Bober XM v2.0# ₿ober XM v2.0 Trading Bot Documentation
**Developer's Note**: While our previous Bot 1.3.1 was removed due to guideline violations, this setback only fueled our determination to create something even better. Rising from this challenge, Bober XM 2.0 emerges not just as an update, but as a complete reimagining with multi-timeframe analysis, enhanced filters, and superior adaptability. This adversity pushed us to innovate further and deliver a strategy that's smarter, more agile, and more powerful than ever before. Challenges create opportunity - welcome to Cryptobeat's finest work yet.
## !!!!You need to tune it for your own pair and timeframe and retune it periodicaly!!!!!
## Overview
The ₿ober XM v2.0 is an advanced dual-channel trading bot with multi-timeframe analysis capabilities. It integrates multiple technical indicators, customizable risk management, and advanced order execution via webhook for automated trading. The bot's distinctive feature is its separate channel systems for long and short positions, allowing for asymmetric trade strategies that adapt to different market conditions across multiple timeframes.
### Key Features
- **Multi-Timeframe Analysis**: Analyze price data across multiple timeframes simultaneously
- **Dual Channel System**: Separate parameter sets for long and short positions
- **Advanced Entry Filters**: RSI, Volatility, Volume, Bollinger Bands, and KEMAD filters
- **Machine Learning Moving Average**: Adaptive prediction-based channels
- **Multiple Entry Strategies**: Breakout, Pullback, and Mean Reversion modes
- **Risk Management**: Customizable stop-loss, take-profit, and trailing stop settings
- **Webhook Integration**: Compatible with external trading bots and platforms
### Strategy Components
| Component | Description |
|---------|-------------|
| **Dual Channel Trading** | Uses either Keltner Channels or Machine Learning Moving Average (MLMA) with separate settings for long and short positions |
| **MLMA Implementation** | Machine learning algorithm that predicts future price movements and creates adaptive bands |
| **Pivot Point SuperTrend** | Trend identification and confirmation system based on pivot points |
| **Three Entry Strategies** | Choose between Breakout, Pullback, or Mean Reversion approaches |
| **Advanced Filter System** | Multiple customizable filters with multi-timeframe support to avoid false signals |
| **Custom Exit Logic** | Exits based on OBV crossover of its moving average combined with pivot trend changes |
### Note for Novice Users
This is a fully featured real trading bot and can be tweaked for any ticker — SOL is just an example. It follows this structure:
1. **Indicator** – gives the initial signal
2. **Entry strategy** – decides when to open a trade
3. **Exit strategy** – defines when to close it
4. **Trend confirmation** – ensures the trade follows the market direction
5. **Filters** – cuts out noise and avoids weak setups
6. **Risk management** – controls losses and protects your capital
To tune it for a different pair, you'll need to start from scratch:
1. Select the timeframe (candle size)
2. Turn off all filters and trend entry/exit confirmations
3. Choose a channel type, channel source and entry strategy
4. Adjust risk parameters
5. Tune long and short settings for the channel
6. Fine-tune the Pivot Point Supertrend and Main Exit condition OBV
This will generate a lot of signals and activity on the chart. Your next task is to find the right combination of filters and settings to reduce noise and tune it for profitability.
### Default Strategy values
Default values are tuned for: Symbol BITGET:SOLUSDT.P 5min candle
Filters are off by default: Try to play with it to understand how it works
## Configuration Guide
### General Settings
| Setting | Description | Default Value |
|---------|-------------|---------------|
| **Long Positions** | Enable or disable long trades | Enabled |
| **Short Positions** | Enable or disable short trades | Enabled |
| **Risk/Reward Area** | Visual display of stop-loss and take-profit zones | Enabled |
| **Long Entry Source** | Price data used for long entry signals | hl2 (High+Low/2) |
| **Short Entry Source** | Price data used for short entry signals | hl2 (High+Low/2) |
The bot allows you to trade long positions, short positions, or both simultaneously. Each direction has its own set of parameters, allowing for fine-tuned strategies that recognize the asymmetric nature of market movements.
### Multi-Timeframe Settings
1. **Enable Multi-Timeframe Analysis**: Toggle 'Enable Multi-Timeframe Analysis' in the Multi-Timeframe Settings section
2. **Configure Timeframes**: Set appropriate higher timeframes based on your trading style:
- Timeframe 1: Default is now 15 minutes (intraday confirmation)
- Timeframe 2: Default is 4 hours (trend direction)
3. **Select Sources per Indicator**: For each indicator (RSI, KEMAD, Volume, etc.), choose:
- The desired timeframe (current, mtf1, or mtf2)
- The appropriate price type (open, high, low, close, hl2, hlc3, ohlc4)
### Entry Strategies
- **Breakout**: Enter when price breaks above/below the channel
- **Pullback**: Enter when price pulls back to the channel
- **Mean Reversion**: Enter when price is extended from the channel
You can enable different strategies for long and short positions.
### Core Components
### Risk Management
- **Position Size**: Control risk with percentage-based position sizing
- **Stop Loss Options**:
- Fixed: Set a specific price or percentage from entry
- ATR-based: Dynamic stop-loss based on market volatility
- Swing: Uses recent swing high/low points
- **Take Profit**: Multiple targets with percentage allocation
- **Trailing Stop**: Dynamic stop that follows price movement
## Advanced Usage Strategies
### Moving Average Type Selection Guide
- **SMA**: More stable in choppy markets, good for higher timeframes
- **EMA/WMA**: More responsive to recent price changes, better for entry signals
- **VWMA**: Adds volume weighting for stronger trends, use with Volume filter
- **HMA**: Balance between responsiveness and noise reduction, good for volatile markets
### Multi-Timeframe Strategy Approaches
- **Trend Confirmation**: Use higher timeframe RSI (mtf2) for overall trend, current timeframe for entries
- **Entry Precision**: Use KEMAD on current timeframe with volume filter on mtf1
- **False Signal Reduction**: Apply RSI filter on mtf1 with strict KEMAD settings
### Market Condition Optimization
| Market Condition | Recommended Settings |
|------------------|----------------------|
| **Trending** | Use Breakout strategy with KEMAD filter on higher timeframe |
| **Ranging** | Use Mean Reversion with strict RSI filter (mtf1) |
| **Volatile** | Increase ATR multipliers, use HMA for moving averages |
| **Low Volatility** | Decrease noise parameters, use pullback strategy |
## Webhook Integration
The strategy features a professional webhook system that allows direct connectivity to your exchange or trading platform of choice through third-party services like 3commas, Alertatron, or Autoview.
The webhook payload includes all necessary parameters for automated execution:
- Entry price and direction
- Stop loss and take profit levels
- Position size
- Custom identifier for webhook routing
## Performance Optimization Tips
1. **Start with Defaults**: Begin with the default settings for your timeframe before customizing
2. **Adjust One Component at a Time**: Make incremental changes and test the impact
3. **Match MA Types to Market Conditions**: Use appropriate moving average types based on the Market Condition Optimization table
4. **Timeframe Synergy**: Create logical relationships between timeframes (e.g., 5min chart with 15min and 4h higher timeframes)
5. **Periodic Retuning**: Markets evolve - regularly review and adjust parameters
## Common Setups
### Crypto Trend-Following
- MLMA with EMA or HMA
- Higher RSI thresholds (75/25)
- KEMAD filter on mtf1
- Breakout entry strategy
### Stock Swing Trading
- MLMA with SMA for stability
- Volume filter with higher threshold
- KEMAD with increased filter order
- Pullback entry strategy
### Forex Scalping
- MLMA with WMA and lower noise parameter
- RSI filter on current timeframe
- Use highest timeframe for trend direction only
- Mean Reversion strategy
## Webhook Configuration
- **Benefits**:
- Automated trade execution without manual intervention
- Immediate response to market conditions
- Consistent execution of your strategy
- **Implementation Notes**:
- Requires proper webhook configuration on your exchange or platform
- Test thoroughly with small position sizes before full deployment
- Consider latency between signal generation and execution
### Backtesting Period
Define a specific historical period to evaluate the bot's performance:
| Setting | Description | Default Value |
|---------|-------------|---------------|
| **Start Date** | Beginning of backtest period | January 1, 2025 |
| **End Date** | End of backtest period | December 31, 2026 |
- **Best Practice**: Test across different market conditions (bull markets, bear markets, sideways markets)
- **Limitation**: Past performance doesn't guarantee future results
## Entry and Exit Strategies
### Dual-Channel System
A key innovation of the Bober XM is its dual-channel approach:
- **Independent Parameters**: Each trade direction has its own channel settings
- **Asymmetric Trading**: Recognizes that markets often behave differently in uptrends versus downtrends
- **Optimized Performance**: Fine-tune settings for both bullish and bearish conditions
This approach allows the bot to adapt to the natural asymmetry of markets, where uptrends often develop gradually while downtrends can be sharp and sudden.
### Channel Types
#### 1. Keltner Channels
Traditional volatility-based channels using EMA and ATR:
| Setting | Long Default | Short Default |
|---------|--------------|---------------|
| **EMA Length** | 37 | 20 |
| **ATR Length** | 13 | 17 |
| **Multiplier** | 1.4 | 1.9 |
| **Source** | low | high |
- **Strengths**:
- Reliable in trending markets
- Less prone to whipsaws than Bollinger Bands
- Clear visual representation of volatility
- **Weaknesses**:
- Can lag during rapid market changes
- Less effective in choppy, non-trending markets
#### 2. Machine Learning Moving Average (MLMA)
Advanced predictive model using kernel regression (RBF kernel):
| Setting | Description | Options |
|---------|-------------|--------|
| **Source MA** | Price data used for MA calculations | Any price source (low/high/close/etc.) |
| **Moving Average Type** | Type of MA algorithm for calculations | SMA, EMA, WMA, VWMA, RMA, HMA |
| **Trend Source** | Price data used for trend determination | Any price source (close default) |
| **Window Size** | Historical window for MLMA calculations | 5+ (default: 16) |
| **Forecast Length** | Number of bars to forecast ahead | 1+ (default: 3) |
| **Noise Parameter** | Controls smoothness of prediction | 0.01+ (default: ~0.43) |
| **Band Multiplier** | Multiplier for channel width | 0.1+ (default: 0.5-0.6) |
- **Strengths**:
- Predictive rather than reactive
- Adapts quickly to changing market conditions
- Better at identifying trend reversals early
- **Weaknesses**:
- More computationally intensive
- Requires careful parameter tuning
- Can be sensitive to input data quality
### Entry Strategies
| Strategy | Description | Ideal Market Conditions |
|----------|-------------|-------------------------|
| **Breakout** | Enters when price breaks through channel bands, indicating strong momentum | High volatility, emerging trends |
| **Pullback** | Enters when price retraces to the middle band after testing extremes | Established trends with regular pullbacks |
| **Mean Reversion** | Enters at channel extremes, betting on a return to the mean | Range-bound or oscillating markets |
#### Breakout Strategy (Default)
- **Implementation**: Enters long when price crosses above the upper band, short when price crosses below the lower band
- **Strengths**: Captures strong momentum moves, performs well in trending markets
- **Weaknesses**: Can lead to late entries, higher risk of false breakouts
- **Optimization Tips**:
- Increase channel multiplier for fewer but more reliable signals
- Combine with volume confirmation for better accuracy
#### Pullback Strategy
- **Implementation**: Enters long when price pulls back to middle band during uptrend, short during downtrend pullbacks
- **Strengths**: Better entry prices, lower risk, higher probability setups
- **Weaknesses**: Misses some strong moves, requires clear trend identification
- **Optimization Tips**:
- Use with trend filters to confirm overall direction
- Adjust middle band calculation for market volatility
#### Mean Reversion Strategy
- **Implementation**: Enters long at lower band, short at upper band, expecting price to revert to the mean
- **Strengths**: Excellent entry prices, works well in ranging markets
- **Weaknesses**: Dangerous in strong trends, can lead to fighting the trend
- **Optimization Tips**:
- Implement strong trend filters to avoid counter-trend trades
- Use smaller position sizes due to higher risk nature
### Confirmation Indicators
#### Pivot Point SuperTrend
Combines pivot points with ATR-based SuperTrend for trend confirmation:
| Setting | Default Value |
|---------|---------------|
| **Pivot Period** | 25 |
| **ATR Factor** | 2.2 |
| **ATR Period** | 41 |
- **Function**: Identifies significant market turning points and confirms trend direction
- **Implementation**: Requires price to respect the SuperTrend line for trade confirmation
#### Weighted Moving Average (WMA)
Provides additional confirmation layer for entries:
| Setting | Default Value |
|---------|---------------|
| **Period** | 15 |
| **Source** | ohlc4 (average of Open, High, Low, Close) |
- **Function**: Confirms trend direction and filters out low-quality signals
- **Implementation**: Price must be above WMA for longs, below for shorts
### Exit Strategies
#### On-Balance Volume (OBV) Based Exits
Uses volume flow to identify potential reversals:
| Setting | Default Value |
|---------|---------------|
| **Source** | ohlc4 |
| **MA Type** | HMA (Options: SMA, EMA, WMA, RMA, VWMA, HMA) |
| **Period** | 22 |
- **Function**: Identifies divergences between price and volume to exit before reversals
- **Implementation**: Exits when OBV crosses its moving average in the opposite direction
- **Customizable MA Type**: Different MA types provide varying sensitivity to OBV changes:
- **SMA**: Traditional simple average, equal weight to all periods
- **EMA**: More weight to recent data, responds faster to price changes
- **WMA**: Weighted by recency, smoother than EMA
- **RMA**: Similar to EMA but smoother, reduces noise
- **VWMA**: Factors in volume, helpful for OBV confirmation
- **HMA**: Reduces lag while maintaining smoothness (default)
#### ADX Exit Confirmation
Uses Average Directional Index to confirm trend exhaustion:
| Setting | Default Value |
|---------|---------------|
| **ADX Threshold** | 35 |
| **ADX Smoothing** | 60 |
| **DI Length** | 60 |
- **Function**: Confirms trend weakness before exiting positions
- **Implementation**: Requires ADX to drop below threshold or DI lines to cross
## Filter System
### RSI Filter
- **Function**: Controls entries based on momentum conditions
- **Parameters**:
- Period: 15 (default)
- Overbought level: 71
- Oversold level: 23
- Multi-timeframe support: Current, MTF1 (15min), or MTF2 (4h)
- Customizable price source (open, high, low, close, hl2, hlc3, ohlc4)
- **Implementation**: Blocks long entries when RSI > overbought, short entries when RSI < oversold
### Volatility Filter
- **Function**: Prevents trading during excessive market volatility
- **Parameters**:
- Measure: ATR (Average True Range)
- Period: Customizable (default varies by timeframe)
- Threshold: Adjustable multiplier
- Multi-timeframe support
- Customizable price source
- **Implementation**: Blocks trades when current volatility exceeds threshold × average volatility
### Volume Filter
- **Function**: Ensures adequate market liquidity for trades
- **Parameters**:
- Threshold: 0.4× average (default)
- Measurement period: 5 (default)
- Moving average type: Customizable (HMA default)
- Multi-timeframe support
- Customizable price source
- **Implementation**: Requires current volume to exceed threshold × average volume
### Bollinger Bands Filter
- **Function**: Controls entries based on price relative to statistical boundaries
- **Parameters**:
- Period: Customizable
- Standard deviation multiplier: Adjustable
- Moving average type: Customizable
- Multi-timeframe support
- Customizable price source
- **Implementation**: Can require price to be within bands or breaking out of bands depending on strategy
### KEMAD Filter (Kalman EMA Distance)
- **Function**: Advanced trend confirmation using Kalman filter algorithm
- **Parameters**:
- Process Noise: 0.35 (controls smoothness)
- Measurement Noise: 24 (controls reactivity)
- Filter Order: 6 (higher = more smoothing)
- ATR Length: 8 (for bandwidth calculation)
- Upper Multiplier: 2.0 (for long signals)
- Lower Multiplier: 2.7 (for short signals)
- Multi-timeframe support
- Customizable visual indicators
- **Implementation**: Generates signals based on price position relative to Kalman-filtered EMA bands
## Risk Management System
### Position Sizing
Automatically calculates position size based on account equity and risk parameters:
| Setting | Default Value |
|---------|---------------|
| **Risk % of Equity** | 50% |
- **Implementation**:
- Position size = (Account equity × Risk %) ÷ (Entry price × Stop loss distance)
- Adjusts automatically based on volatility and stop placement
- **Best Practices**:
- Start with lower risk percentages (1-2%) until strategy is proven
- Consider reducing risk during high volatility periods
### Stop-Loss Methods
Multiple stop-loss calculation methods with separate configurations for long and short positions:
| Method | Description | Configuration |
|--------|-------------|---------------|
| **ATR-Based** | Dynamic stops based on volatility | ATR Period: 14, Multiplier: 2.0 |
| **Percentage** | Fixed percentage from entry | Long: 1.5%, Short: 1.5% |
| **PIP-Based** | Fixed currency unit distance | 10.0 pips |
- **Implementation Notes**:
- ATR-based stops adapt to changing market volatility
- Percentage stops maintain consistent risk exposure
- PIP-based stops provide precise control in stable markets
### Trailing Stops
Locks in profits by adjusting stop-loss levels as price moves favorably:
| Setting | Default Value |
|---------|---------------|
| **Stop-Loss %** | 1.5% |
| **Activation Threshold** | 2.1% |
| **Trailing Distance** | 1.4% |
- **Implementation**:
- Initial stop remains fixed until profit reaches activation threshold
- Once activated, stop follows price at specified distance
- Locks in profit while allowing room for normal price fluctuations
### Risk-Reward Parameters
Defines the relationship between risk and potential reward:
| Setting | Default Value |
|---------|---------------|
| **Risk-Reward Ratio** | 1.4 |
| **Take Profit %** | 2.4% |
| **Stop-Loss %** | 1.5% |
- **Implementation**:
- Take profit distance = Stop loss distance × Risk-reward ratio
- Higher ratios require fewer winning trades for profitability
- Lower ratios increase win rate but reduce average profit
### Filter Combinations
The strategy allows for simultaneous application of multiple filters:
- **Recommended Combinations**:
- Trending markets: RSI + KEMAD filters
- Ranging markets: Bollinger Bands + Volatility filters
- All markets: Volume filter as minimum requirement
- **Performance Impact**:
- Each additional filter reduces the number of trades
- Quality of remaining trades typically improves
- Optimal combination depends on market conditions and timeframe
### Multi-Timeframe Filter Applications
| Filter Type | Current Timeframe | MTF1 (15min) | MTF2 (4h) |
|-------------|-------------------|-------------|------------|
| RSI | Quick entries/exits | Intraday trend | Overall trend |
| Volume | Immediate liquidity | Sustained support | Market participation |
| Volatility | Entry timing | Short-term risk | Regime changes |
| KEMAD | Precise signals | Trend confirmation | Major reversals |
## Visual Indicators and Chart Analysis
The bot provides comprehensive visual feedback on the chart:
- **Channel Bands**: Keltner or MLMA bands showing potential support/resistance
- **Pivot SuperTrend**: Colored line showing trend direction and potential reversal points
- **Entry/Exit Markers**: Annotations showing actual trade entries and exits
- **Risk/Reward Zones**: Visual representation of stop-loss and take-profit levels
These visual elements allow for:
- Real-time strategy assessment
- Post-trade analysis and optimization
- Educational understanding of the strategy logic
## Implementation Guide
### TradingView Setup
1. Load the script in TradingView Pine Editor
2. Apply to your preferred chart and timeframe
3. Adjust parameters based on your trading preferences
4. Enable alerts for webhook integration
### Webhook Integration
1. Configure webhook URL in TradingView alerts
2. Set up receiving endpoint on your trading platform
3. Define message format matching the bot's output
4. Test with small position sizes before full deployment
### Optimization Process
1. Backtest across different market conditions
2. Identify parameter sensitivity through multiple tests
3. Focus on risk management parameters first
4. Fine-tune entry/exit conditions based on performance metrics
5. Validate with out-of-sample testing
## Performance Considerations
### Strengths
- Adaptability to different market conditions through dual channels
- Multiple layers of confirmation reducing false signals
- Comprehensive risk management protecting capital
- Machine learning integration for predictive edge
### Limitations
- Complex parameter set requiring careful optimization
- Potential over-optimization risk with so many variables
- Computational intensity of MLMA calculations
- Dependency on proper webhook configuration for execution
### Best Practices
- Start with conservative risk settings (1-2% of equity)
- Test thoroughly in demo environment before live trading
- Monitor performance regularly and adjust parameters
- Consider market regime changes when evaluating results
## Conclusion
The ₿ober XM v2.0 represents a significant evolution in trading strategy design, combining traditional technical analysis with machine learning elements and multi-timeframe analysis. The core strength of this system lies in its adaptability and recognition of market asymmetry.
### Market Asymmetry and Adaptive Approach
The strategy acknowledges a fundamental truth about markets: bullish and bearish phases behave differently and should be treated as distinct environments. The dual-channel system with separate parameters for long and short positions directly addresses this asymmetry, allowing for optimized performance regardless of market direction.
### Targeted Backtesting Philosophy
It's counterproductive to run backtests over excessively long periods. Markets evolve continuously, and strategies that worked in previous market regimes may be ineffective in current conditions. Instead:
- Test specific market phases separately (bull markets, bear markets, range-bound periods)
- Regularly re-optimize parameters as market conditions change
- Focus on recent performance with higher weight than historical results
- Test across multiple timeframes to ensure robustness
### Multi-Timeframe Analysis as a Game-Changer
The integration of multi-timeframe analysis fundamentally transforms the strategy's effectiveness:
- **Increased Safety**: Higher timeframe confirmations reduce false signals and improve trade quality
- **Context Awareness**: Decisions made with awareness of larger trends reduce adverse entries
- **Adaptable Precision**: Apply strict filters on lower timeframes while maintaining awareness of broader conditions
- **Reduced Noise**: Higher timeframe data naturally filters market noise that can trigger poor entries
The ₿ober XM v2.0 provides traders with a framework that acknowledges market complexity while offering practical tools to navigate it. With proper setup, realistic expectations, and attention to changing market conditions, it delivers a sophisticated approach to systematic trading that can be continuously refined and optimized.
Cerca negli script per "stop loss"
AlphaTrend++AlphaTrend++
Overview
The AlphaTrend++ is an advanced Pine Script indicator designed to help traders identify buy and sell opportunities in trending and volatile markets. Building on trend-following principles, it uses a modified Average True Range (ATR) calculation combined with volume or momentum data to plot a dynamic trend line. The indicator overlays on the price chart, displaying a colored trend line, a filled trend zone, buy/sell signals, and optional stop-loss tick labels, making it ideal for day trading or swing trading, particularly in markets like futures (e.g., MES).
What It Does
This indicator generates buy and sell signals based on the direction and momentum of a custom trend line, filtered by optional time restrictions and signal frequency logic. The trend line adapts to price action and volatility, with a filled zone highlighting trend strength. Buy/sell signals are plotted as labels, and stop-loss distances are displayed in ticks (customizable for instruments like MES). The indicator supports standard chart types for realistic signal generation.
How It Works
The indicator employs the following components:
Trend Line Calculation: A dynamic trend line is calculated using ATR adjusted by a user-defined multiplier, combined with either Money Flow Index (MFI) or Relative Strength Index (RSI) depending on volume availability. The line tracks price movements, adjusting upward or downward based on trend direction and volatility.
Trend Zone: The area between the current trend line and its value two bars prior is filled, colored green for bullish trends (upward movement) or red for bearish trends (downward movement), providing a visual cue of trend strength.
Signal Generation: Buy signals occur when the trend line crosses above its value two bars ago, and sell signals occur when it crosses below, with optional filtering to reduce signal noise (based on bar timing logic). Signals can be restricted to a 9:00–15:00 UTC trading window.
Stop-Loss Ticks: For each signal, the indicator calculates the distance to the trend line (acting as a stop-loss level) in ticks, using a user-defined tick size (default 0.25 for MES). These are displayed as labels below/above the signal.
Time Filter: An optional filter limits signals to 9:00–15:00 UTC, aligning with active trading sessions like the US market open.
The indicator ensures compatibility with standard chart types (e.g., candlestick or bar charts) to avoid unrealistic results associated with non-standard types like Heikin Ashi or Renko.
How to Use It
Add to Chart: Apply the indicator to a candlestick or bar chart on TradingView.
Configure Settings:
Multiplier: Adjust the ATR multiplier (default 1.0) to control trend line sensitivity. Higher values widen the stop-loss distance.
Common Period: Set the ATR and MFI/RSI period (default 14) for trend calculations.
No Volume Data: Enable if volume data is unavailable (e.g., for certain forex pairs), switching from MFI to RSI.
Tick Size: Set the tick size for stop-loss calculations (default 0.25 for MES futures).
Show Buy/Sell Signals: Toggle signal labels (default enabled).
Show Stop Loss Ticks: Toggle stop-loss tick labels (default enabled).
Use Time Filter: Restrict signals to 9:00–15:00 UTC (default disabled).
Use Filtered Signals: Enable to reduce signal frequency using bar timing logic (default enabled).
Interpret Signals:
Buy Signal: A blue “BUY” label below the bar indicates a potential long entry (trend line crossover, passing filters).
Sell Signal: A red “SELL” label above the bar indicates a potential short entry (trend line crossunder, passing filters).
Trend Zone: Green fill suggests bullish momentum; red fill suggests bearish momentum.
Stop-Loss Ticks: Gray labels show the stop-loss distance in ticks, helping with risk management.
Monitor Context: Use the trend line and filled zone to confirm the market’s direction before acting on signals.
Unique Features
Adaptive Trend Line: Combines ATR with MFI or RSI to create a responsive trend line that adjusts to volatility and market conditions.
Tick-Based Stop-Loss: Displays stop-loss distances in ticks, customizable for specific instruments, aiding precise risk management.
Signal Filtering: Optional bar timing logic reduces false signals, improving reliability in choppy markets.
Trend Zone Visualization: The filled zone between trend line values enhances trend clarity, making it easier to assess momentum.
Time-Restricted Trading: Optional 9:00–15:00 UTC filter aligns signals with high-liquidity sessions.
Notes
Use on standard candlestick or bar charts to ensure accurate signals.
Test the indicator on a demo account to optimize settings for your market and timeframe.
Combine with other analysis (e.g., support/resistance, volume spikes) for better decision-making.
The indicator is not a standalone system; use it as part of a broader trading strategy.
Limitations
Signals may lag in highly volatile or low-liquidity markets due to ATR-based calculations.
The 9:00–15:00 UTC time filter may not suit all markets; disable it for 24-hour assets like forex or crypto.
Stop-loss tick calculations assume consistent tick sizes; verify compatibility with your instrument.
This indicator is designed for traders seeking a robust, trend-following tool with customizable risk management and signal filtering, optimized for active trading sessions.
Heiken Ashi Supertrend ADXHeiken Ashi Supertrend ADX Indicator
Overview
This indicator combines the power of Heiken Ashi candles, Supertrend indicator, and ADX filter to identify strong trend movements across multiple timeframes. Designed primarily for the cryptocurrency market but adaptable to any tradable asset, this system focuses on capturing momentum in established trends while employing a sophisticated triple-layer stop loss mechanism to protect capital and secure profits.
Strategy Mechanics
Entry Signals
The strategy uses a unique blend of technical signals to identify high-probability trade entries:
Heiken Ashi Candles: Looks specifically for Heiken Ashi candles with minimal or no wicks, which signal strong momentum and trend continuation. These "full-bodied" candles represent periods where price moved decisively in one direction with minimal retracement. These are overlayed onto normal candes for more accuarte signalling and plotting
Supertrend Filter: Confirms the underlying trend direction using the Supertrend indicator (default factor: 3.0, ATR period: 10). Entries are aligned with the prevailing Supertrend direction.
ADX Filter (Optional) : Can be enabled to focus only on stronger trending conditions, filtering out choppy or ranging markets. When enabled, trades only trigger when ADX is above the specified threshold (default: 25).
Exit Signals
Positions are closed when either:
An opposing signal appears (Heiken Ashi candle with no wick in the opposite direction)
Any of the three stop loss mechanisms are triggered
Triple-Layer Stop Loss System
The strategy employs a sophisticated three-tier stop loss approach:
ATR Trailing Stop: Adapts to market volatility and locks in profits as the trend extends. This stop moves in the direction of the trade, capturing profit without exiting too early during normal price fluctuations.
Swing Point Stop: Uses natural market structure (recent highs/lows over a lookback period) to place stops at logical support/resistance levels, honoring the market's own rhythm.
Insurance Stop: A percentage-based safety net that protects against sudden adverse moves immediately after entry. This is particularly valuable when the swing point stop might be positioned too far from entry, providing immediate capital protection.
Optimization Features
Customizable Filters : All components (Supertrend, ADX) can be enabled/disabled to adapt to different market conditions
Adjustable Parameters : Fine-tune ATR periods, Supertrend factors, and ADX thresholds
Flexible Stop Loss Settings : Each of the three stop loss mechanisms can be individually enabled/disabled with customizable parameters
Best Practices for Implementation
[Recommended Timeframes : Works best on 4-hour charts and above, where trends develop more reliably
Market Conditions: Performs well across various market conditions due to the ADX filter's ability to identify meaningful trends
Performance Characteristics
When properly optimized, this has demonstrated profit factors exceeding 3 in backtesting. The approach typically produces generous winners while limiting losses through its multi-layered stop loss system. The ATR trailing stop is particularly effective at capturing extended trends, while the insurance stop provides immediate protection against adverse moves.
The visual components on the chart make it easy to follow the strategy's logic, with position status, entry prices, and current stop levels clearly displayed.
This indicator represents a complete trading system with clearly defined entry and exit rules, adaptive stop loss mechanisms, and built-in risk management through position sizing.
Heiken Ashi Supertrend ADX - StrategyHeiken Ashi Supertrend ADX Strategy
Overview
This strategy combines the power of Heiken Ashi candles, Supertrend indicator, and ADX filter to identify strong trend movements across multiple timeframes. Designed primarily for the cryptocurrency market but adaptable to any tradable asset, this system focuses on capturing momentum in established trends while employing a sophisticated triple-layer stop loss mechanism to protect capital and secure profits.
Strategy Mechanics
Entry Signals
The strategy uses a unique blend of technical signals to identify high-probability trade entries:
Heiken Ashi Candles: Looks specifically for Heiken Ashi candles with minimal or no wicks, which signal strong momentum and trend continuation. These "full-bodied" candles represent periods where price moved decisively in one direction with minimal retracement.
Supertrend Filter : Confirms the underlying trend direction using the Supertrend indicator (default factor: 3.0, ATR period: 10). Entries are aligned with the prevailing Supertrend direction.
ADX Filter (Optional) : Can be enabled to focus only on stronger trending conditions, filtering out choppy or ranging markets. When enabled, trades only trigger when ADX is above the specified threshold (default: 25).
Exit Signals
Positions are closed when either:
An opposing signal appears (Heiken Ashi candle with no wick in the opposite direction)
Any of the three stop loss mechanisms are triggered
Triple-Layer Stop Loss System
The strategy employs a sophisticated three-tier stop loss approach:
ATR Trailing Stop: Adapts to market volatility and locks in profits as the trend extends. This stop moves in the direction of the trade, capturing profit without exiting too early during normal price fluctuations.
Swing Point Stop : Uses natural market structure (recent highs/lows over a lookback period) to place stops at logical support/resistance levels, honoring the market's own rhythm.
Insurance Stop: A percentage-based safety net that protects against sudden adverse moves immediately after entry. This is particularly valuable when the swing point stop might be positioned too far from entry, providing immediate capital protection.
Optimization Features
Customizable Filters: All components (Supertrend, ADX) can be enabled/disabled to adapt to different market conditions
Adjustable Parameters: Fine-tune ATR periods, Supertrend factors, and ADX thresholds
Flexible Stop Loss Settings: Each of the three stop loss mechanisms can be individually enabled/disabled with customizable parameters
Best Practices for Implementation
Recommended Timeframes: Works best on 4-hour charts and above, where trends develop more reliably
Market Conditions: Performs well across various market conditions due to the ADX filter's ability to identify meaningful trends
Position Sizing: The strategy uses a percentage of equity approach (default: 3%) for position sizing
Performance Characteristics
When properly optimized, this strategy has demonstrated profit factors exceeding 3 in backtesting. The approach typically produces generous winners while limiting losses through its multi-layered stop loss system. The ATR trailing stop is particularly effective at capturing extended trends, while the insurance stop provides immediate protection against adverse moves.
The visual components on the chart make it easy to follow the strategy's logic, with position status, entry prices, and current stop levels clearly displayed.
This strategy represents a complete trading system with clearly defined entry and exit rules, adaptive stop loss mechanisms, and built-in risk management through position sizing.
Follow Line Strategy Version 2.5 (React HTF)Follow Line Strategy v2.5 (React HTF) - TradingView Script Usage
This strategy utilizes a "Follow Line" concept based on Bollinger Bands and ATR to identify potential trading opportunities. It includes advanced features like optional working hours filtering, higher timeframe (HTF) trend confirmation, and improved trend-following entry/exit logic. Version 2.5 introduces reactivity to HTF trend changes for more adaptive trading.
Key Features:
Follow Line: The core of the strategy. It dynamically adjusts based on price breakouts beyond Bollinger Bands, using either the low/high or ATR-adjusted levels.
Bollinger Bands: Uses a standard Bollinger Bands setup to identify overbought/oversold conditions.
ATR Filter: Optionally uses the Average True Range (ATR) to adjust the Follow Line offset, providing a more dynamic and volatility-adjusted entry point.
Optional Trading Session Filter: Allows you to restrict trading to specific hours of the day.
Higher Timeframe (HTF) Confirmation: A significant feature that allows you to confirm trade signals with the trend on a higher timeframe. This can help to filter out false signals and improve the overall win rate.
HTF Selection Method: Choose between Auto and Manual HTF selection:
Auto: The script automatically determines the appropriate HTF based on the current chart timeframe (e.g., 1min -> 15min, 5min -> 4h, 1h -> 1D, Daily -> Monthly).
Manual: Allows you to select a specific HTF using the Manual Higher Timeframe input.
Trend-Following Entries/Exits: The strategy aims to enter trades in the direction of the established trend, using the Follow Line to define the trend.
Reactive HTF Trend Changes: v2.5 exits positions not only based on the trade timeframe (TTF) trend changing, but also when the higher timeframe trend reverses against the position. This makes the strategy more responsive to larger market movements.
Alerts: Provides buy and sell alerts for convenient trading signal notifications.
Visualizations: Plots the Follow Line for both the trade timeframe and the higher timeframe (optional), making it easy to understand the strategy's logic.
How to Use:
Add to Chart: Add the "Follow Line Strategy Version 2.5 (React HTF)" script to your TradingView chart.
Configure Settings: Customize the strategy's settings to match your trading style and preferences. Here's a breakdown of the key settings:
Indicator Settings:
ATR Period: The period used to calculate the ATR. A smaller period is more sensitive to recent price changes.
Bollinger Bands Period: The period used for the Bollinger Bands calculation. A longer period results in smoother bands.
Bollinger Bands Deviation: The number of standard deviations from the moving average that the Bollinger Bands are plotted. Higher deviations create wider bands.
Use ATR for Follow Line Offset?: Enable to use ATR to calculate the Follow Line offset. Disable to use the simple high/low.
Show Trade Signals on Chart?: Enable to show BUY/SELL labels on the chart.
Time Filter:
Use Trading Session Filter?: Enable to restrict trading to specific hours of the day.
Trading Session: The trading session to use (e.g., 0930-1600 for regular US stock market hours). Use 0000-2400 for all hours.
Higher Timeframe Confirmation:
Enable HTF Confirmation?: Enable to use the HTF trend to filter trade signals. If enabled, only trades in the direction of the HTF trend will be taken.
HTF Selection Method: Choose between "Auto" and "Manual" HTF selection.
Manual Higher Timeframe: If "Manual" is selected, choose the specific HTF (e.g., 240 for 4 hours, D for daily).
Show HTF Follow Line?: Enable to plot the HTF Follow Line on the chart.
Understanding the Signals:
Buy Signal: The price breaks above the upper Bollinger Band, and the HTF (if enabled) confirms the uptrend.
Sell Signal: The price breaks below the lower Bollinger Band, and the HTF (if enabled) confirms the downtrend.
Exit Long: The trade timeframe trend changes to downtrend or the higher timeframe trend changes to downtrend.
Exit Short: The trade timeframe trend changes to uptrend or the higher timeframe trend changes to uptrend.
Alerts:
The script includes alert conditions for buy and sell signals. To set up alerts, click the "Alerts" button in TradingView and select the desired alert condition from the script. The alert message provides the ticker and interval.
Backtesting and Optimization:
Use TradingView's Strategy Tester to backtest the strategy on different assets and timeframes.
Experiment with different settings to optimize the strategy for your specific trading style and risk tolerance. Pay close attention to the ATR Period, Bollinger Bands settings, and the HTF confirmation options.
Tips and Considerations:
HTF Confirmation: The HTF confirmation can significantly improve the strategy's performance by filtering out false signals. However, it can also reduce the number of trades.
Risk Management: Always use proper risk management techniques, such as stop-loss orders and position sizing, when trading any strategy.
Market Conditions: The strategy may perform differently in different market conditions. It's important to backtest and optimize the strategy for the specific markets you are trading.
Customization: Feel free to modify the script to suit your specific needs. For example, you could add additional filters or entry/exit conditions.
Pyramiding: The pyramiding = 0 setting prevents multiple entries in the same direction, ensuring the strategy doesn't compound losses. You can adjust this value if you prefer to pyramid into winning positions, but be cautious.
Lookahead: The lookahead = barmerge.lookahead_off setting ensures that the HTF data is calculated based on the current bar's closed data, preventing potential future peeking bias.
Trend Determination: The logic for determining the HTF trend and reacting to changes is critical. Carefully review the f_calculateHTFData function and the conditions for exiting positions to ensure you understand how the strategy responds to different market scenarios.
Disclaimer:
This script is for informational and educational purposes only. It is not financial advice, and you should not trade based solely on the signals generated by this script. Always do your own research and consult with a qualified financial advisor before making any trading decisions. The author is not responsible for any losses incurred as a result of using this script.
Market Structure Break with Volume & ATR#### Indicator Overview:
The *Market Structure Break with Volume & ATR (MSB+VolATR)* indicator is designed to identify significant market structure breakouts and breakdowns using a combination of price action, volume analysis, and volatility (ATR). It is particularly useful for traders who rely on higher timeframes for swing trading or positional trading. The indicator highlights bullish and bearish breakouts, retests, fakeouts, and potential buy/sell signals based on RSI overbought/oversold conditions.
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### Key Features:
1. *Market Structure Analysis*:
- Identifies swing highs and lows on a user-defined higher timeframe.
- Detects breakouts and breakdowns when price exceeds these levels with volume and ATR validation.
2. *Volume Validation*:
- Ensures breakouts are accompanied by above-average volume, reducing the likelihood of false signals.
3. *ATR Filter*:
- Filters out insignificant breakouts by requiring the breakout size to exceed a multiple of the ATR.
4. *RSI Integration*:
- Adds a momentum filter by considering overbought/oversold conditions using RSI.
5. *Visual Enhancements*:
- Draws colored boxes to highlight breakout zones.
- Labels breakouts, retests, and fakeouts for easy interpretation.
- Displays stop levels for potential trades.
6. *Alerts*:
- Provides alert conditions for buy and sell signals, enabling real-time notifications.
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### Input Settings and Their Effects:
1. **Timeframe (tf):
- Determines the higher timeframe for market structure analysis.
- *Effect*: A higher timeframe (e.g., 1D) reduces noise and provides more reliable swing points, while a lower timeframe (e.g., 4H) may generate more frequent but less reliable signals.
2. **Lookback Period (length):
- Defines the number of historical bars used to identify significant highs and lows.
- *Effect*: A longer lookback period (e.g., 50) captures broader market structure, while a shorter period (e.g., 20) reacts faster to recent price action.
3. **ATR Length (atr_length):
- Sets the period for ATR calculation.
- *Effect*: A shorter ATR length (e.g., 14) reacts faster to recent volatility, while a longer length (e.g., 21) smooths out volatility spikes.
4. **ATR Multiplier (atr_multiplier):
- Filters insignificant breakouts by requiring the breakout size to exceed ATR × multiplier.
- *Effect*: A higher multiplier (e.g., 0.2) reduces false signals but may miss smaller breakouts.
5. **Volume Multiplier (volume_multiplier):
- Sets the volume threshold for breakout validation.
- *Effect*: A higher multiplier (e.g., 1.0) ensures stronger volume confirmation but may reduce the number of signals.
6. **RSI Length (rsi_length):
- Defines the period for RSI calculation.
- *Effect*: A shorter RSI length (e.g., 10) makes the indicator more sensitive to recent price changes, while a longer length (e.g., 20) smooths out RSI fluctuations.
7. *RSI Overbought/Oversold Levels*:
- Sets the thresholds for overbought (default: 70) and oversold (default: 30) conditions.
- *Effect*: Adjusting these levels can make the indicator more or less conservative in generating signals.
8. **Stop Loss Multiplier (SL_Multiplier):
- Determines the distance of the stop-loss level from the entry price based on ATR.
- *Effect*: A higher multiplier (e.g., 2.0) provides wider stops, reducing the risk of being stopped out prematurely but increasing potential losses.
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### How It Works:
1. *Breakout Detection*:
- A bullish breakout occurs when the close exceeds the highest high of the lookback period, with volume above the threshold and breakout size exceeding ATR × multiplier.
- A bearish breakout occurs when the close falls below the lowest low of the lookback period, with similar volume and ATR validation.
2. *Retest Logic*:
- After a breakout, if price retests the breakout zone without closing beyond it, a retest label is displayed.
3. *Fakeout Detection*:
- If price briefly breaks out but reverses back into the range, a fakeout label is displayed.
4. *Buy/Sell Signals*:
- A sell signal is generated when price reverses below a bullish breakout zone and RSI is overbought.
- A buy signal is generated when price reverses above a bearish breakout zone and RSI is oversold.
5. *Stop Levels*:
- Stop-loss levels are plotted based on ATR × SL_Multiplier, providing a visual guide for risk management.
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### Who Can Use It and How:
1. *Swing Traders*:
- Use the indicator on daily or 4-hour timeframes to identify high-probability breakout trades.
- Combine with other technical analysis tools (e.g., trendlines, Fibonacci levels) for confirmation.
2. *Positional Traders*:
- Apply the indicator on weekly or daily charts to capture long-term trends.
- Use the stop-loss levels to manage risk over extended periods.
3. *Algorithmic Traders*:
- Integrate the buy/sell signals into automated trading systems.
- Use the alert conditions to trigger trades programmatically.
4. *Risk-Averse Traders*:
- Adjust the ATR and volume multipliers to filter out low-probability trades.
- Use wider stop-loss levels to avoid premature exits.
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### Where to Use It:
- *Forex*: Identify breakouts in major currency pairs.
- *Stocks*: Spot trend reversals in high-volume stocks.
- *Commodities*: Trade breakouts in gold, oil, or other commodities.
- *Crypto*: Apply to Bitcoin, Ethereum, or other cryptocurrencies for volatile breakout opportunities.
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### Example Use Case:
- *Timeframe*: 1D
- *Lookback Period*: 50
- *ATR Length*: 14
- *ATR Multiplier*: 0.1
- *Volume Multiplier*: 0.5
- *RSI Length*: 14
- *RSI Overbought/Oversold*: 70/30
- *SL Multiplier*: 1.5
In this setup, the indicator will:
1. Identify significant swing highs and lows on the daily chart.
2. Validate breakouts with volume and ATR filters.
3. Generate buy/sell signals when price reverses and RSI confirms overbought/oversold conditions.
4. Plot stop-loss levels for risk management.
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### Conclusion:
The *MSB+VolATR* indicator is a versatile tool for traders seeking to capitalize on market structure breakouts with added confirmation from volume and volatility. By customizing the input settings, traders can adapt the indicator to their preferred trading style and risk tolerance. Whether you're a swing trader, positional trader, or algorithmic trader, this indicator provides actionable insights to enhance your trading strategy.
Stop/Take BoundsThe Stop/Take Bounds indicator is tool for setting dynamic stop-loss and take-profit levels based on percentage distance from the price. Unlike traditional ATR-based methods, this indicator allows traders to set stop levels as a fixed percentage of the price and define the take-profit multiple.
- Stop-loss distanceis determined as a percentage of the current price (e.g., 1% means the stop-loss is always 1% away from the price).
- Take-profit distance is calculated by multiplying the stop-loss distance by a user-defined multiplier (e.g., a multiplier of 2 places the take-profit level twice as far as the stop-loss).
- The indicator plots red lines for stop-loss levels and green lines for take-profit levels, making it easy to visualize risk-to-reward scenarios.
How to Use
1. Set Stop-Loss Distance (%) – Define how far the stop-loss should be from the price.
2. Set Take-Profit Multiplier – Choose how many times larger the take-profit should be compared to the stop-loss.
3. Apply to Long and Short Trades – The indicator automatically plots levels for both long and short positions.
4. Use in Manual or Algorithmic Trading – Ideal for discretionary traders as well as for integration into algorithmic strategies.
Use Cases
- Risk Management – Helps maintain disciplined risk-to-reward ratios.
- Strategy Development – Can be used in the creation of algorithmic trading systems.
- Trailing Stop Simulation – Can act as a trailing stop mechanism when used dynamically.
This indicator is a great addition to any trading strategy!
Advanced Adaptive Grid Trading StrategyThis strategy employs an advanced grid trading approach that dynamically adapts to market conditions, including trend, volatility, and risk management considerations. The strategy aims to capitalize on price fluctuations in both rising (long) and falling (short) markets, as well as during sideways movements. It combines multiple indicators to determine the trend and automatically adjusts grid parameters for more efficient trading.
How it Works:
Trend Analysis:
Short, long, and super long Moving Averages (MA) to determine the trend direction.
RSI (Relative Strength Index) to identify overbought and oversold levels, and to confirm the trend.
MACD (Moving Average Convergence Divergence) to confirm momentum and trend direction.
Momentum indicator.
The strategy uses a weighted scoring system to assess trend strength (strong bullish, moderate bullish, strong bearish, moderate bearish, sideways).
Grid System:
The grid size (the distance between buy and sell levels) changes dynamically based on market volatility, using the ATR (Average True Range) indicator.
Grid density also adapts to the trend: in a strong trend, the grid is denser in the direction of the trend.
Grid levels are shifted depending on the trend direction (upwards in a bear market, downwards in a bull market).
Trading Logic:
The strategy opens long positions if the trend is bullish and the price reaches one of the lower grid levels.
It opens short positions if the trend is bearish and the price reaches one of the upper grid levels.
In a sideways market, it can open positions in both directions.
Risk Management:
Stop Loss for every position.
Take Profit for every position.
Trailing Stop Loss to protect profits.
Maximum daily loss limit.
Maximum number of positions limit.
Time-based exit (if the position is open for too long).
Risk-based position sizing (optional).
Input Options:
The strategy offers numerous settings that allow users to customize its operation:
Timeframe: The chart's timeframe (e.g., 1 minute, 5 minutes, 1 hour, 4 hours, 1 day, 1 week).
Base Grid Size (%): The base size of the grid, expressed as a percentage.
Max Positions: The maximum number of open positions allowed.
Use Volatility Grid: If enabled, the grid size changes dynamically based on the ATR indicator.
ATR Length: The period of the ATR indicator.
ATR Multiplier: The multiplier for the ATR to fine-tune the grid size.
RSI Length: The period of the RSI indicator.
RSI Overbought: The overbought level for the RSI.
RSI Oversold: The oversold level for the RSI.
Short MA Length: The period of the short moving average.
Long MA Length: The period of the long moving average.
Super Long MA Length: The period of the super long moving average.
MACD Fast Length: The fast period of the MACD.
MACD Slow Length: The slow period of the MACD.
MACD Signal Length: The period of the MACD signal line.
Stop Loss (%): The stop loss level, expressed as a percentage.
Take Profit (%): The take profit level, expressed as a percentage.
Use Trailing Stop: If enabled, the strategy uses a trailing stop loss.
Trailing Stop (%): The trailing stop loss level, expressed as a percentage.
Max Loss Per Day (%): The maximum daily loss, expressed as a percentage.
Time Based Exit: If enabled, the strategy exits the position after a certain amount of time.
Max Holding Period (hours): The maximum holding time in hours.
Use Risk Based Position: If enabled, the strategy calculates position size based on risk.
Risk Per Trade (%): The risk per trade, expressed as a percentage.
Max Leverage: The maximum leverage.
Important Notes:
This strategy does not guarantee profits. Cryptocurrency markets are volatile, and trading involves risk.
The strategy's effectiveness depends on market conditions and settings.
It is recommended to thoroughly backtest the strategy under various market conditions before using it live.
Past performance is not indicative of future results.
Multi-Timeframe Parabolic SAR Strategy ver 1.0Multi-Timeframe Parabolic SAR Strategy (MTF PSAR) - Enhanced Trend Trading
This strategy leverages the power of the Parabolic SAR (Stop and Reverse) indicator across multiple timeframes to provide robust trend identification, precise entry/exit signals, and dynamic trailing stop management. By combining the insights of both the current chart's timeframe and a user-defined higher timeframe, this strategy aims to improve trading accuracy, reduce risk, and capture more significant market moves.
Key Features:
Dual Timeframe Analysis: Simultaneously analyzes the Parabolic SAR on the current chart and a higher timeframe (e.g., Daily PSAR on a 1-hour chart). This allows you to align your trades with the dominant trend and filter out noise from lower timeframes.
Configurable PSAR: Fine-tune the PSAR calculation with adjustable Start, Increment, and Maximum values to optimize sensitivity for your trading style and the asset's volatility.
Independent Timeframe Control: Choose to display and trade based on either or both the current timeframe PSAR and the higher timeframe PSAR. Focus on the most relevant information for your analysis.
Clear Visual Signals: Distinct colors for the current and higher timeframe PSAR dots provide a clear visual representation of potential entry and exit points.
Multiple Entry Strategies: The strategy offers flexible entry conditions, allowing you to trade based on:
Confirmation: Both current and higher timeframe PSAR signals agree and the current timeframe PSAR has just flipped direction. (Most conservative)
Current Timeframe Only: Trades based solely on the current timeframe PSAR, ideal for when the higher timeframe is less relevant or disabled.
Higher Timeframe Only: Trades based solely on the higher timeframe PSAR.
Dynamic Trailing Stop (PSAR-Based): Implements a trailing stop-loss based on the current timeframe's Parabolic SAR. This helps protect profits by automatically adjusting the stop-loss as the price moves in your favor. Exits are triggered when either the current or HTF PSAR flips.
No Repainting: Uses lookahead=barmerge.lookahead_off in the security() function to ensure that the higher timeframe data is accessed without any data leakage, preventing repainting issues.
Fully Configurable: All parameters (PSAR settings, higher timeframe, visibility, colors) are adjustable through the strategy's settings panel, allowing for extensive customization and optimization.
Suitable for Various Trading Styles: Applicable to swing trading, day trading, and trend-following strategies across various markets (stocks, forex, cryptocurrencies, etc.).
How it Works:
PSAR Calculation: The strategy calculates the standard Parabolic SAR for both the current chart's timeframe and the selected higher timeframe.
Trend Identification: The direction of the PSAR (dots below price = uptrend, dots above price = downtrend) determines the current trend for each timeframe.
Entry Signals: The strategy generates buy/sell signals based on the chosen entry strategy (Confirmation, Current Timeframe Only, or Higher Timeframe Only). The Confirmation strategy offers the highest probability signals by requiring agreement between both timeframes.
Trailing Stop Exit: Once a position is entered, the strategy uses the current timeframe PSAR as a dynamic trailing stop. The stop-loss is automatically adjusted as the PSAR dots move, helping to lock in profits and limit losses. The strategy exits when either the Current or HTF PSAR changes direction.
Backtesting and Optimization: The strategy automatically backtests on the chart's historical data, allowing you to evaluate its performance and optimize the settings for different assets and timeframes.
Example Use Cases:
Trend Confirmation: A trader on a 1-hour chart observes a bullish PSAR flip on the current timeframe. They check the MTF PSAR strategy and see that the Daily PSAR is also bullish, confirming the strength of the uptrend and providing a high-probability long entry signal.
Filtering Noise: A trader on a 5-minute chart wants to avoid whipsaws caused by short-term price fluctuations. They use the strategy with a 1-hour higher timeframe to filter out noise and only trade in the direction of the dominant trend.
Dynamic Risk Management: A trader enters a long position and uses the current timeframe PSAR as a trailing stop. As the price rises, the PSAR dots move upwards, automatically raising the stop-loss and protecting profits. The trade is exited when the current (or HTF) PSAR flips to bearish.
Disclaimer:
The Parabolic SAR is a lagging indicator and can produce false signals, particularly in ranging or choppy markets. This strategy is intended for educational and informational purposes only and should not be considered financial advice. It is essential to backtest and optimize the strategy thoroughly, use it in conjunction with other technical analysis tools, and implement sound risk management practices before using it with real capital. Past performance is not indicative of future results. Always conduct your own due diligence and consider your risk tolerance before making any trading decisions.
Liquidity Market Seeking SwiftEdgeThis indicator is designed to identify potential liquidity levels on the chart by detecting swing highs and lows, which are often areas where stop-loss orders or significant orders accumulate. It visualizes these levels with horizontal lines and labels on the right side of the chart, color-coded based on volume to help traders understand where the market might seek liquidity.
How It Works
Swing Highs and Lows: The indicator uses the ta.pivothigh and ta.pivotlow functions to identify significant swing points over a user-defined lookback period (Swing Length). These points are considered potential liquidity levels where stop-loss orders might be placed.
Volume Analysis: The indicator compares the volume at each swing point to the average volume over a specified period (Volume Average Length). Levels with above-average volume are colored red, indicating higher liquidity, while levels with below-average volume are colored green.
Liquidity Visualization: Horizontal dashed lines are drawn at each identified level, extending across the chart. Labels on the right side display the estimated liquidity amount (simulated based on volume and a multiplier, Volume Multiplier for Liquidity).
Sell Signal: A "SELL NOW" label appears when the price approaches a liquidity level after an uptrend (detected using a simple moving average crossover). This suggests a potential reversal as the market may target liquidity at that level.
Strategy Concept: Market Seeking Liquidity
The indicator is based on the concept that markets often move toward areas of high liquidity, such as clusters of stop-loss orders or significant order accumulations. These liquidity pools are typically found around swing highs and lows, where traders place their stop-losses or large orders. By identifying these levels and highlighting those with higher volume (red lines), the indicator aims to show where the market might move to "grab" this liquidity. For example, after an uptrend, the market may reverse at a swing high to take out stop-losses above that level, providing liquidity for larger players to enter or exit positions.
Settings
Swing Length: The number of bars to look back for detecting swing highs and lows. Default is 20.
Liquidity Threshold: The price threshold for merging nearby levels to avoid duplicates. Default is 0.001.
Volume Average Length: The period for calculating the average volume to compare against. Default is 20.
Volume Multiplier for Liquidity: A multiplier to scale the volume into a simulated liquidity amount (displayed as "K"). Default is 1000.
Usage Notes
Use this indicator on any timeframe, though it may be more effective on higher timeframes (e.g., 1H, 4H) where swing points are more significant.
Red lines indicate levels with higher volume, suggesting stronger liquidity pools that the market might target.
Green lines indicate levels with lower volume, which may be less significant.
The "SELL NOW" signal is a basic example of how to use liquidity levels for trading decisions. It appears when the price approaches a liquidity level after an uptrend, but it should be used in conjunction with other analysis.
Adjust the Volume Multiplier for Liquidity to scale the displayed liquidity amounts based on your instrument (e.g., forex pairs may need a higher multiplier than indices).
Liquidations Levels [RunRox]📈 Liquidation Levels is an indicator designed to visualize key price levels on the chart, highlighting potential reversal points where liquidity may trigger significant price movements.
Liquidity is essential in trading - price action consistently moves from one liquidity area to another. We’ve created this free indicator to help traders easily identify and visualize these liquidity zones on their charts.
📌 HOW IT WORKS
The indicator works by marking visible highs and lows, points widely recognized by traders. Because many traders commonly place their stop-loss orders beyond these visible extremes, significant liquidity accumulates behind these points. By analyzing trading volume and visible extremes, the indicator estimates areas where clusters of stop-loss orders (liquidity pools) are likely positioned, giving traders valuable insights into potential market moves.
As shown in the screenshot above, the price aggressively moved toward Sell-Side liquidity. After sweeping this liquidity level for the second time, it reversed and began targeting Buy-Side liquidity. This clearly demonstrates how price moves from one liquidity pool to another, continually seeking out liquidity to fuel its next directional move.
As shown in the screenshot, price levels with fewer anticipated trader stop-losses are indicated by less vibrant, faded colors. When the lines become more saturated and vivid, it signals that sufficient liquidity - in the form of clustered stop-losses has accumulated, potentially attracting price movement toward these areas.
⚙️ SETTINGS
🔹 Period – Increasing this setting makes the marked highs and lows more significant, filtering out minor price swings.
🔹 Low Volume – Select the color displayed for low-liquidity levels.
🔹 High Volume – Select the color displayed for high-liquidity levels.
🔹 Levels to Display – Choose between 1 and 15 nearest liquidity levels to be shown on the chart.
🔹 Volume Sensitivity – Adjust the sensitivity of the indicator to volume data on the chart.
🔹 Show Volume – Enable or disable the display of volume values next to each liquidity level.
🔹 Max Age – Limits displayed liquidity levels to those not older than the specified number of bars.
✅ HOW TO USE
One method of using this indicator is demonstrated in the screenshot above.
Price reached a high-liquidity level and showed an initial reaction. We then waited for a second confirmation - a liquidity sweep followed by a clear market structure break - to enter the trade.
Our target is set at the liquidity accumulated below, with the stop-loss placed behind the manipulation high responsible for the liquidity sweep.
By following this approach, you can effectively identify trading opportunities using this indicator.
🔶 We’ve made every effort to create an indicator that’s as simple and user-friendly as possible. We’ll continue to improve and enhance it based on your feedback and suggestions in the future.
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.
BuyTheDips Trade on Trend and Fixed TP/SL
This strategy is designed to trade in the direction of the trend using exponential moving average (EMA) crossovers as signals while employing fixed percentages for take profit (TP) and stop loss (SL) to manage risk and reward. It is suitable for both scalping and swing trading on any timeframe, with its default settings optimized for short-term price movements.
How It Works
EMA Crossovers:
The strategy uses two EMAs: a fast EMA (shorter period) and a slow EMA (longer period).
A buy signal is triggered when the fast EMA crosses above the slow EMA, indicating a potential bullish trend.
A sell signal is triggered when the fast EMA crosses below the slow EMA, signaling a bearish trend.
Trend Filtering:
To improve signal reliability, the strategy only takes trades in the direction of the overall trend:
Long trades are executed only when the fast EMA is above the slow EMA (bullish trend).
Short trades are executed only when the fast EMA is below the slow EMA (bearish trend).
This filtering ensures trades are aligned with the prevailing market direction, reducing false signals.
Risk Management (Fixed TP/SL):
The strategy uses fixed percentages for take profit and stop loss:
Take Profit: A percentage above the entry price for long trades (or below for short trades).
Stop Loss: A percentage below the entry price for long trades (or above for short trades).
These percentages can be customized to balance risk and reward according to your trading style.
For example:
If the take profit is set to 2% and the stop loss to 1%, the strategy operates with a 2:1 risk-reward ratio. BINANCE:BTCUSDT
Precision Trade Zone By KittisakThis indicator is designed for Money Management calculations, helping to facilitate risk management in trading, determining suitable leverage based on acceptable risk, and adjusting the Stop Loss level to align with the calculated leverage.
Abbreviation Descriptions
LR : Suitable Leverage.
EP : Entry Price.
BEP : Break-Even Point (a point where you can move your Stop Loss to prevent losses once the price reaches a certain level).
SL : Stop Loss (a recalculated Stop Loss level to match the leverage. You should use this as the Stop Loss price instead of the initial level you set).
TP : Take Profit (a point where you take profit based on the defined risk-reward ratio).
Note
When first activating the indicator, an error may occur, and no output will be displayed. This happens because you must first specify the Entry Price and Stop Loss in the indicator settings.
How Much Leverage Should You Use?
It may seem like a simple question but is difficult to answer.
Method for Calculating Suitable Leverage
Use the formula:
Leverage = Acceptable Loss / (Distance between Entry Price and Stop Loss + (Buy Fee + Sell Fee))
Calculating the Correct Stop Loss Point
(Stop Loss levels will be slightly adjusted or extended)
For Long Positions :
New Stop Loss = Entry Price * (1 - Acceptable Loss / (Calculated Leverage * 100))
For Short Positions :
New Stop Loss = Entry Price * (1 + Acceptable Loss / (Calculated Leverage * 100))
Calculating the Correct Take Profit Point
(Take Profit levels will be slightly adjusted or extended)
For Long Positions :
Take Profit = Entry Price * (1 + (Acceptable Loss / (Calculated Leverage * 100) * RR) + ((Buy Fee + Sell Fee) / 100))
For Short Positions :
Take Profit = Entry Price * (1 - (Acceptable Loss / (Calculated Leverage * 100) * RR) + ((Buy Fee + Sell Fee) / 100))
Benefits of This Calculation
1. Accurate Risk Assessment
The calculated leverage accounts for trading fees. For example, if you aim for a 2% loss, this method ensures the actual loss is exactly 2%, not more (e.g., 2% plus fees).
2. Eliminates Guesswork
Randomly setting leverage can lead to risks because the Stop Loss level may not align with your position. This calculation ensures that the leverage aligns precisely with your desired Stop Loss level.
3. Realistic Profit Targets
For example, with a 2% acceptable loss and a 1:2 RR, you expect a 4% profit. However, without this calculation, fees may reduce your profit below 4%. This method includes fees, ensuring your profit matches the intended target.
Caution
This indicator does not account for slippage or requotes. Use it with caution and allow a buffer for slippage in your calculations.
Indicator นี้มีไว้สำหรับคำนวณ Money Management ซึ่งจะช่วยอำนวยความสะดวกในการจัดการความเสี่ยงในการเทรด การคำนวณ Leverage ที่เหมาะสมกับความเสี่ยงที่คุณยอมรับได้ และจัดการจุด Stop Loss ให้เหมาะสมกับ Leverage นั้น
คำอธิบายเกี่ยวกับคำย่อ
LR หมายถึง Leverage ที่เหมาะสม
EP หมายถึง Entry Price หรือราคาเข้าซื้อ
BEP หมายถึง Break-Even Point หรือจุดคุ้มทุน (คุณสามารถย้าย Stop Loss มาที่จุดนี้เมื่อราคาไปถึงจุดหนึ่งเพื่อป้องกันการขาดทุนได้)
SL หมายถึง Stop Loss (ซึ่งเป็น Stop Loss ที่คำนวณใหม่เพื่อให้ตำแหน่งเหมาะสมกับ Leverage ที่คำนวณได้ คุณควรใช้จุดนี้เพื่อเป็นราคา Stop Loss แทนจุด Stop Loss ที่คุณกำหนดไว้ในตอนแรก)
TP หมายถึง Take Profit (เป็นจุดที่คุณจะขายทำกำไรตาม RR ที่กำหนดไว้)
* หมายเหตุ เมื่อเริ่มเปิด Indicator จะเกิด Error ขึ้น และไม่มีผลลัพท์ใด ๆ แสดงให้เห็น นั่นเป็นเพราะคุณต้องเข้าไปกำหนด Entry Price และ Stop Loss ในการตั้งค่าของ Indicator เสียก่อน
ต้องใช้ Leverage เท่าไหร่? มันเป็นคำถามที่ดูเหมือนง่าย แต่ตอบยาก
วิธีคำนวณ Leverage ที่เหมาะสม ใช้สมการคือ
Levarage = การขาดทุนที่ยอมรับได้ / (ระยะห่างระหว่าง Entry Price และ Stop Loss + (ค่าธรรมเนียมซื้อ + ค่าธรรมเนียมขาย))
นำผลลัพท์ Leverage ที่ได้มาคำนวณเพื่อหาจุด Stop Loss ที่ถูกต้อง (จุดของ Stop Loss จะมีการยืดขยายออกไปเล็กน้อย) โดยใช้สมการ
ตำแหน่ง Stop Loss ใหม่ = Entry Price * (1 - การขาดทุนที่ยอมรับได้ / (Leverage ที่คำนวณได้ * 100)) // สำหรับ Long
ตำแหน่ง Stop Loss ใหม่ = Entry Price * (1 + การขาดทุนที่ยอมรับได้ / (Leverage ที่คำนวณได้ * 100)) // สำหรับ Short
นำผลลัพท์ Leverage ที่ได้มาคำนวณเพื่อหาจุด Take Profit ที่ถูกต้อง (จุดของ Take Profit จะมีการยืดขยายออกไปเล็กน้อย) โดยใช้สมการ
ตำแหน่ง Take Profit = Entry Price * (1 + (การขาดทุนที่ยอมรับได้ / (Leverage ที่คำนวณได้ * 100) * RR) + ((ค่าธรรมเนียมซื้อ + ค่าธรรมเนียมขาย) / 100)) // สำหรับ Long
ตำแหน่ง Take Profit = Entry Price * (1 - (การขาดทุนที่ยอมรับได้ / (Leverage ที่คำนวณได้ * 100) * RR) + ((ค่าธรรมเนียมซื้อ + ค่าธรรมเนียมขาย) / 100)) // สำหรับ Short
ข้อดีของการคำนวณคือ
1. คุณจะได้ค่า Leverage ที่เหมาะสมกับความเสี่ยงที่คุณยอมรับได้โดยรวมค่าธรรมเนียมเข้าไปในนั้นแล้ว นั่นหมายความว่า ความสูญเสียจะเป็น 2% (ตามตัวอย่าง) จริง ๆ ไม่ใช่ 2% และถูกหักค่าธรรมเนียมเพิ่มอีก กลายเป็นสูญเสียมากกว่า 2%
2. การตั้ง Leverage มั่ว ๆ กลายเป็นความเสี่ยง นั่นเพราะตำแหน่งของ Stop Loss ไม่ได้อยู่ในจุดที่ควรจะเป็น การคำนวณนี้ช่วยให้คุณได้ Leverage ในตำแหน่ง Stop Loss ที่คุณต้องการโดยแท้จริง
3. ผลกำไรที่ได้รับตรงกับความต้องการจริง ๆ เช่น การขาดทุนที่ยอมรับได้ 2% และ RR 1:2 สิ่งที่คุณคิดคือกำไร 4% แต่จริง ๆ แล้วไม่ถึง 4% นั่นเพราะว่าโดนหักค่าธรรมเนียมไปส่วนหนึ่ง การคำนวณนี้ได้รวมค่าธรรมเนียมให้แล้ว คุณจึงได้กำไรที่ 4% อย่างถูกต้องตามต้องการ
ข้อควรระวัง
Indicator นี้ไม่ได้มีการควบคุมความเสี่ยงในเรื่องของ slippage หรือ requote โปรดใช้งานอย่างระมัดระวังและมีการเผื่อระยะสำหรับ slippage ด้วย
Smart Money Breakouts [iskess 01-02 11:05]This is an big update to the excellent Smart Money Breakout Script published in Oct 2023 by ChartPrime who, to my knowledge, was the original author.
FULL CREDIT GOES TO CHARTPRIME FOR THIS ORIGINAL WORK.
Per the moderator's rules, you will find below a meaningful, detailed self-contained description that does not rely on delegation to the open source code or links to other content. You will find in the description details on what the script does, how it does that, how to use it, and how it is original.
The "Smart Money Breakouts" indicator is designed to identify breakouts based on changes in character (CHOCH) or breaks of structure (BOS) patterns, facilitating automated trading with user-defined Take Profit (TP) level.
The indicator incorporates essential elements such as volume analysis and a data table to assist traders in optimizing their strategies.
🔸Breakout Detection:
The indicator scans price movements for "Change in Character" (CHOCH) and "Break of Structure" (BOS) patterns, signaling potential breakout opportunities in the market.
🔸User-Defined TP/SL :
Traders can customize the Take Profit (TP) and Stop Loss (SL) through the indicator settings, with these levels dynamically calculated based on the Average True Range (ATR). This allows for precise risk management and profit targets that adapt to market volatility. Traders can also select the lookback period for the TP/SL calculations.
🔸Volume Analysis and Trade Direction Specific Analysis:
The indicator includes a volume checker that provides valuable insights into the strength of the breakout, taking into account trade direction.
🔸If the volume label is red and the trade is long, it suggests a higher likelihood of hitting the Stop Loss (SL).
🔸If the volume label is green and the trade is long, it indicates a higher probability of hitting the Take Profit (TP).
🔸For short trades, a red volume label suggests a higher likelihood of hitting TP, while a green label suggests a higher likelihood of hitting SL.
🔸A yellow volume label suggests that the volume is inconclusive, neither favoring bullish nor bearish movements.
🔸Data Table:
The indicator features a data table that keeps track of the number of winning and losing trades for specific timeframes or configurations. It also shows the percentage of profits vs losses, and the overall profit/loss for the selected lookback period.
This table serves as a valuable tool for traders to analyze performance and discover optimal settings and timeframes.
The "Smart Money Breakouts" indicator provides traders with a comprehensive solution for breakout trading, combining technical analysis of changes in character and breaks of structure, volume insights, and performance tracking while dynamically adjusting TP and SL levels based on market volatility through the ATR.
This version of the script is a "significant improvement" from Chart Prime's original work in the following ways:
- A selectable range of candles for the profit/loss calculations to look back on.
- An updated table that includes the percentage of wins/losses, and and overall P&L during the selected lookback range.
- The user can now select only Long trades, Short trades, or both.
- The percentage gain/loss is now indicated for every trade on the chart.
- The user can now select a different multiplier for Stop Loss or Take Profit thresholds.
RISK MANAGEMENT TABLEThis updated Risk Management Indicator is a powerful and customizable tool designed to help traders effectively manage risk on every trade. By dynamically calculating position size, stop-loss, and take-profit levels, it enables traders to stay disciplined and follow predefined risk parameters directly on their charts.
Features:
Dynamic Stop-Loss and Take-Profit Levels:
Stop-loss is based on the Average True Range (ATR), offering a flexible way to account for
market volatility.
Take-profit levels can be customized as a percentage of the entry price, providing a clear
target for trade exits.
Position Sizing Calculation:
The indicator computes the maximum position size by considering:
Trade amount (montant_ligne).
Risk percentage per trade.
Transaction fees.
Visual Representation:
Displays stop-loss and take-profit levels on the chart as customizable lines.
Optional visibility of these lines through checkboxes in the settings panel.
Comprehensive Risk Table:
A table on the chart summarizes essential risk metrics:
Stop-loss value.
Distance from entry in percentage.
Position size (maximum suggested).
Take-profit price.
Customizable:
Adjust parameters like ATR length, smoothing type, risk percentage, transaction fees,
and take-profit percentage.
Modify the visual length of lines representing stop-loss and take-profit levels.
How It Works:
Stop-Loss Calculation:
The stop-loss level is calculated using ATR and a volatility factor (default: 2).
This ensures your stop-loss adapts to market conditions.
Take-Profit Calculation:
Take-profit is derived as a percentage increase from the entry price.
Position Size:
The optimal position size is computed as:
Position Size = Risk per Trade /ATR-based Stop Distance
The risk per trade deducts transaction fees to provide a more accurate calculation.
Visual Lines:
Risk Table:
The table displays updated stop-loss, position size, and take-profit metrics at a glance.
Settings Panel:
Length: ATR length for calculating market volatility.
Smoothing: Choose RMA, SMA, EMA, or WMA for ATR smoothing.
Trade Amount: The capital allocated to a single trade.
Risk by Trade (%): Define how much of your trade capital is at risk per trade.
Transaction Fees: Input fees to ensure realistic calculations.
Take Profit (%): Specify your desired take-profit percentage.
Show Entry Stop Loss: Toggle visibility of the stop-loss line.
Show Entry Take Profit: Toggle visibility of the take-profit line.
Filtered ATR with EMA OverlayFiltered ATR with EMA Overlay is an advanced volatility indicator designed to provide a more accurate representation of market conditions by smoothing the standard Average True Range (ATR). This is achieved by filtering out extreme price movements and abnormal bars that can distort traditional ATR calculations.
The indicator applies an Exponential Moving Average (EMA) to the filtered ATR, creating a dual-layered system that highlights periods of increased or decreased volatility.
Key Features:
Filtered ATR: Filters out extreme bars, reducing noise and making the ATR line more reliable.
EMA Overlay: An EMA (default period of 10) is applied to the filtered ATR, allowing traders to track average volatility trends.
Volatility Signals:
Filtered ATR > EMA(10): Indicates higher-than-average volatility. This often correlates with trend breakouts or strong price movements.
Filtered ATR < EMA(10): Suggests reduced volatility, signaling potential consolidation or sideways price action.
Parameters:
atrLength (Default: 5):
The number of bars used to calculate the ATR. A shorter period (e.g., 3-5) responds faster to price changes, while a longer period (e.g., 10-14) provides smoother results.
multiplier (Default: 1.8):
Controls the sensitivity of the filter. A lower multiplier (e.g., 1.5) filters out more bars, resulting in smoother ATR. Higher values (e.g., 2.0) allow more bars to pass through, retaining more price volatility.
maxIterations (Default: 20):
The maximum number of bars processed to detect abnormal values. Increasing this may improve accuracy at the cost of performance.
ema10Period (Default: 10):
The period for the Exponential Moving Average applied to the filtered ATR. Shorter periods provide faster signals, while longer periods give smoother, lagging signals.
Trading Strategies:
1. Breakout Strategy:
When filtered ATR crosses above EMA(10):
Enter long positions when price breaks above a key resistance level.
Higher volatility suggests strong price action and momentum.
When filtered ATR drops below EMA(10):
Exit positions or tighten stop-loss orders as volatility decreases.
Lower volatility may indicate consolidation or trend exhaustion.
2. Trend Following Strategy:
Use the filtered ATR line to track overall volatility.
If filtered ATR consistently stays above EMA: Hold positions or add to trades.
If filtered ATR remains below EMA: Reduce position size or stay out of trades.
3. Mean Reversion Strategy:
When filtered ATR spikes significantly above EMA, it may indicate market overreaction.
Look for price to revert to the mean once ATR returns below the EMA.
4. Stop-Loss Adjustment:
As volatility increases (ATR above EMA), widen stop-loss levels to avoid being stopped out by random fluctuations.
In low volatility (ATR below EMA), tighten stop-losses to minimize losses during low activity periods.
Benefits:
Reduced Noise: By filtering abnormal bars, the indicator provides cleaner signals.
Better Trend Detection: EMA smoothing highlights volatility trends.
Adaptable: The indicator can be customized for scalping, day trading, or swing trading.
Intuitive Visualization: Traders can visually see volatility shifts and adjust strategies in real-time.
Best Practices:
Timeframes: Works effectively on all timeframes, but higher timeframes (e.g., 1H, 4H, Daily) yield more reliable signals.
Markets: Suitable for forex, crypto, stocks, and commodities.
Combining Indicators: Use in combination with RSI, Moving Averages, Bollinger Bands, or price action analysis for stronger signals.
How It Works (Under the Hood):
The script calculates the Daily Range (High - Low) for each bar.
The largest and smallest bars are filtered out if their difference exceeds the multiplier (default 1.8).
The remaining bars are averaged to generate the filtered ATR.
An EMA(10) is then applied to the filtered ATR for smoother visualization.
Milvetti_TraderPost_LibraryLibrary "Milvetti_TraderPost_Library"
This library has methods that provide practical signal transmission for traderpost.Developed By Milvetti
cancelOrders(symbol)
This method generates a signal in JSON format that cancels all orders for the specified pair. (If you want to cancel stop loss and takeprofit orders together, use the “exitOrder” method.
Parameters:
symbol (string)
exitOrders(symbol)
This method generates a signal in JSON format that close all orders for the specified pair.
Parameters:
symbol (string)
createOrder(ticker, positionType, orderType, entryPrice, signalPrice, qtyType, qty, stopLoss, stopType, stopValue, takeProfit, profitType, profitValue, timeInForce)
This function is designed to send buy or sell orders to traderpost. It can create customized orders by flexibly specifying parameters such as order type, position type, entry price, quantity calculation method, stop-loss, and take-profit. The purpose of the function is to consolidate all necessary details for opening a position into a single structure and present it as a structured JSON output. This format can be sent to trading platforms via webhooks.
Parameters:
ticker (string) : The ticker symbol of the instrument. Default value is the current chart's ticker (syminfo.ticker).
positionType (string) : Determines the type of order (e.g., "long" or "buy" for buying and "short" or "sell" for selling).
orderType (string) : Defines the order type for execution. Options: "market", "limit", "stop". Default is "market"
entryPrice (float) : The price level for entry orders. Only applicable for limit or stop orders. Default is 0 (market orders ignore this).
signalPrice (float) : Optional. Only necessary when using relative take profit or stop losses, and the broker does not support fetching quotes to perform the calculation. Default is 0
qtyType (string) : Determines how the order quantity is calculated. Options: "fixed_quantity", "dollar_amount", "percent_of_equity", "percent_of_position".
qty (float) : Quantity value. Can represent units of shares/contracts or a dollar amount, depending on qtyType.
stopLoss (bool) : Enable or disable stop-loss functionality. Set to `true` to activate.
stopType (string) : Specifies the stop-loss calculation type. Options: percent, "amount", "stopPrice", "trailPercent", "trailAmount". Default is "stopPrice"
stopValue (float) : Stop-loss value based on stopType. Can be a percentage, dollar amount, or a specific stop price. Default is "stopPrice"
takeProfit (bool) : Enable or disable take-profit functionality. Set to `true` to activate.
profitType (string) : Specifies the take-profit calculation type. Options: "percent", "amount", "limitPrice". Default is "limitPrice"
profitValue (float) : Take-profit value based on profitType. Can be a percentage, dollar amount, or a specific limit price. Default is 0
timeInForce (string) : The time in force for your order. Options: day, gtc, opg, cls, ioc and fok
Returns: Return result in Json format.
addTsl(symbol, stopType, stopValue, price)
This method adds trailing stop loss to the current position. “Price” is the trailing stop loss starting level. You can leave price blank if you want it to start immediately
Parameters:
symbol (string)
stopType (string) : Specifies the trailing stoploss calculation type. Options: "trailPercent", "trailAmount".
stopValue (float) : Stop-loss value based on stopType. Can be a percentage, dollar amount.
price (float) : The trailing stop loss starting level. You can leave price blank if you want it to start immediately. Default is current price.
Wave Surge [UAlgo]The "Wave Surge " is a comprehensive indicator designed to provide advanced wave pattern analysis for market trends and price movements. Built with customizable parameters, it caters to both beginner and advanced traders looking to improve their decision-making process.
This indicator utilizes wave-based calculations, adaptive thresholds, and volume analysis to detect and visualize key market signals. By integrating multiple analysis techniques.
It calculates waves for high, low, and close prices using a configurable moving average (EMA) technique and pairs it with volume and baseline analysis to confirm patterns. The result is a robust framework for identifying potential entry and exit points in the market.
🔶 Key Features
Wave-Based Analysis: This indicator computes waves using exponential moving averages (EMA) of high, low, and close prices, with an adjustable wave period to suit different market conditions.
Customizable Baseline: Traders can select from multiple baseline types, including VWMA (Volume-Weighted Moving Average), EMA, SMA (Simple Moving Average), and HMA (Hull Moving Average), for trend confirmation.
Adaptive Thresholds: The adaptive threshold feature dynamically adjusts sensitivity based on a chosen period, ensuring the indicator remains responsive to varying market volatility.
Volume Analysis: The integrated volume analysis calculates volume ratios and allows traders to enable or disable this feature to refine signal accuracy.
Pattern Recognition: The indicator identifies specific wave patterns (Wave 1, Wave 3, Wave 4, Wave 5, Wave 6) and visually plots them on the chart for easy interpretation.
Visual and Color-Coded Signals: Clear visual signals (upward and downward arrows) are plotted on the chart to highlight potential bullish or bearish patterns. The baseline is color-coded for an intuitive understanding of market trends.
Configuration: Parameters for wave period, baseline length, volume factors, and sensitivity can be tailored to align with the trader’s strategy and market environment.
🔶 Interpreting the Indicator
Wave Patterns
The indicator detects and plots six unique wave patterns based on price changes that exceed an adaptive threshold. These patterns are validated by the direction of the baseline:
Wave 1 (Bullish): Triggered when the price increases above the threshold while the baseline is falling.
Wave 3, 4, and 6 (Bearish): Indicate potential downtrends validated by a rising baseline.
Wave 5 (Bullish): Suggests upward momentum when prices exceed the threshold with a falling baseline.
Baseline Trend
The baseline serves as a trend confirmation tool, dynamically changing color to reflect market direction:
Aqua (Rising): Indicates an upward trend.
Red (Falling): Indicates a downward trend.
Volume Confirmation
When enabled, the volume analysis feature ensures that signals are supported by significant volume movements. Patterns with high volume are considered more reliable.
Signal Visualization
Upward Arrows (🡹): Highlight potential bullish opportunities.
Downward Arrows (🡻): Highlight potential bearish opportunities.
Alerts
Alerts are triggered when key wave patterns are identified, providing traders with timely notifications to take action without being tied to the screen.
🔶 Disclaimer
Use with Caution: This indicator is provided for educational and informational purposes only and should not be considered as financial advice. Users should exercise caution and perform their own analysis before making trading decisions based on the indicator's signals.
Not Financial Advice: The information provided by this indicator does not constitute financial advice, and the creator (UAlgo) shall not be held responsible for any trading losses incurred as a result of using this indicator.
Backtesting Recommended: Traders are encouraged to backtest the indicator thoroughly on historical data before using it in live trading to assess its performance and suitability for their trading strategies.
Risk Management: Trading involves inherent risks, and users should implement proper risk management strategies, including but not limited to stop-loss orders and position sizing, to mitigate potential losses.
No Guarantees: The accuracy and reliability of the indicator's signals cannot be guaranteed, as they are based on historical price data and past performance may not be indicative of future results.
MultiLayer Acceleration/Deceleration Strategy [Skyrexio]Overview
MultiLayer Acceleration/Deceleration Strategy leverages the combination of Acceleration/Deceleration Indicator(AC), Williams Alligator, Williams Fractals and Exponential Moving Average (EMA) to obtain the high probability long setups. Moreover, strategy uses multi trades system, adding funds to long position if it considered that current trend has likely became stronger. Acceleration/Deceleration Indicator is used for creating signals, while Alligator and Fractal are used in conjunction as an approximation of short-term trend to filter them. At the same time EMA (default EMA's period = 100) is used as high probability long-term trend filter to open long trades only if it considers current price action as an uptrend. More information in "Methodology" and "Justification of Methodology" paragraphs. The strategy opens only long trades.
Unique Features
No fixed stop-loss and take profit: Instead of fixed stop-loss level strategy utilizes technical condition obtained by Fractals and Alligator to identify when current uptrend is likely to be over (more information in "Methodology" and "Justification of Methodology" paragraphs)
Configurable Trading Periods: Users can tailor the strategy to specific market windows, adapting to different market conditions.
Multilayer trades opening system: strategy uses only 10% of capital in every trade and open up to 5 trades at the same time if script consider current trend as strong one.
Short and long term trend trade filters: strategy uses EMA as high probability long-term trend filter and Alligator and Fractal combination as a short-term one.
Methodology
The strategy opens long trade when the following price met the conditions:
1. Price closed above EMA (by default, period = 100). Crossover is not obligatory.
2. Combination of Alligator and Williams Fractals shall consider current trend as an upward (all details in "Justification of Methodology" paragraph)
3. Acceleration/Deceleration shall create one of two types of long signals (all details in "Justification of Methodology" paragraph). Buy stop order is placed one tick above the candle's high of last created long signal.
4. If price reaches the order price, long position is opened with 10% of capital.
5. If currently we have opened position and price creates and hit the order price of another one long signal, another one long position will be added to the previous with another one 10% of capital. Strategy allows to open up to 5 long trades simultaneously.
6. If combination of Alligator and Williams Fractals shall consider current trend has been changed from up to downtrend, all long trades will be closed, no matter how many trades has been opened.
Script also has additional visuals. If second long trade has been opened simultaneously the Alligator's teeth line is plotted with the green color. Also for every trade in a row from 2 to 5 the label "Buy More" is also plotted just below the teeth line. With every next simultaneously opened trade the green color of the space between teeth and price became less transparent.
Strategy settings
In the inputs window user can setup strategy setting: EMA Length (by default = 100, period of EMA, used for long-term trend filtering EMA calculation). User can choose the optimal parameters during backtesting on certain price chart.
Justification of Methodology
Let's explore the key concepts of this strategy and understand how they work together. We'll begin with the simplest: the EMA.
The Exponential Moving Average (EMA) is a type of moving average that assigns greater weight to recent price data, making it more responsive to current market changes compared to the Simple Moving Average (SMA). This tool is widely used in technical analysis to identify trends and generate buy or sell signals. The EMA is calculated as follows:
1.Calculate the Smoothing Multiplier:
Multiplier = 2 / (n + 1), Where n is the number of periods.
2. EMA Calculation
EMA = (Current Price) × Multiplier + (Previous EMA) × (1 − Multiplier)
In this strategy, the EMA acts as a long-term trend filter. For instance, long trades are considered only when the price closes above the EMA (default: 100-period). This increases the likelihood of entering trades aligned with the prevailing trend.
Next, let’s discuss the short-term trend filter, which combines the Williams Alligator and Williams Fractals. Williams Alligator
Developed by Bill Williams, the Alligator is a technical indicator that identifies trends and potential market reversals. It consists of three smoothed moving averages:
Jaw (Blue Line): The slowest of the three, based on a 13-period smoothed moving average shifted 8 bars ahead.
Teeth (Red Line): The medium-speed line, derived from an 8-period smoothed moving average shifted 5 bars forward.
Lips (Green Line): The fastest line, calculated using a 5-period smoothed moving average shifted 3 bars forward.
When the lines diverge and align in order, the "Alligator" is "awake," signaling a strong trend. When the lines overlap or intertwine, the "Alligator" is "asleep," indicating a range-bound or sideways market. This indicator helps traders determine when to enter or avoid trades.
Fractals, another tool by Bill Williams, help identify potential reversal points on a price chart. A fractal forms over at least five consecutive bars, with the middle bar showing either:
Up Fractal: Occurs when the middle bar has a higher high than the two preceding and two following bars, suggesting a potential downward reversal.
Down Fractal: Happens when the middle bar shows a lower low than the surrounding two bars, hinting at a possible upward reversal.
Traders often use fractals alongside other indicators to confirm trends or reversals, enhancing decision-making accuracy.
How do these tools work together in this strategy? Let’s consider an example of an uptrend.
When the price breaks above an up fractal, it signals a potential bullish trend. This occurs because the up fractal represents a shift in market behavior, where a temporary high was formed due to selling pressure. If the price revisits this level and breaks through, it suggests the market sentiment has turned bullish.
The breakout must occur above the Alligator’s teeth line to confirm the trend. A breakout below the teeth is considered invalid, and the downtrend might still persist. Conversely, in a downtrend, the same logic applies with down fractals.
In this strategy if the most recent up fractal breakout occurs above the Alligator's teeth and follows the last down fractal breakout below the teeth, the algorithm identifies an uptrend. Long trades can be opened during this phase if a signal aligns. If the price breaks a down fractal below the teeth line during an uptrend, the strategy assumes the uptrend has ended and closes all open long trades.
By combining the EMA as a long-term trend filter with the Alligator and fractals as short-term filters, this approach increases the likelihood of opening profitable trades while staying aligned with market dynamics.
Now let's talk about Acceleration/Deceleration signals. AC indicator is calculated using the Awesome Oscillator, so let's first of all briefly explain what is Awesome Oscillator and how it can be calculated. The Awesome Oscillator (AO), developed by Bill Williams, is a momentum indicator designed to measure market momentum by contrasting recent price movements with a longer-term historical perspective. It helps traders detect potential trend reversals and assess the strength of ongoing trends.
The formula for AO is as follows:
AO = SMA5(Median Price) − SMA34(Median Price)
where:
Median Price = (High + Low) / 2
SMA5 = 5-period Simple Moving Average of the Median Price
SMA 34 = 34-period Simple Moving Average of the Median Price
The Acceleration/Deceleration (AC) Indicator, introduced by Bill Williams, measures the rate of change in market momentum. It highlights shifts in the driving force of price movements and helps traders spot early signs of trend changes. The AC Indicator is particularly useful for identifying whether the current momentum is accelerating or decelerating, which can indicate potential reversals or continuations. For AC calculation we shall use the AO calculated above is the following formula:
AC = AO − SMA5(AO), where SMA5(AO)is the 5-period Simple Moving Average of the Awesome Oscillator
When the AC is above the zero line and rising, it suggests accelerating upward momentum.
When the AC is below the zero line and falling, it indicates accelerating downward momentum.
When the AC is below zero line and rising it suggests the decelerating the downtrend momentum. When AC is above the zero line and falling, it suggests the decelerating the uptrend momentum.
Now we can explain which AC signal types are used in this strategy. The first type of long signal is when AC value is below zero line. In this cases we need to see three rising bars on the histogram in a row after the falling one. The second type of signals occurs above the zero line. There we need only two rising AC bars in a row after the falling one to create the signal. The signal bar is the last green bar in this sequence. The strategy places the buy stop order one tick above the candle's high, which corresponds to the signal bar on AC indicator.
After that we can have the following scenarios:
Price hit the order on the next candle in this case strategy opened long with this price.
Price doesn't hit the order price, the next candle set lower high. If current AC bar is increasing buy stop order changes by the script to the high of this new bar plus one tick. This procedure repeats until price finally hit buy order or current AC bar become decreasing. In the second case buy order cancelled and strategy wait for the next AC signal.
If long trades are initiated, the strategy continues utilizing subsequent signals until the total number of trades reaches a maximum of 5. All open trades are closed when the trend shifts to a downtrend, as determined by the combination of the Alligator and Fractals described earlier.
Why we use AC signals? If currently strategy algorithm considers the high probability of the short-term uptrend with the Alligator and Fractals combination pointed out above and the long-term trend is also suggested by the EMA filter as bullish. Rising AC bars after period of falling AC bars indicates the high probability of local pull back end and there is a high chance to open long trade in the direction of the most likely main uptrend. The numbers of rising bars are different for the different AC values (below or above zero line). This is needed because if AC below zero line the local downtrend is likely to be stronger and needs more rising bars to confirm that it has been changed than if AC is above zero.
Why strategy use only 10% per signal? Sometimes we can see the false signals which appears on sideways. Not risking that much script use only 10% per signal. If the first long trade has been open and price continue going up and our trend approximation by Alligator and Fractals is uptrend, strategy add another one 10% of capital to every next AC signal while number of active trades no more than 5. This capital allocation allows to take part in long trades when current uptrend is likely to be strong and use only 10% of capital when there is a high probability of sideways.
Backtest Results
Operating window: Date range of backtests is 2023.01.01 - 2024.11.01. It is chosen to let the strategy to close all opened positions.
Commission and Slippage: Includes a standard Binance commission of 0.1% and accounts for possible slippage over 5 ticks.
Initial capital: 10000 USDT
Percent of capital used in every trade: 10%
Maximum Single Position Loss: -5.15%
Maximum Single Profit: +24.57%
Net Profit: +2108.85 USDT (+21.09%)
Total Trades: 111 (36.94% win rate)
Profit Factor: 2.391
Maximum Accumulated Loss: 367.61 USDT (-2.97%)
Average Profit per Trade: 19.00 USDT (+1.78%)
Average Trade Duration: 75 hours
How to Use
Add the script to favorites for easy access.
Apply to the desired timeframe and chart (optimal performance observed on 3h BTC/USDT).
Configure settings using the dropdown choice list in the built-in menu.
Set up alerts to automate strategy positions through web hook with the text: {{strategy.order.alert_message}}
Disclaimer:
Educational and informational tool reflecting Skyrex commitment to informed trading. Past performance does not guarantee future results. Test strategies in a simulated environment before live implementation
These results are obtained with realistic parameters representing trading conditions observed at major exchanges such as Binance and with realistic trading portfolio usage parameters.
2-Year MA Multiplier [UAlgo]The 2-Year MA Multiplier is a technical analysis tool designed to assist traders and investors in identifying potential overbought and oversold conditions in the market. By plotting the 2-year moving average (MA) of an asset's closing price alongside an upper band set at five times this moving average, the indicator provides visual cues to assess long-term price trends and significant market movements.
🔶 Key Features
2-Year Moving Average (MA): Calculates the simple moving average of the asset's closing price over a 730-day period, representing approximately two years.
Visual Indicators: Plots the 2-year MA in forest green and the upper band in firebrick red for clear differentiation.
Fills the area between the 2-year MA and the upper band to highlight the normal trading range.
Uses color-coded fills to indicate overbought (tomato red) and oversold (cornflower blue) conditions based on the asset's closing price relative to the bands.
🔶 Idea
The concept behind the 2-Year MA Multiplier is rooted in the cyclical nature of markets, particularly in assets like Bitcoin. By analyzing long-term price movements, the indicator aims to identify periods of significant deviation from the norm, which may signal potential buying or selling opportunities.
2-year MA smooths out short-term volatility, providing a clearer view of the asset's long-term trend. This timeframe is substantial enough to capture major market cycles, making it a reliable baseline for analysis.
Multiplying the 2-year MA by five establishes an upper boundary that has historically correlated with market tops. When the asset's price exceeds this upper band, it may indicate overbought conditions, suggesting a potential for price correction. Conversely, when the price falls below the 2-year MA, it may signal oversold conditions, presenting potential buying opportunities.
🔶 Disclaimer
Use with Caution: This indicator is provided for educational and informational purposes only and should not be considered as financial advice. Users should exercise caution and perform their own analysis before making trading decisions based on the indicator's signals.
Not Financial Advice: The information provided by this indicator does not constitute financial advice, and the creator (UAlgo) shall not be held responsible for any trading losses incurred as a result of using this indicator.
Backtesting Recommended: Traders are encouraged to backtest the indicator thoroughly on historical data before using it in live trading to assess its performance and suitability for their trading strategies.
Risk Management: Trading involves inherent risks, and users should implement proper risk management strategies, including but not limited to stop-loss orders and position sizing, to mitigate potential losses.
No Guarantees: The accuracy and reliability of the indicator's signals cannot be guaranteed, as they are based on historical price data and past performance may not be indicative of future results.
MultiLayer Awesome Oscillator Saucer Strategy [Skyrexio]Overview
MultiLayer Awesome Oscillator Saucer Strategy leverages the combination of Awesome Oscillator (AO), Williams Alligator, Williams Fractals and Exponential Moving Average (EMA) to obtain the high probability long setups. Moreover, strategy uses multi trades system, adding funds to long position if it considered that current trend has likely became stronger. Awesome Oscillator is used for creating signals, while Alligator and Fractal are used in conjunction as an approximation of short-term trend to filter them. At the same time EMA (default EMA's period = 100) is used as high probability long-term trend filter to open long trades only if it considers current price action as an uptrend. More information in "Methodology" and "Justification of Methodology" paragraphs. The strategy opens only long trades.
Unique Features
No fixed stop-loss and take profit: Instead of fixed stop-loss level strategy utilizes technical condition obtained by Fractals and Alligator to identify when current uptrend is likely to be over (more information in "Methodology" and "Justification of Methodology" paragraphs)
Configurable Trading Periods: Users can tailor the strategy to specific market windows, adapting to different market conditions.
Multilayer trades opening system: strategy uses only 10% of capital in every trade and open up to 5 trades at the same time if script consider current trend as strong one.
Short and long term trend trade filters: strategy uses EMA as high probability long-term trend filter and Alligator and Fractal combination as a short-term one.
Methodology
The strategy opens long trade when the following price met the conditions:
1. Price closed above EMA (by default, period = 100). Crossover is not obligatory.
2. Combination of Alligator and Williams Fractals shall consider current trend as an upward (all details in "Justification of Methodology" paragraph)
3. Awesome Oscillator shall create the "Saucer" long signal (all details in "Justification of Methodology" paragraph). Buy stop order is placed one tick above the candle's high of last created "Saucer signal".
4. If price reaches the order price, long position is opened with 10% of capital.
5. If currently we have opened position and price creates and hit the order price of another one "Saucer" signal another one long position will be added to the previous with another one 10% of capital. Strategy allows to open up to 5 long trades simultaneously.
6. If combination of Alligator and Williams Fractals shall consider current trend has been changed from up to downtrend, all long trades will be closed, no matter how many trades has been opened.
Script also has additional visuals. If second long trade has been opened simultaneously the Alligator's teeth line is plotted with the green color. Also for every trade in a row from 2 to 5 the label "Buy More" is also plotted just below the teeth line. With every next simultaneously opened trade the green color of the space between teeth and price became less transparent.
Strategy settings
In the inputs window user can setup strategy setting: EMA Length (by default = 100, period of EMA, used for long-term trend filtering EMA calculation). User can choose the optimal parameters during backtesting on certain price chart.
Justification of Methodology
Let's go through all concepts used in this strategy to understand how they works together. Let's start from the easies one, the EMA. Let's briefly explain what is EMA. The Exponential Moving Average (EMA) is a type of moving average that gives more weight to recent prices, making it more responsive to current price changes compared to the Simple Moving Average (SMA). It is commonly used in technical analysis to identify trends and generate buy or sell signals. It can be calculated with the following steps:
1.Calculate the Smoothing Multiplier:
Multiplier = 2 / (n + 1), Where n is the number of periods.
2. EMA Calculation
EMA = (Current Price) × Multiplier + (Previous EMA) × (1 − Multiplier)
In this strategy uses EMA an initial long term trend filter. It allows to open long trades only if price close above EMA (by default 50 period). It increases the probability of taking long trades only in the direction of the trend.
Let's go to the next, short-term trend filter which consists of Alligator and Fractals. Let's briefly explain what do these indicators means. The Williams Alligator, developed by Bill Williams, is a technical indicator designed to spot trends and potential market reversals. It uses three smoothed moving averages, referred to as the jaw, teeth, and lips:
Jaw (Blue Line): The slowest of the three, based on a 13-period smoothed moving average shifted 8 bars ahead.
Teeth (Red Line): The medium-speed line, derived from an 8-period smoothed moving average shifted 5 bars forward.
Lips (Green Line): The fastest line, calculated using a 5-period smoothed moving average shifted 3 bars forward.
When these lines diverge and are properly aligned, the "alligator" is considered "awake," signaling a strong trend. Conversely, when the lines overlap or intertwine, the "alligator" is "asleep," indicating a range-bound or sideways market. This indicator assists traders in identifying when to act on or avoid trades.
The Williams Fractals, another tool introduced by Bill Williams, are used to pinpoint potential reversal points on a price chart. A fractal forms when there are at least five consecutive bars, with the middle bar displaying the highest high (for an up fractal) or the lowest low (for a down fractal), relative to the two bars on either side.
Key Points:
Up Fractal: Occurs when the middle bar has a higher high than the two preceding and two following bars, suggesting a potential downward reversal.
Down Fractal: Happens when the middle bar shows a lower low than the surrounding two bars, hinting at a possible upward reversal.
Traders often combine fractals with other indicators to confirm trends or reversals, improving the accuracy of trading decisions.
How we use their combination in this strategy? Let’s consider an uptrend example. A breakout above an up fractal can be interpreted as a bullish signal, indicating a high likelihood that an uptrend is beginning. Here's the reasoning: an up fractal represents a potential shift in market behavior. When the fractal forms, it reflects a pullback caused by traders selling, creating a temporary high. However, if the price manages to return to that fractal’s high and break through it, it suggests the market has "changed its mind" and a bullish trend is likely emerging.
The moment of the breakout marks the potential transition to an uptrend. It’s crucial to note that this breakout must occur above the Alligator's teeth line. If it happens below, the breakout isn’t valid, and the downtrend may still persist. The same logic applies inversely for down fractals in a downtrend scenario.
So, if last up fractal breakout was higher, than Alligator's teeth and it happened after last down fractal breakdown below teeth, algorithm considered current trend as an uptrend. During this uptrend long trades can be opened if signal was flashed. If during the uptrend price breaks down the down fractal below teeth line, strategy considered that uptrend is finished with the high probability and strategy closes all current long trades. This combination is used as a short term trend filter increasing the probability of opening profitable long trades in addition to EMA filter, described above.
Now let's talk about Awesome Oscillator's "Sauser" signals. Briefly explain what is the Awesome Oscillator. The Awesome Oscillator (AO), created by Bill Williams, is a momentum-based indicator that evaluates market momentum by comparing recent price activity to a broader historical context. It assists traders in identifying potential trend reversals and gauging trend strength.
AO = SMA5(Median Price) − SMA34(Median Price)
where:
Median Price = (High + Low) / 2
SMA5 = 5-period Simple Moving Average of the Median Price
SMA 34 = 34-period Simple Moving Average of the Median Price
Now we know what is AO, but what is the "Saucer" signal? This concept was introduced by Bill Williams, let's briefly explain it and how it's used by this strategy. Initially, this type of signal is a combination of the following AO bars: we need 3 bars in a row, the first one shall be higher than the second, the third bar also shall be higher, than second. All three bars shall be above the zero line of AO. The price bar, which corresponds to third "saucer's" bar is our signal bar. Strategy places buy stop order one tick above the price bar which corresponds to signal bar.
After that we can have the following scenarios.
Price hit the order on the next candle in this case strategy opened long with this price.
Price doesn't hit the order price, the next candle set lower low. If current AO bar is increasing buy stop order changes by the script to the high of this new bar plus one tick. This procedure repeats until price finally hit buy order or current AO bar become decreasing. In the second case buy order cancelled and strategy wait for the next "Saucer" signal.
If long trades has been opened strategy use all the next signals until number of trades doesn't exceed 5. All trades are closed when the trend changes to downtrend according to combination of Alligator and Fractals described above.
Why we use "Saucer" signals? If AO above the zero line there is a high probability that price now is in uptrend if we take into account our two trend filters. When we see the decreasing bars on AO and it's above zero it's likely can be considered as a pullback on the uptrend. When we see the stop of AO decreasing and the first increasing bar has been printed there is a high probability that this local pull back is finished and strategy open long trade in the likely direction of a main trend.
Why strategy use only 10% per signal? Sometimes we can see the false signals which appears on sideways. Not risking that much script use only 10% per signal. If the first long trade has been open and price continue going up and our trend approximation by Alligator and Fractals is uptrend, strategy add another one 10% of capital to every next saucer signal while number of active trades no more than 5. This capital allocation allows to take part in long trades when current uptrend is likely to be strong and use only 10% of capital when there is a high probability of sideways.
Backtest Results
Operating window: Date range of backtests is 2023.01.01 - 2024.11.25. It is chosen to let the strategy to close all opened positions.
Commission and Slippage: Includes a standard Binance commission of 0.1% and accounts for possible slippage over 5 ticks.
Initial capital: 10000 USDT
Percent of capital used in every trade: 10%
Maximum Single Position Loss: -5.10%
Maximum Single Profit: +22.80%
Net Profit: +2838.58 USDT (+28.39%)
Total Trades: 107 (42.99% win rate)
Profit Factor: 3.364
Maximum Accumulated Loss: 373.43 USDT (-2.98%)
Average Profit per Trade: 26.53 USDT (+2.40%)
Average Trade Duration: 78 hours
These results are obtained with realistic parameters representing trading conditions observed at major exchanges such as Binance and with realistic trading portfolio usage parameters.
How to Use
Add the script to favorites for easy access.
Apply to the desired timeframe and chart (optimal performance observed on 3h BTC/USDT).
Configure settings using the dropdown choice list in the built-in menu.
Set up alerts to automate strategy positions through web hook with the text: {{strategy.order.alert_message}}
Disclaimer:
Educational and informational tool reflecting Skyrex commitment to informed trading. Past performance does not guarantee future results. Test strategies in a simulated environment before live implementation
Support/Resistance Strength [UAlgo]The Support/Resistance Strength indicator is a tool designed for traders seeking a precise understanding of key support and resistance levels in the market. This tool dynamically identifies and visualizes support and resistance zones based on pivot points and strength criteria, providing traders with actionable insights for better decision-making.
By incorporating features such as ATR-based or percentage-based channel calculations, customizable strength thresholds, and intuitive visualization of key levels, the indicator caters to traders of various skill levels and strategies. It also adapts dynamically to market conditions, allowing users to identify frequently tested zones with minimal manual input.
🔶 Key Features
Dynamic Support and Resistance Zones
Automatically detects significant support and resistance levels using pivot high and low calculations.
Offers ATR-based or percentage-based channel customization to cater to diverse trading styles.
Customizable Parameters
Lookback period for pivot calculations, strength threshold, and maximum stored pivots are fully adjustable.
Display options for showing specific numbers of recent support/resistance lines.
Intuitive Visualization
Highlights key support and resistance levels with color-coded lines and labels.
Includes percentage deviation from the current price for quick assessment.
Interactive Updates
Continuously updates support and resistance levels to reflect changing market dynamics.
Displays pivot points visually for enhanced clarity.
Can be used effectively on various timeframes, from intraday to daily and weekly charts.
🔶 Interpreting the Indicator
Identifying Key Levels
Support levels are indicated by green (lime) lines and resistance levels by red lines. The transparency of colors is adjustable for visual preference.
Labels display the exact price level and the percentage difference from the current price.
Strength Threshold
The "Minimum S/R Strength" parameter defines how frequently a level must be tested to be considered significant.
Higher strength values indicate zones that have been tested more frequently, suggesting stronger support or resistance.
Pivot Points
The indicator marks pivot high and low points on the chart to provide a visual representation of the calculated levels.
Dynamic Updates
The indicator adapts to the most recent price action. If the price moves above a resistance level or below a support level, the color of the lines and labels will dynamically change to reflect the current price positioning.
🔶 Disclaimer
Use with Caution: This indicator is provided for educational and informational purposes only and should not be considered as financial advice. Users should exercise caution and perform their own analysis before making trading decisions based on the indicator's signals.
Not Financial Advice: The information provided by this indicator does not constitute financial advice, and the creator (UAlgo) shall not be held responsible for any trading losses incurred as a result of using this indicator.
Backtesting Recommended: Traders are encouraged to backtest the indicator thoroughly on historical data before using it in live trading to assess its performance and suitability for their trading strategies.
Risk Management: Trading involves inherent risks, and users should implement proper risk management strategies, including but not limited to stop-loss orders and position sizing, to mitigate potential losses.
No Guarantees: The accuracy and reliability of the indicator's signals cannot be guaranteed, as they are based on historical price data and past performance may not be indicative of future results.
