Combo Backtest 123 Reversal & Ergodic TSI This is combo strategies for get a cumulative signal.
First strategy
This System was created from the Book "How I Tripled My Money In The
Futures Market" by Ulf Jensen, Page 183. This is reverse type of strategies.
The strategy buys at market, if close price is higher than the previous close
during 2 days and the meaning of 9-days Stochastic Slow Oscillator is lower than 50.
The strategy sells at market, if close price is lower than the previous close price
during 2 days and the meaning of 9-days Stochastic Fast Oscillator is higher than 50.
Second strategy
r - Length of first EMA smoothing of 1 day momentum 4
s - Length of second EMA smoothing of 1 day smoothing 8
u- Length of third EMA smoothing of 1 day momentum 6
Length of EMA signal line 3
Source of Ergotic TSI Close
This is one of the techniques described by William Blau in his book "Momentum,
Direction and Divergence" (1995). If you like to learn more, we advise you to
read this book. His book focuses on three key aspects of trading: momentum,
direction and divergence. Blau, who was an electrical engineer before becoming
a trader, thoroughly examines the relationship between price and momentum in
step-by-step examples. From this grounding, he then looks at the deficiencies
in other oscillators and introduces some innovative techniques, including a
fresh twist on Stochastics. On directional issues, he analyzes the intricacies
of ADX and offers a unique approach to help define trending and non-trending periods.
WARNING:
- For purpose educate only
- This script to change bars colors.
Pesquisar nos scripts por "momentum"
Script Criptomaníacos FuturesThis Script runs a strategy for long and short entries.
The strategy is based on a breakout system, that enters long or short based on previous support and resistences, and a series of indicators in order to read the trend and momentum of price charts.
We are only able to place entry orders when the background collor indicates price matches with the Trend/Momentum filters, being green for long and red for short trades.
The exit will always based on a trailling stop.
__________________________________________
Esse script roda uma estratégia para entradas em long e short.
A estratégia é baseada em um estratégias de rompimento, que entra Long ou Short baseado em suportes e resistências anteriores, além de uma série de indicadores afim de ler a tendência e o momentum do gráfico de preço.
Só estamos autorizados a emitir ordens de entrada quando o Background indica que o preço concorda com os filtros de Tendência/Momentum, sendo verde para Long (compra) e Short (venda).
A saída sempre vai ser baseada em um método de trailling stop.
IndianPivotBossMUPSThis is a new avatar of the MUPS (ManojUltimatePivotScalpingStrategy).
This Indicator is to be used with the following Indicators :
1) IndianPivotBossPEMA
2) IndianPivotBossPIVOTRSI
3) IndianPivotBossDPWMACD
4) IndianPivotBossPIVOTSHIFT
BcondA = crossover(close,dtime_up) or low > dtime_up
BcondB = crossover(low,imap) or crossover(low,dpivotema) or crossover(low,imapw) or crossover(low,imapm)
//BcondC = crossover(low,ddtime_pivot)
BcondD = crossover(low,wtime_pivot)
BcondE = crossover(low,mtime_pivot)
BcondF = crossover(low,idtime_pivot)
BcondG = imacd > 0 or imacdw > 0 or imacdm > 0
BcondH = (rsipe > 50 and rsipe > rsippe) or (rsipew > 50 and rsipew > rsippew) or (rsipem > 50 and rsipem > rsippem)
BcondI = crossover(imacd,0) and close > maFast
//BcondI = ( dtime_pwd < ema(dtime_pwd,8) and crossover(low,dtime_r1))
EcondS = (imacd < 0 or crossunder(imacd,0) or close < maSlow) and rsipe < 50 and rsippe < 50 //crossunder(high,dtime_pivot) or crossunder(high,dpivotema) or crossunder(close,wtime_pivot) or crossunder(high,idtime_pivot) or crossunder(rsipe,rsippe) or crossunder(rsipe,50) or crossunder(high,dtime_r1)
Objective :
To enter into a trade when the direction, trend and momentum is confirmed.
Rules :
The following are the broad conditions for taking a long position. Reverse is for Short.
Direction - Defined by price crossing either daily cpr / weekly pivot / monthly pivot / intraday 125 min pivot
Trend - Defined by IndianPivotBossPIVOTSHIFT and IndiaPivotBossDPWMACD. The latter is a variant of the former. The former gives advance indication of a trend, while the latter confirms moments later.
Momentum - Defined by IndianPivotBossPIVOTRSI.
The strategy takes long when direction is established by the price crossing pivots and trend is established with pivot shift indicator sloping upwards which is further confirmed by DPWMACD, which is a variant of pivot shift indicator, crossing midline and sloping upwards and Momentum is established by Pivot RSI indicator when it crosses 50 and is above its own EMA.
Exits are usually at close. In case if the combination fizzles out, the strategy shows exit signal if any of the 3 ie, direction / trend / momentum fizzles out.
It is suggested to close down the positions at day end as sometimes the strategy continues the position overnight if deemed fit.
Other Rules when you take a long trade based on the signal.
1) Ensure the price is above PEMA and PEMA is upward sloping.
2) Ensure the Pivot shift indicator is upward sloping; Ensure the DPWMACD is also upward sloping.
3) Ensure the Daily Pivot RSI is above 50 and is above its own EMA.
This is not a holy grail. Hence have a proper position sizing which is your ultimate defense.
IMPORTANT : WHEN YOU USE THIS INDICATOR ALONG WITH 1,2,3,4 MENTIONED IN THE TOP PORTION OF THIS POST, PLS ENSURE THAT THE STRATEGY CHOSEN IS MUPS AS ALL THOSE MENTIONED ABOVE ARE ALSO STRATEGIES ON ITS OWN. MUPS COMBINES ALL THESE.
Trading Public School ST1This is a derivative of Trading Public School "TTM Squeeze" volatility indicator, as discussed in his book "Mastering the Trade" (chapter 11).
Black crosses on the midline show that the market just entered a squeeze ( Bollinger Bands are with in Keltner Channel). This signifies low volatility , market preparing itself for an explosive move (up or down). Gray crosses signify "Squeeze release".
Mr.Carter suggests waiting till the first gray after a black cross, and taking a position in the direction of the momentum (for ex., if momentum value is above zero, go long). Exit the position when the momentum changes (increase or decrease --- signified by a color change). My (limited) experience with this shows, an additional indicator like ADX / WaveTrend, is needed to not miss good entry points. Also, Mr.Carter uses simple momentum indicator , while I have used a different method (linreg based) to plot the histogram. 100% Profit & loss 10% Only
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.
Combo Backtest 123 Reversal & CMOfilt This is combo strategies for get a cumulative signal.
First strategy
This System was created from the Book "How I Tripled My Money In The
Futures Market" by Ulf Jensen, Page 183. This is reverse type of strategies.
The strategy buys at market, if close price is higher than the previous close
during 2 days and the meaning of 9-days Stochastic Slow Oscillator is lower than 50.
The strategy sells at market, if close price is lower than the previous close price
during 2 days and the meaning of 9-days Stochastic Fast Oscillator is higher than 50.
Second strategy
This indicator plots a CMO which ignores price changes which are less
than a threshold value. CMO was developed by Tushar Chande. A scientist,
an inventor, and a respected trading system developer, Mr. Chande developed
the CMO to capture what he calls "pure momentum". For more definitive
information on the CMO and other indicators we recommend the book The New
Technical Trader by Tushar Chande and Stanley Kroll.
The CMO is closely related to, yet unique from, other momentum oriented
indicators such as Relative Strength Index, Stochastic, Rate-of-Change, etc.
It is most closely related to Welles Wilder`s RSI, yet it differs in several ways:
- It uses data for both up days and down days in the numerator, thereby directly
measuring momentum;
- The calculations are applied on unsmoothed data. Therefore, short-term extreme
movements in price are not hidden. Once calculated, smoothing can be applied to the
CMO, if desired;
- The scale is bounded between +100 and -100, thereby allowing you to clearly see
changes in net momentum using the 0 level. The bounded scale also allows you to
conveniently compare values across different securities.
WARNING:
- For purpose educate only
- This script to change bars colors.
Combo Backtest 123 Reversal & CMOav This is combo strategies for get a cumulative signal.
First strategy
This System was created from the Book "How I Tripled My Money In The
Futures Market" by Ulf Jensen, Page 183. This is reverse type of strategies.
The strategy buys at market, if close price is higher than the previous close
during 2 days and the meaning of 9-days Stochastic Slow Oscillator is lower than 50.
The strategy sells at market, if close price is lower than the previous close price
during 2 days and the meaning of 9-days Stochastic Fast Oscillator is higher than 50.
Second strategy
This indicator plots average of three different length CMO's. This indicator
was developed by Tushar Chande. A scientist, an inventor, and a respected
trading system developer, Mr. Chande developed the CMO to capture what he
calls "pure momentum". For more definitive information on the CMO and other
indicators we recommend the book The New Technical Trader by Tushar Chande
and Stanley Kroll.
The CMO is closely related to, yet unique from, other momentum oriented
indicators such as Relative Strength Index, Stochastic, Rate-of-Change, etc.
It is most closely related to Welles Wilder?s RSI, yet it differs in several ways:
- It uses data for both up days and down days in the numerator, thereby directly
measuring momentum;
- The calculations are applied on unsmoothed data. Therefore, short-term extreme
movements in price are not hidden. Once calculated, smoothing can be applied to
the CMO, if desired;
- The scale is bounded between +100 and -100, thereby allowing you to clearly see
changes in net momentum using the 0 level. The bounded scale also allows you to
conveniently compare values across different securities.
WARNING:
- For purpose educate only
- This script to change bars colors.
Combo Backtest 123 Reversal & CMOabsThis is combo strategies for get a cumulative signal.
First strategy
This System was created from the Book "How I Tripled My Money In The
Futures Market" by Ulf Jensen, Page 183. This is reverse type of strategies.
The strategy buys at market, if close price is higher than the previous close
during 2 days and the meaning of 9-days Stochastic Slow Oscillator is lower than 50.
The strategy sells at market, if close price is lower than the previous close price
during 2 days and the meaning of 9-days Stochastic Fast Oscillator is higher than 50.
Second strategy
This indicator plots the absolute value of CMO. CMO was developed by Tushar
Chande. A scientist, an inventor, and a respected trading system developer,
Mr. Chande developed the CMO to capture what he calls "pure momentum". For
more definitive information on the CMO and other indicators we recommend the
book The New Technical Trader by Tushar Chande and Stanley Kroll.
The CMO is closely related to, yet unique from, other momentum oriented indicators
such as Relative Strength Index, Stochastic, Rate-of-Change, etc. It is most closely
related to Welles Wilder`s RSI, yet it differs in several ways:
- It uses data for both up days and down days in the numerator, thereby directly
measuring momentum;
- The calculations are applied on unsmoothed data. Therefore, short-term extreme
movements in price are not hidden. Once calculated, smoothing can be applied to
the CMO, if desired;
- The scale is bounded between +100 and -100, thereby allowing you to clearly see
changes in net momentum using the 0 level. The bounded scale also allows you to
conveniently compare values across different securities.
WARNING:
- For purpose educate only
- This script to change bars colors.
Combo Backtest 123 Reversal & CMO & WMA This is combo strategies for get a cumulative signal.
First strategy
This System was created from the Book "How I Tripled My Money In The
Futures Market" by Ulf Jensen, Page 183. This is reverse type of strategies.
The strategy buys at market, if close price is higher than the previous close
during 2 days and the meaning of 9-days Stochastic Slow Oscillator is lower than 50.
The strategy sells at market, if close price is lower than the previous close price
during 2 days and the meaning of 9-days Stochastic Fast Oscillator is higher than 50.
Second strategy
This indicator plots Chande Momentum Oscillator and its WMA on the
same chart. This indicator plots the absolute value of CMO.
The CMO is closely related to, yet unique from, other momentum oriented
indicators such as Relative Strength Index, Stochastic, Rate-of-Change,
etc. It is most closely related to Welles Wilder?s RSI, yet it differs
in several ways:
- It uses data for both up days and down days in the numerator, thereby
directly measuring momentum;
- The calculations are applied on unsmoothed data. Therefore, short-term
extreme movements in price are not hidden. Once calculated, smoothing
can be applied to the CMO, if desired;
- The scale is bounded between +100 and -100, thereby allowing you to clearly
see changes in net momentum using the 0 level. The bounded scale also allows
you to conveniently compare values across different securities.
WARNING:
- For purpose educate only
- This script to change bars colors.
TRIX strategy (lirshah)TRIX is an indicator that combines trend with momentum. The triple smoothed moving average covers the trend, while the 1-period percentage change measures momentum. In this regard, TRIX is similar to MACD and PPO. The standard setting for TRIX is 15 for the triple smoothed EMA and 9 for the signal line.
this strategy gives signals according to TRIX plot movement and has good resaults on xbtusd,btcusd, ethusd ,and ...
CMO & WMA Backtest ver 2.0 This indicator plots Chandre Momentum Oscillator and its WMA on the
same chart. This indicator plots the absolute value of CMO.
The CMO is closely related to, yet unique from, other momentum oriented
indicators such as Relative Strength Index, Stochastic, Rate-of-Change,
etc. It is most closely related to Welles Wilder?s RSI, yet it differs
in several ways:
- It uses data for both up days and down days in the numerator, thereby
directly measuring momentum;
- The calculations are applied on unsmoothed data. Therefore, short-term
extreme movements in price are not hidden. Once calculated, smoothing
can be applied to the CMO, if desired;
- The scale is bounded between +100 and -100, thereby allowing you to clearly
see changes in net momentum using the 0 level. The bounded scale also allows
you to conveniently compare values across different securities.
CMOfilt BacktestThis indicator plots a CMO which ignores price changes which are less
than a threshold value. CMO was developed by Tushar Chande. A scientist,
an inventor, and a respected trading system developer, Mr. Chande developed
the CMO to capture what he calls "pure momentum". For more definitive
information on the CMO and other indicators we recommend the book The New
Technical Trader by Tushar Chande and Stanley Kroll.
The CMO is closely related to, yet unique from, other momentum oriented
indicators such as Relative Strength Index, Stochastic, Rate-of-Change, etc.
It is most closely related to Welles Wilder`s RSI, yet it differs in several ways:
- It uses data for both up days and down days in the numerator, thereby directly
measuring momentum;
- The calculations are applied on unsmoothed data. Therefore, short-term extreme
movements in price are not hidden. Once calculated, smoothing can be applied to the
CMO, if desired;
- The scale is bounded between +100 and -100, thereby allowing you to clearly see
changes in net momentum using the 0 level. The bounded scale also allows you to
conveniently compare values across different securities.
You can change long to short in the Input Settings
Please, use it only for learning or paper trading. Do not for real trading.
CMOabs Backtest This indicator plots the absolute value of CMO. CMO was developed by Tushar
Chande. A scientist, an inventor, and a respected trading system developer,
Mr. Chande developed the CMO to capture what he calls "pure momentum". For
more definitive information on the CMO and other indicators we recommend the
book The New Technical Trader by Tushar Chande and Stanley Kroll.
The CMO is closely related to, yet unique from, other momentum oriented indicators
such as Relative Strength Index, Stochastic, Rate-of-Change, etc. It is most closely
related to Welles Wilder`s RSI, yet it differs in several ways:
- It uses data for both up days and down days in the numerator, thereby directly
measuring momentum;
- The calculations are applied on unsmoothed data. Therefore, short-term extreme
movements in price are not hidden. Once calculated, smoothing can be applied to
the CMO, if desired;
- The scale is bounded between +100 and -100, thereby allowing you to clearly see
changes in net momentum using the 0 level. The bounded scale also allows you to
conveniently compare values across different securities.
You can change long to short in the Input Settings
Please, use it only for learning or paper trading. Do not for real trading.
CMO & WMA Backtest This indicator plots Chande Momentum Oscillator and its WMA on the
same chart. This indicator plots the absolute value of CMO.
The CMO is closely related to, yet unique from, other momentum oriented
indicators such as Relative Strength Index, Stochastic, Rate-of-Change,
etc. It is most closely related to Welles Wilder?s RSI, yet it differs
in several ways:
- It uses data for both up days and down days in the numerator, thereby
directly measuring momentum;
- The calculations are applied on unsmoothed data. Therefore, short-term
extreme movements in price are not hidden. Once calculated, smoothing
can be applied to the CMO, if desired;
- The scale is bounded between +100 and -100, thereby allowing you to clearly
see changes in net momentum using the 0 level. The bounded scale also allows
you to conveniently compare values across different securities.
Ergotic TSI Strategy Backtest r - Length of first EMA smoothing of 1 day momentum 4
s - Length of second EMA smoothing of 1 day smoothing 8
u- Length of third EMA smoothing of 1 day momentum 6
Length of EMA signal line 3
Source of Ergotic TSI Close
This is one of the techniques described by William Blau in his book "Momentum,
Direction and Divergence" (1995). If you like to learn more, we advise you to
read this book. His book focuses on three key aspects of trading: momentum,
direction and divergence. Blau, who was an electrical engineer before becoming
a trader, thoroughly examines the relationship between price and momentum in
step-by-step examples. From this grounding, he then looks at the deficiencies
in other oscillators and introduces some innovative techniques, including a
fresh twist on Stochastics. On directional issues, he analyzes the intricacies
of ADX and offers a unique approach to help define trending and non-trending periods.
You can use in the xPrice any series: Open, High, Low, Close, HL2, HLC3, OHLC4 and ect...
You can change long to short in the Input Settings
Please, use it only for learning or paper trading. Do not for real trading.
TrendStrike PRO X🧠 TrendStrike Pro X — Advanced Trend-Following Strategy
TrendStrike Pro X is a precision-engineered trading system designed for trending markets. It combines price action with a multi-layered confirmation model to generate high-quality trade signals.
________________________________________
🚀 Core Logic
This strategy uses a dual-filter approach based on:
• Trend Detection: A crossover between fast and slow EMAs confirms directional bias.
• Entry Signal: A strict single-candle engulfing pattern serves as the trigger, providing clean entries aligned with market momentum.
• Signals only appear when both conditions align, increasing the probability of success and reducing noise.
________________________________________
🎯 Risk Management & Performance
Each trade dynamically calculates risk parameters:
• Stop Loss: Dynamically calculated based on price distance from EMA structure plus a volatility buffer.
• Take Profit: Always fixed at a 1:2 Risk-Reward Ratio.
• Risk Per Trade: Set at 0.5% of the account balance (configurable externally via position sizing).
📊 With a consistent 1:2 RR, the strategy only requires a 50% win rate to remain profitable. In forward testing and live conditions, the average win rate ranges between 62% and 68% depending on market volatility and asset class.
________________________________________
⏱️ Recommended Timeframes
• Works across all timeframes and assets.
• Optimized for 5-minute and 15-minute charts, especially on high-volume pairs or commodities like NAS100 and XAUUSD.
________________________________________
⚠️ Market Conditions
TrendStrike Pro X performs best in clearly trending environments.
During low-volatility or ranging markets, false signals may occur, as with any trend-based system. Users are encouraged to combine the strategy with higher-timeframe structure or volatility filters if needed.
________________________________________
🔍 Key Features
• Dynamic trend filtering using dual EMA logic
• Strict engulfing candle entry trigger
• Adaptive SL/TP engine based on trend zones
• Clean visual interface with optional signal history display
________________________________________
📘 How to Use
1. Add the strategy to your chart and choose your preferred timeframe.
2. Monitor for signals — trades are only generated under high-confluence setups.
3. Optional: Use alerts to be notified when a signal occurs (manual setup via TradingView alerts).
📡 Alerts & Automation
TrendStrike Pro X supports real-time TradingView alerts when entry conditions are met, allowing users to stay informed without constantly monitoring charts.
system signals 15System Signals 15
## Overview
This is a comprehensive Pine Script v5 trading strategy that combines multiple technical indicators and market conditions to generate buy/sell signals. The strategy offers 7 different modes, each with unique entry criteria, plus advanced risk management features.
## Strategy Modes Explained
### Mode 1: Only Divergence
- **Entry Condition**: Pure RSI divergence signals
- **Buy Signal**: Bullish divergence (regular or hidden) detected
- **Sell Signal**: Bearish divergence (regular or hidden) detected
- **Use Case**: For traders who rely solely on momentum divergence
### Mode 2: Divergence + SuperTrend
- **Entry Condition**: RSI divergence + SuperTrend confirmation
- **Buy Signal**: Bullish divergence detected AND SuperTrend changes to bullish (trend2 == 1)
- **Sell Signal**: Bearish divergence detected AND SuperTrend changes to bearish (trend2 == -1)
- **Logic**: Waits for trend confirmation after divergence is spotted
### Mode 3: Divergence + SuperTrend + Volume
- **Entry Condition**: All Mode 2 conditions + volume filter
- **Buy Signal**: Mode 2 conditions + volume above SMA threshold
- **Sell Signal**: Mode 2 conditions + volume above SMA threshold
- **Benefit**: Adds volume confirmation to reduce false signals
### Mode 4: Divergence + Volume
- **Entry Condition**: RSI divergence + volume confirmation (no trend requirement)
- **Buy Signal**: Bullish divergence + volume above threshold
- **Sell Signal**: Bearish divergence + volume above threshold
- **Strategy**: Volume-confirmed divergence without waiting for trend change
### Mode 5: SuperTrend + Volume
- **Entry Condition**: SuperTrend change + volume confirmation (no divergence needed)
- **Buy Signal**: SuperTrend turns bullish + volume above threshold
- **Sell Signal**: SuperTrend turns bearish + volume above threshold
- **Approach**: Pure trend following with volume confirmation
### Mode 6: SuperTrend Only
- **Entry Condition**: SuperTrend direction change only
- **Buy Signal**: SuperTrend changes to bullish
- **Sell Signal**: SuperTrend changes to bearish
- **Use**: Simple trend following system
### Mode 7: Session Liquidity Sweep (Special Mode)
- **Entry Condition**: 3-candle pattern after session high/low liquidity sweep
- **Complex Logic**:
- Detects when price sweeps session highs/lows
- Waits for 3-candle pattern completion
- Enters on return to middle candle level
- **Advanced**: Uses session-based liquidity concepts
## Key Filters and Conditions
### 1. Session Time Filter
```pinescript
startHour/startMinute to endHour/endMinute
```
- Allows trading only during specified hours
- Configurable start and end times
- Can be enabled/disabled
### 2. Volume Filter
```pinescript
volumeThreshold = volumeSMA * volumeMultiplier
```
- **Volume SMA Length**: 15 periods (default)
- **Volume Multiplier**: 40% above SMA (default)
- Ensures trades only occur during higher volume periods
### 3. RSI Divergence Detection
```pinescript
RSI Period: 22 (default)
Lookback Left: 10, Lookback Right: 10
```
- **Regular Bullish**: Price makes lower low, RSI makes higher low
- **Regular Bearish**: Price makes higher high, RSI makes lower high
- **Hidden Bullish**: Price makes higher low, RSI makes lower low
- **Hidden Bearish**: Price makes lower high, RSI makes higher high
### 4. SuperTrend Indicator
```pinescript
ATR Period: 10
ATR Multiplier: 3.0
```
- Dynamic support/resistance levels
- Trend direction indicator
- Used for trend change detection
### 5. Trend Bands Filter
```pinescript
Length: 4
```
- Custom trend strength indicator
- Shows bullish/bearish strength levels
- Optional trend condition filter
### 6. Session High/Low Distance Filter
- **Points Mode**: Maximum distance in points from session levels
- **Percentage Mode**: Maximum percentage distance from session levels
- Prevents entries too far from key levels
## Risk Management System
### 1. Time-Based Take Profit/Stop Loss
The strategy uses different TP/SL percentages based on trading sessions:
#### Period 1 (8:00-12:00 GMT)
- **Take Profit**: 0.10% (default)
- **Stop Loss**: 0.12% (default)
#### Period 2 (13:00-17:00 GMT)
- **Take Profit**: 0.15% (default)
- **Stop Loss**: 0.18% (default)
#### Period 3 (18:00-22:00 GMT)
- **Take Profit**: 0.08% (default)
- **Stop Loss**: 0.10% (default)
#### Default (Outside Sessions)
- **Take Profit**: 0.12% (default)
- **Stop Loss**: 0.14% (default)
### 2. Three Stop Loss Types
#### A. Fixed Stop Loss
```pinescript
fix_stop = 4% (default)
```
- Static percentage-based stop loss
- Calculated from entry price
- Simple and predictable
#### B. Trailing Stop Loss
```pinescript
trailing_stop = 0.8% (default)
```
- **Long Positions**: Stop loss trails price upward
- **Short Positions**: Stop loss trails price downward
- Locks in profits as trade moves favorably
- **Logic**:
```pinescript
longstoppriceTrailing = max(current_trailing_level, previous_trailing_level)
```
#### C. Candle-Based Stop Loss
- Uses recent high/low levels
- **Long**: Stop below recent low + offset
- **Short**: Stop above recent high + offset
- **Offset**: 2.0 pips (default)
- **Risk-Reward Ratio**: 1.5:1 (default)
### 3. Daily Trade Limits (Mode 6 Only)
```pinescript
maxDailyTrades = 5 (default)
```
- Prevents overtrading
- Resets at start of new trading day
- Helps maintain discipline
### 4. Position Sizing
```pinescript
contracts = 1 (default)
```
- Configurable contract/share quantity
- Applied to all entries
## Session Management
### Asia Session (00:00-09:00 GMT)
- Tracks session high/low levels
- Background color: Yellow (when Mode 6 active)
### London Session (08:00-17:00 GMT)
- Overlap with Asia creates opportunities
- Background color: Orange (when Mode 6 active)
### New York Session (13:00-22:00 GMT)
- Highest volume period
- Background color: Blue (when Mode 6 active)
### Session Liquidity Logic (Mode 7)
1. **Level Detection**: Identifies when one session takes out another session's high/low
2. **Pattern Formation**: Waits for 3-candle pattern after level taken
3. **Entry Trigger**: Price returns to specified percentage of middle candle
4. **Direction Logic**:
- If high taken → expect short opportunity
- If low taken → expect long opportunity
## Visual Elements
### 1. Trend Lines and Levels
- SuperTrend lines (green for bullish, red for bearish)
- Session high/low levels
- Swing high/low levels
### 2. Entry/Exit Visualization
- Entry price line (blue)
- Take profit lines (green)
- Stop loss lines (red)
- Filled areas showing risk/reward zones
### 3. Signal Indicators
- Buy signals: Green triangle up
- Sell signals: Red triangle down
- RSI divergence markers
- Trend change alerts
## Performance Monitoring
### Real-Time Statistics Table
- **Percent Profitable**: Win rate percentage
- **Total Trades**: Number of completed trades
- **Winning/Losing Trades**: Breakdown of results
- **Net Profit**: Overall profit/loss
- **Open Trades**: Current active positions
### Alert System
- Real-time buy/sell alerts
- Trend change notifications
- Divergence detection alerts
- Liquidity sweep alerts
## Strategy Recommendations
### For Beginners
- Start with **Mode 6** (SuperTrend only)
- Use **Fixed Stop Loss** initially
- Enable **Session Time Filter** for specific hours
### For Intermediate Traders
- Try **Mode 2 or 3** (Divergence + SuperTrend)
- Experiment with **Trailing Stop Loss**
- Use **Volume Filter** for confirmation
### For Advanced Traders
- Explore **Mode 7** (Session Liquidity Sweep)
- Combine multiple filters
- Fine-tune time-based TP/SL levels
- Utilize **Daily Trade Limits**
## Risk Warnings
1. **Backtesting Required**: Test thoroughly before live trading
2. **Market Conditions**: Performance varies across different market environments
3. **Parameter Sensitivity**: Small changes in settings can significantly impact results
4. **Slippage Consideration**: Real trading may differ from backtest results
5. **Risk Management**: Never risk more than you can afford to lose
## Conclusion
This strategy offers tremendous flexibility through its multiple modes and comprehensive filtering system. The sophisticated risk management features, including trailing stops and time-based TP/SL levels, make it suitable for various trading styles and market conditions. However, proper testing and gradual implementation are essential for success.
Advanced Order Management: Limit Orders & Offset
Limit Order System
How Limit Orders Work in This Strategy:
For Long Entries:
pinescriptif (orderType == "Market")
strategy.entry("Long", strategy.long)
else
limitPrice = close * (1 - limitOffset / 100)
strategy.entry("Long", strategy.long, limit=limitPrice)
Market Order: Enters immediately at current market price
Limit Order: Waits for price to drop by the offset percentage before entering
Example: If current price is $100 and offset is 0.1%, limit order placed at $99.90
For Short Entries:
pinescriptif (orderType == "Market")
strategy.entry("Short", strategy.short)
else
limitPrice = close * (1 + limitOffset / 100)
strategy.entry("Short", strategy.short, limit=limitPrice)
Limit Order: Waits for price to rise by the offset percentage before entering
Example: If current price is $100 and offset is 0.1%, limit order placed at $100.10
Benefits of Limit Orders with Offset
1. Better Entry Prices
Avoids chasing momentum
Gets filled at more favorable prices
Reduces slippage in volatile markets
2. Risk Reduction
Prevents entering at temporary price spikes
Allows for slight retracements before entry
Better risk-reward ratios
3. Market Efficiency
Takes advantage of brief pullbacks
Reduces impact of bid-ask spreads
More precise execution
Offset Strategy Examples
Conservative Approach (0.05-0.1% offset)
Minimal price improvement
Higher fill probability
Good for trending markets
Moderate Approach (0.1-0.2% offset)
Balance between price improvement and fill rate
Suitable for most market conditions
Recommended for beginners
Aggressive Approach (0.2-0.5% offset)
Maximum price improvement
Lower fill probability
Best for ranging/choppy markets
Stop Loss Offset System
pinescriptSL_offset_pips = input.float(2.0, title='StopLoss Offset (Pips)', minval=0.0, step=1.0)
SL_offset = SL_offset_pips * pip_value
Candle-Based Stop Loss with Offset:
pinescriptCandlelongStopPrice = strategy.position_avg_price * (1 - CandleSLpercentageL) + SL_offset
CandleshortStopPrice = strategy.position_avg_price * (1 + CandleSLpercentageS) + SL_offset
Why Offset is Important:
Prevents False Stops: Small market noise won't trigger stops
Accounts for Spreads: Ensures stops are beyond bid-ask spread
Reduces Whipsaws: Gives trades breathing room
Professional Approach: Mimics institutional trading practices
Practical Implementation Tips
For Day Trading:
Use smaller offsets (0.05-0.1%)
Market orders for momentum trades
Limit orders for counter-trend entries
For Swing Trading:
Larger offsets acceptable (0.2-0.5%)
Limit orders preferred for better entries
Wider stop loss offsets (3-5 pips)
For Scalping:
Minimal offsets (0.02-0.05%)
Quick market orders often preferred
Tight stop loss offsets (1-2 pips)
Order Management Best Practices
1. Market Conditions Consideration
Trending Markets: Smaller offsets, more market orders
Ranging Markets: Larger offsets, more limit orders
High Volatility: Increase all offsets
Low Volatility: Decrease offsets
2. Time of Day Adjustments
Market Open: Wider offsets due to volatility
Mid-Session: Standard offsets
Market Close: Wider offsets for gap protection
3. Asset-Specific Settings
Forex: Smaller pip-based offsets
Stocks: Percentage-based offsets
Crypto: Larger offsets due to volatility
Commodities: Medium offsets
4. Risk Management Integration
pinescript// Dynamic offset based on ATR
dynamicOffset = ta.atr(14) * 0.5 / close * 100
Consider using volatility-based offsets for optimal performance.
NA GPT - TTM Squeeze Strategy### Strategy Overview
“**NA GPT – TTM Squeeze Strategy**” converts John Carter’s TTM Squeeze indicator into a long-only, fully back-testable TradingView strategy. It looks for prolonged volatility compression, rides the breakout, and exits only when momentum fades beneath a 21-period EMA **after** the squeeze has fired.
---
#### 1. Core Concepts & Calculations
**Squeeze state** – A squeeze is “ON” when a 20-period Bollinger Band (2 × std-dev) fits completely inside a 20-period Keltner Channel (1.5 × ATR or High-Low range). This signals tight volatility ready to expand.
**Momentum histogram** – The script measures price’s deviation from a blended average of (highest + lowest)/2 and the 20-SMA, then applies a 20-bar linear regression. Rising green/lime bars show strengthening bulls; falling maroon/red bars show growing bears.
**Blue-dot theme** – Dots plotted at the chart bottom highlight the squeeze status:
* Navy-blue = squeeze ON (volatility compressed)
* Steel-blue = squeeze just released
* Sky-blue = no squeeze
---
#### 2. Trading Logic
* **Entry (long):** fires when three consecutive navy-blue dots appear. Requiring three bars filters out one-bar false signals.
* **Exit (flat):** triggers only when price **closes below the 21-period EMA *and* the squeeze is no longer ON**. This keeps the position alive during healthy up-trend closes above the EMA or while the squeeze is still building.
* **Positioning:** one long position at a time; no shorts.
---
#### 3. Inputs & Parameters
* Bollinger Band length and multiplier (default 20 / 2.0).
* Keltner Channel length and multiplier (default 20 / 1.5).
* Option to base KC width on True Range instead of High-Low.
* User-defined trade window — by default 1 Jan 2022 through 31 Dec 2069 — lets you restrict back-tests to specific periods.
* Commission is fixed at **0.01 %**, slippage at **3 ticks**, both set in the strategy header and easily editable.
---
#### 4. Visual Outputs
* Momentum histogram coloured lime/green/red/maroon.
* Zero line tinted blue/navy/grey by squeeze status.
* Blue-dot row marking each squeeze bar.
These visuals are identical to the original indicator, so you can quickly see why each trade fired.
---
#### 5. How to Use
1. Add the script to any symbol and timeframe.
2. Adjust BB/KC settings to suit your instrument’s volatility.
3. Narrow or widen the trade-window dates for focused testing.
4. Open the **Strategy Tester** to review historical performance, trade list, and drawdowns.
5. Validate trades visually: entries follow three navy dots; exits occur only once price drops below EMA-21 and the squeeze has released.
6. Layer in your own filters (higher-timeframe trend, volume, risk-management, etc.) before live deployment.
---
#### 6. Practical Notes
* Built for research and education — **not financial advice**.
* EMA-based exits can lag during violent reversals; use additional stops if trading thin or fast markets.
* The script is closed-source, but all key calculations and trade rules are fully described above so you can understand exactly what drives every entry and exit.
Divergência MACD + Reversão (Comprado)This strategy is designed for long-only trades in cryptocurrency futures markets, operating exclusively on the buy side. It combines two key technical analysis concepts to identify high-probability reversal zones and trigger entries with confirmation.
1. Bullish Divergence (MACD Histogram):
The strategy looks for a bullish divergence between price and the MACD histogram. This occurs when:
Price makes a lower low (new swing low).
MACD histogram forms a higher low, indicating loss of downside momentum.
This divergence signals a potential trend reversal or bounce.
2. Reversal Confirmation (Trigger Candle):
To avoid premature entries, a confirmation candle is required:
A bullish candlestick must close above the high of the previous bar.
This candle serves as a "trigger" for the actual trade entry.
3. Entry Conditions:
A trade is entered only when both:
A valid bullish divergence is detected.
A bullish reversal candle is confirmed, or the MACD histogram crosses into positive territory.
📉 Risk Management
Stop Loss: Set just below the most recent swing low (the divergence low).
Take Profit: Calculated based on a customizable Risk:Reward ratio (e.g., 2:1).
Trailing Stop: Optional feature that follows price with a dynamic stop once the trade is in profit, helping to lock in gains.
TrendMaster Pro 2.3 with Alerts
Hello friends,
A member of the community approached me and asked me how to write an indicator that would achieve a particular set of goals involving comprehensive trend analysis, risk management, and session-based trading controls. Here is one example method of how to create such a system:
Core Strategy Components
Multi-Moving Average System - Uses configurable MA types (EMA, SMA, SMMA) with short-term (9) and long-term (21) periods for primary signal generation through crossovers
Higher Timeframe Trend Filter - Optional trend confirmation using a separate MA (default 50-period) to ensure trades align with broader market direction
Band Power Indicator - Dynamic high/low bands calculated using different MA types to identify price channels and volatility zones
Advanced Signal Filtering
Bollinger Bands Volatility Filter - Prevents trading during low-volatility ranging markets by requiring sufficient band width
RSI Momentum Filter - Uses customizable thresholds (55 for longs, 45 for shorts) to confirm momentum direction
MACD Trend Confirmation - Ensures MACD line position relative to signal line aligns with trade direction
Stochastic Oscillator - Adds momentum confirmation with overbought/oversold levels
ADX Strength Filter - Only allows trades when trend strength exceeds 25 threshold
Session-Based Trading Management
Four Trading Sessions - Asia (18:00-00:00), London (00:00-08:00), NY AM (08:00-13:00), NY PM (13:00-18:00)
Individual Session Limits - Separate maximum trade counts for each session (default 5 per session)
Automatic Session Closure - All positions close at specified market close time
Risk Management Features
Multiple Stop Loss Options - Percentage-based, MA cross, or band-based SL methods
Risk/Reward Ratio - Configurable TP levels based on SL distance (default 1:2)
Auto-Risk Calculation - Dynamic position sizing based on dollar risk limits ($150-$250 range)
Daily Limits - Stop trading after reaching specified TP or SL counts per day
Support & Resistance System
Multiple Pivot Types - Traditional, Fibonacci, Woodie, Classic, DM, and Camarilla calculations
Flexible Timeframes - Auto-adjusting or manual timeframe selection for S/R levels
Historical Levels - Configurable number of past S/R levels to display
Visual Customization - Individual color and display settings for each S/R level
Additional Features
Alert System - Customizable buy/sell alert messages with once-per-bar frequency
Visual Trade Management - Color-coded entry, SL, and TP levels with fill areas
Session Highlighting - Optional background colors for different trading sessions
Comprehensive Filtering - All signals must pass through multiple confirmation layers before execution
This approach demonstrates how to build a professional-grade trading system that combines multiple technical analysis methods with robust risk management and session-based controls, suitable for algorithmic trading across different market sessions.
Good luck and stay safe!
Algoway V4.2📌 Algoway V4.2 — Multi-layered Strategy Powered by ADX, MACD & PSO
Overview
Algoway V4.2 is a layered algorithmic strategy designed for volatility-rich assets like cryptocurrencies. While some core components (such as PSO, MACD, and ADX oscillators) are adapted from known indicator models, the original logic, state tracking, and Candle Strength Oscillator (CSO) are fully custom-developed.
This strategy is not a simple combination of tools — it implements a conditional entry-exit logic system based on ADX zone transitions, momentum structure, and MACD/PSO signal synchronization, enhanced by custom-built CSO filtering.
🧠 Key Modules and How They Work Together
PSO (Premium Stochastic Oscillator)
Used to confirm local oversold/overbought pressure. Acts as a directional filter.
MACD (Normalized)
Volatility-normalized MACD values allow consistent signal detection even on volatile pairs. It triggers entries when momentum begins shifting.
ADX Zonal Logic
Divides the market into Range / MidRange / Trend Peak zones. Entries are allowed only under specific transitions — e.g., long entries only in yellow (low volatility) zones or in trend climax zones under certain pullbacks.
CSO (Candle Strength Oscillator) — Custom Module
Designed to measure real candle momentum and price structure consistency. It avoids false breakouts and filters trend fatigue.
🔁 How Logic Works
Strategy maintains state variables to track entry type and zone.
Exit conditions depend on the entry origin: entries from "Range" exit in "Peak", while "Peak" entries exit during pullbacks or mid-strength trend reversals.
Additional logic prevents entries when signals are not aligned across modules, minimizing noise.
Optional CSO module acts as a final microstructure confirmation before executing MACD-based midpoint entries.
📊 Example Parameters (for 5M crypto scalping)
Each module is tuned to respond to 5-minute crypto volatility:
Stochastic: fast response, tight thresholds
MACD: shortened EMAs, normalized
ADX: traditional smoothing, custom thresholds for zone switching
CSO: candle-based dynamic filter with visual zone mapping
🧪 Conclusion
Algoway V4.2 is not a script merger — it is a custom logic engine using familiar technical components but governed by a proprietary decision model, with additional filters and dynamic variable tracking.
It’s suitable for scalping or swing setups, and the internal logic is optimized for real trading conditions, not just visual backtests.
Antony.N4A -NQ ORB Quartile Str v6.3Antony.N4A – NQ ORB Quartile Strategy v6.3
A precision-engineered intraday breakout system built for the Nasdaq futures market, combining the Opening Range Breakout (ORB) logic with dynamic standard deviation targets, structural filters, and multi-layer risk management.
🧠 Key Features
Opening Range Breakout (ORB):
Automatically defines a breakout window (default: 09:30–09:45) and triggers entries when price breaks the high or low of that range.
Standard Deviation Profit Targets:
Supports SD0.5, SD1.0, SD1.5, and SD2.0 targets relative to the ORB range.
EMA Filtering (200-period):
Filters trades based on EMA direction and price position to validate breakout direction and avoid false entries.
Range Filtering:
Detects directional bias and volatility trends using smoothed range logic.
Momentum Triggering:
Validates breakout momentum and allows entries when directional momentum is positive and increasing.
⚙️ User Inputs
ORB Settings: Timeframe, session, and timezone customization
Entry Window: Define when trades are allowed to trigger
Day Filters: Enable/disable trading by weekday
SD Targets: Configure exit % and active levels (SD0.5 – SD2.0)
EMA Filter & Sensitivity
Cross Filter (Anti-chop logic)
Range Filter Parameters
Visual Toggles: ORB range, SD levels, EMA clouds
🎯 Trade Management Rules
Entry:
Triggered at the close of a 5-minute candle confirming a breakout of the ORB range.
Stop Loss:
Defined by structural invalidation (quartile boundaries & mid-range buffers).
Take Profit Strategy:
75% closed at SD1.0 level
Remaining 25% trailed to further SD2 target
SL is moved to breakeven after partial exit
Execution Controls:
No pyramiding
No re-entries (cooldown enforced)
🔧 Trading Modes
✅ Safe Mode
EMA Filter: Enabled
EMA Sensitivity: 19
Range Filter: Disabled
Ideal for conservative setups and reduced noise environments
🔥 Aggressive Mode
EMA Filter: Enabled
EMA Sensitivity: 5
Range Filter: Disabled
Suited for high-frequency setups and faster breakouts
📊 Backtest Performance (7-Month Sample)
Safe Mode:
Win Rate: 66%
Total Trades: 29
Net PnL: +21.79R (~$4,357 with R = $200)
Max Red Days: 3
Max Drawdown: -$663
Best Month: +9R, Worst Month: -2R
Aggressive Mode:
Win Rate: 63%
Total Trades: 52
Net PnL: +30R (~$6,080)
Max Red Days: 6
Max Drawdown: -$1,357
Best Month: +12R, Worst Month: -3.2R
👨💻 Developed by Antony.N4A
This tool is crafted for strategic intraday traders, system developers, and backtesters.
For access, customization, or licensing options, contact the developer directly.
Protected script. Redistribution or reuse without permission is prohibited.
Trend Surge with Pullback FilterTrend Surge with Pullback Filter
Overview
Trend Surge with Pullback Filter is a price action-based strategy designed to enter strong trends not at the breakout, but at the first controlled pullback after a surge. It filters out noise by requiring momentum confirmation and low volatility conditions, aiming for better entry prices and reduced risk exposure.
How It Works
A strong upward trend is identified when the Rate of Change (ROC) exceeds a defined percentage (e.g., 2%).
Instead of jumping into the trend immediately, the strategy waits for a pullback: the price must drop at least 1% below its recent high (over the past 3 candles).
A low volatility environment is also required for entry — measured using ATR being below its 20-period average multiplied by a safety factor.
If all three conditions are met (trend + pullback + quiet volatility), the system enters a long position.
The trade is managed using a dynamic ATR-based stop-loss and a take-profit at 2x ATR.
An automatic exit occurs after 30 bars if neither SL nor TP is hit.
Key Features
- Momentum-triggered trend detection via ROC
- Smart pullback filter avoids overbought entries
- Volatility-based filter to eliminate noise and choppy conditions
- Dynamic risk-reward ratio with ATR-driven exit logic
- Time-limited exposure using bar-based exit
Parameter Explanation
ROC Length (10): Looks for short-term price surges
ROC Threshold (2.0%): Trend is considered valid if price increased more than 2%
Pullback Lookback (3): Checks last 3 candles for price retracement
Minimum Pullback % (1.0%): Entry only if price pulled back at least 1%
ATR Length (14): Measures current volatility
Low Volatility Multiplier (1.2): ATR must be below this multiple of its 20-period average
Risk-Reward (2.0): Target is set at 2x the stop-loss distance
Max Bars (30): Trade is closed automatically after 30 bars
Originality Statement
This strategy doesn’t enter at the trend start, unlike many momentum bots. Instead, it waits for the first market hesitation — a minor pullback under low volatility — before entering. This logic mimics how real traders often wait for a better entry after a breakout, avoiding emotional overbought buys. The combined use of ROC, dynamic pullback detection, and ATR-based environment filters makes it both practical and original for real-world trading.
Disclaimer
This strategy is intended for educational and research purposes. Backtest thoroughly and understand the logic before using with real capital.
Intraday Trading Hit and Run# Strategy Overview
This is a short-term trading system designed for quick entries/exits (intraday). It uses multiple technical indicators to identify momentum trades in the direction of the trend, with built-in risk management through trailing stops.
# Main Components
1. Trend Filter
Uses two EMAs (10-period "fast" blue line and 100-period "slow" red line)
Only trades when:
Long: Price AND fast EMA are above slow EMA
Short: Price AND fast EMA are below slow EMA
2. Main Signal
////Stochastic Oscillator (14-period):
Buy when %K line crosses above %D line
Sell when %K crosses below %D
////Trend Strength Check
Smoothed ADX indicator (5-period EMA of ADX):
Requires ADX value ≥ 25 to confirm strong trend
3. Confirmation using Volume Filter (Optional)
Checks if current volume is 1.5× greater than 20-period average volume
# Entry Rules
A trade is only taken when:
All 3 indicators agree (EMA trend, Stochastic momentum, ADX strength)
Volume filter is satisfied (if enabled)
# Exit Rules
1. Emergency Exit:
Close long if price drops below fast EMA
Close short if price rises above fast EMA
2. Trailing Stop:
Actively protects profits by moving stop-loss:
Maintains 0.1% distance from highest price (longs) or lowest price (shorts)
# Risk Management
Only use 10% of account per trade
Includes 0.04% commission cost in calculations
All trades monitored with trailing stops
# How It Operates
The strategy looks for strong, high-volume momentum moves in the direction of the established trend (as determined by EMAs). It jumps in quickly ("hit") when conditions align, then protects gains with an automatic trailing stop ("run"). Designed for fast markets where trends develop rapidly.
You can use it on 15m, 1h or 4h
