Show EMA and SMA's at the same timeYou can now add both exponential and simple moving averages at the same time. ie a 7 day Simple Moving Average and a 21 day Exponential Moving Average.
"Exponential Moving Average"に関するスクリプトを検索
Moving Average Envelopes Backtest Moving Average Envelopes are percentage-based envelopes set above and
below a moving average. The moving average, which forms the base for
this indicator, can be a simple or exponential moving average. Each
envelope is then set the same percentage above or below the moving average.
This creates parallel bands that follow price action. With a moving average
as the base, Moving Average Envelopes can be used as a trend following indicator.
However, this indicator is not limited to just trend following. The envelopes
can also be used to identify overbought and oversold levels when the trend is
relatively flat.
You can change long to short in the Input Settings
WARNING:
- For purpose educate only
- This script to change bars colors.
Moving Average Envelopes Moving Average Envelopes are percentage-based envelopes set above and
below a moving average. The moving average, which forms the base for
this indicator, can be a simple or exponential moving average. Each
envelope is then set the same percentage above or below the moving average.
This creates parallel bands that follow price action. With a moving average
as the base, Moving Average Envelopes can be used as a trend following indicator.
However, this indicator is not limited to just trend following. The envelopes
can also be used to identify overbought and oversold levels when the trend is
relatively flat.
WARNING:
- This script to change bars colors.
Moving Average Envelopes Moving Average Envelopes are percentage-based envelopes set above and
below a moving average. The moving average, which forms the base for
this indicator, can be a simple or exponential moving average. Each
envelope is then set the same percentage above or below the moving average.
This creates parallel bands that follow price action. With a moving average
as the base, Moving Average Envelopes can be used as a trend following indicator.
However, this indicator is not limited to just trend following. The envelopes
can also be used to identify overbought and oversold levels when the trend is
relatively flat.
Noro's MAs Tests v1.1Trade strategy from one moving average. To choose what sliding average it is more effective to use for this pair and this timeframe.
Types:
1 = SMA = Simple Moving Average
2 = EMA = Exponential Moving Average
3 = VWMA = Volume-Weighted Moving Average
4 = DEMA = Double Exponential Moving Average
5 = TEMA = Triple Exponential Moving Average
6 = KAMA = Kaufman's Adaptive Moving Average
7 = Price Channel
In new version 1.1:
+ "antipila"
+ longs
+ shorts
Noro's MAs TestsTrade strategy from one moving average. To choose what sliding average it is more effective to use for this pair and this timeframe.
Types:
1 = SMA = Simple Moving Average
2 = EMA = Exponential Moving Average
3 = VWMA = Volume-Weighted Moving Average
4 = DEMA = Double Exponential Moving Average
5 = TEMA = Triple Exponential Moving Average
6 = KAMA = Kaufman's Adaptive Moving Average
7 = Price Channel
Multi Movings Averages
This tool can plot a maximum of 10 movings averages that are easily adaptable and configurable.
You can also use a exponential moving average instead of the simple moving average.
hope you enjoy :)
Stochastic Momentum IndexThis is an implementation of the Stochastic Momentum Index from William Blau's his article in Stocks & Commodities .
This also allows the use of various different kinds of moving averages for the signal line. Options for this argument are:
sma (simple moving average)
ema (exponential moving average)
wma (weighted moving average)
trima (triangular moving average)
zlema (zero-lag exponential moving average)
dema (double exponential moving average)
tema (triple exponential moving average)
hma (hull moving average)
On-Balance Volume with Multiple MA TypesOn-Balance Volume with Multiple MA Types
English Description
Overview
This is the first version of the "On-Balance Volume with Multiple MA Types" indicator designed to overlay directly on the price chart, a significant evolution from its previous iterations, which functioned solely as an oscillator in a separate window. The indicator calculates On-Balance Volume (OBV) and applies various smoothing methods to provide a clear view of volume dynamics in relation to price movements. It is pinned to the price scale for seamless integration with the chart.
Interpretation Recommendations
Price Pushing the OBV Line from Below: When the price chart pushes the OBV line upward and remains below it, this indicates rising volume, suggesting strong buying pressure.
Price Above the OBV Line: When the price chart is above the OBV line, it signals falling volume, indicating weakening momentum or selling pressure.
OBV Line Crossings: When the price crosses the OBV line, it represents a balance point in volume dynamics. The price level at the current crossing can be compared to the previous crossing to assess changes in market sentiment or momentum.
Moving Average Types
The indicator offers eight smoothing options for the OBV line, each with unique characteristics:
EMA (Exponential Moving Average): A weighted average that prioritizes recent data, providing a smooth yet responsive line.
DEMA (Double Exponential Moving Average): Uses two EMAs to reduce lag, offering faster response to volume changes.
HMA (Hull Moving Average): Combines weighted moving averages to minimize lag while maintaining smoothness.
WMA (Weighted Moving Average): Assigns more weight to recent data, balancing responsiveness and noise reduction.
TMA (Triangular Moving Average): A double-smoothed simple moving average, emphasizing central data points for smoother output.
VIDYA (Variable Index Dynamic Average): Adapts smoothing based on market volatility, using a CMO (Chande Momentum Oscillator) for dynamic weighting. Controlled by the VIDYA Alpha parameter (default: 0.2, range: 0–1), which adjusts sensitivity to volatility.
FRAMA (Fractal Adaptive Moving Average): Adjusts smoothing based on fractal dimensions of the OBV data, adapting to market conditions.
JMA (Jurik Moving Average): A proprietary adaptive average designed for minimal lag and high smoothness. Controlled by two parameters:
JMA Phase (default: 50, range: -100 to 100): Adjusts the balance between responsiveness and smoothness.
JMA Power (default: 1, range: 0.1+): Controls the strength of smoothing.
Input Parameters
OBV MA Length (default: 10): The lookback period for smoothing the OBV. Higher values produce smoother results but increase lag.
OBV MA Type (default: JMA): Selects the moving average type from the eight options listed above.
Line Width (default: 2): Thickness of the OBV line on the chart.
Bullish Color (default: Blue): Color of the OBV line when rising (indicating increasing volume).
Bearish Color (default: Red): Color of the OBV line when falling (indicating decreasing volume).
JMA Phase (default: 50): Adjusts the JMA’s responsiveness (used only when JMA is selected).
JMA Power (default: 1): Adjusts the JMA’s smoothing strength (used only when JMA is selected).
VIDYA Alpha (default: 0.2): Controls the sensitivity of VIDYA to market volatility (used only when VIDYA is selected).
How to Use
Add the indicator to your TradingView chart. It will overlay directly on the price chart, aligned with the price scale.
Adjust the OBV MA Type to select your preferred smoothing method based on your trading style (e.g., JMA for low lag, TMA for smoothness).
Modify the OBV MA Length to balance responsiveness and noise reduction. Shorter periods (e.g., 5–10) are better for short-term trading, while longer periods (e.g., 20–50) suit longer-term analysis.
Use the Bullish Color and Bearish Color to visually distinguish rising and falling volume trends.
For JMA or VIDYA, fine-tune the JMA Phase, JMA Power, or VIDYA Alpha to optimize the indicator for specific market conditions.
Interpret the OBV line in relation to price:
Watch for price pushing the OBV line upward (rising volume) or moving above it (falling volume).
Note crossings of the OBV line to identify balance points and compare with prior crossings to gauge momentum shifts.
Combine with other technical tools (e.g., support/resistance levels, trendlines) for a comprehensive trading strategy.
Notes
This indicator is designed to work on any timeframe and market, but its effectiveness depends on the chosen moving average type and parameters.
Experiment with different MA types and lengths to find the best fit for your trading approach.
The indicator is licensed under the Mozilla Public License 2.0 and copyrighted by TradingStrategyCourses © 2025.
Logarithmic Moving Average (LMA) [QuantAlgo]🟢 Overview
The Logarithmic Moving Average (LMA) uses advanced logarithmic weighting to create a dynamic trend-following indicator that prioritizes recent price action while maintaining statistical significance. Unlike traditional moving averages that use linear or exponential weights, this indicator employs logarithmic decay functions to create a more sophisticated price averaging system that adapts to market volatility and momentum conditions.
The indicator displays a smoothed signal line that oscillates around zero, with positive values indicating bullish momentum and negative values indicating bearish momentum. The signal incorporates trend quality assessment, momentum confirmation, and multiple filtering mechanisms to help traders and investors identify trend continuation and reversal opportunities across different timeframes and asset classes.
🟢 How It Works
The indicator's core innovation lies in its logarithmic weighting system, where weights are calculated using the formula: w = 1.0 / math.pow(math.log(i + steepness), 2) The steepness parameter controls how aggressively recent data is prioritized over historical data, creating a dynamic weight decay that can be fine-tuned for different trading styles. This logarithmic approach provides more nuanced weight distribution compared to exponential moving averages, offering better responsiveness while maintaining stability.
The LMA calculation combines multiple sophisticated components. First, it calculates the logarithmic weighted average of closing prices. Then it measures the slope of this average over a 10-period lookback: lmaSlope = (lma - lma ) / lma * 100 The system also incorporates trend quality assessment using R-squared correlation analysis of log-transformed prices, measuring how well the price data fits a linear trend model over the specified period.
The final signal generation uses the formula: signal = lmaSlope * (0.5 + rSquared * 0.5) which combines the LMA slope with trend quality weighting. When momentum confirmation is enabled, the indicator calculates annualized log-return momentum and applies a multiplier when the momentum direction aligns with the signal direction, strengthening confirmed signals while filtering out weak or counter-trend movements.
🟢 How to Use
1. Signal Interpretation and Threshold Zones
Positive Values (Above Zero): LMA slope indicating bullish momentum with upward price trajectory relative to logarithmic baseline
Negative Values (Below Zero): LMA slope indicating bearish momentum with downward price trajectory relative to logarithmic baseline
Zero Line Crosses: Signal transitions between bullish and bearish regimes, indicating potential trend changes
Long Entry Threshold Zone: Area above positive threshold (default 0.5) indicating confirmed bullish signals suitable for long positions
Short Entry Threshold Zone: Area below negative threshold (default -0.5) indicating confirmed bearish signals suitable for short positions
Extreme Values: Signals exceeding ±1.0 represent strong momentum conditions with higher probability of continuation
2. Momentum Confirmation and Visual Analysis
Signal Color Intensity: Gradient coloring shows signal strength, with brighter colors indicating stronger momentum
Bar Coloring: Optional price bar coloring matches signal direction for quick visual trend identification
Position Labels: Real-time position classification (Bullish/Bearish/Neutral) displayed on the latest bar
Momentum Weight Factor: When short-term log-return momentum aligns with LMA signal direction, the signal receives additional weight confirmation
Trend Quality Component: R-squared values weight the signal strength, with higher correlation indicating more reliable trend conditions
3. Examples: Preconfigured Settings
Default: Universally applicable configuration balanced for medium-term investing and general trading across multiple timeframes and asset classes.
Scalping: Highly responsive setup with shorter period and higher steepness for ultra-short-term trades on 1-15 minute charts, optimized for quick momentum shifts.
Swing Trading: Extended period with moderate steepness and increased smoothing for multi-day positions, designed to filter noise while capturing larger price swings on 1-4 hour and daily charts.
Trend Following: Maximum smoothing with lower steepness for established trend identification, generating fewer but more reliable signals optimal for daily and weekly timeframes.
Mean Reversion: Shorter period with high steepness for counter-trend strategies, more sensitive to extreme moves and reversal opportunities in ranging market conditions.
Market Matrix ViewThis technical indicator is designed to provide traders with a quick and integrated view of market dynamics by combining several popular indicators into a single tool. It's not a magic bullet, but a practical aid for analyzing buying/selling pressure, trends, volume, and divergences, saving you time in the decision-making process. Built for flexibility, the indicator adapts to various trading styles (scalping, swing, or long-term) and offers customizable settings to suit your needs.
🟡 Multi-Timeframe Trends
➤ This section displays the trend direction (bullish, bearish, or neutral) across 15-minute, 1-hour, 4-hour, and Daily timeframes, providing multi-timeframe market context. Timeframes lower than the one currently selected will show "N/A."
➤It utilizes fast and slow Exponential Moving Averages (EMAs) for each timeframe:
15m: Fast EMA 42, Slow EMA 170
1h: Fast EMA 40, Slow EMA 100
4h: Fast EMA 36, Slow EMA 107
Daily: Fast EMA 20, Slow EMA 60
🟡 Smart Flow & RVOL
➤ This section displays "Buying Pressure" or "Selling Pressure" signals based on indicator confluence, alongside volume activity ("High Activity," "Normal Activity," or "Low Activity").
➤ Smart Flow combines Chaikin Money Flow (CMF) and Money Flow Index (MFI) to detect buying/selling pressure. CMF measures money flow based on price position within the high-low range, while MFI analyzes money flow considering typical price and volume. A signal is generated only when both indicators simultaneously increase/decrease beyond an adjustable threshold ("Buy/Sell Sensitivity") and volume exceeds a Simple Moving Average (SMA) scaled by the "Volume Multiplier."
➤ RVOL (Relative Volume) calculates relative volume separately for bullish and bearish candles, comparing recent volume (fast SMA) with a reference volume (slow SMA). Thresholds are adjusted based on the selected mode.
🟡 ADX & RSI
This section displays trend strength ("Strong," "Moderate," or "Weak"), its direction ("Bullish" or "Bearish"), and the RSI momentum status ("Overbought," "Oversold," "Buy/Sell Momentum," or "Neutral").
➤ ADX (Average Directional Index) measures trend strength (above 40 = "Strong," 20–40 = "Moderate," below 20 = "Weak"). Direction is determined by comparing +DI (upward movement) with -DI (downward movement). Additionally, an arrow indicates whether the trend's strength is decreasing or increasing.
➤RSI (Relative Strength Index) evaluates price momentum. Extreme levels (above 80/85 = "Overbought," below 15/20 = "Oversold") and intermediate zones (47–53 = "Neutral," above 53 = "Buy Momentum," below 47 = "Sell Momentum") are adjusted based on the selected mode.
🟡 When these signals are active for a potential trade setup, the table's background lights up green or red, respectively.
🟡 Volume Spikes
➤This feature highlights bars with significantly higher volume than the recent average, coloring them yellow on the chart to draw attention to intense market activity.
➤It uses the Z-Score method to detect volume anomalies. Current volume is compared to a 10-bar Simple Moving Average (SMA) and the standard deviation of volume over the same period. If the Z-Score exceeds a certain threshold, the bar is marked as a volume spike.
🟡 Divergences (Volume Divergence Detection)
➤ This feature marks divergences between price and technical indicators on the chart, using diamond-shaped labels (green for bullish divergences, red for bearish divergences) to signal potential trend reversals.
➤ It compares price deviations from a Simple Moving Average (SMA) with deviations of three indicators: Chaikin Money Flow (CMF), Money Flow Index (MFI), and On-Balance Volume (OBV). A bullish divergence occurs when price falls below its average, but CMF, MFI, and OBV rise above their averages, indicating hidden accumulation. A bearish divergence occurs when price rises above its average, but CMF, MFI, and OBV fall, suggesting distribution. The length of the moving averages is adjustable (default 13/10/5 bars for Scalping/Balanced/Swing), and detection thresholds are scaled by "Divergence Sensitivity" (default 1.0).
🟡 Adaptive Stop-Loss (ATR)
➤Draws dynamic stop-loss lines (red, dashed) on the chart for buy or sell signals, helping traders manage risk.Uses the Average True Range (ATR) to calculate stop-loss levels, set at low/high ± ATR × multiplier
🟡 Alerts for trend direction changes in the Info Panel:
➤ Triggers notifications when the trend shifts to Bullish (when +DI crosses above -DI) or Bearish (when +DI crosses below -DI), helping you stay informed about key market shifts.
How to use: Set alerts in Trading View for “Trend Changed to Bullish” or “Trend Changed to Bearish” with “Once Per Bar Close” for reliable signals.
🟡 Settings (Inputs)
➤ The indicator offers customizable settings to fit your trading style, but it's already optimized for Scalping (1m–15m), Balanced (16m–3h59m), and Swing (4h–Daily) modes, which automatically adjust based on the selected timeframe. The visible inputs allow you to adjust the following parameters:
Show Info Panel: Enables/disables the information panel (default: enabled).
Show Volume Spikes: Turns on/off coloring for volume spike bars (default: enabled).
Spike Sensitivity: Controls the Z-Score threshold for detecting volume spikes (default: 2.0; lower values increase signal frequency).
Show Divergence: Enables/disables the display of divergence labels (default: enabled).
Divergence Sensitivity: Adjusts the thresholds for divergence detection (default: 1.0; higher values reduce sensitivity).
Divergence Lookback Length: Sets the length of the moving averages used for divergences (default: 5, automatically adjusted to 13/10/5 for Scalping/Balanced/Swing).
RVOL Reference Period: Defines the reference period for relative volume (default: 20, automatically adjusted to 7/15/20).
RSI Length: Sets the RSI length (default: 14, automatically adjusted to 5/10/14).
Buy Sensitivity: Controls the increase threshold for Buying Pressure signals (default: 0.007; higher values reduce frequency).
Sell Sensitivity: Controls the decrease threshold for Selling Pressure signals (default: 0.007; higher values reduce frequency).
Volume Multiplier (B/S Pressure): Adjusts the volume threshold for Smart Flow signals (default: 0.6; higher values require greater volume).
🟡 This indicator is created to simplify market analysis, but I am not a professional in Pine Script or technical indicators. This indicator is not a standalone solution. For optimal results, it must be integrated into a well-defined trading strategy that includes risk management and other confirmations.
BACAP PRICE STRUCTURE 21 EMA TREND21dma-STRUCTURE
Overview
The 21dma-STRUCTURE indicator is a sophisticated overlay indicator that visualizes price action relative to a triple 21-period exponential moving average structure. Originally developed by BalarezoCapital and enhanced by PrimeTrading, this indicator provides clear visual cues for trend direction and momentum through dynamic bar coloring and EMA structure analysis.
Key Features
Triple EMA Structure
- 21 EMA High: Tracks the exponential moving average of high prices
- 21 EMA Close: Tracks the exponential moving average of closing prices
- 21 EMA Low: Tracks the exponential moving average of low prices
- Dynamic Cloud: Gray fill between high and low EMAs for visual structure reference
Smart Bar Coloring System
- Blue Bars: Price closes above all three EMAs (strong bullish momentum)
- Pink Bars: Daily high falls below the lowest EMA (strong bearish signal)
- Gray Bars: Neutral conditions or transitional phases
- Color Memory: Maintains previous color until new condition is met
Dynamic Center Line
- Trend-Following Color: Green when all EMAs are rising, red when all are falling
- Color Persistence: Maintains trend color during sideways movement
- Visual Clarity: Thicker center line for easy trend identification
Customizable Visual Elements
- Adjustable line thickness for all EMA plots
- Customizable colors for bullish and bearish conditions
- Configurable trend colors for uptrend and downtrend phases
- Optional bar color changes with toggle control
How to Use
Trend Identification
- Rising Green Center Line: All EMAs trending upward (bullish structure)
- Falling Red Center Line: All EMAs trending downward (bearish structure)
- Flat Center Line: Maintains last trend color during consolidation
Momentum Analysis
- Blue Bars: Strong bullish momentum with price above entire EMA structure
- Pink Bars: Strong bearish momentum with high below lowest EMA
- Gray Bars: Neutral or transitional momentum phases
Entry and Exit Signals
- Bullish Setup: Look for blue bars during green center line periods
- Bearish Setup: Look for pink bars during red center line periods
- Exit Consideration: Watch for color changes as potential momentum shifts
Structure Trading
- Support/Resistance: Use EMA cloud as dynamic support and resistance zones
- Breakout Confirmation: Bar color changes can confirm structure breakouts
- Trend Continuation: Color persistence suggests ongoing momentum
Settings
Visual Customization
- Change Bar Color: Toggle to enable/disable bar coloring
- Line Size: Adjust thickness of EMA lines (default: 3)
- Bullish Candle Color: Customize blue bar color
- Bearish Candle Color: Customize pink bar color
Trend Colors
- Uptrend Color: Color for rising EMA center line (default: green)
- Downtrend Color: Color for falling EMA center line (default: red)
- Cloud Color: Fill color between high and low EMAs (default: gray)
Advanced Features
Modified Bar Logic
Unlike traditional EMA systems, this indicator uses refined conditions:
- Bullish signals require close above ALL three EMAs
- Bearish signals require high below the LOWEST EMA
- Enhanced precision reduces false signals compared to single EMA systems
Trend Memory System
- Intelligent color persistence during sideways movement
- Reduces noise from minor EMA fluctuations
- Maintains trend context during consolidation periods
Performance Optimization
- Efficient calculation methods for real-time performance
- Clean visual design that doesn't clutter charts
- Compatible with all timeframes and instruments
Best Practices
Multi-Timeframe Analysis
- Use higher timeframes to identify overall trend direction
- Apply on multiple timeframes for confluence
- Combine with weekly/monthly charts for position trading
Risk Management
- Use bar color changes as early warning signals
- Consider position sizing based on EMA structure strength
- Set stops relative to EMA support/resistance levels
Combination Strategies
- Pair with volume indicators for confirmation
- Use alongside RSI or MACD for momentum confirmation
- Combine with key support/resistance levels
Market Context
- More effective in trending markets than choppy conditions
- Consider overall market environment and sector strength
- Adjust expectations during high volatility periods
Technical Specifications
- Based on 21-period exponential moving averages
- Uses Pine Script v6 for optimal performance
- Overlay indicator that works with any chart type
- Maximum 500 lines for clean performance
Ideal Applications
- Swing trading on daily charts
- Position trading on weekly charts
- Intraday momentum trading (adjust timeframe accordingly)
- Trend following strategies
- Structure-based trading approaches
Disclaimer
This indicator is for educational and informational purposes only. It should not be used as the sole basis for trading decisions. Always combine with other forms of analysis, proper risk management, and consider your individual trading plan and risk tolerance.
Compatible with Pine Script v6 | Works on all timeframes | Optimized for trending markets
Multi-Indicator Trend-Following Strategy v6Multi-Indicator Trend-Following Strategy v6
This strategy uses a combination of technical indicators to identify potential trend-following trade entries and exits. It is intended for educational and research purposes.
How it works:
Moving Averages (EMA): Entry signals are generated on crossovers between a fast and slow exponential moving average.
RSI Filter: Confirms momentum with a threshold above/below 50 for long/short entries.
Volume Confirmation: Requires volume to exceed a moving average multiplied by a user-defined factor.
ATR-Based Risk Management: Stop loss and take profit levels are calculated using the Average True Range (ATR), allowing for dynamic risk control based on market volatility.
Customizable Inputs:
Fast/Slow MA lengths
RSI length and levels
MACD settings (used in calculation, not directly in signal)
Volume MA and multiplier
ATR period and multipliers for stop loss and take profit
Notes:
This strategy does not guarantee future results.
It is provided for analysis and backtesting only.
Alerts are available for buy/sell conditions.
Feel free to adjust parameters to explore different market conditions and asset classes.
EMA Pullback Speed Strategy 📌 **Overview**
The **EMA Pullback Speed Strategy** is a trend-following approach that combines **price momentum** and **Exponential Moving Averages (EMA)**.
It aims to identify high-probability entry points during brief pullbacks within ongoing uptrends or downtrends.
The strategy evaluates **speed of price movement**, **relative position to dynamic EMA**, and **candlestick patterns** to determine ideal timing for entries.
One of the key concepts is checking whether the price has **“not pulled back too much”**, helping focus only on situations where the trend is likely to continue.
⚠️ This strategy is designed for educational and research purposes only. It does not guarantee future profits.
🧭 **Purpose**
This strategy addresses the common issue of **"jumping in too late during trends and taking unnecessary losses."**
By waiting for a healthy pullback and confirming signs of **trend resumption**, traders can enter with greater confidence and reduce false entries.
🎯 **Strategy Objectives**
* Enter in the direction of the prevailing trend to increase win rate
* Filter out false signals using pullback depth, speed, and candlestick confirmations
* Predefine Take-Profit (TP) and Stop-Loss (SL) levels for safer, rule-based trading
✨ **Key Features**
* **Dynamic EMA**: Reacts faster when price moves quickly, slower when market is calm – adapting to current momentum
* **Pullback Filter**: Avoids trades when price pulls back too far (e.g., more than 5%), indicating a trend may be weakening
* **Speed Check**: Measures how strongly the price returns to the trend using candlestick body speed (open-to-close range in ticks)
📊 **Trading Rules**
**■ Long Entry Conditions:**
* Current price is above the dynamic EMA (indicating uptrend)
* Price has pulled back toward the EMA (a "buy the dip" situation)
* Pullback depth is within the threshold (not excessive)
* Candlesticks show consecutive bullish closes and break the previous high
* Price speed is strong (positive movement with momentum)
**■ Short Entry Conditions:**
* Current price is below the dynamic EMA (indicating downtrend)
* Price has pulled back up toward the EMA (a "sell the rally" setup)
* Pullback is within range (not too deep)
* Candlesticks show consecutive bearish closes and break the previous low
* Price speed is negative (downward momentum confirmed)
**■ Exit Conditions (TP/SL):**
* **Take-Profit (TP):** Fixed 1.5% target above/below entry price
* **Stop-Loss (SL):** Based on recent price volatility, calculated using ATR × 4
💰 **Risk Management Parameters**
* Symbol & Timeframe: BTCUSD on 1-hour chart (H1)
* Test Capital: \$3000 (simulated account)
* Commission: 0.02%
* Slippage: 2 ticks (minimal execution lag)
* Max risk per trade: 5% of account balance
* Backtest Period: Aug 30, 2023 – May 9, 2025
* Profit Factor (PF): 1.965 (Net profit ÷ Net loss, including spreads & fees)
⚙️ **Trading Parameters & Indicator Settings**
* Maximum EMA Length: 50
* Accelerator Multiplier: 3.0
* Pullback Threshold: 5.0%
* ATR Period: 14
* ATR Multiplier (SL distance): 4.0
* Fixed TP: 1.5%
* Short-term EMA: 21
* Long-term EMA: 50
* Long Speed Threshold: ≥ 1000.0 (ticks)
* Short Speed Threshold: ≤ -1000.0 (ticks)
⚠️Adjustments are based on BTCUSD.
⚠️Forex and other currency pairs require separate adjustments.
🔧 **Strategy Improvements & Uniqueness**
Unlike basic moving average crossovers or RSI triggers, this strategy emphasizes **"momentum-supported pullbacks"**.
By combining dynamic EMA, speed checks, and candlestick signals, it captures trades **as if surfing the wave of a trend.**
Its built-in filters help **avoid overextended pullbacks**, which often signal the trend is ending – making it more robust than traditional trend-following systems.
✅ **Summary**
The **EMA Pullback Speed Strategy** is easy to understand, rule-based, and highly reproducible – ideal for both beginners and intermediate traders.
Because it shows **clear visual entry/exit points** on the chart, it’s also a great tool for practicing discretionary trading decisions.
⚠️ Past performance is not a guarantee of future results.
Always respect your Stop-Loss levels and manage your position size according to your risk tolerance.
Quadruple EMA (QEMA)The Quadruple Exponential Moving Average (QEMA) is an advanced technical indicator that extends the concept of lag reduction beyond TEMA (Triple Exponential Moving Average) to a fourth order. By applying a sophisticated four-stage EMA cascade with optimized coefficient distribution, QEMA provides the ultimate evolution in EMA-based lag reduction techniques.
Unlike traditional compund moving averages like DEMA and TEMA, QEMA implements a progressive smoothing system that strategically distributes alphas across four EMA stages and combines them with balanced coefficients (4, -6, 4, -1). This approach creates an indicator that responds extremely quickly to price changes while still maintaining sufficient smoothness to be useful for trading decisions. QEMA is particularly valuable for traders who need the absolute minimum lag possible in trend identification.
▶️ **Core Concepts**
Fourth-order processing: Extends the EMA cascade to four stages for maximum possible lag reduction while maintaining a useful signal
Progressive alpha system: Uses mathematically derived ratio-based alpha progression to balance responsiveness across all four EMA stages
Optimized coefficients: Employs calculated weights (4, -6, 4, -1) to effectively eliminate lag while preserving compound signal stability
Numerical stability control: Implements initialization and alpha distribution to ensure consistent results from the first calculation bar
QEMA achieves its exceptional lag reduction by combining four progressive EMAs with mathematically optimized coefficients. The formula is designed to maximize responsiveness while minimizing the overshoot problems that typically occur with aggressive lag reduction techniques. The implementation uses a ratio-based alpha progression that ensures each EMA stage contributes appropriately to the final result.
▶️ **Common Settings and Parameters**
Period: Default: 15| Base smoothing period | When to Adjust: Decrease for extremely fast signals, increase for more stable output
Alpha: Default: auto | Direct control of base smoothing factor | When to Adjust: Manual setting allows precise tuning beyond standard period settings
Source: Default: Close | Data point used for calculation | When to Adjust: Change to HL2 or HLC3 for more balanced price representation
Pro Tip: Professional traders often use QEMA with longer periods than other moving averages (e.g., QEMA(20) instead of EMA(10)) since its extreme lag reduction provides earlier signals even with longer periods.
▶️ **Calculation and Mathematical Foundation**
Simplified explanation:
QEMA works by calculating four EMAs in sequence, with each EMA taking the previous one as input. It then combines these EMAs using balancing weights (4, -6, 4, -1) to create a moving average with extremely minimal lag and high level of smoothness. The alpha factors for each EMA are progressively adjusted using a mathematical ratio to ensure balanced responsiveness across all stages.
Technical formula:
QEMA = 4 × EMA₁ - 6 × EMA₂ + 4 × EMA₃ - EMA₄
Where:
EMA₁ = EMA(source, α₁)
EMA₂ = EMA(EMA₁, α₂)
EMA₃ = EMA(EMA₂, α₃)
EMA₄ = EMA(EMA₃, α₄)
α₁ = 2/(period + 1) is the base smoothing factor
r = (1/α₁)^(1/3) is the derived ratio
α₂ = α₁ × r, α₃ = α₂ × r, α₄ = α₃ × r are the progressive alphas
Mathematical Rationale for the Alpha Cascade:
The QEMA indicator employs a specific geometric progression for its smoothing factors (alphas) across the four EMA stages. This design is intentional and aims to optimize the filter's performance. The ratio between alphas is **r = (1/α₁)^(1/3)** - derived from the cube root of the reciprocal of the base alpha.
For typical smoothing (α₁ < 1), this results in a sequence of increasing alpha values (α₁ < α₂ < α₃ < α₄), meaning that subsequent EMAs in the cascade are progressively faster (less smoothed). This specific progression, when combined with the QEMA coefficients (4, -6, 4, -1), is chosen for the following reasons:
1. Optimized Frequency Response:
Using the same alpha for all EMA stages (as in a naive multi-EMA approach) can lead to an uneven frequency response, potentially causing over-shooting of certain frequencies or creating undesirable resonance. The geometric progression of alphas in QEMA helps to create a more balanced and controlled filter response across a wider range of movement frequencies. Each stage's contribution to the overall filtering characteristic is more harmonized.
2. Minimized Phase Lag:
A key goal of QEMA is extreme lag reduction. The specific alpha cascade, particularly the relationship defined by **r**, is designed to minimize the cumulative phase lag introduced by the four smoothing stages, while still providing effective noise reduction. Faster subsequent EMAs contribute to this reduced lag.
🔍 Technical Note: The ratio-based alpha progression is crucial for balanced response. The ratio r is calculated as the cube root of 1/α₁, ensuring that the combined effect of all four EMAs creates a mathematically optimal response curve. All EMAs are initialized with the first source value rather than using progressive initialization, eliminating warm-up artifacts and providing consistent results from the first bar.
▶️ **Interpretation Details**
QEMA provides several key insights for traders:
When price crosses above QEMA, it signals the beginning of an uptrend with minimal delay
When price crosses below QEMA, it signals the beginning of a downtrend with minimal delay
The slope of QEMA provides immediate insight into trend direction and momentum
QEMA responds to price reversals significantly faster than other moving averages
Multiple QEMA lines with different periods can identify immediate support/resistance levels
QEMA is particularly valuable in fast-moving markets and for short-term trading strategies where speed of signal generation is critical. It excels at capturing the very beginning of trends and identifying reversals earlier than any other EMA-derived indicator. This makes it especially useful for breakout trading and scalping strategies where getting in early is essential.
▶️ **Limitations and Considerations**
Market conditions: Can generate excessive signals in choppy, sideways markets due to its extreme responsiveness
Overshooting: The aggressive lag reduction can create some overshooting during sharp reversals
Calculation complexity: Requires four separate EMA calculations plus coefficient application, making it computationally more intensive
Parameter sensitivity: Small changes in the base alpha or period can significantly alter behavior
Complementary tools: Should be used with momentum indicators or volatility filters to confirm signals and reduce false positives
▶️ **References**
Mulloy, P. (1994). "Smoothing Data with Less Lag," Technical Analysis of Stocks & Commodities .
Ehlers, J. (2001). Rocket Science for Traders . John Wiley & Sons.
EMA & MA Crossover StrategyGuys, you asked, we did. Strategy for crossing moving averages .
The Moving Average Crossover trading strategy is possibly the most popular
trading strategy in the world of trading. First of them were written in the
middle of XX century, when commodities trading strategies became popular.
This strategy is a good example of so-called traditional strategies.
Traditional strategies are always long or short. That means they are never
out of the market. The concept of having a strategy that is always long or
short may be scary, particularly in today’s market where you don’t know what
is going to happen as far as risk on any one market. But a lot of traders
believe that the concept is still valid, especially for those of traders who
do their own research or their own discretionary trading.
This version uses crossover of moving average and its exponential moving average.
Strategy parameters:
Take Profit % - when it receives the opposite signal
Stop Loss % - when it receives the opposite signal
Current Backtest:
Account: 1000$
Trading size: 0.01
Commission: 0.05%
WARNING:
- For purpose educate only
- This script to change bars colors.
[SM-042] EMA 5-8-13 with ADX FilterWhat is the strategy?
The strategy combines three exponential moving averages (EMAs) — 5, 8, and 13 periods — with an optional ADX (Average Directional Index) filter. It is designed to enter long or short positions based on EMA crossovers and to exit positions when the price crosses a specific EMA. The ADX filter, if enabled, adds a condition that only allows trades when the ADX value is above a certain threshold, indicating trend strength.
Who is it for?
This strategy is for traders leveraging EMAs and trend strength indicators to make trade decisions. It can be used by anyone looking for a simple trend-following strategy, with the flexibility to adjust for trend strength using the ADX filter.
When is it used?
- **Long trades**: When the 5-period EMA crosses above the 8-period EMA, with an optional ADX condition (if enabled) that requires the ADX value to be above a specified threshold.
- **Short trades**: When the 5-period EMA crosses below the 8-period EMA, with the ADX filter again optional.
- **Exits**: The strategy exits a long position when the price falls below the 13-period EMA and exits a short position when the price rises above the 13-period EMA.
Where is it applied?
This strategy is applied on a chart with any asset on TradingView, with the EMAs and ADX plotted for visual reference. The strategy uses `strategy.entry` to open positions and `strategy.close` to close them based on the set conditions.
Why is it useful?
This strategy helps traders identify trending conditions and filter out potential false signals by using both EMAs (to capture short-term price movements) and the ADX (to confirm the strength of the trend). The ADX filter can be turned off if not desired, making the strategy flexible for both trending and range-bound markets.
How does it work?
- **EMA Crossover**: The strategy enters a long position when the 5-period EMA crosses above the 8-period EMA, and enters a short position when the 5-period EMA crosses below the 8-period EMA.
- **ADX Filter**: If enabled, the strategy checks whether the ADX value is above a set threshold (default is 20) before allowing a trade.
- **Exit Conditions**: Long positions are closed when the price falls below the 13-period EMA, and short positions are closed when the price rises above the 13-period EMA.
- **Plotting**: The strategy plots the three EMAs and the ADX value on the chart for visualization. It also displays a horizontal line at the ADX threshold.
This setup allows for clear decision-making based on the interaction between different time-frame EMAs and trend strength as indicated by ADX.
Price Extreme BandsPrice Extreme Bands Description
This indicator calculates and displays Price Extreme Bands based on an Exponential Moving Average (EMA) and True Range Average True Range (TR ATR). It utilizes a custom "Super Smoother" function to smooth the bands, providing a clearer representation of potential price extremes without sacrificing accuracy.
Usage
Built for specifically for intraday timeframes, this indicator identifies short term price extremes and volatility ranges. Traders can observe when price moves towards the outer bands, suggesting strong momentum or potential overbought/oversold conditions. The filled zones highlight areas of increased volatility which can used as exit criteria for a trade, possible reversal points in ranging markets or price ranges where price momentum could slow in trending markets.
Key Features
Length Input: Controls the length of the EMA and TR ATR calculations.
Multiplier Inputs: Uses two fixed multipliers (1.71 and 2.50) to create bands.
Super Smoother: Applies a custom smoothing function to the bands for reduced noise.
Fill Zones: Fills the areas between the inner and outer bands to highlight potential volatility ranges.
Calculation:
1. EMA (Basis): Calculates the Exponential Moving Average of the selected source.
2. TR ATR: Calculates the True Range and then smoothes it using RMA (Rolling Moving Average).
3. Bands: Calculates upper and lower bands using the EMA and ATR, with multipliers of 1.71 and 2.50.
4. Super Smoother: Applies a smoothing function to the calculated bands.
Visuals:
Basis Line: Plots the EMA (basis) (invisible by default).
Inner Bands (1.71 Multiplier): Plots the smoothed bands with a distinct color (e.g., orange) (invisible by default).
Outer Bands (2.50 Multiplier): Plots the smoothed bands with a different color (e.g., purple) (invisible by default).
Fill Zones: Fills the region between the inner and outer upper bands and the inner and outer lower bands with a translucent color (e.g. light blue).
// Note: The plot lines are invisible by default. To view the basis, upper and lower band lines, adjust the visibility settings in the indicator's settings.
Uniqueness: Ready of the box. Code and parameters built specifically for 1m to 15m timeframes provides users with an indicator to easily identify price extremes. The use of TR ATR and addition of the Super Smoother calculation create a easier visualization and implementation compared to existing price band options.
[F.B]_ZLEMA MACD ZLEMA MACD – A Zero-Lag Variant of the Classic MACD
Introduction & Motivation
The Moving Average Convergence Divergence (MACD) is a standard indicator for measuring trend strength and momentum. However, it suffers from the latency of traditional Exponential Moving Averages (EMAs).
This variant replaces EMAs with Zero Lag Exponential Moving Averages (ZLEMA), reducing delay and increasing the indicator’s responsiveness. This can potentially lead to earlier trend change detection, especially in highly volatile markets.
Calculation Methodology
2.1 Zero-Lag Exponential Moving Average (ZLEMA)
The classic EMA formula is extended with a correction factor:
ZLEMA_t = EMA(2 * P_t - EMA(P_t, L), L)
where:
P_t is the closing price,
L is the smoothing period length.
2.2 MACD Calculation Using ZLEMA
MACD_t = ZLEMA_short,t - ZLEMA_long,t
with standard parameters of 12 and 26 periods.
2.3 Signal Line with Adaptive Methodology
The signal line can be calculated using ZLEMA, EMA, or SMA:
Signal_t = f(MACD, S)
where f is the chosen smoothing function and S is the period length.
2.4 Histogram as a Measure of Momentum Changes
Histogram_t = MACD_t - Signal_t
An increasing histogram indicates a relative acceleration in trend strength.
Potential Applications in Data Analysis
Since the indicator is based solely on price time series, its effectiveness as a standalone trading signal is limited. However, in quantitative models, it can be used as a feature for trend quantification or for filtering market phases with strong trend dynamics.
Potential use cases include:
Trend Classification: Segmenting market phases into "trend" vs. "mean reversion."
Momentum Regime Identification: Analyzing histogram dynamics to detect increasing or decreasing trend strength.
Signal Smoothing: An alternative to classic EMA smoothing in more complex multi-factor models.
Important: Using this as a standalone trading indicator without additional confirmation mechanisms is not recommended, as it does not demonstrate statistical superiority over other momentum indicators.
Evaluation & Limitations
✅ Advantages:
Reduced lag compared to the classic MACD.
Customizable signal line smoothing for different applications.
Easy integration into existing analytical pipelines.
⚠️ Limitations:
Not a standalone trading system: Like any moving average, this indicator is susceptible to noise and false signals in sideways markets.
Parameter sensitivity: Small changes in period lengths can lead to significant signal deviations, requiring robust optimization.
Conclusion
The ZLEMA MACD is a variant of the classic MACD with reduced latency, making it particularly useful for analytical purposes where faster adaptation to price movements is required.
Its application in trading strategies should be limited to multi-factor models with rigorous evaluation. Backtests and out-of-sample analyses are essential to avoid overfitting to past market data.
Disclaimer: This indicator is provided for informational and educational purposes only and does not constitute financial advice. The author assumes no responsibility for any trading decisions made based on this indicator. Trading involves significant risk, and past performance is not indicative of future results.
Aggressive Strategy for High IV Market### Strategic background
In a volatile high IV market, prices are volatile and market expectations of future uncertainty are high. This environment provides opportunities for aggressive trading strategies, but also comes with a high level of risk. In pursuit of a high Sharpe ratio (i.e., risk-adjusted return), we need to design a strategy that captures the benefits of market volatility while effectively controlling risk. Based on daily line cycles, I choose a combination of trend tracking and volatility filtering for highly volatile assets such as stocks, futures or cryptocurrencies.
---
### Strategy framework
#### Data
- Use daily data, including opening, closing, high and low prices.
- Suitable for highly volatile markets such as technology stocks, cryptocurrencies or volatile index futures.
#### Core indicators
1. ** Trend Indicators ** :
Fast Exponential Moving Average (EMA_fast) : 10-day EMA, used to capture short-term trends.
- Slow Exponential Moving Average (EMA_slow) : 30-day EMA, used to determine the long-term trend.
2. ** Volatility Indicators ** :
Average true Volatility (ATR) : 14-day ATR, used to measure market volatility.
- ATR mean (ATR_mean) : A simple moving average of the 20-day ATR that serves as a volatility benchmark.
- ATR standard deviation (ATR_std) : The standard deviation of the 20-day ATR, which is used to judge extreme changes in volatility.
#### Trading logic
The strategy is based on a trend following approach of double moving averages and filters volatility through ATR indicators, ensuring that trading only in a high-volatility environment is in line with aggressive and high sharpe ratio goals.
---
### Entry and exit conditions
#### Admission conditions
- ** Multiple entry ** :
- EMA_fast Crosses EMA_slow (gold cross), indicating that the short-term trend is turning upward.
-ATR > ATR_mean + 1 * ATR_std indicates that the current volatility is above average and the market is in a state of high volatility.
- ** Short Entry ** :
- EMA_fast Crosses EMA_slow (dead cross) downward, indicating that the short-term trend turns downward.
-ATR > ATR_mean + 1 * ATR_std, confirming high volatility.
#### Appearance conditions
- ** Long show ** :
- EMA_fast Enters the EMA_slow (dead cross) downward, and the trend reverses.
- or ATR < ATR_mean-1 * ATR_std, volatility decreases significantly and the market calms down.
- ** Bear out ** :
- EMA_fast Crosses the EMA_slow (gold cross) on the top, and the trend reverses.
- or ATR < ATR_mean-1 * ATR_std, the volatility is reduced.
---
### Risk management
To control the high risk associated with aggressive strategies, set up the following mechanisms:
1. ** Stop loss ** :
- Long: Entry price - 2 * ATR.
- Short: Entry price + 2 * ATR.
- Dynamic stop loss based on ATR can adapt to market volatility changes.
2. ** Stop profit ** :
- Fixed profit target can be selected (e.g. entry price ± 4 * ATR).
- Or use trailing stop losses to lock in profits following price movements.
3. ** Location Management ** :
- Reduce positions appropriately in times of high volatility, such as dynamically adjusting position size according to ATR, ensuring that the risk of a single trade does not exceed 1%-2% of the account capital.
---
### Strategy features
- ** Aggressiveness ** : By trading only in a high ATR environment, the strategy takes full advantage of market volatility and pursues greater returns.
- ** High Sharpe ratio potential ** : Trend tracking combined with volatility filtering to avoid ineffective trades during periods of low volatility and improve the ratio of return to risk.
- ** Daily line Cycle ** : Based on daily line data, suitable for traders who operate frequently but are not too complex.
---
### Implementation steps
1. ** Data Preparation ** :
- Get the daily data of the target asset.
- Calculate EMA_fast (10 days), EMA_slow (30 days), ATR (14 days), ATR_mean (20 days), and ATR_std (20 days).
2. ** Signal generation ** :
- Check EMA cross signals and ATR conditions daily to generate long/short signals.
3. ** Execute trades ** :
- Enter according to the signal, set stop loss and profit.
- Monitor exit conditions and close positions in time.
4. ** Backtest and Optimization ** :
- Use historical data to backtest strategies to evaluate Sharpe ratios, maximum retracements, and win rates.
- Optimize parameters such as EMA period and ATR threshold to improve policy performance.
---
### Precautions
- ** Trading costs ** : Highly volatile markets may result in frequent trading, and the impact of fees and slippage on earnings needs to be considered.
- ** Risk Control ** : Aggressive strategies may face large retracements and need to strictly implement stop losses.
- ** Scalability ** : Additional metrics (such as volume or VIX) can be added to enhance strategy robustness, or combined with machine learning to predict trends and volatility.
---
### Summary
This is a trend following strategy based on dual moving averages and ATR, designed for volatile high IV markets. By entering into high volatility and exiting into low volatility, the strategy combines aggressive and risk-adjusted returns for traders seeking a high sharpe ratio. It is recommended to fully backtest before implementation and adjust the parameters according to the specific market.
Trend Strength & Direction📌 Assumptions of the "Trend Strength & Direction" Model
This model is designed to measure both trend strength and trend direction, using a modified version of the ADX (Average Directional Index) while also identifying ranging markets. Below is a detailed breakdown of all key assumptions.
1️⃣ Using ADX as the Basis for Trend Strength
Why ADX?
The ADX (Average Directional Index) is one of the most commonly used indicators for measuring trend strength, regardless of direction.
How is it calculated?
ATR (Average True Range) is used to normalize volatility.
Directional movement (+DM and -DM) is smoothed with an Exponential Moving Average (EMA) to obtain the +DI (Positive Directional Indicator) and -DI (Negative Directional Indicator).
Trend strength is derived by normalizing the absolute difference between +DI and -DI, divided by the sum of both.
🔹 Assumption: A high ADX means the trend is strong (whether bullish or bearish).
2️⃣ 50-Period Moving Average for Trend Strength
Why add a moving average?
ADX can be very volatile in the short term.
A 50-period SMA (Simple Moving Average) is used to smooth out trend strength and identify sustained trends.
🔹 Assumption: The SMA reduces false signals caused by short-term ADX spikes.
3️⃣ Identifying a Ranging Market (ADX Below 35)
How is a ranging market defined?
If the trend strength (ADX) is below 35, the market is considered "ranging".
The 35-level threshold is chosen empirically since ADX values below this level often indicate a lack of strong price direction.
When the market is ranging, the background color turns yellow.
🔹 Assumption: ADX < 35 indicates a sideways market, so the indicator colors the background yellow.
4️⃣ Determining Trend Direction Using +DI and -DI
How is direction determined?
If +DI > -DI, the trend is bullish (green).
If -DI > +DI, the trend is bearish (red).
If ADX is below 35, the market is ranging and turns yellow.
🔹 Assumption: Trend direction is determined by the relationship between +DI and -DI, not ADX values.
5️⃣ Background Color to Highlight Market Conditions
Yellow background if ADX < 35 → Ranging market.
Green background if ADX ≥ 35 and bullish.
Red background if ADX ≥ 35 and bearish.
🔹 Assumption: The background color visually differentiates trending vs. ranging phases.
6️⃣ Reference Levels for ADX
Lateral Threshold (35) → Below this, the trend is weak or ranging.
Neutral Threshold (50) → Intermediate level indicating moderate trend strength.
Strong Trend Threshold (75) → Above this, the trend is very strong and possibly overextended.
🔹 Assumption: ADX above 75 indicates a very strong trend, potentially near exhaustion.
🔹 Summary of Key Assumptions
1️⃣ ADX is the core strength metric → Strong trends when ADX > 35, weak below 35.
2️⃣ The 50-period SMA smooths out volatility → Prevents false signals.
3️⃣ Ranging markets are defined as ADX < 35 → Yellow background color.
4️⃣ Trend direction is based on +DI vs. -DI → Green = bullish, Red = bearish.
5️⃣ Background colors enhance readability → Helps distinguish different market phases.
6️⃣ ADX reference levels (35, 50, 75) indicate increasing trend strength.
Conclusion
This model combines ADX with a moving average and color-based logic to highlight trend strength, trend direction, and sideways markets. It helps traders quickly identify the best conditions for entering or exiting trades. 🚀
Consecutive Bars Above/Below EMA Buy the Dip Strategy█ STRATEGY DESCRIPTION
The "Consecutive Bars Above/Below EMA Buy the Dip Strategy" is a mean-reversion strategy designed to identify potential buying opportunities when the price dips below a moving average for a specified number of consecutive bars. It enters a long position when the dip condition is met and exits when the price shows strength by exceeding the previous bar's high. This strategy is suitable for use on various timeframes.
█ WHAT IS THE MOVING AVERAGE?
The strategy uses either a Simple Moving Average (SMA) or an Exponential Moving Average (EMA) as a reference for identifying dips. The type and length of the moving average can be customized in the settings.
█ SIGNAL GENERATION
1. LONG ENTRY
A Buy Signal is triggered when:
The close price is below the selected moving average for a specified number of consecutive bars (`consecutiveBarsTreshold`).
The signal occurs within the specified time window (between `Start Time` and `End Time`).
2. EXIT CONDITION
A Sell Signal is generated when the current closing price exceeds the high of the previous bar (`close > high `). This indicates that the price has shown strength, potentially confirming the reversal and prompting the strategy to exit the position.
█ ADDITIONAL SETTINGS
Consecutive Bars Threshold: The number of consecutive bars the price must remain below the moving average to trigger a Buy Signal. Default is 3.
MA Type: The type of moving average used (SMA or EMA). Default is SMA.
MA Length: The length of the moving average. Default is 5.
Start Time and End Time: The time window during which the strategy is allowed to execute trades.
█ PERFORMANCE OVERVIEW
This strategy is designed for mean-reverting markets and performs best when the price frequently oscillates around the moving average.
It is sensitive to the number of consecutive bars below the moving average, which helps to identify potential dips.
Backtesting results should be analysed to optimize the Consecutive Bars Threshold, MA Type, and MA Length for specific instruments.
BBSS+This Pine Script implements a custom indicator overlaying Bollinger Bands with additional features for trend analysis using Exponential Moving Averages (EMAs). Here's a breakdown of its functionality:
Bollinger Bands:
The script calculates the Bollinger Bands using a 20-period Simple Moving Average (SMA) as the basis and a multiplier of 2 for the standard deviation.
It plots the Upper Band and Lower Band in red.
EMA Calculations:
Three EMAs are calculated for the close price with periods of 5, 10, and 40.
The EMAs are plotted in green (5-period), cyan (10-period), and orange (40-period) to distinguish between them.
Trend Detection:
The script determines bullish or bearish EMA alignments:
Bullish Order: EMA 5 > EMA 10 > EMA 40.
Bearish Order: EMA 5 < EMA 10 < EMA 40.
Entry Signals:
Long Entry: Triggered when:
The close price crosses above the Upper Bollinger Band.
The Upper Band is above its 5-period SMA (indicating momentum).
The EMAs are in a bullish order.
Short Entry: Triggered when:
The close price crosses below the Lower Bollinger Band.
The Lower Band is below its 5-period SMA.
The EMAs are in a bearish order.
Trend State Tracking:
A variable tracks whether the market is in a Long or Short trend based on conditions:
A Long trend continues unless conditions for a Short Entry are met or the Upper Band dips below its average.
A Short trend continues unless conditions for a Long Entry are met or the Lower Band rises above its average.
Visual Aids:
Signal Shapes:
Triangle-up shapes indicate Long Entry points below the bar.
Triangle-down shapes indicate Short Entry points above the bar.
Bar Colors:
Green bars indicate a Long trend.
Red bars indicate a Short trend.
This script combines Bollinger Bands with EMA crossovers to generate entry signals and visualize market trends, making it a versatile tool for identifying momentum and trend reversals.
