Reversal & Breakout Strategy - CompleteThis is a complete intraday trading strategy script for TradingView that lets you:
1. Choose Between Two Styles of Trades:
Reversals: It looks for large bullish or bearish candles during market sessions and enters trades expecting price to reverse.
Breakouts: It scans for price breaking above or below a recent high or low (based on a lookback range) and enters in the direction of the breakout.
2. Filters Trades by Session and Day Type:
Trades only during sessions you choose: NY1, NY2, London, Asia, etc.
Trades only on specific day types (e.g., DNP, DWP, Range 1, Range 2), as classified by a custom daily behavior model.
3. Uses 9:30 AM Candle Logic (ORB):
Captures the 9:30 AM Eastern candle's high/low using 1-minute data.
Allows breakout confirmation using this range.
4. Entry + Exit Logic:
Enters on reversal or breakout confirmation.
Automatically places stop-loss and take-profit orders (based on your input, in ticks or points).
Can require classification before entry (e.g., don’t trade until the market type is known).
5. Tracks Trades and Performance:
Records each trade's PnL, drawdown, win/loss, classification, time, and session.
Displays a table with analytics like win rate, expectancy, average drawdown, trade distribution by day/classification.
6. Visually Shows All Trades:
Draws arrows and shapes when trades are triggered.
Labels when trades are blocked (e.g., if not classified yet).
Plots breakout levels and 9:30 AM box.
Statistics
🏆 UNMITIGATED LEVELS ACCUMULATIONPDH TO ATH RISK FREE
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Linear Mean Reversion Strategy📘 Strategy Introduction: Linear Mean Reversion with Fixed Stop
This strategy implements a simple yet powerful mean reversion model that assumes price tends to oscillate around a dynamic average over time. It identifies statistically significant deviations from the moving average using a z-score, and enters trades expecting a return to the mean.
🧠 Core Logic:
A z-score is calculated by comparing the current price to its moving average, normalized by standard deviation, over a user-defined half-life window.
Trades are entered when the z-score crosses a threshold (e.g., ±1), signaling overbought or oversold conditions.
The strategy exits positions either when price reverts back near the mean (z-score close to 0), or if a fixed stop loss of 100 points is hit, whichever comes first.
⚙️ Key Features:
Dynamic mean and volatility estimation using moving average and standard deviation
Configurable z-score thresholds for entry and exit
Position size scaling based on z-score magnitude
Fixed stop loss to control risk and avoid prolonged drawdowns
🧪 Use Case:
Ideal for range-bound markets or assets that exhibit stationary behavior around a mean, this strategy is especially useful on assets with mean-reverting characteristics like currency pairs, ETFs, or large-cap stocks. It is best suited for traders looking for short-term reversions rather than long-term trends.
EUR/USD Multi-Layer Statistical Regression StrategyStrategy Overview
This advanced EUR/USD trading system employs a triple-layer linear regression framework with statistical validation and ensemble weighting. It combines short, medium, and long-term regression analyses to generate high-confidence directional signals while enforcing strict risk controls.
Core Components
Multi-Layer Regression Engine:
Parallel regression analysis across 3 customizable timeframes (short/medium/long)
Projects future price values using prediction horizons
Statistical significance filters (R-squared, correlation, slope thresholds)
Signal Validation System:
Lookback validation tests historical prediction accuracy
Ensemble weighting of layer signals (adjustable influence per timeframe)
Confidence scoring combining statistical strength, layer agreement, and validation accuracy
Risk Management:
Position sizing scaled by signal confidence (1%-100% of equity)
Daily loss circuit breaker (halts trading at user-defined threshold)
Forex-tailored execution (pip slippage, percentage-based commissions)
Visual Intelligence:
Real-time regression line plots (3 layered colors)
Projection markers for short-term forecasts
Background coloring for market bias indication
Comprehensive statistics dashboard (R-squared metrics, validation scores, P&L)
Key Parameters
Category Settings
Regression Short/Med/Long lengths (20/50/100 bars)
Statistics Min R² (0.65), Correlation (0.7), Slope (0.0001)
Validation 30-bar lookback, 10-bar projection
Risk Controls 50% position size, 12% daily loss limit, 75% confidence threshold
Trading Logic
Entries require:
Ensemble score > |0.5|
Confidence > threshold
Short & medium-term significance
Active daily loss limit not breached
Exits triggered by:
Opposite high-confidence signals
Daily loss limit violation (emergency exit)
The strategy blends quantitative finance techniques with practical trading safeguards, featuring a self-optimizing design where signal quality directly impacts position sizing. The visual dashboard provides real-time feedback on model performance and market conditions.
CCI-MACD Strategy 4.2
I cerchi si basano sull'oscillatore CCI (Commodity Channel Index).
L’indicatore CCI ci permette di osservare se il livello attuale del prezzo è particolarmente al di sopra o al di sotto di una certa media mobile, avente un numero di periodi scelto da noi.
Più la deviazione dal prezzo medio nel breve termine è forte, e maggiormente l’indicatore si allontanerà dallo 0: verso l’alto in caso di uptrend, o verso il basso in caso di downtrend.
Il segnale viene dato quando il valore del CCI supera la linea dello zero.
Il tutto è filtrato con un altro indicatore, il MACD, acronimo di "Moving Average Convergence Divergence", usato per identificare cambiamenti nel momentum del prezzo.
The circles are based on the CCI (Commodity Channel Index) oscillator.
The CCI indicator allows us to observe whether the current price level is significantly above or below a certain moving average, with a number of periods chosen by us.
The greater the deviation from the short-term average price, the further the indicator will deviate from 0: upwards in the case of an uptrend, or downwards in the case of a downtrend.
The signal is given when the CCI value crosses the zero line.
This is all filtered through another indicator, the MACD, which stands for "Moving Average Convergence Divergence," used to identify changes in price momentum.
DOGE 15MIN**Warm Reminder:** This strategy is intended solely for exploratory research and experimentation to evaluate the effectiveness of various signals. Drawing inspiration from patterns observed on the DOGE cryptocurrency 15-minute chart, it provides a tailored framework to identify potential trading opportunities. For optimal results, it is currently recommended exclusively for DOGE 15min charts. Remember, trading involves inherent risks, and past performance is not indicative of future results. We are dedicated to ongoing optimizations and refinements to enhance its robustness across broader applications—stay tuned for updates!
#### **A. Long Entry Signals**
These conditions trigger a long position entry, provided the strategy has no existing position (position_size == 0) and is not blocked. Signals can be enabled/disabled via input toggles (e.g., enable_vix).
- **VIX Reversal (vix_long)**: VIX signal shifts from high to low volatility (non-high volatility), with RSI between 30-50.
- **RSI Oversold (rsi_long)**: RSI crosses above 30.
- **CVD Bullish (cvd_long)**: CVD is rising.
- **Price RSI Bullish (prsi_long)**: Price RSI crosses above 30 or a long signal is triggered.
- **RangeEMA Bullish (rema_long)**: Candlestick is above POC, with KAMA trend flipping upward.
- **ZVWAP Oversold (zvwap_long)**: ZVWAP enters the oversold zone.
- **KAMA + Volume Bullish (kama_long)**: KAMA trend flips upward, candlestick is above POC, volume is rising, and the candle is bullish (green).
- **Volume Burst Bullish (vol_burst_long)**: Volume RSI crosses below threshold (default 70), open > close (bearish/red candle), triggered within the last two candles. **Special: Ignores all blocks** (bypasses not_long, Pivot, OI, RSI/ADX extreme filters).
#### **B. Short Entry Signals**
Similar to long entries: requires no existing position and no blocks.
- **RSI Overbought (rsi_short)**: RSI crosses below 70.
- **CVD Bearish (cvd_short)**: CVD is declining.
- **Price RSI Bearish (prsi_short)**: Price RSI crosses below 70 or a short signal is triggered.
- **RangeEMA Bearish (rema_short)**: Candlestick is below POC, with KAMA trend flipping downward.
- **ZVWAP Overbought (zvwap_short)**: ZVWAP enters the overbought zone.
- **KAMA + Volume Bearish (kama_short)**: KAMA trend flips downward, candlestick is below POC, volume is declining, and the candle is bearish (red).
- **Chop Bearish (chop_short)**: Chop crosses below 38.2, with RSI > 50.
- **Volume Burst Bearish (vol_burst_short)**: Volume RSI crosses below threshold (default 70), RSI > 70, and close > open (bullish/green candle), triggered within the last two candles. **Special: Ignores all blocks** (bypasses not_short, Pivot, OI, RSI/ADX extreme filters).
#### **C. Long Entry Blocks/Filters**
These conditions block long entries unless the signal ignores blocks (e.g., Volume Burst).
- **Base Prohibition (not_long)**: Volume is declining, or ADX is bearish (di_bear), or VIX is in high volatility (vix_flag), or RSI < 30.
- **Pivot Filter**: Recent Pivot is in a disadvantaged position.
- **OI Filter**: OI is declining.
- **RSI/ADX Extreme Filter**: RSI > 70 or ADX is bullish (di_bull).
- **Other**: Strategy already has a position (position_size != 0), or extreme volatility (is_extreme, though disabled in code).
#### **D. Short Entry Blocks/Filters**
Similar to long blocks.
- **Base Prohibition (not_short)**: Volume is rising, or (Chop < 38.2 and RSI > 50), or ADX is bullish (di_bull), or RSI > 70.
- **Pivot Filter**: Recent Pivot is in a disadvantaged position.
- **OI Filter**: OI is rising.
- **RSI/ADX Extreme Filter**: RSI < 30 or ADX is bearish (di_bear).
- **Other**: Existing position, or extreme volatility.
#### **E. Long Exit Signals**
Triggers closing of long positions, based on states (e.g., super_long, weak_long, only_kama).
- **KAMA Bearish Flip (exist_long)**: KAMA trend flips downward, or KAMA is downward with a short signal.
- **VIX Signal**: VIX shifts from low to high volatility, with RSI < 50.
- **Reversal Signal**: Short signal present and KAMA is downward.
- **Weak Trend Stop-Loss (weak_stop_long)**: In weak_long state, candlestick near POC, and close crosses below POC.
- **Weak KAMA Stop-Loss (weak_kama_long)**: In weak_long state, candlestick far from POC, and KAMA trend reverses.
- **Global Exit (exist_all)**: Volume RSI crosses below threshold (vol_under), or KAMA exit (kama_exit_long), or weak stop-loss, etc.
- **Special**: If in strong_long_hold (only_kama and KAMA remains bullish), ignore certain exit signals to hold the position.
#### **F. Short Exit Signals**
Similar to long exits.
- **KAMA Bullish Flip (exist_short)**: KAMA trend flips upward, or KAMA is upward with a long signal.
- **Reversal Signal**: Long signal present and KAMA is upward.
- **Weak Trend Stop-Loss (weak_stop_short)**: In weak_short state, candlestick near POC, and close crosses above short_state.current_max.
- **Weak KAMA Stop-Loss (weak_kama_short)**: In weak_short state, candlestick far from POC, and KAMA flips upward.
- **Global Exit (exist_all)**: Same as above.
Eliora Gold 1min (Heikin Ashi)Eliora -focused trading strategy designed for anything on the 1-minute timeframe using Heikin Ashi candles. This mode combines advanced market logic with structured risk management to deliver smooth, disciplined trade execution.
Key Features:
✅ Trend Confirmation – Aligns with dominant market direction for higher accuracy.
✅ ATR-Based Volatility Filter – Avoids high-risk conditions and chaotic price action.
✅ Candle Strength Logic – Filters weak setups, focusing on strong momentum.
✅ Balanced Risk/Reward – Calculates stop-loss and take-profit dynamically for consistent results.
✅ Cooldown & Overtrade Protection – Limits frequency to maintain trade quality.
This version of Eliora is built for scalpers and intraday traders seeking high-probability entries with graceful exits.
Long/Short/Exit/Risk management Strategy # LongShortExit Strategy Documentation
## Overview
The LongShortExit strategy is a versatile trading system for TradingView that provides complete control over entry, exit, and risk management parameters. It features a sophisticated framework for managing long and short positions with customizable profit targets, stop-loss mechanisms, partial profit-taking, and trailing stops. The strategy can be enhanced with continuous position signals for visual feedback on the current trading state.
## Key Features
### General Settings
- **Trading Direction**: Choose to trade long positions only, short positions only, or both.
- **Max Trades Per Day**: Limit the number of trades per day to prevent overtrading.
- **Bars Between Trades**: Enforce a minimum number of bars between consecutive trades.
### Session Management
- **Session Control**: Restrict trading to specific times of the day.
- **Time Zone**: Specify the time zone for session calculations.
- **Expiration**: Optionally set a date when the strategy should stop executing.
### Contract Settings
- **Contract Type**: Select from common futures contracts (MNQ, MES, NQ, ES) or custom values.
- **Point Value**: Define the dollar value per point movement.
- **Tick Size**: Set the minimum price movement for accurate calculations.
### Visual Signals
- **Continuous Position Signals**: Implement 0 to 1 visual signals to track position states.
- **Signal Plotting**: Customize color and appearance of position signals.
- **Clear Visual Feedback**: Instantly see when entry conditions are triggered.
### Risk Management
#### Stop Loss and Take Profit
- **Risk Type**: Choose between percentage-based, ATR-based, or points-based risk management.
- **Percentage Mode**: Set SL/TP as a percentage of entry price.
- **ATR Mode**: Set SL/TP as a multiple of the Average True Range.
- **Points Mode**: Set SL/TP as a fixed number of points from entry.
#### Advanced Exit Features
- **Break-Even**: Automatically move stop-loss to break-even after reaching specified profit threshold.
- **Trailing Stop**: Implement a trailing stop-loss that follows price movement at a defined distance.
- **Partial Profit Taking**: Take partial profits at predetermined price levels:
- Set first partial exit point and percentage of position to close
- Set second partial exit point and percentage of position to close
- **Time-Based Exit**: Automatically exit a position after a specified number of bars.
#### Win/Loss Streak Management
- **Streak Cutoff**: Automatically pause trading after a series of consecutive wins or losses.
- **Daily Reset**: Option to reset streak counters at the start of each day.
### Entry Conditions
- **Source and Value**: Define the exact price source and value that triggers entries.
- **Equals Condition**: Entry signals occur when the source exactly matches the specified value.
### Performance Analytics
- **Real-Time Stats**: Track important performance metrics like win rate, P&L, and largest wins/losses.
- **Visual Feedback**: On-chart markers for entries, exits, and important events.
### External Integration
- **Webhook Support**: Compatible with TradingView's webhook alerts for automated trading.
- **Cross-Platform**: Connect to external trading systems and notification platforms.
- **Custom Order Execution**: Implement advanced order flows through external services.
## How to Use
### Setup Instructions
1. Add the script to your TradingView chart.
2. Configure the general settings based on your trading preferences.
3. Set session trading hours if you only want to trade specific times.
4. Select your contract specifications or customize for your instrument.
5. Configure risk parameters:
- Choose your preferred risk management approach
- Set appropriate stop-loss and take-profit levels
- Enable advanced features like break-even, trailing stops, or partial profit taking as needed
6. Define entry conditions:
- Select the price source (such as close, open, high, or an indicator)
- Set the specific value that should trigger entries
### Entry Condition Examples
- **Example 1**: To enter when price closes exactly at a whole number:
- Long Source: close
- Long Value: 4200 (for instance, to enter when price closes exactly at 4200)
- **Example 2**: To enter when an indicator reaches a specific value:
- Long Source: ta.rsi(close, 14)
- Long Value: 30 (triggers when RSI equals exactly 30)
### Best Practices
1. **Always backtest thoroughly** before using in live trading.
2. **Start with conservative risk settings**:
- Small position sizes
- Reasonable stop-loss distances
- Limited trades per day
3. **Monitor and adjust**:
- Use the performance table to track results
- Adjust parameters based on how the strategy performs
4. **Consider market volatility**:
- Use ATR-based stops during volatile periods
- Use fixed points during stable markets
## Continuous Position Signals Implementation
The LongShortExit strategy can be enhanced with continuous position signals to provide visual feedback about the current position state. These signals can help you track when the strategy is in a long or short position.
### Adding Continuous Position Signals
Add the following code to implement continuous position signals (0 to 1):
```pine
// Continuous position signals (0 to 1)
var float longSignal = 0.0
var float shortSignal = 0.0
// Update position signals based on your indicator's conditions
longSignal := longCondition ? 1.0 : 0.0
shortSignal := shortCondition ? 1.0 : 0.0
// Plot continuous signals
plot(longSignal, title="Long Signal", color=#00FF00, linewidth=2, transp=0, style=plot.style_line)
plot(shortSignal, title="Short Signal", color=#FF0000, linewidth=2, transp=0, style=plot.style_line)
```
### Benefits of Continuous Position Signals
- Provides clear visual feedback of current position state (long/short)
- Signal values stay consistent (0 or 1) until condition changes
- Can be used for additional calculations or alert conditions
- Makes it easier to track when entry conditions are triggered
### Using with Custom Indicators
You can adapt the continuous position signals to work with any custom indicator by replacing the condition with your indicator's logic:
```pine
// Example with moving average crossover
longSignal := fastMA > slowMA ? 1.0 : 0.0
shortSignal := fastMA < slowMA ? 1.0 : 0.0
```
## Webhook Integration
The LongShortExit strategy is fully compatible with TradingView's webhook alerts, allowing you to connect your strategy to external trading platforms, brokers, or custom applications for automated trading execution.
### Setting Up Webhooks
1. Create an alert on your chart with the LongShortExit strategy
2. Enable the "Webhook URL" option in the alert dialog
3. Enter your webhook endpoint URL (from your broker or custom trading system)
4. Customize the alert message with relevant information using TradingView variables
### Webhook Message Format Example
```json
{
"strategy": "LongShortExit",
"action": "{{strategy.order.action}}",
"price": "{{strategy.order.price}}",
"quantity": "{{strategy.position_size}}",
"time": "{{time}}",
"ticker": "{{ticker}}",
"position_size": "{{strategy.position_size}}",
"position_value": "{{strategy.position_value}}",
"order_id": "{{strategy.order.id}}",
"order_comment": "{{strategy.order.comment}}"
}
```
### TradingView Alert Condition Examples
For effective webhook automation, set up these alert conditions:
#### Entry Alert
```
{{strategy.position_size}} != {{strategy.position_size}}
```
#### Exit Alert
```
{{strategy.position_size}} < {{strategy.position_size}} or {{strategy.position_size}} > {{strategy.position_size}}
```
#### Partial Take Profit Alert
```
strategy.order.comment contains "Partial TP"
```
### Benefits of Webhook Integration
- **Automated Trading**: Execute trades automatically through supported brokers
- **Cross-Platform**: Connect to custom trading bots and applications
- **Real-Time Notifications**: Receive trade signals on external platforms
- **Data Collection**: Log trade data for further analysis
- **Custom Order Management**: Implement advanced order types not available in TradingView
### Compatible External Applications
- Trading bots and algorithmic trading software
- Custom order execution systems
- Discord, Telegram, or Slack notification systems
- Trade journaling applications
- Risk management platforms
### Implementation Recommendations
- Test webhook delivery using a free service like webhook.site before connecting to your actual trading system
- Include authentication tokens or API keys in your webhook URL or payload when required by your external service
- Consider implementing confirmation mechanisms to verify trade execution
- Log all webhook activities for troubleshooting and performance tracking
## Strategy Customization Tips
### For Scalping
- Set smaller profit targets (1-3 points)
- Use tighter stop-losses
- Enable break-even feature after small profit
- Set higher max trades per day
### For Day Trading
- Use moderate profit targets
- Implement partial profit taking
- Enable trailing stops
- Set reasonable session trading hours
### For Swing Trading
- Use longer-term charts
- Set wider stops (ATR-based often works well)
- Use higher profit targets
- Disable daily streak reset
## Common Troubleshooting
### Low Win Rate
- Consider widening stop-losses
- Verify that entry conditions aren't triggering too frequently
- Check if the equals condition is too restrictive; consider small tolerances
### Missing Obvious Trades
- The equals condition is extremely precise. Price must exactly match the specified value.
- Consider using floating-point precision for more reliable triggers
### Frequent Stop-Outs
- Try ATR-based stops instead of fixed points
- Increase the stop-loss distance
- Enable break-even feature to protect profits
## Important Notes
- The exact equals condition is strict and may result in fewer trade signals compared to other conditions.
- For instruments with decimal prices, exact equality might be rare. Consider the precision of your value.
- Break-even and trailing stop calculations are based on points, not percentage.
- Partial take-profit levels are defined in points distance from entry.
- The continuous position signals (0 to 1) provide valuable visual feedback but don't affect the strategy's trading logic directly.
- When implementing continuous signals, ensure they're aligned with the actual entry conditions used by the strategy.
---
*This strategy is for educational and informational purposes only. Always test thoroughly before using with real funds.*
Outside Bar Strategy with Multiple Entry ModelsOutside Bar Strategy with Multiple Entry Models
This Pine Script strategy implements a versatile trading system based on the Outside Bar pattern, offering three distinct entry models: Close Entry, High/Low Entry, and Midpoint Entry. Designed for traders seeking flexibility, the strategy includes customizable risk/reward ratios, an optional EMA trend filter, and enhanced visualization with line fills.
Key Features:
Entry Models:
Close Entry: Enters a long position when the current candle closes above the high of the previous outside bullish bar . For short, it enters when the candle closes below the low of the previous outside bearish bar.
High/Low Entry: Enters a long position when the price crosses above the high of the previous outside bullish bar . For short, it enters when the price crosses below the low of the previous outside bearish bar .
Midpoint Entry: Places a limit order at the midpoint of the previous outside bar, entering when the price reaches this level.
EMA Trend Filter: Optionally filters signals based on the alignment of EMAs (7 > 25 > 99 > 200 for long, 7 < 25 < 99 < 200 for short). Can be toggled via the Use EMA Filter input.
Risk/Reward Management: Configurable risk/reward ratio (default 2.0) with stop-loss set at the low/high of the outside bar and take-profit calculated based on the bar's range multiplied by the ratio.
Visualization:
Lines for entry, stop-loss, and take-profit levels (dashed for active trades, solid for pending Midpoint Entry orders).
Line fills: Red between entry and stop-loss, green between entry and take-profit.
Previous lines and fills persist on the chart for historical reference (line deletion disabled).
Pending limit orders for Midpoint Entry extend dynamically to the right until triggered or canceled.
Information Table: Displays real-time trade details (entry model, RR ratio, open trade status, entry/stop/take-profit levels, profit/loss percentage) and strategy statistics (success rate, total trades). For Midpoint Entry, pending order details are shown.
Inputs:
Entry Model: Choose between Close Entry, High/Low Entry, or Midpoint Entry (default: Close Entry).
Risk/Reward Ratio: Set the RR ratio (default: 2.0, step: 0.5).
Use EMA Filter: Enable/disable the EMA trend filter (default: true).
Line Colors and Style: Customize colors for entry, stop-loss, and take-profit lines, and select line style (solid or dashed).
Table Settings: Adjust table text color, size (small/normal/large), and position (right top/middle/bottom).
Disclaimer: This strategy is for educational purposes only. Backtest thoroughly and use at your own risk. Past performance is not indicative of future results.
Price Statistical Strategy-Z Score V 1.01
Price Statistical Strategy – Z Score V 1.01
Overview
A technical breakdown of the logic and components of the “Price Statistical Strategy – Z Score V 1.01”.
This script implements a smoothed Z-Score crossover mechanism applied to the closing price to detect potential statistical deviations from local price mean. The strategy operates solely on price data (close) and includes signal spacing control and momentum-based candle filters. No volume-based or trend-detection components are included.
Core Methodology
The strategy is built on the statistical concept of Z-Score, which quantifies how far a value (closing price) is from its recent average, normalized by standard deviation. Two moving averages of the raw Z-Score are calculated: a short-term and a long-term smoothed version. The crossover between them generates long entries and exits.
Signal Conditions
Entry Condition:
A long position is opened when the short-term smoothed Z-Score crosses above the long-term smoothed Z-Score, and additional entry conditions are met.
Exit Condition:
The position is closed when the short-term Z-Score crosses below the long-term Z-Score, provided the exit conditions allow.
Signal Gapping:
A minimum number of bars (Bars gap between identical signals) must pass between repeated entry or exit signals to reduce noise.
Momentum Filter:
Entries are prevented during sequences of three or more consecutively bullish candles, and exits are prevented during three or more consecutively bearish candles.
Z-Score Function
The Z-Score is calculated as:
Z = (Close - SMA(Close, N)) / STDEV(Close, N)
Where N is the base period selected by the user.
Input Parameters
Enable Smoothed Z-Score Strategy
Enables or disables the Z-Score strategy logic. When disabled, no trades are executed.
Z-Score Base Period
Defines the number of bars used to calculate the simple moving average and standard deviation for the Z-Score. This value affects how responsive the raw Z-Score is to price changes.
Short-Term Smoothing
Sets the smoothing window for the short-term Z-Score. Higher values produce smoother short-term signals, reducing sensitivity to short-term volatility.
Long-Term Smoothing
Sets the smoothing window for the long-term Z-Score, which acts as the reference line in the crossover logic.
Bars gap between identical signals
Minimum number of bars that must pass before another signal of the same type (entry or exit) is allowed. This helps reduce redundant or overly frequent signals.
Trade Visualization Table
A table positioned at the bottom-right displays live PnL for open trades:
Entry Price
Unrealized PnL %
Text colors adapt based on whether unrealized profit is positive, negative, or neutral.
Technical Notes
This strategy uses only close prices — no trend indicators or volume components are applied.
All calculations are based on simple moving averages and standard deviation over user-defined windows.
Designed as a minimal, isolated Z-Score engine without confirmation filters or multi-factor triggers.
LANZ Strategy 4.0 [Backtest]🔷 LANZ Strategy 4.0 — Strategy Execution Based on Confirmed Structure + Risk-Based SL/TP
LANZ Strategy 4.0 is the official backtesting engine for the LANZ Strategy 4.0 trading logic. It simulates real-time executions based on breakout of Strong/Weak Highs or Lows, using a consistent structural system with SL/TP dynamically calculated per trade. With integrated risk management and lot size logic, this script allows traders to validate LANZ Strategy 4.0 performance with real strategy metrics.
🧠 Core Components:
Confirmed Breakout Entries: Trades are executed only when price breaks the most recent structural level (Strong High or Strong Low), detected using swing pivots.
Dynamic SL and TP Logic: SL is placed below/above the breakout point with a customizable buffer. TP is defined using a fixed Risk-Reward (RR) ratio.
Capital-Based Risk Management: Lot size is calculated based on account equity, SL distance, and pip value (e.g. $10 per pip on XAUUSD).
Clean and Controlled Executions: Only one trade is active at a time. No new entries are allowed until the current position is closed.
📊 Visual Features:
Automatic plotting of Entry, SL, and TP levels.
Full control of swing sensitivity (swingLength) and SL buffer.
SL and TP lines extend visually for clarity of trade risk and reward zones.
⚙️ How It Works:
Detects pivots and classifies trend direction.
Waits for breakout above Strong High (BUY) or below Strong Low (SELL).
Calculates dynamic SL and TP based on buffer and RR.
Computes trade size automatically based on risk per trade %.
Executes entry and manages exits via strategy engine.
📝 Notes:
Ideal for evaluating the LANZ Strategy 4.0 logic over historical data.
Must be paired with the original indicator (LANZ Strategy 4.0) for live trading.
Best used on assets with clear structural behavior (gold, indices, FX).
📌 Credits:
Backtest engine developed by LANZ based on the official rules of LANZ Strategy 4.0. This script ensures visual and logical consistency between live charting and backtesting simulations.
MMTools - Backtester❖ Overview
Backtester is a script implemented as a strategy, featuring multiple conditions and tools to offer an alternative way to work with Catcher. It supports both backtesting and algorithmic trading, allowing you to evaluate the indicator's performance on historical data for any instrument using the Strategy Tester.
❖ Settings
⚙️ Custom Conditions and Signals
This section is intended to provide flexibility when working with Catcher. (If you intend to use Catcher alone, this section can be disregarded). You may combine the primary indicator (Catcher) with additional custom indicators to define entry and exit signals. Simply add the custom indicator to your chart, display it and then select its name in the corresponding dropdown menu. By default, the 'Close' option is selected, meaning custom conditions are disabled.
Operator 'OR': An entry order is activated when either your custom signal or the primary signal occurs.
Operator 'AND': An entry order is activated only when both the custom and primary signals occur simultaneously.
If both 'AND' and 'OR' operators are used, enabling the 'Only Primary' option will apply the 'AND' operator only to the primary indicator.
Custom Exit: Allows the strategy to close a position based on a custom signal, in addition to standard exit conditions. The first condition met will trigger the exit.
Note: The strategy executes orders at the open of the next bar after the custom condition is met.
⚙️ Confirmation
When enabled, the strategy will enter a position only if a specified number of signals occur within a defined lookback period.
⚙️ Exits
Two types of exit mechanisms are available for take-profit and stop-loss:
Timeout: Sets a maximum duration (in bars) that a trade can remain open. If this limit is exceeded, the strategy will close the position.
Percentage-Based: Exit positions based on a specified percentage move.
⚙️ Start Date
Specifies the starting point for the backtest.
⚙️ Plotting
The green line represents the take-profit level, while the red line indicates the stop-loss level. Plotting is limited to the last 250 bars.
⚙️ Other Settings
Remember to configure additional parameters under the “Properties” tab, including commissions, slippage, and pyramiding. Default commission is set at 0.05%.
❖ Access
Please refer to the Author's Instructions field to request access to the script.
-----------------------------------------------------------
Disclaimer
The information provided by my scripts is for informational purposes only and does not constitute financial advice. Past performance is not indicative of future results. Always do your own research before making financial decisions.
LANZ Strategy 3.0 [Backtest]🔷 LANZ Strategy 3.0 — Asian Range Fibonacci Scalping Strategy
LANZ Strategy 3.0 is a precision-engineered backtesting tool tailored for intraday traders who rely on the Asian session range to determine directional bias. This strategy implements dynamic Fibonacci projections and strict time-window validation to simulate a clean and disciplined trading environment.
🧠 Core Components:
Asian Range Bias Definition: Direction is established between 01:15–02:15 a.m. NY time based on the candle’s close in relation to the midpoint of the Asian session range (18:00–01:15 NY).
Limit Order Execution: Only one trade is placed daily, using a limit order at the Asian range high (for sells) or low (for buys), between 01:15–08:00 a.m. NY.
Fibonacci-Based TP/SL:
Original Mode: TP = 2.25x range, SL = 0.75x range.
Optimized Mode: TP = 1.95x range, SL = 0.65x range.
No Trade After 08:00 NY: If the limit order is not executed before 08:00 a.m. NY, it is canceled.
Fallback Logic at 02:15 NY: If the market direction misaligns with the setup at 02:15 a.m., the system re-evaluates and can re-issue the order.
End-of-Day Closure: All positions are closed at 15:45 NY if still open.
📊 Backtest-Ready Design:
Entries and exits are executed using strategy.entry() and strategy.exit() functions.
Position size is fixed via capital risk allocation ($100 per trade by default).
Only one position can be active at a time, ensuring controlled risk.
📝 Notes:
This strategy is ideal for assets sensitive to the Asian/London session overlap, such as Forex pairs and indices.
Easily switch between Fibonacci versions using a single dropdown input.
Fully deterministic: all entries are based on pre-defined conditions and time constraints.
👤 Credits:
Strategy developed by rau_u_lanz using Pine Script v6. Built for traders who favor clean sessions, directional clarity, and consistent execution using time-based logic and Fibonacci projections.
LANZ Strategy 2.0 [Backtest]🔷 LANZ Strategy 2.0 — Structural Breakout Logic with Dynamic Swing Protection
LANZ Strategy 2.0 is a precision-focused backtesting system built for intraday traders who rely on structural confirmations before the London session to guide directional bias. This tool uses smart swing detection, risk-defined position sizing, and strict time-based execution to simulate real trading conditions with clarity and control.
🧠 Core Components:
Structural Confirmation (Trend & BoS): Detects trend direction and break of structure (BoS) using a three-swing logic, aligning trade entries with valid structural movement.
Time-Based Execution: Trades are triggered exclusively at 02:00 a.m. New York time, ensuring disciplined and repeatable intraday testing.
Swing-Based SL Models: Traders can select between three stop-loss protection types:
First Swing: Most recent structural level
Second Swing: Prior level
Full Coverage: All recent swing levels + configurable pip buffer
Dynamic TP Calculation: Take-Profit is projected as a risk-based multiple (RR), fully adjustable via input.
Capital-Based Risk Management: Risk is defined as a percentage of a fixed account size (e.g., $100 per trade from $10,000), and lot size is automatically calculated based on SL distance.
Fallback Entry Logic: If structural breakout is present but trend is not confirmed, a secondary entry is triggered.
End-of-Session Management: Any open trades are automatically closed at 11:45 a.m. NY time, with optional manual labeling or review.
📊 Visual Features (Optional in Indicator Version):
(Note: Visuals apply to the indicator version of LANZ 2.0, not this backtest script)
Swing level labels (1st, 2nd) and dynamic SL/TP lines.
Real-time session coloring for clarity: Pre-London, Entry Window, and NY Close.
Outcome labels: +RR, -RR, or net % at close.
Auto-cleanup of previous drawings for a clean chart per session.
⚙️ How It Works:
Detects last trend and BoS using swing logic before 02:00 a.m. NY.
At 02:00 a.m., evaluates directional bias and executes BUY or SELL if confirmed.
Applies selected SL logic (1st, 2nd, or full swing protection).
Sets TP based on the RR multiplier.
Closes the trade either on SL, TP, or at 11:45 a.m. NY manually.
🔔 Alerts:
Time-of-day alert at 02:00 a.m. NY to monitor execution.
Can be extended to cover SL/TP triggers or new BoS events.
📝 Notes:
Designed for backtesting precision and discretionary decision-making.
Ideal for Forex pairs, indices, or assets active during the London session.
Fully customizable: session timing, swing logic, SL buffer, and RR.
👤 Credits:
Strategy built by @rau_u_lanz using Pine Script v6, combining structural logic, capital-based risk control, and London-session timing in a backtest-ready framework for traders who demand accuracy and structure.
Ai BTC Signals Buy & Whales / Liquidation - Strategy [Ai Whales]Dear Trader,
The development involved professional analysts and incorporated AI to adapt signals to the modern, constantly changing, and highly volatile BTCUSD market, also taking into account the presence and actions of large institutional players — the so-called "Whales." The strategy allows you to instantly evaluate any configuration you set within the indicator and see the results reflected in professional performance metrics aligned with your chosen strategy.
The indicator displays several signals on the chart:
1) Buy signal (not sell signals)
2) Take profit line and price
3) Stop loss line and price
4) Manipulations & Liquidations observed in the market
5) Whale activity—buying in small, medium, and large amounts
The indicator does not repaint because it is based on showing signals only after the candle closes, so the calculations are true and not distorted.
Recommended pair: BTCUSD ; BTCUSDT ; BTCUSDTP and same.
The indicator can show R/R - 0.5:1 1:1 1:2 1:3 1:4
Recommended timeframes for use: from 4 hours up to 1 week, with the ideal being 1 day. However, you are free to experiment with other near timeframes.
Possible trading modes: spot or futures.
Some methods used in the calculations of the indicator:
- statistical patterns that have the ability to repeat in the future. Bitcoin cycles in different market phases that also have the ability to repeat and are included in the indicator,
- miners' capitulation and hashrate level are also taken into account by the indicator,
- candle volumes and their deltas are taken into account in the calculations,
- as well as other bases such as RSI and its divergence, the crossing of EMA of various configurations and etc.
**How the strategy calculates positions:**
A position opens at the Buy signal level and is fixed at the level of the thick green line, which serves as the primary take profit target. Pyramiding (adding to positions) can be enabled in the settings.
The size of each position is adjustable via the settings. Importantly, each signal creates its own take profit lines. When pyramiding is enabled, all positions are eventually closed at the nearest take profit level generated by any of the pyramiding signals. This approach minimizes potential losses if the price doesn’t reach the maximum take profit levels initially set; the strategy closes positions at the closest available take profit level. This conservative method for strategy reduces risk, although ideally, each position in the pyramid should be closed at an individual take-profit level, which would lead to even better results during deep backtesting.
The strategy includes alerts that can be configured based on your platform’s capabilities. Alerts trigger on the chart when "Buy" or "Whale" signals are detected.
**Settings Overview:**
- Inside the strategy: default platform options.
- Inside the indicato have some filters:
1) allows traders to choose display modes
2) position entries based on market phase—rising or falling
3) can also select whether to trade after manipulations and liquidations
4) can also select whether to trade after whale activity (small medium or big amounts of whales).
You can manually adjust take profit and stop loss levels via simple method selections, making these flexible yet user-friendly. The indicator offers three main styles:
- "Universal" (standard levels)
- "Aggressive"
- "Conservative"
**Performance and caveats:**
Deep Backtested from day one of Bitcoin’s listing on various exchanges under specific conditions (no liquidations, certain settings), the indicator has shown a maximum drawdown of about 5-15%, with final returns surpassing "buy and hold" more than 1000000% and WinRate 93-100% However, it’s crucial to understand that such spectacular past performance does not guarantee future results.
If you are serious about your investments, remember that geopolitical events, institutional shifts, or other unforeseen factors can significantly impact Bitcoin’s price—or even its existence. Unfortunately, AI has not yet learned to fully account for these macro conditions within its adaptive mechanisms.
Trade wisely, and use this powerful tool responsibly.
Best regards,
Trend Shift Trend Shift – Precision Trend Strategy with TP1/TP2 and Webhook Alerts
Trend Shift is an original, non-repainting algorithmic trading strategy designed for 1H crypto charts, combining trend, momentum, volume compression, and price structure filters. It uses real-time components and avoids repainting, while supporting webhook alerts, customizable dashboard display, and multi-level take-profit exits.
🔍 How It Works
The strategy uses a multi-layered system:
📊 Trend Filters
McGinley Baseline: Adaptive non-lagging baseline to define overall trend.
White Line Bias: Midpoint of recent high/low range to assess directional bias.
Tether Lines (Fast/Slow): Price structure-based cloud for trend validation.
📉 Momentum Confirmation
ZLEMA + CCI: Combines Zero Lag EMA smoothing with Commodity Channel Index slope to confirm strong directional movement.
💥 Volatility Squeeze
TTM Squeeze Logic: Detects low-volatility compression zones (BB inside KC) to anticipate breakout direction.
📈 Vortex Strength
Confirms sustained price movement with a threshold-based Vortex differential.
⚠️ Trap Filters
Wick Trap Detection: Prevents entries on manipulative candle structures (false breakouts).
🔄 Exit Timing
Uses ZLEMA slope as a weak-trend exit mechanism to get out before reversals.
🎯 Take-Profit Logic
TP1: Closes 50% of the position at a configurable profit target.
TP2: Closes remaining 100% of the position at a second target.
Full position closure is enforced before any new trade begins.
A 1-bar cooldown ensures no same-bar reversals occur.
🖥️ Real-Time Dashboard
Includes live stats such as:
Current position (Long/Short/Flat)
Entry price
TP1/TP2 hit status
Bars in trade
Win rate
Profit factor
You can adjust its size and screen corner using input settings.
🔔 Webhook Alerts Included
Long/Short Entry
TP1 and TP2 Hit (Long/Short)
Exit on Trend Reversal
Alerts are formatted for automated bot integration (JSON payload format).
⚠️ Important Notes
This strategy is 100% non-repainting.
No same-bar entry/exit occurs.
Backtested with 0.05% commission, 1 tick slippage, and $1,000 initial capital.
Default sizing: 10% equity per trade (adjustable).
Designed for crypto markets on the 1H timeframe, but can be adapted.
✅ Disclaimer
This script is for educational and informational purposes only and does not constitute financial advice. Past performance is not indicative of future results. Always test any strategy in a risk-free environment before using it in live trading.
Would you like a visual cover image for TradingView too (like a black/lime-green "Trend Shift Strategy" branded graphic)?
You said:
thats good keep all of it but you need to explaine its not just a mash up of indicators it an origional designe
ChatGPT said:
Absolutely — here's the revised and fully TradingView-compliant description with your request integrated. It now clearly explains that Trend Shift is not just a mashup, but an original, structured algorithm:
📈 Trend Shift – Precision Trend Strategy with TP1/TP2 and Webhook Alerts
Trend Shift is a fully original and carefully engineered algorithmic trading strategy — not just a mash-up of common indicators. It is purpose-built for high-accuracy crypto trend trading on the 1H timeframe using a layered decision framework. Every component has a defined role in identifying high-probability trades while avoiding lag and false signals. The logic has been rigorously tested to ensure non-repainting, stable behavior, and clear entry/exit timing — with support for webhook automation and customizable dashboards.
🔍 How It Works (Component Roles)
This strategy is constructed from custom logic blocks, not a random combination of standard tools:
📊 Trend Filters (Foundation)
McGinley Dynamic Baseline: Smooths price with adaptive logic — better than EMA for live crypto trends.
White Line Bias (Original Midpoint Logic): Midpoint of recent high/low range — provides bias without lag.
Tether Lines (Fast/Slow): Act as structure-based confirmation of trend health and direction.
📉 Momentum Confirmation
ZLEMA-smoothed CCI Momentum: Uses zero-lag smoothing and CCI slope steepness to confirm trend strength and direction. This combo is highly responsive and original in design.
💥 Volatility Breakout Detection
TTM Squeeze Logic (Custom Threshold Logic): Confirms volatility contraction and directional momentum before breakouts — not just raw BB/KC overlap.
📈 Vortex Strength Confirmation
Uses a threshold-filtered differential of Vortex Up/Down to confirm strong directional moves. Avoids trend entries during weak or sideways conditions.
⚠️ Trap Filter (Original Logic)
Wick Trap Detection: Prevents entries on likely fakeouts by analyzing wick-to-body ratio and previous candle positioning. This is custom-built and unique.
🔄 Smart Exit Logic
ZLEMA Slope Exit Filter: Identifies early signs of trend weakening to exit trades ahead of reversals — an original adaptive method, not a basic cross.
🎯 Take-Profit Structure
TP1: Closes 50% at a customizable first target.
TP2: Closes remaining 100% at a second target.
No overlapping trades. Reentry is delayed by 1 bar to prevent same-bar reversals and improve backtest accuracy.
🖥️ Live Trading Dashboard
Toggleable, repositionable UI showing:
Current Position (Long, Short, Flat)
Entry Price
TP1/TP2 Hit Status
Bars in Trade
Win Rate
Profit Factor
Includes sizing controls and lime/white color coding for fast clarity.
🔔 Webhook Alerts Included
Entry: Long & Short
Take Profits: TP1 & TP2 for Long/Short
Exits: Based on ZLEMA trend weakening logic
Alerts are JSON-formatted for webhook integration with bots or alert services.
🛠️ Originality Statement
This script is not a mashup. Every component — from Tether Line confirmation to wick traps and slope-based exits — is custom-constructed and combined into a cohesive trading engine. No reused indicator templates. No repainting. No guesswork. Each filter complements the others to reduce risk, not stack lag.
⚠️ Important Notes
100% Non-Repainting
No same-bar entry/exits
Tested with 0.05% commission, 1 tick slippage, and $1,000 starting capital
Adjustable for equity % sizing, TP levels, and dashboard layout
✅ Disclaimer
This script is for educational purposes only and does not constitute financial advice. Use in demo or backtest environments before applying to live markets. No guarantee of future returns.
Reverse Keltner Channel StrategyReverse Keltner Channel Strategy
Overview
The Reverse Keltner Channel Strategy is a mean-reversion trading system that capitalizes on price movements between Keltner Channels. Unlike traditional Keltner Channel strategies that trade breakouts, this system takes the contrarian approach by entering positions when price returns to the channel after overextending.
Strategy Logic
Long Entry Conditions:
Price crosses above the lower Keltner Channel from below
This signals a potential reversal after an oversold condition
Position is entered at market price upon signal confirmation
Long Exit Conditions:
Take Profit: Price reaches the upper Keltner Channel
Stop Loss: Placed at half the channel width below entry price
Short Entry Conditions:
Price crosses below the upper Keltner Channel from above
This signals a potential reversal after an overbought condition
Position is entered at market price upon signal confirmation
Short Exit Conditions:
Take Profit: Price reaches the lower Keltner Channel
Stop Loss: Placed at half the channel width above entry price
Key Features
Mean Reversion Approach: Takes advantage of price tendency to return to mean after extreme moves
Adaptive Stop Loss: Stop loss dynamically adjusts based on market volatility via ATR
Visual Signals: Entry points clearly marked with directional triangles
Fully Customizable: All parameters can be adjusted to fit various market conditions
Customizable Parameters
Keltner EMA Length: Controls the responsiveness of the channel (default: 20)
ATR Multiplier: Determines channel width/sensitivity (default: 2.0)
ATR Length: Affects volatility calculation period (default: 10)
Stop Loss Factor: Adjusts risk management aggressiveness (default: 0.5)
Best Used On
This strategy performs well on:
Currency pairs with defined ranging behavior
Commodities that show cyclical price movements
Higher timeframes (4H, Daily) for more reliable signals
Markets with moderate volatility
Risk Management
The built-in stop loss mechanism automatically adjusts to market conditions by calculating position risk relative to the current channel width. This approach ensures that risk remains proportional to potential reward across varying market conditions.
Notes for Optimization
Consider adjusting the EMA length and ATR multiplier based on the specific asset and timeframe:
Lower values increase sensitivity and generate more signals
Higher values produce fewer but potentially more reliable signals
As with any trading strategy, thorough backtesting is recommended before live implementation.
Past performance is not indicative of future results. Always practice sound risk management.
Daily Breakout + Daily Shadow By RouroThis script is a Pine v5 strategy designed to detect daily candle body breakouts and execute them on any intraday timeframe, while also providing:
Daily Data Retrieval
Using request.security(..., "D", ...) it fetches the OHLC and timestamp of the daily candle, regardless of the chart’s current timeframe.
Calculation of Yesterday’s and Day-Before-Yesterday’s Bodies
b1High and b1Low → the high/low of yesterday’s daily candle body
b2High and b2Low → the high/low of the previous day’s body
Detection of the First Intraday Bar After a New Day
By using ta.change(time("D")), it marks the start of each new trading day.
Drawing the Previous Day’s “Shadow” on the Chart
It overlays a box (box.new) and two wick lines (line.new) with configurable colors and transparency, so you can clearly see the full range of yesterday’s candle on any intraday chart.
Automatic End-of-Day Position Closure
It will automatically close any open position at the start of the next day to avoid unintended rollovers.
Entry Signals
On the very first intraday bar after the daily close:
Long if yesterday’s close broke above the body of the day before yesterday
Short if yesterday’s close broke below the body of the day before yesterday
…which triggers a strategy.entry at the intraday open.
Fully Customizable Stop-Loss and Take-Profit
SL options:
Opposite end of yesterday’s body
Fixed pips from entry
A risk-reward ratio on yesterday’s wick
Optional “safety SL” in fixed pips that overrides the above
TP options:
Fixed pips
Yesterday’s wick extreme (high/low)
Partial exit on the wick (TP1), then second exit (TP2) either:
At a multiplied RR
Or at the daily close (“Close of Day”)
You can also choose to move SL to breakeven after TP1 is hit.
Live Metrics Table
In the upper-right corner it displays in real time:
Start of backtest (date of first trade)
Number of ✅ Winning trades and ❌ Losing trades
Total number of trades
Win rate (%)
Profit Factor
All within a fixed table layout so it never runs out of rows or columns.
[Kpt-Ahab] Simple AlgoPilot Riskmgt and Backtest Simple AlgoPilot Riskmgt and Backtest
This script provides a compact solution for automated risk management and backtesting within TradingView.
It offers the following core functionalities:
Risk Management:
The system integrates various risk limitation mechanisms:
Percentage-based or trailing stop-loss
Maximum losing streak limitation
Maximum drawdown limitation relative to account equity
Flexible position sizing control (based on equity, fixed size, or contracts)
Dynamic repurchasing of positions ("Repurchase") during losses with adjustable size scaling
Supports multi-stage take-profit targets (TP1/TP2) and automatic stop-loss adjustment to breakeven
External Signal Processing for Backtesting:
In addition to its own moving average crossovers, the script can process external trading signals:
External signals are received via a source input variable (e.g., from other indicators or signal generators)
Positive values (+1) trigger long positions, negative values (–1) trigger short positions
This allows for easy integration of other indicator-based strategies into backtests
Additional Backtesting Features:
Selection between different MA types (SMA, EMA, WMA, VWMA, HMA)
Flexible time filtering (trade only within defined start and end dates)
Simulation of commission costs, slippage, and leverage
Optional alert functions for moving average crossovers
Visualization of liquidation prices and portfolio development in an integrated table
Note: This script is primarily intended for strategic backtesting and risk setting optimization.
Real-time applications should be tested with caution. All order executions, alerts, and risk calculations are purely simulation-based.
Explanation of Calculations and Logics:
1. Risk Management and Position Sizing:
The position size is calculated based on the user’s choice using three possible methods:
Percentage of Equity:
The position size is a defined fraction of the available capital, dynamically adjusted based on market price (riskPerc / close).
Fixed Size (in currency): The user defines a fixed monetary amount to be used per trade.
Contracts: A fixed number of contracts is traded regardless of the current price.
Leverage: The selected leverage multiplies the position size for margin calculations.
2. Trade Logic and Signal Triggering:
Trades can be triggered through two mechanisms:
Internal Signals:
When a fast moving average crosses above or below a slower moving average (ta.crossover, ta.crossunder). The type of moving averages (SMA, EMA, WMA, VWMA, HMA) can be freely selected.
External Signals:
Signals from other indicators can be received via an input source field.
+1 triggers a long entry, –1 triggers a short entry.
Position Management:
Once entered, the position is actively managed.
Multiple take-profit targets are set.
Upon reaching a profit target, the stop-loss can optionally be moved to breakeven.
3. Stop-Loss and Take-Profit Logic:
Stop-Loss Types:
Fixed Percentage Stop:
A fixed distance below/above the entry price.
Trailing Stop:
Dynamically adjusts as the trade moves into profit.
Fast Trailing Stop:
A more aggressive variant of trailing that reacts quicker to price changes.
Take-Profit Management:
Two take-profit targets (TP1 and TP2) are supported, allowing partial exits at different stages.
Remaining positions can either reach the second target or be closed by the stop-loss.
4. Repurchase Strategy ("Scaling In" on Losses):
If a position reaches a specified loss threshold (e.g., –15%), an automatic additional purchase can occur.
The position size is increased by a configurable percentage.
Repurchases happen only if an initial position is already open.
5. Backtesting Control and Filters:
Time Filters:
A trading period can be defined (start and end date).
All trades outside the selected period are ignored.
Risk Filters: Trading is paused if:
A maximum losing streak is reached.
A maximum allowed drawdown is exceeded.
6. Liquidation Calculation (Simulation Only):
The script simulates liquidation prices based on the account balance and position size.
Liquidation lines are drawn on the chart to better visualize potential risk exposure.
This is purely a visual aid — no real broker-side liquidation is performed.
Prop Firm Business SimulatorThe prop firm business simulator is exactly what it sounds like. It's a plug and play tool to test out any tradingview strategy and simulate hypothetical performance on CFD Prop Firms.
Now what is a modern day CFD Prop Firm?
These companies sell simulated trading challenges for a challenge fee. If you complete the challenge you get access to simulated capital and you get a portion of the profits you make on those accounts payed out.
I've included some popular firms in the code as presets so it's easy to simulate them. Take into account that this info will likely be out of date soon as these prices and challenge conditions change.
Also, this tool will never be able to 100% simulate prop firm conditions and all their rules. All I aim to do with this tool is provide estimations.
Now why is this tool helpful?
Most traders on here want to turn their passion into their full-time career, prop firms have lately been the buzz in the trading community and market themselves as a faster way to reach that goal.
While this all sounds great on paper, it is sometimes hard to estimate how much money you will have to burn on challenge fees and set realistic monthly payout expectations for yourself and your trading. This is where this tool comes in.
I've specifically developed this for traders that want to treat prop firms as a business. And as a business you want to know your monthly costs and income depending on the trading strategy and prop firm challenge you are using.
How to use this tool
It's quite simple you remove the top part of the script and replace it with your own strategy. Make sure it's written in same version of pinescript before you do that.
//--$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$--//--------------------------------------------------------------------------------------------------------------------------$$$$$$
//--$$$$$--Strategy-- --$$$$$$--// ******************************************************************************************************************************
//--$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$--//--------------------------------------------------------------------------------------------------------------------------$$$$$$
length = input.int(20, minval=1, group="Keltner Channel Breakout")
mult = input(2.0, "Multiplier", group="Keltner Channel Breakout")
src = input(close, title="Source", group="Keltner Channel Breakout")
exp = input(true, "Use Exponential MA", display = display.data_window, group="Keltner Channel Breakout")
BandsStyle = input.string("Average True Range", options = , title="Bands Style", display = display.data_window, group="Keltner Channel Breakout")
atrlength = input(10, "ATR Length", display = display.data_window, group="Keltner Channel Breakout")
esma(source, length)=>
s = ta.sma(source, length)
e = ta.ema(source, length)
exp ? e : s
ma = esma(src, length)
rangema = BandsStyle == "True Range" ? ta.tr(true) : BandsStyle == "Average True Range" ? ta.atr(atrlength) : ta.rma(high - low, length)
upper = ma + rangema * mult
lower = ma - rangema * mult
//--Graphical Display--// *-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-$$$$$$
u = plot(upper, color=#2962FF, title="Upper", force_overlay=true)
plot(ma, color=#2962FF, title="Basis", force_overlay=true)
l = plot(lower, color=#2962FF, title="Lower", force_overlay=true)
fill(u, l, color=color.rgb(33, 150, 243, 95), title="Background")
//--Risk Management--// *-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-$$$$$$
riskPerTradePerc = input.float(1, title="Risk per trade (%)", group="Keltner Channel Breakout")
le = high>upper ? false : true
se = lowlower
strategy.entry('PivRevLE', strategy.long, comment = 'PivRevLE', stop = upper, qty=riskToLots)
if se and upper>lower
strategy.entry('PivRevSE', strategy.short, comment = 'PivRevSE', stop = lower, qty=riskToLots)
The tool will then use the strategy equity of your own strategy and use this to simulat prop firms. Since these CFD prop firms work with different phases and payouts the indicator will simulate the gains until target or max drawdown / daily drawdown limit gets reached. If it reaches target it will go to the next phase and keep on doing that until it fails a challenge.
If in one of the phases there is a reward for completing, like a payout, refund, extra it will add this to the gains.
If you fail the challenge by reaching max drawdown or daily drawdown limit it will substract the challenge fee from the gains.
These gains are then visualised in the calendar so you can get an idea of yearly / monthly gains of the backtest. Remember, it is just a backtest so no guarantees of future income.
The bottom pane (non-overlay) is visualising the performance of the backtest during the phases. This way u can check if it is realistic. For instance if it only takes 1 bar on chart to reach target you are probably risking more than the firm wants you to risk. Also, it becomes much less clear if daily drawdown got hit in those high risk strategies, the results will be less accurate.
The daily drawdown limit get's reset every time there is a new dayofweek on chart.
If you set your prop firm preset setting to "'custom" the settings below that are applied as your prop firm settings. Otherwise it will use one of the template by default it's FTMO 100K.
The strategy I'm using as an example in this script is a simple Keltner Channel breakout strategy. I'm using a 0.05% commission per trade as that is what I found most common on crypto exchanges and it's close to the commissions+spread you get on a cfd prop firm. I'm targeting a 1% risk per trade in the backtest to try and stay within prop firm boundaries of max 1% risk per trade.
Lastly, the original yearly and monthly performance table was developed by Quantnomad and I've build ontop of that code. Here's a link to the original publication:
That's everything for now, hope this indicator helps people visualise the potential of prop firms better or to understand that they are not a good fit for their current financial situation.
VBSMI Strategy by QTX Algo SystemsVolatility Based SMI Strategy by QTX Algo Systems
Overview
The Volatility Based SMI Strategy transforms our popular VBSMI with Dynamic Bands indicator into a fully automated strategy that traders can backtest inside TradingView. It retains all core logic from the indicator—including adaptive volatility scaling and trend-based overbought/oversold thresholds—but adds two configurable entry methods, exit conditions, and a dual-mode trade execution engine.
This script is published separately from the VBSMI indicator because some traders use VBSMI as a confluence tool within their existing system, while others prefer a rules-based strategy that can be simulated, optimized, and tracked over time. This script serves the latter use case.
How It Works
Like the original indicator, this strategy uses:
Double-Smoothed SMI Calculation: Based on smoothed momentum using EMA of the relative and full range.
Adaptive Volatility Scaling: Uses a normalized BBWP-based factor to reflect current market volatility.
Dynamic Band Adjustment: Trend direction and strength shift overbought/oversold levels upward or downward.
Band Tilt & Compression Controls: Inputs allow users to define how aggressively the bands shift with trend conditions.
What’s different is the strategy layer—you now choose from two types of entry and exit logic, and two execution styles.
🛠️ Entry & Exit Modes
There are two logic modes for both entry and exit, allowing you to adapt the strategy to your own philosophy:
Cross Mode (SMI Crosses EMA):
Entry: Buy when SMI crosses above its EMA
Exit: Close when SMI crosses below its EMA
Exit OB/OS Mode (Band Exit Logic):
Entry: Buy when price exits dynamic oversold zone (crosses back above tilted oversold band)
Exit: Close when price exits dynamic overbought zone (crosses back below tilted overbought band)
You can mix and match the modes (e.g., enter on Cross, exit on Band Exit).
⚙️ Spot vs. Leverage Mode
Spot Mode
Designed for traders who prefer long-only setups
Enters a long position and holds until the exit condition is met
Prevents overlapping trades—ensures only one position at a time
Leverage Mode
Designed for those testing bi-directional systems (e.g., long/short switching)
Automatically flips between long and short entries depending on the signals
Useful for testing symmetrical strategies or inverse conditions
Both modes work across any asset class and timeframe.
Customization Options
Users can adjust:
Smoothing K/D: Controls how fast or slow the momentum reacts
SMI EMA Length: Determines the responsiveness of the signal line
Trend Lookback Period: Influences how stable the dynamic band tilt is
Band Tilt & Compression Strengths: Refines how far bands adjust based on trend
Entry/Exit Logic Type: Choose between “Cross” or “Exit OB/OS” logic
Trading Mode: Select either "Spot" or "Leverage" depending on your use case
Why It’s Published Separately
This script is not a cosmetic or minor variation of the original indicator. It introduces:
Entry/exit logic
Order execution
Strategy testing capabilities
Mode selection (Spot vs. Leverage)
Signal logic control (Cross vs. Band Exit)
Because the original VBSMI indicator is widely used as a charting and confirmation tool, converting it into a strategy changes how it functions. This version is intended for strategy evaluation and automation, while the original remains available for discretionary and visual use.
Use Cases
This strategy is best suited for:
Evaluating VBSMI-based signals in backtests
Comparing entry and exit logic over time
Testing setups on different assets and timeframes
Automating VBSMI-based logic in a structured and risk-aware framework
Disclaimer
This strategy is for educational purposes only. It does not guarantee future results or profitability. Always test in simulation before using any strategy live, and use proper risk management and trade discipline.
