and paste the message for the deal start signal and close order at Market Price of the DCA Bot. This is the message that will be sent with the alert to the Bot, you must verify that it is the same as the bot so that it can process properly.
DCA Bot Multi-Pair: You must activate it if you want to use the signals in a DCA Bot Multi-pair in the text box you must enter (using the correct format) the symbol in which you are creating the alert, you can check the format of each symbol when you create the bot.
👨🏻💻💭 We hope this tool helps enhance your trading. Your feedback is invaluable, so feel free to share any suggestions for improvements or new features you'd like to see implemented.
__
The information and publications within the 3Commas TradingView account are not meant to be and do not constitute financial, investment, trading, or other types of advice or recommendations supplied or endorsed by 3Commas and any of the parties acting on behalf of 3Commas, including its employees, contractors, ambassadors, etc.
EMA 5 Alert Candle ShortThe 5 EMA (Exponential Moving Average) Strategy is a simple yet effective trading strategy that helps traders identify short-term trends and potential entry and exit points. This strategy is widely used in intraday and swing trading, particularly in forex, stocks, and crypto markets.
Components of the 5 EMA Strategy
5 EMA: A fast-moving average that reacts quickly to price movements.
15-minute or 1-hour timeframe (commonly used, but adaptable to other timeframes).
Candlestick Patterns: To confirm entry signals.
How the 5 EMA Strategy Works
Buy (Long) Setup:
Price Above the 5 EMA: The price should be trading above the 5 EMA.
Pullback to the 5 EMA: A minor retracement or consolidation near the 5 EMA.
Bullish Candlestick Confirmation: A bullish candle (e.g., engulfing or pin bar) forms near the 5 EMA.
Entry: Enter a long trade at the close of the bullish candle.
Stop Loss: Place below the recent swing low or 5-10 pips below the 5 EMA.
Take Profit: Aim for a risk-reward ratio of at least 1:2 or trail the stop using a higher EMA (e.g., 10 or 20 EMA).
Sell (Short) Setup:
Price Below the 5 EMA: The price should be trading below the 5 EMA.
Pullback to the 5 EMA: A small retracement towards the 5 EMA.
Bearish Candlestick Confirmation: A bearish candle (e.g., engulfing or pin bar) near the 5 EMA.
Entry: Enter a short trade at the close of the bearish candle.
Stop Loss: Place above the recent swing high or 5-10 pips above the 5 EMA.
Take Profit: Aim for a 1:2 risk-reward ratio or use a trailing stop.
Additional Filters for Better Accuracy
Higher Timeframe Confirmation: Check the trend on a higher timeframe (e.g., 1-hour or 4-hour).
Volume Confirmation: Enter trades when volume is increasing.
Avoid Sideways Market: Use the strategy only when the market is trending.
Advantages of the 5 EMA Strategy
✔️ Simple and easy to use.
✔️ Works well in trending markets.
✔️ Helps traders capture short-term momentum.
Disadvantages
❌ Less effective in choppy or sideways markets.
❌ Requires discipline in following stop-loss rules.
SMA Strategy Builder: Create & Prove Profitability📄 Pine Script Strategy Description (For Publishing on TradingView)
🎯 Strategy Title:
SMA Strategy Builder: Create & Prove Profitability
✨ Description:
This tool is designed for traders who want to build, customize, and prove their own SMA-based trading strategies. The strategy tracks capital growth in real-time, providing clear evidence of profitability after each trade. Users can adjust key parameters such as SMA period, take profit levels, and initial capital, making it a flexible solution for backtesting and strategy validation.
🔍 Key Features:
✅ SMA-Based Logic:
Core trading logic revolves around the Simple Moving Average (SMA).
SMA period is fully adjustable to suit various trading styles.
🎯 Customizable Take Profit (TP):
User-defined TP percentages per position.
TP line displayed as a Step Line with Breaks for clear segmentation.
Visual 🎯TP label for quick identification of profit targets.
💵 Capital Tracking (Proof of Profitability):
Initial capital is user-defined.
Capital balance updates after each closed trade.
Shows both absolute profit/loss and percentage changes for every position.
Darker green profit labels for better readability and dark red for losses.
📈 Capital Curve (Performance Visualization):
Capital growth curve available (hidden by default, can be enabled via settings).
📏 Dynamic Label Positioning:
Label positions adjust dynamically based on the price range.
Ensures consistent visibility across low and high-priced assets.
⚡ How It Works:
Long Entry:
Triggered when the price crosses above the SMA.
TP level is calculated as a user-defined percentage above the entry price.
Short Entry:
Triggered when the price crosses below the SMA.
TP level is calculated as a user-defined percentage below the entry price.
TP Execution:
Positions close immediately once the TP level is reached (no candle close confirmation needed).
🔔 Alerts:
🟩 Long Signal Alert: When the price crosses above the SMA.
🟥 Short Signal Alert: When the price crosses below the SMA.
🎯 TP Alert: When the TP target is reached.
⚙️ Customization Options:
📅 SMA Period: Choose the moving average period that best fits your strategy.
🎯 Take Profit (%): Adjust TP percentages for flexible risk management.
💵 Initial Capital: Set the starting capital for realistic backtesting.
📈 Capital Curve Toggle: Enable or disable the capital curve to track overall performance.
🌟 Why Use This Tool?
🔧 Flexible Strategy Creation: Adjust core parameters and create tailored SMA-based strategies.
📈 Performance Proof: Capital tracking acts as real proof of profitability after each trade.
🎯 Immediate TP Execution: No waiting for candle closures; profits lock in as soon as targets are hit.
💹 Comprehensive Performance Insights: Percentage-based and absolute capital tracking with dynamic visualization.
🏦 Clean Visual Indicators: Strategy insights made clear with dynamic labeling and adjustable visuals.
⚠️ Disclaimer:
This script is provided for educational and informational purposes only. Trading financial instruments carries risk, and past performance does not guarantee future results. Always perform your own due diligence before making any trading decisions.
Indicator BMS V5 [Traderhood]Introducing BMS (Base Market Strategy)
Overview
Base Market Strategy (BMS) is a trend-following and oscillator indicator designed to detect market trends with high accuracy while providing clear entry signals. BMS utilizes four Exponential Moving Averages (EMA) to filter trends across multiple timeframes and Bollinger Bands (BB) to identify overbought and oversold zones. This approach makes BMS highly suitable for scalping strategies in lower timeframes with a high win rate potential.
Key Features
📈 Multi-EMA Trend Filtering
Uses 4 EMAs to confirm the dominant trend.
Separates trend detection between lower timeframes and H1 for additional validation.
🎯 Dynamic Overbought & Oversold Detection
Sell signal occurs when the price touches the Bollinger Bands Upper.
Buy signal occurs when the price touches the Bollinger Bands Lower.
🔥 High Win Rate Scalping Strategy
Designed to capture quick price movements in trending markets.
Ideal for traders looking for fast executions with controlled risk.
🎨 Customizable Visual Enhancements
Users can adjust indicator colors to match their personal preferences.
How It Works
1️⃣ EMA-Based Trend Identification
The indicator applies 4 EMAs to determine short-term and medium-term trends.
If the price is above all EMAs → Bullish trend.
If the price is below all EMAs → Bearish trend.
2️⃣ Bollinger Bands Signal Generation
Sell Entry: When the price touches Bollinger Bands Upper, indicating an overbought area.
Buy Entry: When the price touches Bollinger Bands Lower, indicating an oversold area.
3️⃣ Scalping Execution
Entries are executed only on lower timeframes with trend confirmation from H1 EMA.
Profit targets are adjusted based on volatility, while stop loss is placed outside the Bollinger Bands.
4️⃣ Visual Customization
Indicator colors can be modified for better visibility.
Practical Applications
✅ Scalping Strategy – Uses Bollinger Bands and EMA filtering for fast trades.
✅ Trend Confirmation – Multi-timeframe EMA validation ensures precise entries.
✅ Dynamic Support & Resistance – Bollinger Bands help identify potential reversals.
✅ Noise Reduction – EMA filtering removes minor price fluctuations for clearer signals.
🛠 Settings
EMA Periods: 4 EMAs for trend filtering.
Bollinger Bands Length: 20 (default), adjustable.
Bollinger Bands Deviation: 2 (default).
Color Customization: Users can personalize indicator colors as needed.
📌 Conclusion
Base Market Strategy (BMS) is a high win-rate scalping indicator, combining trend-following EMA filtering with momentum reversal detection from Bollinger Bands. With a dynamic and adaptive approach, this indicator provides precise entry signals while reducing noise from insignificant price movements.
Key Takeaways:
✔ High Accuracy – A combination of EMA and Bollinger Bands provides clear signals.
✔ Scalping Optimization – Works best on lower timeframes with H1 validation.
✔ Visual Customization – Users can adjust the indicator colors to their preference.
✔ Simple Yet Powerful – Easy to use but highly effective in capturing market opportunities.
🔹 Disclaimer: Trading carries high risks. Always backtest and optimize settings to align with your risk tolerance before live trading.
PRC-ALMA | QuantEdgeBIntroducing PRC-ALMA by QuantEdgeB
Overview
The PRC-ALMA (Percentile Adaptive ALMA) is an advanced dynamic trend and volatility filtering indicator that leverages the Arnaud Legoux Moving Average (ALMA) combined with Percentile Rank Filtering and Median Absolute Deviation (MAD) Bands. It is designed to enhance market structure clarity, detect breakout zones, and provide trade signals by dynamically adjusting its filtering based on recent price action.
____
Key Features
1. 📈 Adaptive ALMA Smoothing:
- Uses ALMA for smoothing price action while reducing lag.
- Provides a more responsive moving average than traditional EMAs and SMAs.
2. 📊 Percentile Rank-Based Thresholds:
- Determines upper and lower regions using 75th and 25th percentile ranks.
- Allows for adaptive thresholding based on historical price movements.
3. 🎯 Median Absolute Deviation (MAD) Volatility Filtering:
- Filters out noise using robust statistical deviation measures.
- MAD Bands dynamically adjust based on volatility expansion and contraction.
4. 🔄 Dynamic Trade Signals:
- Generates long signals when price exceeds the upper threshold.
- Generates short signals when price drops below the lower threshold.
5. 🎨 Customizable Color Modes & Visual Enhancements:
- Choose between multiple color schemes to match trading preferences.
- Optional candlestick coloring to indicate market sentiment shifts.
____
How It Works
1. ALMA Calculation:
- The indicator starts by computing the ALMA (Arnaud Legoux Moving Average) with a customizable length, offset, and sigma.
2. Percentile Rank Filtering:
- It then calculates the 75th and 25th percentile ranks over a selected period, determining dynamic levels for trend identification.
3. Volatility Adjustment Using Median Absolute Deviation (MAD):
- MAD is applied to filter noise and adapt the upper/lower bands based on market volatility.
- The higher the MAD multiplier, the wider the bands, allowing more price fluctuations before a signal triggers.
4. Entry & Exit Conditions:
- Long Entry: When price crosses above the upper percentile band + MAD filter.
- Short Entry: When price crosses below the lower percentile band - MAD filter.
5. Visual Enhancements:
- Dynamic band plotting with shading between percentile ranks.
- Candlestick coloring to visually indicate long/short sentiment shifts.
____
Practical Applications
✅ Trend Following & Momentum Trading – Uses ALMA for trend smoothing and percentile-based breakouts.
✅ Mean Reversion Strategies – Adaptive MAD filtering ensures only significant deviations trigger signals.
✅ Multi-Timeframe Trading – Works on intraday, daily, and weekly timeframes based on user customization.
✅ Noise Reduction – Eliminates minor fluctuations while capturing meaningful market moves.
____
🛠 Settings
-ALMA Length: 24 – Defines the smoothing period for the Arnaud Legoux Moving Average.
-ALMA Offset: 0.7 – Adjusts the shift factor, controlling responsiveness.
-ALMA Sigma: 4 – Determines the smoothing strength, balancing trend-following and noise reduction.
-Percentile Length: 21 – Lookback period for calculating percentile rank levels.
-Median Period: 21 – The period used for the Median Absolute Deviation (MAD) filter.
-Median Multiplier: 1.8 – Adjusts the sensitivity of the MAD filter, impacting how signals are generated.
-Color Mode: Strategy – Various visual themes available for better chart readability.
-Signal Label: Off - If turned off the indicator produced a Long or Cash signal when the trend changes.
📌 Conclusion
The PRC-ALMA | QuantEdgeB is an advanced valuation and signal generation tool that dynamically adjusts based on market conditions. By combining ALMA for trend smoothing, percentile rank thresholds, and MAD-based volatility filtering, it provides traders with a versatile indicator for momentum, breakout, and mean reversion strategies.
Key Takeaways:
✔ Smooth & Adaptive – ALMA ensures minimal lag while maintaining trend responsiveness.
✔ Dynamic Overbought/Oversold Zones – Adjusts to real-time market conditions using percentile-based bands.
✔ Volatility-Aware Filtering – Uses MAD to eliminate market noise, making signals more reliable.
✔ Customizable & Multi-Timeframe Ready – Works on various asset classes and timeframes with adjustable settings.
🔹 Disclaimer: Past performance is not indicative of future results. No trading strategy can guarantee success in financial markets.
🔹 Strategic Advice: Always backtest, optimize, and align parameters with your trading objectives and risk tolerance before live trading.
Iron Bot Statistical Trend Filter📌 Iron Bot Statistical Trend Filter
📌 Overview
Iron Bot Statistical Trend Filter is an advanced trend filtering strategy that combines statistical methods with technical analysis.
By leveraging Z-score and Fibonacci levels, this strategy quantitatively analyzes market trends to provide high-precision entry signals.
Additionally, it includes an optional EMA filter to enhance trend reliability.
Risk management is reinforced with Stop Loss (SL) and four Take Profit (TP) levels, ensuring a balanced approach to risk and reward.
📌 Key Features
🔹 1. Statistical Trend Filtering with Z-Score
This strategy calculates the Z-score to measure how much the price deviates from its historical mean.
Positive Z-score: Indicates a statistically high price, suggesting a strong uptrend.
Negative Z-score: Indicates a statistically low price, signaling a potential downtrend.
Z-score near zero: Suggests a ranging market with no strong trend.
By using the Z-score as a filter, market noise is reduced, leading to more reliable entry signals.
🔹 2. Fibonacci Levels for Trend Reversal Detection
The strategy integrates Fibonacci retracement levels to identify potential reversal points in the market.
High Trend Level (Fibo 23.6%): When the price surpasses this level, an uptrend is likely.
Low Trend Level (Fibo 78.6%): When the price falls below this level, a downtrend is expected.
Trend Line (Fibo 50%): Acts as a midpoint, helping to assess market balance.
This allows traders to visually confirm trend strength and turning points, improving entry accuracy.
🔹 3. EMA Filter for Trend Confirmation (Optional)
The strategy includes an optional 200 EMA (Exponential Moving Average) filter for trend validation.
Price above 200 EMA: Indicates a bullish trend (long entries preferred).
Price below 200 EMA: Indicates a bearish trend (short entries preferred).
Enabling this filter reduces false signals and improves trend-following accuracy.
🔹 4. Multi-Level Take Profit (TP) and Stop Loss (SL) Management
To ensure effective risk management, the strategy includes four Take Profit levels and a Stop Loss:
Stop Loss (SL): Automatically closes trades when the price moves against the position by a certain percentage.
TP1 (+0.75%): First profit-taking level.
TP2 (+1.1%): A higher probability profit target.
TP3 (+1.5%): Aiming for a stronger trend move.
TP4 (+2.0%): Maximum profit target.
This system secures profits at different stages and optimizes risk-reward balance.
🔹 5. Automated Long & Short Trading Logic
The strategy is built using Pine Script®’s strategy.entry() and strategy.exit(), allowing fully automated trading.
Long Entry:
Price is above the trend line & high trend level.
Z-score is positive (indicating an uptrend).
(Optional) Price is also above the EMA for stronger confirmation.
Short Entry:
Price is below the trend line & low trend level.
Z-score is negative (indicating a downtrend).
(Optional) Price is also below the EMA for stronger confirmation.
This logic helps filter out unnecessary trades and focus only on high-probability entries.
📌 Trading Parameters
This strategy is designed for flexible capital management and risk control.
💰 Account Size: $5000
📉 Commissions and Slippage: Assumes 94 pips commission per trade and 1 pip slippage.
⚖️ Risk per Trade: Adjustable, with a default setting of 1% of equity.
These parameters help preserve capital while optimizing the risk-reward balance.
📌 Visual Aids for Clarity
To enhance usability, the strategy includes clear visual elements for easy market analysis.
✅ Trend Line (Blue): Indicates market midpoint and helps with entry decisions.
✅ Fibonacci Levels (Yellow): Highlights high and low trend levels.
✅ EMA Line (Green, Optional): Confirms long-term trend direction.
✅ Entry Signals (Green for Long, Red for Short): Clearly marked buy and sell signals.
These features allow traders to quickly interpret market conditions, even without advanced technical analysis skills.
📌 Originality & Enhancements
This strategy is developed based on the IronXtreme and BigBeluga indicators,
combining a unique Z-score statistical method with Fibonacci trend analysis.
Compared to conventional trend-following strategies, it leverages statistical techniques
to provide higher-precision entry signals, reducing false trades and improving overall reliability.
📌 Summary
Iron Bot Statistical Trend Filter is a statistically-driven trend strategy that utilizes Z-score and Fibonacci levels.
High-precision trend analysis
Enhanced accuracy with an optional EMA filter
Optimized risk management with multiple TP & SL levels
Visually intuitive chart design
Fully customizable parameters & leverage support
This strategy reduces false signals and helps traders ride the trend with confidence.
Try it out and take your trading to the next level! 🚀
Pure Price Action Breakout with 1:5 RR
Description of the Price Action Trading Script (Pine Script v6)
Overview
This script is a pure price action-based breakout strategy designed for TradingView. It identifies key breakout levels and executes long and short trades based on market structure. The strategy ensures a minimum risk-to-reward ratio (RR) of 1:5, aiming for high profitability with well-defined stop-loss and take-profit levels.
How the Script Works
1️⃣ Breakout Identification
The script uses a lookback period to find the highest high and lowest low over the last n bars.
A bullish breakout occurs when the price closes above the previous highest high.
A bearish breakout happens when the price closes below the previous lowest low.
2️⃣ Entry & Exit Strategy
Long Entry: If a bullish breakout is detected, the script enters a long position.
Short Entry: If a bearish breakout is detected, the script enters a short position.
The stop-loss is placed at the recent swing low (for long trades) or recent swing high (for short trades).
The target price is calculated based on a risk-to-reward ratio of 1:5, ensuring profitable trades.
3️⃣ Risk Management
The stop-loss prevents excessive losses by exiting trades when the market moves unfavorably.
The strategy ensures that each trade has a reward potential at least 5 times the risk.
Positions are executed based on price action only, without indicators like moving averages or RSI.
4️⃣ Visual Representation
The script plots breakout levels to help traders visualize potential trade setups.
Entry points, stop-loss, and take-profit levels are labeled on the chart for easy tracking.
Key Features & Benefits
✔ Pure Price Action – No lagging indicators, only real-time price movements.
✔ High Risk-to-Reward Ratio (1:5) – Ensures high-profit potential trades.
✔ Real-time Entry & Exit Signals – Provides accurate trade setups.
✔ Dynamic Stop-loss Calculation – Adjusts based on recent market structure.
✔ Customizable Parameters – Lookback periods and risk ratios can be modified.
Enhanced Bollinger Bands Strategy with SL/TP// Title: Enhanced Bollinger Bands Strategy with SL/TP
// Description:
// This strategy is based on the classic Bollinger Bands indicator and incorporates Stop Loss (SL) and Take Profit (TP) levels for automated trading. It identifies potential long and short entry points based on price crossing the lower and upper Bollinger Bands, respectively. The strategy allows users to customize several parameters to suit different market conditions and risk tolerances.
// Key Features:
// * **Bollinger Bands:** Uses Simple Moving Average (SMA) as the basis and calculates upper and lower bands based on a user-defined standard deviation multiplier.
// * **Customizable Parameters:** Offers extensive customization, including SMA length, standard deviation multiplier, Stop Loss (SL) in pips, and Take Profit (TP) in pips.
// * **Long/Short Position Control:** Allows users to independently enable or disable long and short positions.
// * **Stop Loss and Take Profit:** Implements Stop Loss and Take Profit levels based on pip values to manage risk and secure profits. Entry prices are set to the band levels on signals.
// * **Visualizations:** Provides options to display Bollinger Bands and entry signals on the chart for easy analysis.
// Strategy Logic:
// 1. **Bollinger Bands Calculation:** The strategy calculates the Bollinger Bands using the specified SMA length and standard deviation multiplier.
// 2. **Entry Conditions:**
// * **Long Entry:** Enters a long position when the closing price crosses above the lower Bollinger Band and the `Enable Long Positions` setting is enabled.
// * **Short Entry:** Enters a short position when the closing price crosses below the upper Bollinger Band and the `Enable Short Positions` setting is enabled.
// 3. **Exit Conditions:**
// * **Stop Loss:** Exits the position if the price reaches the Stop Loss level, calculated based on the input `Stop Loss (Pips)`.
// * **Take Profit:** Exits the position if the price reaches the Take Profit level, calculated based on the input `Take Profit (Pips)`.
// Input Parameters:
// * **SMA Length (length):** The length of the Simple Moving Average used to calculate the Bollinger Bands (default: 20).
// * **Standard Deviation Multiplier (mult):** The multiplier applied to the standard deviation to determine the width of the Bollinger Bands (default: 2.0).
// * **Enable Long Positions (enableLong):** A boolean value to enable or disable long positions (default: true).
// * **Enable Short Positions (enableShort):** A boolean value to enable or disable short positions (default: true).
// * **Pip Value (pipValue):** The value of a pip for the traded instrument. This is crucial for accurate Stop Loss and Take Profit calculations (default: 0.0001 for most currency pairs). **Important: Adjust this value to match the specific instrument you are trading.**
// * **Stop Loss (Pips) (slPips):** The Stop Loss level in pips (default: 10).
// * **Take Profit (Pips) (tpPips):** The Take Profit level in pips (default: 20).
// * **Show Bollinger Bands (showBands):** A boolean value to show or hide the Bollinger Bands on the chart (default: true).
// * **Show Entry Signals (showSignals):** A boolean value to show or hide entry signals on the chart (default: true).
// How to Use:
// 1. Add the strategy to your TradingView chart.
// 2. Adjust the input parameters to optimize the strategy for your chosen instrument and timeframe. Pay close attention to the `Pip Value`.
// 3. Backtest the strategy over different periods to evaluate its performance.
// 4. Use the `Enable Long Positions` and `Enable Short Positions` settings to customize the strategy for specific market conditions (e.g., only long positions in an uptrend).
// Important Notes and Disclaimers:
// * **Backtesting Results:** Past performance is not indicative of future results. Backtesting results can be affected by various factors, including market volatility, slippage, and transaction costs.
// * **Risk Management:** This strategy is provided for informational and educational purposes only and should not be considered financial advice. Always use proper risk management techniques when trading. Adjust Stop Loss and Take Profit levels according to your risk tolerance.
// * **Slippage:** The strategy takes into account slippage by specifying a slippage parameter on the `strategy` declaration. However, real-world slippage may vary.
// * **Market Conditions:** The performance of this strategy can vary significantly depending on market conditions. It may perform well in trending markets but poorly in ranging or choppy markets.
// * **Pip Value Accuracy:** **Ensure the `Pip Value` is correctly set for the specific instrument you are trading. Incorrect pip value will result in incorrect stop loss and take profit placement.** This is critical.
// * **Broker Compatibility:** The strategy's performance may vary depending on your broker's execution policies and fees.
// * **Disclaimer:** I am not a financial advisor, and this script is not financial advice. Use this strategy at your own risk. I am not responsible for any losses incurred while using this strategy.
Bollinger Bounce Reversal Strategy – Visual EditionOverview:
The Bollinger Bounce Reversal Strategy – Visual Edition is designed to capture potential reversal moves at price extremes—often termed “bounce points”—by using a combination of technical indicators. The strategy integrates Bollinger Bands, MACD, and volume analysis, and it provides rich on‑chart visual cues to help traders understand its signals and conditions. Additionally, the strategy enforces a maximum of 5 trades per day and uses fixed risk management parameters. This publication is intended for educational purposes and offers a systematic, transparent approach that you can further adjust to fit your market or risk profile.
How It Works:
Bollinger Bands:
A 20‑period simple moving average (SMA) and a user‑defined standard deviation multiplier (default 2.0) are used to calculate the Bollinger Bands.
When the price reaches or crosses these bands (i.e. falls below the lower band or rises above the upper band), it suggests that the price is in an extreme, potentially oversold or overbought, state.
MACD Filter:
The MACD (calculated with standard lengths, e.g. 12, 26, 9) provides momentum information.
For a bullish (long) signal, the MACD line should be above its signal line; for a bearish (short) signal, the MACD line should be below.
Volume Confirmation:
The strategy uses a 20‑period volume moving average to determine if current volume is strong enough to validate a signal.
A signal is confirmed only if the current volume is at or above a specified multiple (by default, 1.0×) of this moving average, ensuring that the move is supported by increased market participation.
Visual Cues:
Bollinger Bands and Fill: The basis (SMA), upper, and lower Bollinger Bands are plotted, and the area between the upper and lower bands is filled with a semi‑transparent color.
Signal Markers: When a long or short signal is generated, corresponding markers (labels) appear on the chart.
Background Coloring: The chart’s background changes color (green for long signals and red for short signals) on the bars where signals occur.
Information Table: An on‑chart table displays key indicator values (MACD, signal line, volume, average volume) and the number of trades executed that day.
Entry Conditions:
Long Entry:
A long trade is triggered when the previous bar’s close is below the lower Bollinger Band and the current bar’s close crosses above it, combined with a bullish MACD condition and strong volume.
Short Entry:
A short trade is triggered when the previous bar’s close is above the upper Bollinger Band and the current bar’s close crosses below it, with a bearish MACD condition and high volume.
Risk Management:
Daily Trade Limit: The strategy restricts trading to no more than 5 trades per day.
Stop-Loss and Take-Profit:
For each position, a stop loss is set at a fixed percentage away from the entry price (typically 2%), and a take profit is set to target a 1:2 risk-reward ratio (typically 4% from the entry price).
Backtesting Setup:
Initial Capital: $10,000
Commission: 0.1% per trade
Slippage: 1 tick per bar
These realistic parameters help ensure that backtesting results reflect the conditions of an average trader.
Disclaimer:
Past performance is not indicative of future results. This strategy is experimental and provided solely for educational purposes. It is essential to backtest extensively and paper trade before any live deployment. All risk management practices are advisory, and you should adjust parameters to suit your own trading style and risk tolerance.
Conclusion:
By combining Bollinger Bands, MACD, and volume analysis, the Bollinger Bounce Reversal Strategy – Visual Edition provides a clear, systematic method to identify potential reversal opportunities at price extremes. The added visual cues help traders quickly interpret signals and assess market conditions, while strict risk management and a daily trade cap help keep trading disciplined. Adjust and refine the settings as needed to better suit your specific market and risk profile.
EMA Crossover Backtest [BarScripts]This indicator lets you backtest an EMA crossover strategy with built-in risk management and trade tracking. It simulates long and short trades based on EMA crossovers, allowing you to fine-tune entry conditions, stop-loss placement, and reward/risk settings.
🔹 How It Works:
Long Entry: Fast EMA crosses above Slow EMA, and price closes above Fast EMA.
Short Entry: Fast EMA crosses below Slow EMA, and price closes below Fast EMA.
Stop Loss: Set based on previous bars or a fixed amount.
Take Profit: Adjustable reward/risk ratio.
Higher Timeframe Confluence: Confirms trades based on a larger timeframe.
Trade Hours Filter: Limits trades to specific time windows.
🔹 Key Features:
✅ Shows Entry & Exit Points with visual trade lines.
✅ Customizable EMA Lengths to fit any strategy.
✅ P&L Tracking & Statistics to measure performance.
✅ Position Sizing Options: Fixed position, fixed risk, or percentage of balance.
✅ Commissions Tracking (based on total trades, not contracts).
Use this tool to fine-tune your EMA crossover strategy and see how it performs over time! 🚀
💬 Let me know your feedback—suggest improvements, report issues, or request new features!
Volatility Momentum Breakout StrategyDescription:
Overview:
The Volatility Momentum Breakout Strategy is designed to capture significant price moves by combining a volatility breakout approach with trend and momentum filters. This strategy dynamically calculates breakout levels based on market volatility and uses these levels along with trend and momentum conditions to identify trade opportunities.
How It Works:
1. Volatility Breakout:
• Methodology:
The strategy computes the highest high and lowest low over a defined lookback period (excluding the current bar to avoid look-ahead bias). A multiple of the Average True Range (ATR) is then added to (or subtracted from) these levels to form dynamic breakout thresholds.
• Purpose:
This method helps capture significant price movements (breakouts) while ensuring that only past data is used, thereby maintaining realistic signal generation.
2. Trend Filtering:
• Methodology:
A short-term Exponential Moving Average (EMA) is applied to determine the prevailing trend.
• Purpose:
Long trades are considered only when the current price is above the EMA, indicating an uptrend, while short trades are taken only when the price is below the EMA, indicating a downtrend.
3. Momentum Confirmation:
• Methodology:
The Relative Strength Index (RSI) is used to gauge market momentum.
• Purpose:
For long entries, the RSI must be above a mid-level (e.g., above 50) to confirm upward momentum, and for short entries, it must be below a similar threshold. This helps filter out signals during overextended conditions.
Entry Conditions:
• Long Entry:
A long position is triggered when the current closing price exceeds the calculated long breakout level, the price is above the short-term EMA, and the RSI confirms momentum (e.g., above 50).
• Short Entry:
A short position is triggered when the closing price falls below the calculated short breakout level, the price is below the EMA, and the RSI confirms momentum (e.g., below 50).
Risk Management:
• Position Sizing:
Trades are sized to risk a fixed percentage of account equity (set here to 5% per trade in the code, with each trade’s stop loss defined so that risk is limited to approximately 2% of the entry price).
• Stop Loss & Take Profit:
A stop loss is placed a fixed ATR multiple away from the entry price, and a take profit target is set to achieve a 1:2 risk-reward ratio.
• Realistic Backtesting:
The strategy is backtested using an initial capital of $10,000, with a commission of 0.1% per trade and slippage of 1 tick per bar—parameters chosen to reflect conditions faced by the average trader.
Important Disclaimers:
• No Look-Ahead Bias:
All breakout levels are calculated using only past data (excluding the current bar) to ensure that the strategy does not “peek” into future data.
• Educational Purpose:
This strategy is experimental and provided solely for educational purposes. Past performance is not indicative of future results.
• User Responsibility:
Traders should thoroughly backtest and paper trade the strategy under various market conditions and adjust parameters to fit their own risk tolerance and trading style before live deployment.
Conclusion:
By integrating volatility-based breakout signals with trend and momentum filters, the Volatility Momentum Breakout Strategy offers a unique method to capture significant price moves in a disciplined manner. This publication provides a transparent explanation of the strategy’s components and realistic backtesting parameters, making it a useful tool for educational purposes and further customization by the TradingView community.
Advanced Multi-Timeframe Trading System (Risk Managed)Description:
This strategy is an original approach that combines two main analytical components to identify potential trade opportunities while simulating realistic trading conditions:
1. Market Trend Analysis via an Approximate Hurst Exponent
• What It Does:
The strategy computes a rough measure of market trending using an approximate Hurst exponent. A value above 0.5 suggests persistent, trending behavior, while a value below 0.5 indicates a tendency toward mean-reversion.
• How It’s Used:
The Hurst exponent is calculated on both the chart’s current timeframe and a higher timeframe (default: Daily) to capture both local and broader market dynamics.
2. Fibonacci Retracement Levels
• What It Does:
Using daily high and low data from a selected timeframe (default: Daily), the script computes key Fibonacci retracement levels.
• How It’s Used:
• The 61.8% level (Golden Ratio) serves as a key threshold:
• A long entry is signaled when the price crosses above this level if the daily Hurst exponent confirms a trending market.
• The 38.2% level is used to identify short-entry opportunities when the price crosses below it and the daily Hurst indicates non-trending conditions.
Signal Logic:
• Long Entry:
When the price crosses above the 61.8% Fibonacci level (Golden Ratio) and the daily Hurst exponent is greater than 0.5, suggesting a trending market.
• Short Entry:
When the price crosses below the 38.2% Fibonacci level and the daily Hurst exponent is less than 0.5, indicating a less trending or potentially reversing market.
Risk Management & Trade Execution:
• Stop-Loss:
Each trade is risk-managed with a stop-loss set at 2% below (for longs) or above (for shorts) the entry price. This ensures that no single trade risks more than a small, sustainable portion of the account.
• Take Profit:
A take profit order targets a risk-reward ratio of 1:2 (i.e., the target profit is twice the amount risked).
• Position Sizing:
Trades are executed with a fixed position size equal to 10% of account equity.
• Trade Frequency Limits:
• Daily Limit: A maximum of 5 trades per day
• Overall Limit: No more than 510 trades during the backtesting period (e.g., since 2019)
These limits are imposed to simulate realistic trading frequency and to avoid overtrading in backtest results.
Backtesting Parameters:
• Initial Capital: $10,000
• Commission: 0.1% per trade
• Slippage: 1 tick per bar
These settings aim to reflect the conditions faced by the average trader and help ensure that the backtesting results are realistic and not misleading.
Chart Overlays & Visual Aids:
• Fibonacci Levels:
The key Fibonacci retracement levels are plotted on the chart, and the zone between the 61.8% and 38.2% levels is highlighted to show a key retracement area.
• Market Trend Background:
The chart background is tinted green when the daily Hurst exponent indicates a trending market (value > 0.5) and red otherwise.
• Information Table:
An on-chart table displays key parameters such as the current Hurst exponent, daily Hurst value, the number of trades executed today, and the global trade count.
Disclaimer:
Past performance is not indicative of future results. This strategy is experimental and provided solely for educational purposes. It is essential that you backtest and paper trade using your own settings before considering any live deployment. The Hurst exponent calculation is an approximation and should be interpreted as a rough gauge of market behavior. Adjust the parameters and risk management settings according to your personal risk tolerance and market conditions.
Additional Notes:
• Originality & Usefulness:
This script is an original mashup that combines trend analysis with Fibonacci retracement methods. The description above explains how these components work together to provide trading signals.
• Realistic Results:
The strategy uses realistic account sizes, commission rates, slippage, and risk management rules to generate backtesting results that are representative of real-world trading.
• Educational Purpose:
This script is intended to support the TradingView community by offering insights into combining multiple analysis techniques in one strategy. It is not a “get-rich-quick” system but rather an educational tool to help traders understand risk management and trade signal logic.
By using this script, you acknowledge that trading involves risk and that you are responsible for testing and adjusting the strategy to fit your own trading environment. This publication is fully open source, and any modifications should include proper attribution if significant portions of the code are reused.
Prev Day High EMA Crossover with 7-Day SMA Trailing StopPrev Day High EMA Crossover with 7-Day SMA Trailing Stop
Overview
This indicator is designed for traders who seek high-probability breakout trades using a combination of Exponential Moving Averages (EMAs), the previous day's high, and a 7-day Simple Moving Average (SMA) trailing stop. It helps identify bullish and bearish crossover signals while ensuring confirmation with price action above or below key levels.
How It Works
1. Entry Signals:
✅ Bullish Entry:
The 9 EMA crosses above the 15 EMA (bullish momentum).
The price is above the previous day’s high (confirming a breakout).
The candle closes above the open (bullish confirmation).
✅ Bearish Entry:
The 9 EMA crosses below the 15 EMA (bearish momentum).
The price is below the previous day’s high (confirming a failure to break higher).
The candle closes below the open (bearish confirmation).
2. Exit Strategy (Trailing Stop):
📌 Long Exit: If in a long trade, exit when the price closes below the 7-day SMA.
📌 Short Exit: If in a short trade, exit when the price closes above the 7-day SMA.
High-Probability IndicatorExplanation of the Code
Trend Filter (EMA):
A 50-period Exponential Moving Average (EMA) is used to determine the overall trend.
trendUp is true when the price is above the EMA.
trendDown is true when the price is below the EMA.
Momentum Filter (RSI):
A 14-period RSI is used to identify overbought and oversold conditions.
oversold is true when RSI ≤ 30.
overbought is true when RSI ≥ 70.
Volatility Filter (ATR):
A 14-period Average True Range (ATR) is used to measure volatility.
ATR is multiplied by a user-defined multiplier (default: 2.0) to set a volatility threshold.
Ensures trades are only taken during periods of sufficient volatility.
Entry Conditions:
Long Entry: Price is above the EMA (uptrend), RSI is oversold, and the candle range exceeds the ATR threshold.
Short Entry: Price is below the EMA (downtrend), RSI is overbought, and the candle range exceeds the ATR threshold.
Exit Conditions:
Take Profit: A fixed percentage above/below the entry price.
Stop Loss: A fixed percentage below/above the entry price.
Visualization:
The EMA is plotted on the chart.
Background colors highlight uptrends and downtrends.
Buy and sell signals are displayed as labels on the chart.
Alerts:
Alerts are triggered for buy and sell signals.
How to Use the Indicator
Trend Filter:
Only take trades in the direction of the trend (e.g., long in an uptrend, short in a downtrend).
Momentum Filter:
Look for oversold conditions in an uptrend for long entries.
Look for overbought conditions in a downtrend for short entries.
Volatility Filter:
Ensure the candle range exceeds the ATR threshold to avoid low-volatility trades.
Risk Management:
Use the built-in take profit and stop loss levels to manage risk.
Optimization Tips
Backtesting:
Test the indicator on multiple timeframes and assets to evaluate its performance.
Adjust the input parameters (e.g., EMA length, RSI length, ATR multiplier) to optimize for specific markets.
Combination with Other Strategies:
Add additional filters, such as volume analysis or support/resistance levels, to improve accuracy.
Risk Management:
Use proper position sizing and risk-reward ratios to maximize profitability.
Disclaimer
No indicator can guarantee an 85% win ratio due to the inherent unpredictability of financial markets. This script is provided for educational purposes only. Always conduct thorough backtesting and paper trading before using any strategy in live trading.
Let me know if you need further assistance or enhancements!
