TitanGrid L/S SuperEngineTitanGrid L/S SuperEngine
Experimental Trend-Aligned Grid Signal Engine for Long & Short Execution
🔹 Overview
TitanGrid is an advanced, real-time signal engine built around a tactical grid structure.
It manages Long and Short trades using trend-aligned entries, layered scaling, and partial exits.
Unlike traditional strategy() -based scripts, TitanGrid runs as an indicator() , but includes its own full internal simulation engine.
This allows it to track capital, equity, PnL, risk exposure, and trade performance bar-by-bar — effectively simulating a custom backtest, while remaining compatible with real-time alert-based execution systems.
The concept was born from the fusion of two prior systems:
Assassin’s Grid (grid-based execution and structure) + Super 8 (trend-filtering, smart capital logic), both developed under the AssassinsGrid framework.
🔹 Disclaimer
This is an experimental tool intended for research, testing, and educational use.
It does not provide guaranteed outcomes and should not be interpreted as financial advice.
Use with demo or simulated accounts before considering live deployment.
🔹 Execution Logic
Trend direction is filtered through a custom SuperTrend engine. Once confirmed:
• Long entries trigger on pullbacks, exiting progressively as price moves up
• Short entries trigger on rallies, exiting as price declines
Grid levels are spaced by configurable percentage width, and entries scale dynamically.
🔹 Stop Loss Mechanism
TitanGrid uses a dual-layer stop system:
• A static stop per entry, placed at a fixed percentage distance matching the grid width
• A trend reversal exit that closes the entire position if price crosses the SuperTrend in the opposite direction
Stops are triggered once per cycle, ensuring predictable and capital-aware behavior.
🔹 Key Features
• Dual-side grid logic (Long-only, Short-only, or Both)
• SuperTrend filtering to enforce directional bias
• Adjustable grid spacing, scaling, and sizing
• Static and dynamic stop-loss logic
• Partial exits and reset conditions
• Webhook-ready alerts (browser-based automation compatible)
• Internal simulation of equity, PnL, fees, and liquidation levels
• Real-time dashboard for full transparency
🔹 Best Use Cases
TitanGrid performs best in structured or mean-reverting environments.
It is especially well-suited to assets with the behavioral profile of ETH — reactive, trend-intraday, and prone to clean pullback formations.
While adaptable to multiple timeframes, it shows strongest performance on the 15-minute chart , offering a balance of signal frequency and directional clarity.
🔹 License
Published under the Mozilla Public License 2.0 .
You are free to study, adapt, and extend this script.
🔹 Panel Reference
The real-time dashboard displays performance metrics, capital state, and position behavior:
• Asset Type – Automatically detects the instrument class (e.g., Crypto, Stock, Forex) from symbol metadata
• Equity – Total simulated capital: realized PnL + floating PnL + remaining cash
• Available Cash – Capital not currently allocated to any position
• Used Margin – Capital locked in open trades, based on position size and leverage
• Net Profit – Realized gain/loss after commissions and fees
• Raw Net Profit – Gross result before trading costs
• Floating PnL – Unrealized profit or loss from active positions
• ROI – Return on initial capital, including realized and floating PnL. Leverage directly impacts this metric, amplifying both gains and losses relative to account size.
• Long/Short Size & Avg Price – Open position sizes and volume-weighted average entry prices
• Leverage & Liquidation – Simulated effective leverage and projected liquidation level
• Hold – Best-performing hold side (Long or Short) over the session
• Hold Efficiency – Performance efficiency during holding phases, relative to capital used
• Profit Factor – Ratio of gross profits to gross losses (realized)
• Payoff Ratio – Average profit per win / average loss per loss
• Win Rate – Percent of profitable closes (including partial exits)
• Expectancy – Net average result per closed trade
• Max Drawdown – Largest recorded drop in equity during the session
• Commission Paid – Simulated trading costs: maker, taker, funding
• Long / Short Trades – Count of entry signals per side
• Time Trading – Number of bars spent in active positions
• Volume / Month – Extrapolated 30-day trading volume estimate
• Min Capital – Lowest equity level recorded during the session
🔹 Reference Ranges by Strategy Type
Use the following metrics as reference depending on the trading style:
Grid / Mean Reversion
• Profit Factor: 1.2 – 2.0
• Payoff Ratio: 0.5 – 1.2
• Win Rate: 50% – 70% (based on partial exits)
• Expectancy: 0.05% – 0.25%
• Drawdown: Moderate to high
• Commission Impact: High
Trend-Following
• Profit Factor: 1.5 – 3.0
• Payoff Ratio: 1.5 – 3.5
• Win Rate: 30% – 50%
• Expectancy: 0.3% – 1.0%
• Drawdown: Low to moderate
Scalping / High-Frequency
• Profit Factor: 1.1 – 1.6
• Payoff Ratio: 0.3 – 0.8
• Win Rate: 80% – 95%
• Expectancy: 0.01% – 0.05%
• Volume / Month: Very high
Breakout Strategies
• Profit Factor: 1.4 – 2.2
• Payoff Ratio: 1.2 – 2.0
• Win Rate: 35% – 60%
• Expectancy: 0.2% – 0.6%
• Drawdown: Can be sharp after failed breakouts
🔹 Note on Performance Simulation
TitanGrid includes internal accounting of fees, slippage, and funding costs.
While its logic is designed for precision and capital efficiency, performance is naturally affected by exchange commissions.
In frictionless environments (e.g., zero-fee simulation), its high-frequency logic could — in theory — extract substantial micro-edges from the market.
However, real-world conditions introduce limits, and all results should be interpreted accordingly.
Tìm kiếm tập lệnh với "stop loss"
Pucci Trend EMA-SMA Crossover with TolerancePucci Trend EMA-SMA Crossover with Tolerance
This indicator helps identify market trends and generates trading signals based on the crossover between an Exponential Moving Average (EMA) and a Simple Moving Average (SMA) with an adjustable tolerance threshold. The signals work as follows:
Buy Signal (B) -> Triggers when the EMA crosses above the SMA, exceeding a user-defined tolerance (in basis points). Optionally, a price filter can require the high or low to be below the EMA for confirmation.
Sell Signal (S) -> Triggers when the SMA crosses above the EMA, exceeding the tolerance. The optional price filter may require the high or low to be above the EMA.
The tolerance helps reduce false signals by requiring a minimum distance between the moving averages before confirming a crossover. The price filter adds an extra confirmation layer by checking if price action respects the EMA level.
Important Notes:
1º No profitability guarantee: This tool is for analysis only and may generate losses.
2º "As Is" disclaimer: Provided without warranties or responsibility for trading outcomes.
3º Use Stop Loss: Users must determine their own risk management.
4º Parameter adjustment needed: Optimal MA periods and tolerance vary by timeframe.
5º Filter impact varies: Enabling/disabling the price filter may improve or worsen performance.
Opening Range BreakoutOPENING RANGE BREAKOUT (ORB) INDICATOR
DESCRIPTION
The Opening Range Breakout indicator is a powerful technical analysis tool designed specifically for US equity markets. It identifies and visualizes the opening range established during the first configurable minutes of each trading day (starting at 9:30 AM EST), then provides clear signals when price breaks out of or rejects from these key levels.
This indicator combines multiple timeframe analysis capabilities with precise breakout detection to help traders identify high-probability trading opportunities based on opening range dynamics.
KEY FEATURES
Configurable Opening Range:
• Set opening range duration from 5 minutes to 4 hours
• Automatically adjusts calculations based on your chart timeframe
• Works on any timeframe (1m, 5m, 15m, 1h, etc.)
Multi-Day Range Display:
• Shows up to 50 days of historical opening ranges
• Each day's range properly contained within its trading session
• Range lines extend from market open (9:30 AM) to market close (4:00 PM EST)
Clear Signal System:
• Green arrows (⬆): Bullish breakouts and rejections
• Red arrows (⬇): Bearish breakouts and rejections
• Two signal types: Close breakouts (normal size) and wick rejections (small size)
Visual Range Highlighting:
• Opening range period highlighted with colored box
• Customizable colors for range fill, borders, and midline
• Clean, professional appearance with configurable line styles
SIGNAL TYPES
Bullish Signals (Green ⬆):
1. Close Breakout Above Range (Normal Size): 5-minute candle closes above the opening range high
2. Wick Rejection from Below (Small Size): Price wicks below the opening range low but closes back inside the range
Bearish Signals (Red ⬇):
1. Close Breakout Below Range (Normal Size): 5-minute candle closes below the opening range low
2. Wick Rejection from Above (Small Size): Price wicks above the opening range high but closes back inside the range
CONFIGURATION OPTIONS
Range Settings:
• Opening Range Minutes: Duration of opening range (default: 30 minutes)
• Lookback Days: Number of historical days to display (default: 20 days)
Visual Customization:
• Range Color: Fill color for the opening range area
• Border Color: Color for range high/low lines
• Midline Color: Color for the range midpoint line
• Opening Range Highlight Color: Color for the opening period box
• Line Style: Solid, Dashed, or Dotted lines
• Line Width: 1-4 pixel width options
Display Options:
• Show Midline: Toggle midpoint line display
• Show Range Labels: Toggle price level labels
• Arrow Distance: Adjust arrow positioning (0.1-2.0%)
USAGE GUIDE
Basic Setup:
1. Add the indicator to your chart (works best on 5-minute timeframe)
2. Configure your preferred opening range duration (15m, 30m, or 60m are popular choices)
3. Adjust lookback days based on your analysis needs
4. Customize colors and line styles to match your chart theme
Trading Applications:
Breakout Trading:
• Long Entry: Green arrow (close breakout above range) + confirmation
• Short Entry: Red arrow (close breakout below range) + confirmation
• Stop Loss: Opposite side of the opening range
• Target: 1-2x the range size or key support/resistance levels
Range Rejection Trading:
• Reversal Setups: Small arrows indicate failed breakouts
• Mean Reversion: Trade back toward range midline
• Support/Resistance: Use range levels as key price zones
Multi-Day Analysis:
• Identify recurring support/resistance levels
• Analyze range expansion/contraction patterns
• Compare current day's activity to recent history
BEST PRACTICES
1. Timeframe Selection: 5-minute charts provide optimal signal clarity
2. Range Duration: 30-minute opening range is most commonly used, but adjust based on:
- Market volatility
- Stock characteristics
- Trading style preference
3. Confirmation: Use additional indicators or price action for trade confirmation
4. Risk Management: Always use appropriate position sizing and stop losses
MARKET SESSIONS
The indicator is specifically designed for US equity markets:
• Market Open: 9:30 AM EST
• Market Close: 4:00 PM EST
• Opening Range: Calculated from market open
• Range Lines: Extend throughout the trading day only
PERFORMANCE NOTES
• Optimized for real-time trading with minimal lag
• Automatically manages memory by cleaning old ranges
• Efficiently handles multiple timeframes and range calculations
KNOWN ISSUES & WORKAROUNDS
Historical Buffer Error:
Issue: Occasionally, you may encounter an error: "The requested historical offset (XXX) is beyond the historical buffer's limit (770)"
Workaround:
1. Switch to a different timeframe temporarily
2. Switch back to your original timeframe
3. The indicator will reload and function normally
This is a Pine Script limitation related to historical data access and doesn't affect the indicator's core functionality.
COMPATIBILITY
• Pine Script Version: v6
• Chart Types: All chart types supported
• Timeframes: All timeframes (optimized for 1m-1h)
• Markets: Designed for US equity markets during regular trading hours
TIPS FOR MAXIMUM EFFECTIVENESS
1. Combine with Volume: High volume on breakouts increases reliability
2. Market Context: Consider overall market direction and volatility
3. News Awareness: Be cautious around earnings and major announcements
4. Range Quality: Wider ranges often provide better breakout opportunities
5. Time of Day: Early breakouts (first 1-2 hours) often have higher follow-through
This indicator is provided for educational and informational purposes. Always conduct your own analysis and manage risk appropriately.
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.
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.
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.
---
### 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.
---
### 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.
---
### 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.
---
### 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.
---
### 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.
---
### 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.
---
### 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!
IU Gap Fill StrategyThe IU Gap Fill Strategy is designed to capitalize on price gaps that occur between trading sessions. It identifies gaps based on a user-defined percentage threshold and executes trades when the price fills the gap within a day. This strategy is ideal for traders looking to take advantage of market inefficiencies that arise due to overnight or session-based price movements. An ATR-based trailing stop-loss is incorporated to dynamically manage risk and lock in profits.
USER INPUTS
Percentage Difference for Valid Gap - Defines the minimum gap size in percentage terms for a valid trade setup. ( Default is 0.2 )
ATR Length - Sets the lookback period for the Average True Range (ATR) calculation. (default is 14 )
ATR Factor - Determines the multiplier for the trailing stop-loss, helping in risk management. ( Default is 2.00 )
LONG CONDITION
A gap-up occurs, meaning the current session opens above the previous session’s close.
The price initially dips below the previous session's close but then recovers and closes above it.
The gap meets the valid percentage threshold set by the user.
The bar is not the first or last bar of the session to avoid false signals.
SHORT CONDITION
A gap-down occurs, meaning the current session opens below the previous session’s close.
The price initially moves above the previous session’s close but then closes below it.
The gap meets the valid percentage threshold set by the user.
The bar is not the first or last bar of the session to avoid false signals.
LONG EXIT
An ATR-based trailing stop-loss is set below the entry price and dynamically adjusts upwards as the price moves in favor of the trade.
The position is closed when the trailing stop-loss is hit.
SHORT EXIT
An ATR-based trailing stop-loss is set above the entry price and dynamically adjusts downwards as the price moves in favor of the trade.
The position is closed when the trailing stop-loss is hit.
WHY IT IS UNIQUE
Precision in Identifying Gaps - The strategy focuses on real price gaps rather than minor fluctuations.
Dynamic Risk Management - Uses ATR-based trailing stop-loss to secure profits while allowing the trade to run.
Versatility - Works on stocks, indices, forex, and any market that experiences session-based gaps.
Optimized Entry Conditions - Ensures entries are taken only when the price attempts to fill the gap, reducing false signals.
HOW USERS CAN BENEFIT FROM IT
Enhance Trade Timing - Captures high-probability trade setups based on market inefficiencies caused by gaps.
Minimize Risk - The ATR trailing stop-loss helps protect gains and limit losses.
Works in Different Market Conditions - Whether markets are trending or consolidating, the strategy adapts to potential gap fill opportunities.
Fully Customizable - Users can fine-tune gap percentage, ATR settings, and stop-loss parameters to match their trading style.
FVG Breakout Lite by tradingbauhausExplanation of "FVG Breakout Lite by tradingbauhaus"
This script is a trading strategy built for TradingView that helps you spot and trade "Fair Value Gaps" (FVGs)—price areas where the market moved quickly, leaving a gap that might act as support or resistance later. It’s designed to catch breakout opportunities when the price moves strongly in one direction, with extra filters to make trades more reliable. Here’s how it works and how you can use it:
What It Does
1. Finds Fair Value Gaps (FVGs):
A "Bullish FVG" happens when the price jumps up quickly, leaving a gap below where it didn’t trade much (e.g., today’s low is higher than the high from two bars ago).
A "Bearish FVG" is the opposite: the price drops fast, leaving a gap above (e.g., today’s high is lower than the low from two bars ago).
The script draws colored boxes on your chart to show these gaps: green for bullish, red for bearish.
2. Spots Breakouts:
It looks for "strong" FVGs by comparing them to a trend (based on the highest highs and lowest lows over a set period).
If a bullish gap forms above the recent highs, or a bearish gap below the recent lows, it’s marked as a breakout opportunity.
3. Adds a Volume Check:
Trades only happen if the market’s volume is higher than usual (e.g., 1.2x the average volume over the last 20 bars). This helps ensure the breakout has real momentum behind it.
4. Trades Automatically:
Long Trades (Buy): If a bullish breakout FVG forms and volume is high, it buys at the current price.
Short Trades (Sell): If a bearish breakout FVG forms with high volume, it sells short.
Each trade comes with a stop loss (to limit losses) and a take profit (to lock in gains), both adjustable by you.
5. Shows Mitigation Lines (Optional):
If you turn on "Display Mitigation Zones," it draws lines at the edge of each breakout FVG. These lines show where the price might return to "fill" the gap later, helping you see key levels.
6. Includes Webull Costs:
The script factors in real trading fees from Webull, like tiny SEC and FINRA fees for selling, and a daily margin cost if you’re borrowing money to trade. These don’t show up on the chart but affect the strategy’s performance in backtesting.
How to Use It
1. Add to Your Chart:
Copy the script into TradingView’s Pine Editor, click "Add to Chart," and it’ll start drawing FVGs and running the strategy.
2. Customize Settings:
Trend Period (Default: 25): How many bars it looks back to define the trend. Longer periods mean fewer but stronger signals.
Volume Lookback (Default: 20) & Volume Threshold (Default: 1.2): Adjust how it measures "high volume." Increase the threshold for stricter trades.
Stop Loss % (Default: 1.5%) & Take Profit % (Default: 3%): Set how much you’re willing to lose or aim to gain per trade.
Margin Rate % (Default: 8.74%): Webull’s rate for borrowing money—lower it if your account qualifies for a better rate.
Display Mitigation Zones (Default: On): Toggle this to see or hide the gap lines.
Colors: Change the green (bullish) and red (bearish) shades to suit your chart.
3. Backtest It:
Go to the "Strategy Tester" tab in TradingView to see how it performs on past data. It’ll show trades, profits, losses, and Webull fees included.
4. Watch It Work:
Green boxes mean bullish FVGs; red boxes mean bearish FVGs. If volume spikes and the price breaks out, you’ll see trades happen automatically.
What to Expect
Visuals: You’ll see colored boxes for FVGs and optional lines showing where they start. These help you spot key price zones even if you’re not trading.
Trades: It’s selective—only trades when FVGs align with a breakout and volume confirms it. Expect fewer trades but with higher potential.
Risk: The stop loss keeps losses in check, while the take profit aims for a 2:1 reward-to-risk ratio by default (3% gain vs. 1.5% loss).
Costs: Webull’s fees are small but baked into the results, so you’re seeing a realistic picture of profits.
Tips for Users
Test it on a small timeframe (like 5-minute charts) for day trading or a larger one (like daily) for swing trading.
Play with the volume threshold—if you get too few trades, lower it (e.g., 1.1); if too many, raise it (e.g., 1.5).
Watch how price reacts to the mitigation lines—they’re often support or resistance zones traders target.
This strategy is lightweight, focused, and built for traders who like breakouts with a bit of confirmation. It’s not foolproof (no strategy is!), but it gives you a clear way to trade FVGs with some smart filters.
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
Bullish Reversal Bar Strategy [Skyrexio]Overview
Bullish Reversal Bar Strategy leverages the combination of candlestick pattern Bullish Reversal Bar (description in Methodology and Justification of Methodology), Williams Alligator indicator and Williams Fractals to create the high probability setups. Candlestick pattern is used for the entering into trade, while the combination of Williams Alligator and Fractals is used for the trend approximation as close condition. Strategy uses 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 or the candlestick pattern invalidation 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.
Trend Trade Filter: strategy uses Alligator and Fractal combination as high probability trend filter.
Methodology
The strategy opens long trade when the following price met the conditions:
1.Current candle's high shall be below the Williams Alligator's lines (Jaw, Lips, Teeth)(all details in "Justification of Methodology" paragraph)
2.Price shall create the candlestick pattern "Bullish Reversal Bar". Optionally if MFI and AO filters are enabled current candle shall have the decreasing AO and at least one of three recent bars shall have the squat state on the MFI (all details in "Justification of Methodology" paragraph)
3.If price breaks through the high of the candle marked as the "Bullish Reversal Bar" the long trade is open at the price one tick above the candle's high
4.Initial stop loss is placed at the Bullish Reversal Bar's candle's low
5.If price hit the Bullish Reversal Bar's low before hitting the entry price potential trade is cancelled
6.If trade is active and initial stop loss has not been hit, trade is closed when the combination of Alligator and Williams Fractals shall consider current trend change from upward to downward.
Strategy settings
In the inputs window user can setup strategy setting:
Enable MFI (if true trades are filtered using Market Facilitation Index (MFI) condition all details in "Justification of Methodology" paragraph), by default = false)
Enable AO (if true trades are filtered using Awesome Oscillator (AO) condition all details in "Justification of Methodology" paragraph), by default = false)
Justification of Methodology
Let's explore the key concepts of this strategy and understand how they work together. The first and key concept is the Bullish Reversal Bar candlestick pattern. This is just the single bar pattern. The rules are simple:
Candle shall be closed in it's upper half
High of this candle shall be below all three Alligator's lines (Jaw, Lips, Teeth)
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.
How we can use all these indicators in this strategy? This strategy is a counter trend one. Candle's high shall be below all Alligator's lines. During this market stage the bullish reversal bar candlestick pattern shall be printed. This bar during the downtrend is a high probability setup for the potential reversal to the upside: bulls were able to close the price in the upper half of a candle. The breaking of its high is a high probability signal that trend change is confirmed and script opens long trade. If market continues going down and break down the bullish reversal bar's low potential trend change has been invalidated and strategy close long trade.
If market really reversed and started moving to the upside strategy waits for the trend change form the downtrend to the uptrend according to approximation of Alligator and Fractals combination. If this change happens strategy close the trade. This approach helps to stay in the long trade while the uptrend continuation is likely and close it if there is a high probability of the uptrend finish.
Optionally users can enable MFI and AO filters. First of all, let's briefly explain what are these two indicators. 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
This indicator is filtering signals in the following way: if current AO bar is decreasing this candle can be interpreted as a bullish reversal bar. This logic is applicable because initially this strategy is a trend reversal, it is searching for the high probability setup against the current trend. Decreasing AO is the additional high probability filter of a downtrend.
Let's briefly look what is MFI. The Market Facilitation Index (MFI) is a technical indicator that measures the price movement per unit of volume, helping traders gauge the efficiency of price movement in relation to trading volume. Here's how you can calculate it:
MFI = (High−Low)/Volume
MFI can be used in combination with volume, so we can divide 4 states. Bill Williams introduced these to help traders interpret the interaction between volume and price movement. Here’s a quick summary:
Green Window (Increased MFI & Increased Volume): Indicates strong momentum with both price and volume increasing. Often a sign of trend continuation, as both buying and selling interest are rising.
Fake Window (Increased MFI & Decreased Volume): Shows that price is moving but with lower volume, suggesting weak support for the trend. This can signal a potential end of the current trend.
Squat Window (Decreased MFI & Increased Volume): Shows high volume but little price movement, indicating a tug-of-war between buyers and sellers. This often precedes a breakout as the pressure builds.
Fade Window (Decreased MFI & Decreased Volume): Indicates a lack of interest from both buyers and sellers, leading to lower momentum. This typically happens in range-bound markets and may signal consolidation before a new move.
For our purposes we are interested in squat bars. This is the sign that volume cannot move the price easily. This type of bar increases the probability of trend reversal. In this indicator we added to enable the MFI filter of reversal bars. If potential reversal bar or two preceding bars have squat state this bar can be interpret as a reversal one.
Backtest Results
Operating window: Date range of backtests is 2023.01.01 - 2024.12.31. 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: 50%
Maximum Single Position Loss: -5.29%
Maximum Single Profit: +29.99%
Net Profit: +5472.66 USDT (+54.73%)
Total Trades: 103 (33.98% win rate)
Profit Factor: 1.634
Maximum Accumulated Loss: 1231.15 USDT (-8.32%)
Average Profit per Trade: 53.13 USDT (+0.94%)
Average Trade Duration: 76 hours
How to Use
Add the script to favorites for easy access.
Apply to the desired timeframe and chart (optimal performance observed on 4h ETH/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.
Dynamic Support and Resistance Pivot Strategy The Dynamic Support and Resistance Pivot Strategy is a flexible and adaptive tool designed to identify short-term support and resistance levels using the concept of price pivots.
### Key Elements of the Strategy
1. Pivot points as support and resistance levels
Pivots are significant turning points on the price chart, often marking local highs and lows where the price has reversed direction. A pivot high occurs when the price forms a local peak, while a pivot low occurs when the price forms a local trough. When a new pivot high is formed, it creates a resistance level. Conversely, when a new pivot low is formed, it creates a support level.
The strategy continuously updates these levels as new pivots are detected, ensuring they remain relevant to the current market conditions. By identifying these price levels, the strategy dynamically adjusts to market conditions, allowing it to adapt to both trending and ranging markets, since it has a long target and can perform reversal operations.
2. Entry Criteria
- Buy (Long): A long position is triggered when the price is near the support level and then crosses it from below to above. This suggests that the price has found support and may start moving upwards.
- Sell (Short): A short position is triggered when the price is near the resistance level and then crosses it from above to below. This indicates that the price may be reversing and moving downward.
3. Support/Resistance distance (%)
- This parameter establishes a percentage range around the identified support and resistance level. For example, if the Support Resistance Distance is 0.4% (default), the closing price must be within a range of 0.4% above support or below the resistance to be considered "close" and trigger a trade.
4. Exit criteria
- Take profit = 27 %
- Stop loss = 10 %
- Reversal if a new entry point is identified in the opposite direction
5. No Repainting
- The Dynamic Support and Resistance Pivot Strategy is not subject to repainting.
6. Position Sizing by Equity and risk management
- This strategy has a default configuration to operate with 35% of the equity. The stop loss is set to 10% from the entry price. This way, the strategy is putting at risk about 10% of 35% of equity, that is, around 3.5% of equity for each trade. The percentage of equity and stop loss can be adjusted by the user according to their risk management.
7. Backtest results
- This strategy was subjected to backtest and operations in replay mode on **1000000MOGUSDT.P**, with the inclusion of transaction fees at 0.12% and slipagge of 5 ticks, and the past results have shown consistent profitability. Past results are no guarantee of future results. The strategy's backtest results may even be due to overfitting with past data.
8. Chart Visualization
- Support and resistance levels are displayed as green (support) and red (resistance) lines.
- Pivot prices are displayed as green (pivot low) and red (pivot high) labels.
In this image above, the Support/Resistance distance (%) parameter was set to 0.8.
9. Default Configuration
Chart Timeframe: 1h
Pivot Lengh: 2
Support/Resistance distance (%): 0.4*
Stop Loss: 10 %
Take Profit: 27 %
* This parameter can alternatively be set to 0.8.
10. Alternative Configuration
Chart Timeframe: 20 min
Pivot Lengh: 4
Support/Resistance distance (%): 0.1
Stop Loss: 10 %
Take Profit: 25 %
BYBIT:1000000MOGUSDT.P
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.
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.
16. SMC Strategy with SL - low TimeframeOverview
The "SMC Strategy with SL - low Timeframe" is a comprehensive trading strategy that uses key concepts from Smart Money Theory to identify favorable areas in the market for buying or selling. This strategy takes advantage of price imbalances, support and resistance zones, and swing highs/lows to generate high-probability trade signals.
The key features of this strategy include:
Swing High/Low Analysis: Used to determine the Premium, Equilibrium, and Discount Zones.
Order Block Integration: An added layer of confluence to identify valid buy and sell signals.
Trend Direction Confirmation: Using a Simple Moving Average (SMA) to determine the overall trend.
Entry and Exit Rules: Based on price position relative to key zones and moving average, along with optional stop-loss and take-profit levels.
Detailed Description
Swing High and Swing Low Analysis
The script calculates Swing High and Swing Low based on the most recent price highs and lows over a specified look-back period (swingHighLength and swingLowLength, set to 8 by default).
It then derives the Premium, Equilibrium, and Discount Zones:
Premium Zone: Represents potential resistance, calculated based on recent swing highs.
Discount Zone: Represents potential support, calculated based on recent swing lows.
Equilibrium: The midpoint between Swing High and Swing Low, dividing the price range into Premium (above equilibrium) and Discount (below equilibrium) areas.
Zone Visualization
The strategy plots the Premium Zone (resistance) in red, the Discount Zone (support) in green, and the Equilibrium level in blue on the chart. This helps visually assess the current price relative to these important areas.
Simple Moving Average (SMA)
A 50-period Simple Moving Average (SMA) is added to help identify the trend direction.
Buy signals are valid only if the price is above the SMA, indicating an uptrend.
Sell signals are valid only if the price is below the SMA, indicating a downtrend.
Entry Rules
The script generates buy or sell signals when certain conditions are met:
A buy signal is triggered when:
Price is below the Equilibrium and within the Discount Zone.
Price is above the SMA.
The buy signal is further confirmed by the presence of an Order Block (recent lowest price area).
A sell signal is triggered when:
Price is above the Equilibrium and within the Premium Zone.
Price is below the SMA.
The sell signal is further confirmed by the presence of an Order Block (recent highest price area).
Order Block
The strategy defines Order Blocks as recent highs and lows within a look-back period (orderBlockLength set to 20 by default).
These blocks represent areas where large players (smart money) have historically been active, increasing the probability of the price reacting in these areas again.
Trade Management and Trade Direction
The user can set Trade Direction to either "Long Only," "Short Only," or "Both." This allows the strategy to adapt based on market conditions or trading preferences.
Based on the Trade Direction, the strategy either:
Closes open trades that are against new signals.
Allows only specific directional trades (either long or short).
Stop-loss levels are defined based on a fixed percentage (stop_loss_percent), which helps to manage risk and minimize losses.
Exit Rules
The strategy uses stop-loss levels for risk management.
A stop-loss price is set at a fixed percentage below the entry price for long positions or above the entry price for short positions.
When the price hits the defined stop-loss level, the trade is closed.
Liquidity Zones
The script identifies recent Swing Highs and Lows as potential liquidity zones. These are levels where price could react strongly, as they represent areas of interest for large traders.
The liquidity zones are plotted as crosses on the chart, marking areas where price may encounter significant buying or selling pressure.
Visual Feedback
The script uses visual markers (green for buy signals and red for sell signals) to indicate potential entries on the chart.
It also plots liquidity zones to help traders identify areas where stop hunts and liquidity grabs might occur.
Monthly Performance Dashboard
The script includes a performance tracking feature that displays monthly profit and loss metrics on the chart.
This dashboard allows the trader to see a visual representation of trading performance over time, providing insights into profitability and consistency.
The table shows profit or loss for each month and year, allowing the user to track the overall success of the strategy.
Key Benefits
Smart Money Concepts (SMC): This strategy incorporates SMC principles like order blocks and liquidity zones, which are used by institutional traders to determine potential market moves.
Zone Analysis: The use of Premium, Discount, and Equilibrium zones provides a solid framework for determining where to enter and exit trades based on price discounts or premiums.
Confluence: Signals are not taken in isolation. They are confirmed by factors like trend direction (SMA) and order blocks, providing greater trade accuracy.
Risk Management: By integrating stop-loss functionality, traders can manage their risks effectively.
Visual Performance Metrics: The monthly and yearly performance dashboard gives valuable feedback on how well the strategy has performed historically.
Practical Use
Buy in Discount Zone: Traders would be looking to buy when the price is discounted relative to its recent range and is above the SMA, indicating an overall uptrend.
Sell in Premium Zone: Conversely, traders would be looking to sell when the price is at a premium relative to its recent range and below the SMA, indicating an overall downtrend.
Order Block Confirmation: Ensures that buying or selling is supported by historical price behavior at significant levels, providing confidence that the market is likely to react at these areas.
This strategy is designed to help traders take advantage of price inefficiencies and areas where institutional traders are likely to be active, increasing the odds of successful trades. By leveraging Smart Money concepts and strong technical confluence, it aims to provide high-probability trade setups.
Bearish BreakerDescription:
The Bearish Breaker is designed to detect significant bearish candles that meet specific customizable conditions, allowing traders to easily identify potential sell signals or strong downtrends. This indicator highlights bearish candles based on size, close position within the candle's range, and other specific criteria, with options to plot Fibonacci levels, a stop loss line, and dollar loss estimation.
Key Features:
1. Customizable Candle Highlighting Conditions:
Highlights candles that are bearish and whose body is greater than a user-defined multiple of the average candle body size over a specified period.
2.Checks if the candle’s close is within a customizable percentage from the bottom of the candle’s range (default is 35%).
3. Ensures the close is lower than the lows of the previous two candles.
Visual Markings:
1. A plus sign appears below large bearish candles that meet the highlighting criteria.
2. Optionally plots a line at the low of the previous candle, labeled as "FVG" (Fair Value Gap).
3. Fibonacci Levels:
Plots 61.8% and 50% Fibonacci levels from the low to high of the highlighted candle.
4. Provides options to show/hide labels and adjust line colors.
5. Shaded Area:
Fills the area between the 50% and 61.8% levels with customizable color and transparency.
Stop Loss and Dollar Calculation:
1. Calculates a stop loss level, set a user-defined number of ticks above the high of the highlighted candle.
2. Displays a label with the potential dollar loss from the "FVG" to the stop loss line, using a specified dollar value per tick.
How To Use
1. Highlight Conditions: Adjust parameters like the average body length, threshold multiplier, and close percentage to fine-tune the bearish candle detection. typically I like to use the 4-6 body length with a 1.5 multiplier
2. Visual Elements: Toggle labels, colors, and transparency of Fibonacci and FVG lines, allowing you to customize the display for clarity.
3. Risk Management: Set the dollar value per tick and stop loss distance (in ticks) to display potential risk for your specific instrument , for example dollar per tick on NQ is $5 , ES is $12.50, CL is $10
4. Alerts:
An alert can be set to trigger each time a large bearish candle forms and meets all conditions, helping you stay notified of potential bearish momentum shifts.
5. Parameters:
Threshold Multiplier: Adjusts the size threshold for highlighting a bearish candle.
Close Percent in Range: Sets how close to the bottom of the candle’s range the close must be (0-100%). I like the candle to close in the lower 75 percent of the candle.
6. Stop Loss Ticks Above High: Controls how far above the high of the highlighted candle to place the stop loss.
7. Dollar Value per Tick: Calculates potential dollar loss between the FVG level and stop loss based on the asset’s tick value.
8. To trade this setup I like to wait for the first 1-2 candles after the highlighted breaker candle to pull back into the shaded area for a short position and target the low of the breaker candle or a 2-1 risk to reward.
Ideal For:
This indicator is ideal for traders looking to identify strong bearish momentum, manage risk visually, and use Fibonacci and fair value gaps on large bearish candles as potential areas for short entries with suggested stop loss areas and target profits.
Disclaimer: This indicator is for educational and informational purposes only and should not be used as a sole trading strategy. Always perform your own analysis before making trading decisions.
Moving Average Pullback Signals [UAlgo]The "Moving Average Pullback Signals " indicator is designed to identify potential trend continuation or reversal points based on moving average (MA) pullback patterns. This tool combines multiple types of moving averages, customized trend validation parameters, and candlestick wick patterns to provide reliable buy and sell signals. By leveraging several advanced MA methods (such as TEMA, DEMA, ZLSMA, and McGinley-D), this script can adapt to different market conditions, providing traders with flexibility and more precise trend-based entries and exits. The addition of a gradient color-coded moving average line and wick validation logic enables traders to visualize market sentiment and trend strength dynamically.
🔶 Key Features
Multiple Moving Average (MA) Calculation Methods: This indicator offers various MA calculation types, including SMA, EMA, DEMA, TEMA, ZLSMA, and McGinley-D, allowing traders to select the MA that best fits their strategy.
Trend Validation and Pattern Recognition: The indicator includes a customizable trend validation length, ensuring that the trend is consistent before buy/sell signals are generated. The "Trend Pattern Mode" setting provides flexibility between "No Trend in Progress," "Trend Continuation," and "Both," tailoring signals to the trader’s preferred style.
Wick Validation Logic: To enhance the accuracy of entries, this indicator identifies specific wick patterns for bullish or bearish pullbacks, which signal potential trend continuation or reversal. Wick length and validation factor are adjustable to suit various market conditions and timeframes.
Gradient Color-coded MA Line: This feature provides a quick visual cue for trend strength, with color changes reflecting relative highs and lows of the MA, enhancing market sentiment interpretation.
Alerts for Buy and Sell Signals: Alerts are triggered when either a bullish or bearish pullback is detected, allowing traders to receive instant notifications without continuously monitoring the chart.
Visual Labels for Reversal Points: The indicator plots labels ("R") at potential reversal points, with color-coded labels for bullish (green) and bearish (red) pullbacks, highlighting pullback opportunities that align with the trend or reversal potential.
🔶 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.
