Baseline TrendBaseline Trend Strategy Overview
Baseline Trend is a crypto-only trading strategy built on straightforward price-based logic: market direction is determined solely by the price’s position relative to a selected baseline open price. No technical indicators like RSI, MACD, or volume are used—this approach is purely focused on price action and position size manipulation.
This strategy is a genuine concept, developed from my own market analysis and logical theory, refined through extensive observation of crypto market behaviour.
While the strategy offers structure and adaptability, it’s important to recognise that no single trading system or indicator fits all market conditions. This tool is meant to support decision-making, not replace it—encouraging traders to stay flexible, informed, and in control of their risk.
Important Usage Note:
This system is intended for crypto markets only.
– When used as an indicator guide, it can be applied to both spot and futures markets.
– However, when used with web-hook automation, it is designed only for futures contracts.
Ensure compatibility with your trading setup before using automation features.
Core Logic: The Baseline
The strategy revolves around the concept of a “Baseline”, with three types available:
Main Baseline: Defines the primary trend direction. If the price is above, go long; if below, go short.
Second Baseline and Third Baseline: Used to measure buying/selling pressure and are key to certain take-profit logic options.
Baselines are customisable to different timeframes—Year, Month, Week, and more—based on available input settings. Structurally, the Main Baseline is the highest-level trend reference, followed by the Second, then Third.
Users can mix and match these baselines across timeframes to backtest crypto symbols and understand behaviour patterns, particularly when used with standard candlestick charts.
Entry & Exit Logic
Entry Signal: Triggered when price crosses over/under a defined distance (percentage) from the Main Baseline. This distance is the Trade Line, calculated based on the close price.
Exit Signal / Stop Loss: If price moves un-favorable and crosses over/under the Stop Loss Line (a defined distance from the Main Baseline), the open position will be force-closed according to user-defined settings.
LiqC (Liquidation Cut)
LiqC is a secondary stop-loss that activates when a leveraged position’s loss equals or exceeds the user-defined liquidation threshold. It forcefully closes the position to help prevent full liquidation before stop-loss, providing an extra layer of protection.
This LiqC is directly tied to the leverage level set by the user. Please ensure you understand how leverage affects liquidation risk, as different broker exchanges may use different liquidation ratio models. Using incorrect assumptions or mismatched leverage values may result in unexpected behaviour.
Position Sizing & Block Units
This strategy features a block-based position sizing system designed for flexibility and precision in trade management:
Block Range: Customisable from 1 to 10 blocks
Risk Allocation: Controlled through a user-defined ROE (Risk of Equity) value
For example, setting an ROE of 0.1% with 10 blocks allocates a total of 1% of account equity to the position. This structure supports both conservative and aggressive risk approaches, depending on user preference.
Block sizes are automatically calculated in alignment with exchange requirements, using Minimum Notional Value (MNV) and Minimum Trade Amount (MTA). These values are dynamically calculated based on the live market price, and scaled relative to the trader’s balance and selected risk percentage. This ensures accurate sizing with built-in adaptability for any account level and current market conditions.
Scalping Meets Trend Holding
This system blends short-term scalping with longer-term trend holding, offering a flexible and adaptive trading style.
Example:
Enter 10 blocks → take quick profits on 5 blocks → let the remaining 5 ride the trend.
This dual-layered approach allows traders to secure early gains while staying positioned for larger market moves. Think of it as:
5 Blocks to Protect: Capture quick wins and manage exposure.
5 Blocks to Pursue: Let profits run by following the broader trend.
By combining both protection and pursuit, the strategy supports risk control without sacrificing the potential for extended returns.
Flexible Take-Profit Logic
The strategy supports multiple, customisable take-profit mechanisms:
TP1–4 (Profit Percentage)
Triggers take profit of 1 block unit when unrealised gains reach defined percentage thresholds (TP1, TP2, TP3, TP4).
Buying/Selling Pressure-Based Take Profit
D1 – Pressure 1
Measures pressure between Second and Third Baselines.
If the distance between them exceeds a user-defined DPT (Decrease Post Threshold) and the price moves far enough from the Third Baseline, D1 activates to take profit or scale out one block.
D2 – Pressure 2
Measures pressure between the Main and Second Baselines.
Works similarly to D1, using a separate distance and pressure trigger.
Note: Both D1 and D2 deactivate in reversal or even trend conditions.
D3–5: High-High / Low-Low Logic
Based on bar index tracking after position entry:
For Long Positions: If after D3 bars the price doesn't exceed the previous bar's high, the system executes a take profit or scale-out.
For Short Positions: If the price doesn't drop below the previous low, the same logic applies.
This approach adds time-based and momentum-aware exit flexibility.
Leverage & Liquidation Risk
When backtesting with leverage enabled, the system checks whether historical candles exceed the liquidation range, calculated based on the average entry price and the leverage input. If the Liquidation Risk Count exceeds 1, profit and loss accuracy may be affected. Traders are encouraged to monitor this count closely to ensure realistic backtesting results.
Since the system cannot directly control or sync with your broker exchange’s actual leverage setting, it’s important to manually match the system’s leverage input with your broker’s configured leverage.
For example: If the system leverage input is set to 10, your exchange leverage setting must also be set to 10. Any mismatch will lead to inaccurate liquidation risk and PnL calculations.
Backtesting and Customisation
All TP1–4 and D1–5 functions are fully optional and customisable. Users are encouraged to backtest different crypto symbols to observe how price behaviour aligns with baseline structures and pressure metrics.
Each of the TP1–4 and D1–5 triggers is designed to execute only once per open position, ensuring controlled and predictable behaviour within each trade cycle.
Since backtesting is based on available historical bar data, please note that data availability varies depending on your TradingView subscription plan. For more reliable insights, it’s recommended to backtest across multiple time ranges, not just the full dataset, to assess the stability and consistency of the strategy’s performance over time.
Additionally, the time frame resolution interval in TradingView is customisable. For best results, use commonly supported time frames such as 30 minutes, 1 hour, 4 hours, 1 day, or 1 week. While the system is designed to support a broad range of intervals, non-standard resolutions may still cause calculation errors.
Currently, the system supports the following resolution ranges:
Intraday: from 1 minute to 720 minutes
(e.g., 60 minutes = 1 hour, 240 minutes = 4 hours, 720 minutes = 12 hours)
Daily: from 1 day to 6 days
Weekly: from 1 week to 3 weeks
Monthly: from 1 month to 4 months
Although the script is built to adapt to various resolutions, users should still monitor output behaviour closely, especially when testing less common or edge-case time frames.
System Usage Notice:
This system can be used as a standalone trading indicator or integrated with an exchange that supports web-hook signal execution. If you choose to automate trades via web-hook, please ensure you fully understand how to configure the setup properly. Web-hook integration methods vary between exchanges, and incorrect setup may lead to unintended trades. Users are responsible for ensuring proper configuration and monitoring of their automation.
Note on Lower Time Frame Usage
When using lower time frames (e.g., 1-minute charts) as the trading time frame, please be aware that available historical data may be limited depending on your subscription plan. This can affect the depth and reliability of backtesting, making it harder to establish a trustworthy probability model for a symbol’s behaviour over time.
Additionally, when pairing a high-level Main Baseline (MBL) time line (such as "1 Month") with low time frame resolutions (like 1-minute), you may encounter order execution limits or calculation overloads during backtesting. This is due to the large number of historical bars required, which can strain the system's capacity.
That said, if a user intentionally chooses to work with lower time frames, that decision is fully respected—but it should be done with awareness and at the user’s own risk.
Things to Be Aware Of (Web-hook Usage Only)
The following points apply if you're using web-hook automation to send signals from the system to an exchange:
Alert Signal Reliability
During extreme market volatility, some broker exchanges may fail to respond to web-hook signals due to traffic overload. While rare, this has occurred in the past and should be considered when relying on automation.
Alert Expiration (TradingView)
If you're on a Basic plan, TradingView alerts are only active for a limited time—typically around 1.5 months. Once expired, signals will no longer be sent out.
To keep your system active, reset the alert before expiration. For uninterrupted alerts, consider upgrading to a Premium plan, which supports permanent alert activation.
TradingView Alert Maintenance
TradingView may occasionally perform system maintenance, during which alerts may temporarily stop functioning. It’s recommended to monitor TradingView’s status if you’re relying on real-time automation.
Repainting
As of the current version, no repainting behaviour has been observed. Signal stability and consistency have been maintained across real-time and historical bars.
Order Execution Type and Fill Logic
All signals use Limit orders by default, except for MBL Exit and Fallback execution, which use Market orders.
Since Limit orders are not guaranteed to fill, the system includes logic to cancel unfilled orders and resend them. If necessary, a Fallback Market order is used to avoid conflict with new incoming trades.
This has only happened once, and is considered rare, but users should always monitor execution status to ensure accuracy and alignment with system behaviour.
Feedback
If you encounter any errors, bugs, or unexpected behaviour while using the system, please don’t hesitate to let me know. Your input is invaluable for helping improve the strategy in future updates.
Likewise, if you have any suggestions or ideas for enhancing the system—whether it’s a new feature, adjustment, or usability improvement—please feel free to share. Together, we can continue refining the tool to make it more robust and beneficial for everyone.
Disclaimer
All trading involves risk, particularly in the crypto market where conditions can be highly volatile. Past performance does not guarantee future outcomes, and market behaviour may evolve over time. This strategy is offered as a tool to support trading decisions and should not be considered financial or investment advice. Each user is responsible for their own actions and accepts full responsibility for any results that may arise from using this system.
Cerca negli script per "profit"
Quantum Reversal# 🧠 Quantum Reversal
## **Quantitative Mean Reversion Framework**
This algorithmic trading system employs **statistical mean reversion theory** combined with **adaptive volatility modeling** to capitalize on Bitcoin's inherent price oscillations around its statistical mean. The strategy integrates multiple technical indicators through a **multi-layered signal processing architecture**.
---
## ⚡ **Core Technical Architecture**
### 📊 **Statistical Foundation**
- **Bollinger Band Mean Reversion Model**: Utilizes 20-period moving average with 2.2 standard deviation bands for volatility-adjusted entry signals
- **Adaptive Volatility Threshold**: Dynamic standard deviation multiplier accounts for Bitcoin's heteroscedastic volatility patterns
- **Price Action Confluence**: Entry triggered when price breaches lower volatility band, indicating statistical oversold conditions
### 🔬 **Momentum Analysis Layer**
- **RSI Oscillator Integration**: 14-period Relative Strength Index with modified oversold threshold at 45
- **Signal Smoothing Algorithm**: 5-period simple moving average applied to RSI reduces noise and false signals
- **Momentum Divergence Detection**: Captures mean reversion opportunities when momentum indicators show oversold readings
### ⚙️ **Entry Logic Architecture**
```
Entry Condition = (Price ≤ Lower_BB) OR (Smoothed_RSI < 45)
```
- **Dual-Condition Framework**: Either statistical price deviation OR momentum oversold condition triggers entry
- **Boolean Logic Gate**: OR-based entry system increases signal frequency while maintaining statistical validity
- **Position Sizing**: Fixed 10% equity allocation per trade for consistent risk exposure
### 🎯 **Exit Strategy Optimization**
- **Profit-Lock Mechanism**: Positions only closed when showing positive unrealized P&L
- **Trend Continuation Logic**: Allows winning trades to run until momentum exhaustion
- **Dynamic Exit Timing**: No fixed profit targets - exits based on profitability state rather than arbitrary levels
---
## 📈 **Statistical Properties**
### **Risk Management Framework**
- **Long-Only Exposure**: Eliminates short-squeeze risk inherent in cryptocurrency markets
- **Mean Reversion Bias**: Exploits Bitcoin's tendency to revert to statistical mean after extreme moves
- **Position Management**: Single position limit prevents over-leveraging
### **Signal Processing Characteristics**
- **Noise Reduction**: SMA smoothing on RSI eliminates high-frequency oscillations
- **Volatility Adaptation**: Bollinger Bands automatically adjust to changing market volatility
- **Multi-Timeframe Coherence**: Indicators operate on consistent timeframe for signal alignment
---
## 🔧 **Parameter Configuration**
| Technical Parameter | Value | Statistical Significance |
|-------------------|-------|-------------------------|
| Bollinger Period | 20 | Standard statistical lookback for volatility calculation |
| Std Dev Multiplier | 2.2 | Optimized for Bitcoin's volatility distribution (95.4% confidence interval) |
| RSI Period | 14 | Traditional momentum oscillator period |
| RSI Threshold | 45 | Modified oversold level accounting for Bitcoin's momentum characteristics |
| Smoothing Period | 5 | Noise reduction filter for momentum signals |
---
## 📊 **Algorithmic Advantages**
✅ **Statistical Edge**: Exploits documented mean reversion tendency in Bitcoin markets
✅ **Volatility Adaptation**: Dynamic bands adjust to changing market conditions
✅ **Signal Confluence**: Multiple indicator confirmation reduces false positives
✅ **Momentum Integration**: RSI smoothing improves signal quality and timing
✅ **Risk-Controlled Exposure**: Systematic position sizing and long-only bias
---
## 🔬 **Mathematical Foundation**
The strategy leverages **Bollinger Band theory** (developed by John Bollinger) which assumes that prices tend to revert to the mean after extreme deviations. The RSI component adds **momentum confirmation** to the statistical price deviation signal.
**Statistical Basis:**
- Mean reversion follows the principle that extreme price deviations from the moving average are temporary
- The 2.2 standard deviation multiplier captures approximately 97.2% of price movements under normal distribution
- RSI momentum smoothing reduces noise inherent in oscillator calculations
---
## ⚠️ **Risk Considerations**
This algorithm is designed for traders with understanding of **quantitative finance principles** and **cryptocurrency market dynamics**. The strategy assumes mean-reverting behavior which may not persist during trending market phases. Proper risk management and position sizing are essential.
---
## 🎯 **Implementation Notes**
- **Market Regime Awareness**: Most effective in ranging/consolidating markets
- **Volatility Sensitivity**: Performance may vary during extreme volatility events
- **Backtesting Recommended**: Historical performance analysis advised before live implementation
- **Capital Allocation**: 10% per trade sizing assumes diversified portfolio approach
---
**Engineered for quantitative traders seeking systematic mean reversion exposure in Bitcoin markets through statistically-grounded technical analysis.**
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.*
DVPOOverview
The DVPO (Dynamic Volume Profile Oscillator) Strategy is a comprehensive and highly customizable trading tool designed for precision and control. It is built around a unique, volume-driven oscillator that identifies potential market entries by analyzing the relationship between price, volume, and volatility.
This strategy is not just another signal generator; it's a complete framework that includes dynamic entry logic, adaptive risk management (ATR Stop Loss and R:R-based Take Profit), and a powerful dashboard of 10+ optional confirmation filters to help you tailor the strategy to your specific instrument, timeframe, and trading style.
The Core Concept: The DVPO Oscillator
The heart of this strategy is the DVPO oscillator. Unlike standard oscillators like RSI or Stochastics, the DVPO's primary goal is to quantify how far the current price has deviated from its recent volume-weighted "fair value."
Here’s how it works conceptually:
Micro Volume Profile: The indicator first analyzes a recent period of bars (defined by Lookback Period) to build a mini-profile of price and volume.
Volume-Weighted Mean: From this profile, it calculates a volume-weighted average price (VWAP) and the average deviation from that mean. This establishes the central point of value for the recent period.
Deviation Measurement: The oscillator's value is derived from how far the current price is from this calculated mean, scaled by the observed price deviation and a user-defined Sensitivity. A value above the midline suggests the price is trading at a premium, while a value below suggests it's at a discount.
Adaptive Volatility Zones: Instead of using fixed overbought/oversold levels (e.g., 70/30), the DVPO calculates dynamic upper and lower zones using the standard deviation of the oscillator itself. These zones expand and contract based on recent market volatility.
An entry signal is triggered not just when the oscillator is "overbought" or "oversold," but when it breaks out of these adaptive volatility zones, signaling that a statistically significant price movement is underway.
📈 Long Entry Condition : The oscillator crosses above the dynamic upper zone.
📉 Short Entry Condition : The oscillator crosses below the dynamic lower zone.
Integrated Risk & Trade Management
A signal is useless without proper risk management. This strategy has professional-grade risk management built directly into its logic.
Stop Loss (ATR-Based): The Stop Loss is not a fixed percentage. It is calculated using the Average True Range (ATR), allowing it to adapt automatically to the market's current volatility. In volatile periods, the stop will be wider; in quiet periods, it will be tighter.
Take Profit (Risk/Reward Ratio): The Take Profit level is calculated based on a user-defined Risk/Reward Ratio. If you set a ratio of 2.0, the Take Profit target will be placed at twice the distance of the Stop Loss from your entry price.
Dynamic Position Sizing: The strategy can automatically calculate the trade quantity for you. It determines the position size based on your specified Capital Size and the % Risk Per Trade you are willing to accept, ensuring disciplined risk control on every trade.
The Filter Dashboard : Enhance Your Signal Quality
To help reduce false signals and adapt to different market conditions, the strategy includes a comprehensive dashboard of optional confirmation filters. An entry signal will only be executed if it aligns with all the filters you have activated.
Trend & Momentum Filters :
T3, VMA, & VWAP Trend Filters: Utilize a suite of advanced moving averages (T3, Variable Moving Average, and a session-based VWAP) to ensure your trades are aligned with the dominant trend.
ADX Filter: Confirms that the market has sufficient directional strength for a trend-following trade, helping to avoid entries during choppy conditions.
Kaufman Efficiency Filter: Uses the Kaufman Efficiency Ratio to measure market noise. It only allows trades when the market is trending efficiently.
Volume & Market State Filters :
Volume Flow (VFI): A sophisticated volume-based filter that confirms whether volume is supporting the price move.
TDFI (Trader's Dynamic Index): A market state indicator designed to identify when the market is primed for a strong, directional move.
Flat Market Detector: A unique filter that identifies and avoids trading in sideways or ranging markets where trend strategies typically underperform.
Trade Condition Filters :
Min TP / Max SL %: Filter out trades where the risk/reward profile doesn't meet your minimum requirements (e.g., ignore a trade if the ATR-based stop loss is more than 10% away from the price).
Session Filters: Allows you to enable or disable trading on specific days of the week and to set a Cooldown Period (a set number of bars to wait after a trade closes before looking for a new entry).
How To Use This Strategy
Start with the Core: Begin by configuring the DVPO Oscillator settings (Lookback Period, Sensitivity, Zone Width) and your Risk Management parameters (ATR Multiplier, RR Ratio, % Risk Per Trade). These form the foundation of the strategy.
Backtest and Observe: Use TradingView's Strategy Tester to see how the core signals perform on your chosen asset and timeframe.
Layer Filters Intelligently: Enable the confirmation filters one by one and re-run your backtest. Observe how each filter impacts performance (e.g., does the T3 filter increase profitability but reduce the number of trades?). The goal is to find the optimal balance between signal quality and frequency.
Visualize and Analyze: Use the Show Risk/Reward Area option to plot your entry, stop loss, and take profit levels directly on the chart for every trade, providing a clear visual representation of your trade plan.
Disclaimer: This strategy is provided for educational and analytical purposes only. Past performance is not indicative of future results. All trading involves risk, and you should conduct your own thorough backtesting and analysis before deploying any strategy in a live market.
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.
Donchian x WMA Crossover (2025 Only, Adjustable TP, Real OHLC)Short Description:
Long-only breakout system that goes long when the Donchian Low crosses up through a Weighted Moving Average, and closes when it crosses back down (with an optional take-profit), restricted to calendar year 2025. All signals use the instrument’s true OHLC data (even on Heikin-Ashi charts), start with 1 000 AUD of capital, and deploy 100 % equity per trade.
Ideal parameters configured for Temple & Webster on ASX 30 minute candles. Adjust parameter to suit however best to download candle interval data and have GPT test the pine script for optimum parameters for your trading symbol.
Detailed Description
1. Strategy Concept
This strategy captures trend-driven breakouts off the bottom of a Donchian channel. By combining the Donchian Low with a WMA filter, it aims to:
Enter when volatility compresses and price breaks above the recent Donchian Low while the longer‐term WMA confirms upward momentum.
Exit when price falls back below that same WMA (i.e. when the Donchian Low crosses back down through WMA), but only if the WMA itself has stopped rising.
Optional Take-Profit: you can specify a profit target in decimal form (e.g. 0.01 = 1 %).
2. Timeframe & Universe
In-sample period: only bars stamped between Jan 1 2025 00:00 UTC and Dec 31 2025 23:59 UTC are considered.
Any resolution (e.g. 30 m, 1 h, D, etc.) is supported—just set your preferred timeframe in the TradingView UI.
3. True-Price Execution
All indicator calculations (Donchian Low, WMA, crossover checks, take-profit) are sourced from the chart’s underlying OHLC via request.security(). This guarantees that:
You can view Heikin-Ashi or other styled candles, but your strategy will execute on the real OHLC bars.
Chart styling never suppresses or distorts your backtest results.
4. Position Sizing & Equity
Initial capital: 1 000 AUD
Size per trade: 100 % of available equity
No pyramiding: one open position at a time
5. Inputs (all exposed in the “Inputs” tab):
Input Default Description
Donchian Length 7 Number of bars to calculate the Donchian channel low
WMA Length 62 Period of the Weighted Moving Average filter
Take Profit (decimal) 0.01 Exit when price ≥ entry × (1 + take_profit_perc)
6. How It Works
Donchian Low: ta.lowest(low, DonchianLength) over the specified look-back.
WMA: ta.wma(close, WMALength) applied to true closes.
Entry: ta.crossover(DonchianLow, WMA) AND barTime ∈ 2025.
Exit:
Cross-down exit: ta.crossunder(DonchianLow, WMA) and WMA is not rising (i.e. momentum has stalled).
Take-profit exit: price ≥ entry × (1 + take_profit_perc).
Calendar exit: barTime falls outside 2025.
7. Usage Notes
After adding to your chart, open the Strategy Tester tab to review performance metrics, list of trades, equity curve, etc.
You can toggle your chart to Heikin-Ashi for visual clarity without affecting execution, thanks to the real-OHLC calls.
Kaufman Trend Strategy# ✅ Kaufman Trend Strategy – Full Description (Script Publishing Version)
**Kaufman Trend Strategy** is a dynamic trend-following strategy based on Kaufman Filter theory.
It detects real-time trend momentum, reduces noise, and aims to enhance entry accuracy while optimizing risk.
⚠️ _For educational and research purposes only. Past performance does not guarantee future results._
---
## 🎯 Strategy Objective
- Smooth price noise using Kaufman Filter smoothing
- Detect the strength and direction of trends with a normalized oscillator
- Manage profits using multi-stage take-profits and adaptive ATR stop-loss logic
---
## ✨ Key Features
- **Kaufman Filter Trend Detection**
Extracts directional signal using a state space model.
- **Multi-Stage Profit-Taking**
Automatically takes partial profits based on color changes and zero-cross events.
- **ATR-Based Volatility Stops**
Stops adjust based on swing highs/lows and current market volatility.
---
## 📊 Entry & Exit Logic
**Long Entry**
- `trend_strength ≥ 60`
- Green trend signal
- Price above the Kaufman average
**Short Entry**
- `trend_strength ≤ -60`
- Red trend signal
- Price below the Kaufman average
**Exit (Long/Short)**
- Blue trend color → TP1 (50%)
- Oscillator crosses 0 → TP2 (25%)
- Trend weakens → Final exit (25%)
- ATR + swing-based stop loss
---
## 💰 Risk Management
- Initial capital: `$3,000`
- Order size: `$100` per trade (realistic, low-risk sizing)
- Commission: `0.002%`
- Slippage: `2 ticks`
- Pyramiding: `1` max position
- Estimated risk/trade: `~0.1–0.5%` of equity
> ⚠️ _No trade risks more than 5% of equity. This strategy follows TradingView script publishing rules._
---
## ⚙️ Default Parameters
- **1st Take Profit**: 50%
- **2nd Take Profit**: 25%
- **Final Exit**: 25%
- **ATR Period**: 14
- **Swing Lookback**: 10
- **Entry Threshold**: ±60
- **Exit Threshold**: ±40
---
## 📅 Backtest Summary
- **Symbol**: USD/JPY
- **Timeframe**: 1H
- **Date Range**: Jan 3, 2022 – Jun 4, 2025
- **Trades**: 924
- **Win Rate**: 41.67%
- **Profit Factor**: 1.108
- **Net Profit**: +$1,659.29 (+54.56%)
- **Max Drawdown**: -$1,419.73 (-31.87%)
---
## ✅ Summary
This strategy uses Kaufman filtering to detect market direction with reduced lag and increased smoothness.
It’s built with visual clarity and strong trade management, making it practical for both beginners and advanced users.
---
## 📌 Disclaimer
This script is for educational and informational purposes only and should not be considered financial advice.
Use with proper risk controls and always test in a demo environment before live trading.
Grid TLong V1The “Grid TLong V1” strategy is based on the classic Grid strategy, but in the mode of buying and selling in favor of the trend and only on Long. This allows to take advantage of large uptrend movements to maximize profits in bull markets. For this reason, excessively sideways or bearish markets may not be very conducive to this strategy.
Like our Grid strategies in favor of the trend, you can enter and exit with the balance with controlled risk, as the distance between each grid functions as a natural and adaptable stop loss and take profit. What differentiates it from bidirectional strategies is that Short uses a minimum amount of follow-through, so that the percentage distance between the grids is maintained.
In this version of the script the entries and exits can be chosen at market or limit , and are based on the profit or loss of the current position, not on the percentage change in price.
The user may also notice that the strategy setup is risk-controlled, because it risks 5% on each trade, has a fairly standard commission and modest initial capital, all in order to protect the strategy user from unrealistic results.
As with all strategies, it is strongly recommended to optimize the parameters for the strategy to be effective for each asset and for each time frame.
RSI SwingRadar🧠 Strategy Overview
This long-only strategy combines RSI/MA crossovers with ATR-based risk management, designed for cleaner entries during potential bounce phases — especially tuned for assets like XMR/USDT.
🔍 Core Logic:
- RSI Crossover: Entry occurs when the 14-period RSI crosses above its 14-period SMA, signaling a potential shift in momentum.
- Oversold Filter: The RSI must have been below a user-defined oversold threshold (default: 35) on the previous candle, filtering for bounce setups after a pullback.
- ATR-Based Stop/Target: Stop-loss is placed below the low by a user-adjustable ATR multiplier (default: 0.5×). Take-profit is calculated with a Risk:Reward multiplier (default: 4×).
These elements work in tandem — RSI crossovers give momentum confirmation, oversold filtering adds context, and ATR-based exits adapt to volatility, creating a compact yet responsive strategy.
📉 Visuals:
- Dynamic Bands: The chart displays the active stop-loss, entry price, and take-profit as colored bands for easy visual tracking.
- Clean Overlay: Designed with simplicity — only confirmed setups are shown, keeping noise low.
✅ Suggested Use:
- Works best on XMR/USDT or similarly trending assets.
- Best suited for pullback entries during broader uptrends.
- Adjustable for different volatility conditions and asset behaviors.
⚠️ Disclaimer
- This strategy is for educational and research purposes only.
- It does not guarantee profitability in any market.
- Always backtest, forward-test, and understand your own risk tolerance before using any
strategy in a live environment.
- Past performance is not indicative of future results.
- This script is not financial advice.
Big Mover Catcher BTC 4h🧠 Big Mover Catcher (BTC 4H Strategy) — Educational Tool
⚠️ Disclaimer: I am not a financial advisor. This script is for educational and testing purposes only. Cryptocurrency trading is highly volatile and involves significant risk. You can lose all of your invested capital.
📌 Overview
The Big Mover Catcher strategy is a work-in-progress trading system designed for Bitcoin (BTC) on the 4-hour chart. It aims to identify strong breakout moves by combining multiple technical indicators and conditions, allowing for high customization and filter-based confirmations.
This script is part of a personal project to learn Pine Script and backtesting on TradingView. It is currently in the testing and research phase.
🎯 Strategy Objective
Catch large, high-momentum breakout moves in the BTC market using:
Bollinger Band breakouts for entry signals
Momentum, volatility, and trend filters for trade confirmation
🧰 Features & Filters
The script provides a flexible set of filters that can be turned ON/OFF and adjusted directly from the settings panel:
✅ Entry Conditions
Price must break above or below Bollinger Bands
All selected filters must align before entry
🧪 Available Filters:
Relative Strength Index (RSI) with EMA/SMA smoothing
Average Directional Index (ADX) with EMA/SMA smoothing
Average True Range (ATR) with EMA/SMA smoothing
MACD Signal above or below zero
EMA 350 trend filter
ATR / ADX / RSI Threshold toggles for added control
🔥 Additional Feature:
Force Take Profit: Optionally closes the trade immediately if a candle closes with more than a defined % movement (default: 5%). This can help lock in quick profits during high volatility moves.
⚙️ Customizable Inputs
You can configure:
Stop loss percentage
All indicator lengths
Smoothing types (EMA/SMA)
Threshold activation toggles
Individual filter ON/OFF switches
This makes the strategy highly adaptable for educational exploration and optimization.
📊 Best Used For
Learning Pine Script and strategy structure
Testing filter combinations for BTC on the 4H timeframe
Understanding how different indicators interact in live markets
⚠️ Note: ❌ Short trades are currently disabled by default, as short-side logic is still under development.
❗ Final Reminder
This script is not financial advice. It is an educational tool. Use it to learn and explore trading logic. Trading cryptocurrencies carries high risk — only invest what you can afford to lose.
EMA Pullback Speed Strategy 📌 **Overview**
The **EMA Pullback Speed Strategy** is a trend-following approach that combines **price momentum** and **Exponential Moving Averages (EMA)**.
It aims to identify high-probability entry points during brief pullbacks within ongoing uptrends or downtrends.
The strategy evaluates **speed of price movement**, **relative position to dynamic EMA**, and **candlestick patterns** to determine ideal timing for entries.
One of the key concepts is checking whether the price has **“not pulled back too much”**, helping focus only on situations where the trend is likely to continue.
⚠️ This strategy is designed for educational and research purposes only. It does not guarantee future profits.
🧭 **Purpose**
This strategy addresses the common issue of **"jumping in too late during trends and taking unnecessary losses."**
By waiting for a healthy pullback and confirming signs of **trend resumption**, traders can enter with greater confidence and reduce false entries.
🎯 **Strategy Objectives**
* Enter in the direction of the prevailing trend to increase win rate
* Filter out false signals using pullback depth, speed, and candlestick confirmations
* Predefine Take-Profit (TP) and Stop-Loss (SL) levels for safer, rule-based trading
✨ **Key Features**
* **Dynamic EMA**: Reacts faster when price moves quickly, slower when market is calm – adapting to current momentum
* **Pullback Filter**: Avoids trades when price pulls back too far (e.g., more than 5%), indicating a trend may be weakening
* **Speed Check**: Measures how strongly the price returns to the trend using candlestick body speed (open-to-close range in ticks)
📊 **Trading Rules**
**■ Long Entry Conditions:**
* Current price is above the dynamic EMA (indicating uptrend)
* Price has pulled back toward the EMA (a "buy the dip" situation)
* Pullback depth is within the threshold (not excessive)
* Candlesticks show consecutive bullish closes and break the previous high
* Price speed is strong (positive movement with momentum)
**■ Short Entry Conditions:**
* Current price is below the dynamic EMA (indicating downtrend)
* Price has pulled back up toward the EMA (a "sell the rally" setup)
* Pullback is within range (not too deep)
* Candlesticks show consecutive bearish closes and break the previous low
* Price speed is negative (downward momentum confirmed)
**■ Exit Conditions (TP/SL):**
* **Take-Profit (TP):** Fixed 1.5% target above/below entry price
* **Stop-Loss (SL):** Based on recent price volatility, calculated using ATR × 4
💰 **Risk Management Parameters**
* Symbol & Timeframe: BTCUSD on 1-hour chart (H1)
* Test Capital: \$3000 (simulated account)
* Commission: 0.02%
* Slippage: 2 ticks (minimal execution lag)
* Max risk per trade: 5% of account balance
* Backtest Period: Aug 30, 2023 – May 9, 2025
* Profit Factor (PF): 1.965 (Net profit ÷ Net loss, including spreads & fees)
⚙️ **Trading Parameters & Indicator Settings**
* Maximum EMA Length: 50
* Accelerator Multiplier: 3.0
* Pullback Threshold: 5.0%
* ATR Period: 14
* ATR Multiplier (SL distance): 4.0
* Fixed TP: 1.5%
* Short-term EMA: 21
* Long-term EMA: 50
* Long Speed Threshold: ≥ 1000.0 (ticks)
* Short Speed Threshold: ≤ -1000.0 (ticks)
⚠️Adjustments are based on BTCUSD.
⚠️Forex and other currency pairs require separate adjustments.
🔧 **Strategy Improvements & Uniqueness**
Unlike basic moving average crossovers or RSI triggers, this strategy emphasizes **"momentum-supported pullbacks"**.
By combining dynamic EMA, speed checks, and candlestick signals, it captures trades **as if surfing the wave of a trend.**
Its built-in filters help **avoid overextended pullbacks**, which often signal the trend is ending – making it more robust than traditional trend-following systems.
✅ **Summary**
The **EMA Pullback Speed Strategy** is easy to understand, rule-based, and highly reproducible – ideal for both beginners and intermediate traders.
Because it shows **clear visual entry/exit points** on the chart, it’s also a great tool for practicing discretionary trading decisions.
⚠️ Past performance is not a guarantee of future results.
Always respect your Stop-Loss levels and manage your position size according to your risk tolerance.
Liquid Pulse Liquid Pulse by Dskyz (DAFE) Trading Systems
Liquid Pulse is a trading algo built by Dskyz (DAFE) Trading Systems for futures markets like NQ1!, designed to snag high-probability trades with tight risk control. it fuses a confluence system—VWAP, MACD, ADX, volume, and liquidity sweeps—with a trade scoring setup, daily limits, and VIX pauses to dodge wild volatility. visuals include simple signals, VWAP bands, and a dashboard with stats.
Core Components for Liquid Pulse
Volume Sensitivity (volumeSensitivity) controls how much volume spikes matter for entries. options: 'Low', 'Medium', 'High' default: 'High' (catches small spikes, good for active markets) tweak it: 'Low' for calm markets, 'High' for chaos.
MACD Speed (macdSpeed) sets the MACD’s pace for momentum. options: 'Fast', 'Medium', 'Slow' default: 'Medium' (solid balance) tweak it: 'Fast' for scalping, 'Slow' for swings.
Daily Trade Limit (dailyTradeLimit) caps trades per day to keep risk in check. range: 1 to 30 default: 20 tweak it: 5-10 for safety, 20-30 for action.
Number of Contracts (numContracts) sets position size. range: 1 to 20 default: 4 tweak it: up for big accounts, down for small.
VIX Pause Level (vixPauseLevel) stops trading if VIX gets too hot. range: 10 to 80 default: 39.0 tweak it: 30 to avoid volatility, 50 to ride it.
Min Confluence Conditions (minConditions) sets how many signals must align. range: 1 to 5 default: 2 tweak it: 3-4 for strict, 1-2 for more trades.
Min Trade Score (Longs/Shorts) (minTradeScoreLongs/minTradeScoreShorts) filters trade quality. longs range: 0 to 100 default: 73 shorts range: 0 to 100 default: 75 tweak it: 80-90 for quality, 60-70 for volume.
Liquidity Sweep Strength (sweepStrength) gauges breakouts. range: 0.1 to 1.0 default: 0.5 tweak it: 0.7-1.0 for strong moves, 0.3-0.5 for small.
ADX Trend Threshold (adxTrendThreshold) confirms trends. range: 10 to 100 default: 41 tweak it: 40-50 for trends, 30-35 for weak ones.
ADX Chop Threshold (adxChopThreshold) avoids chop. range: 5 to 50 default: 20 tweak it: 15-20 to dodge chop, 25-30 to loosen.
VWAP Timeframe (vwapTimeframe) sets VWAP period. options: '15', '30', '60', '240', 'D' default: '60' (1-hour) tweak it: 60 for day, 240 for swing, D for long.
Take Profit Ticks (Longs/Shorts) (takeProfitTicksLongs/takeProfitTicksShorts) sets profit targets. longs range: 5 to 100 default: 25.0 shorts range: 5 to 100 default: 20.0 tweak it: 30-50 for trends, 10-20 for chop.
Max Profit Ticks (maxProfitTicks) caps max gain. range: 10 to 200 default: 60.0 tweak it: 80-100 for big moves, 40-60 for tight.
Min Profit Ticks to Trail (minProfitTicksTrail) triggers trailing. range: 1 to 50 default: 7.0 tweak it: 10-15 for big gains, 5-7 for quick locks.
Trailing Stop Ticks (trailTicks) sets trail distance. range: 1 to 50 default: 5.0 tweak it: 8-10 for room, 3-5 for fast locks.
Trailing Offset Ticks (trailOffsetTicks) sets trail offset. range: 1 to 20 default: 2.0 tweak it: 1-2 for tight, 5-10 for loose.
ATR Period (atrPeriod) measures volatility. range: 5 to 50 default: 9 tweak it: 14-20 for smooth, 5-9 for reactive.
Hardcoded Settings volLookback: 30 ('Low'), 20 ('Medium'), 11 ('High') volThreshold: 1.5 ('Low'), 1.8 ('Medium'), 2 ('High') swingLen: 5
Execution Logic Overview trades trigger when confluence conditions align, entering long or short with set position sizes. exits use dynamic take-profits, trailing stops after a profit threshold, hard stops via ATR, and a time stop after 100 bars.
Features Multi-Signal Confluence: needs VWAP, MACD, volume, sweeps, and ADX to line up.
Risk Control: ATR-based stops (capped 15 ticks), take-profits (scaled by volatility), and trails.
Market Filters: VIX pause, ADX trend/chop checks, volatility gates. Dashboard: shows scores, VIX, ADX, P/L, win %, streak.
Visuals Simple signals (green up triangles for longs, red down for shorts) and VWAP bands with glow. info table (bottom right) with MACD momentum. dashboard (top right) with stats.
Chart and Backtest:
NQ1! futures, 5-minute chart. works best in trending, volatile conditions. tweak inputs for other markets—test thoroughly.
Backtesting: NQ1! Frame: Jan 19, 2025, 09:00 — May 02, 2025, 16:00 Slippage: 3 Commission: $4.60
Fee Typical Range (per side, per contract)
CME Exchange $1.14 – $1.20
Clearing $0.10 – $0.30
NFA Regulatory $0.02
Firm/Broker Commis. $0.25 – $0.80 (retail prop)
TOTAL $1.60 – $2.30 per side
Round Turn: (enter+exit) = $3.20 – $4.60 per contract
Disclaimer this is for education only. past results don’t predict future wins. trading’s risky—only use money you can lose. backtest and validate before going live. (expect moderators to nitpick some random chart symbol rule—i’ll fix and repost if they pull it.)
About the Author Dskyz (DAFE) Trading Systems crafts killer trading algos. Liquid Pulse is pure research and grit, built for smart, bold trading. Use it with discipline. Use it with clarity. Trade smarter. I’ll keep dropping badass strategies ‘til i build a brand or someone signs me up.
2025 Created by Dskyz, powered by DAFE Trading Systems. Trade smart, trade bold.
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.
Fibonacci + TP/SL Strategy [Backtest]✅ Key Features Added and Adjusted:
Fibonacci Retracement Levels:
Automatically calculated based on the last 100 bars' high/low
Plotted levels: 0%, 23.6%, 38.2%, 50%, 61.8%, 78.6%, 100%
Extension targets: 161.8%, 261.8%, 423.6%
Buy/Sell Signal Logic:
Buy: Price is between 78.6% and 38.2% levels
Sell: Price is between 61.8% and 23.6% levels
Both depend on a can_trade time filter to avoid overtrading
ATR-based Stop-Loss:
Stop-loss dynamically adapts to market volatility:
SL = Entry - ATR * 1.5 (long)
SL = Entry + ATR * 1.5 (short)
Fixed Take-Profit:
Configurable via input: default is 4%
Can be changed in TradingView UI
Golden/Death Cross Indicator (Visual Only):
EMA 50 crossing EMA 200 plotted on chart:
Golden Cross = Buy signal (green triangle)
Death Cross = Sell signal (red triangle)
Weekly Profit Cap:
Prevents new trades if weekly profit exceeds 15%
Resets at the start of every week
Visual Elements:
All Fibonacci levels are plotted
Buy/Sell signals are labeled on the chart (BUY, SELL)
[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.
RSI Divergence Strategy - AliferCryptoStrategy Overview
The RSI Divergence Strategy is designed to identify potential reversals by detecting regular bullish and bearish divergences between price action and the Relative Strength Index (RSI). It automatically enters positions when a divergence is confirmed and manages risk with configurable stop-loss and take-profit levels.
Key Features
Automatic Divergence Detection: Scans for RSI pivot lows/highs vs. price pivots using user-defined lookback windows and bar ranges.
Dual SL/TP Methods:
- Swing-based: Stops placed a configurable percentage beyond the most recent swing high/low.
- ATR-based: Stops placed at a multiple of Average True Range, with a separate risk/reward multiplier.
Long and Short Entries: Buys on bullish divergences; sells short on bearish divergences.
Fully Customizable: Input groups for RSI, divergence, swing, ATR, and general SL/TP settings.
Visual Plotting: Marks divergences on chart and plots stop-loss (red) and take-profit (green) lines for active trades.
Alerts: Built-in alert conditions for both bullish and bearish RSI divergences.
Detailed Logic
RSI Calculation: Computes RSI of chosen source over a specified period.
Pivot Detection:
- Identifies RSI pivot lows/highs by scanning a lookback window to the left and right.
- Uses ta.barssince to ensure pivots are separated by a minimum/maximum number of bars.
Divergence Confirmation:
- Bullish: Price makes a lower low while RSI makes a higher low.
- Bearish: Price makes a higher high while RSI makes a lower high.
Entry:
- Opens a Long position when bullish divergence is true.
- Opens a Short position when bearish divergence is true.
Stop-Loss & Take-Profit:
- Swing Method: Computes the recent swing high/low then adjusts by a percentage margin.
- ATR Method: Uses the current ATR × multiplier applied to the entry price.
- Take-Profit: Calculated as entry price ± (risk × R/R ratio).
Exit Orders: Uses strategy.exit to place bracket orders (stop + limit) for both long and short positions.
Inputs and Configuration
RSI Settings: Length & price source for the RSI.
Divergence Settings: Pivot lookback parameters and valid bar ranges.
SL/TP Settings: Choice between Swing or ATR method.
Swing Settings: Swing lookback length, margin (%), and risk/reward ratio.
ATR Settings: ATR length, stop multiplier, and risk/reward ratio.
Usage Notes
Adjust the Pivot Lookback and Range values to suit the volatility and timeframe of your market.
Use higher ATR multipliers for wider stops in choppy conditions, or tighten swing margins in trending markets.
Backtest different R/R ratios to find the balance between win rate and reward.
Disclaimer
This script is for educational purposes only and does not constitute financial advice. Trading carries significant risk and you may lose more than your initial investment. Always conduct your own research and consider consulting a professional before making any trading decisions.
DCA OptimizedMonthly or Daily DCA strategy, with adjustable capital allocation percentages at the beginning of each quarter (January, April, July, and October) as well as for the other months of the year. Capital allocation settings are also customizable for daily DCA.
The strategy consists of performing annual DCA, taking profits at the end of the year, specifically on December 31st of each year, and repeating the process the following year.
If the year ends with an unrealized loss on the total invested, hold the assets until December 31st, until the asset is in profit.
Purchases are made on the first day of each month, at the daily opening price. The same applies to monthly or daily DCA (daily opening price).
By default, it is recommended to invest twice as much at the beginning of each quarter (January/April/July/October) compared to other months of the year. This allows you to optimize the average acquisition price over the long term, thus maximizing profits and reducing potential unrealized losses.
Example: January/April/July/October > 12.5% of the capital / Other months of the year > 6.25% of the capital (Total over 12 months = 100%)
You can select/unselect the months of the year in which to invest as you wish to optimize your periodic preferences.
Supertrend Hombrok BotSupertrend Hombrok Bot – Automated Trading Strategy for Dynamic Market Conditions
This trading strategy script has been developed to operate automatically based on detailed market conditions. It combines the popular Supertrend indicator, RSI (Relative Strength Index), Volume, and ATR (Average True Range) to determine the best entry and exit points while maintaining proper risk management.
Key Features:
Supertrend as the Base: Uses the Supertrend indicator to identify the market's trend direction, generating buy signals when the market is in an uptrend and sell signals when in a downtrend.
RSI Filter: The RSI is used to determine overbought and oversold conditions, helping to avoid entries in extreme market conditions. Entries are avoided when RSI > 70 (overbought) and RSI < 30 (oversold), reducing the risk of false movements.
Volume Filter: The strategy checks if the trading volume is above the average multiplied by a user-defined factor. This ensures that only significant movements, with higher liquidity, are considered.
Candle Body Size: The strategy filters only candles with a body large enough relative to the ATR (Average True Range), ensuring that the price movements on the chart have sufficient strength.
Risk Management: The bot is configured to operate with an adjustable Risk/Reward Ratio (R:R). This means that for each trade, both Take Profit (TP) and Stop Loss (SL) are adjusted based on the market's volatility as measured by the ATR.
Automatic Entries and Exits: The script automatically executes entries based on the specified conditions and exits with predefined Stop Loss and Take Profit levels, ensuring risk is controlled for each trade.
How It Works:
Buy Condition: Triggered when the market is in an uptrend (Supertrend), the volume is above the adjusted average, the candle body is strong enough, and the RSI is below the overbought level.
Sell Condition: Triggered when the market is in a downtrend (Supertrend), the volume is above the adjusted average, the candle body is strong enough, and the RSI is above the oversold level.
Alerts:
Buy and Sell Alerts are configured with detailed information, including Stop Loss and Take Profit values, allowing the user to receive notifications when trading conditions are met.
Capital Management:
The capital per trade can be adjusted based on account size and risk profile.
Important Note:
Always test before trading with real capital: While the strategy has been designed based on solid technical analysis methods, always perform tests in real-time market conditions with demo accounts before applying the bot in live trading.
Disclaimer: This script is a tool to assist in the trading process and does not guarantee profit. Past performance is not indicative of future results, and the trader is always responsible for their investment decisions.
Vinicius Setup ATR
Description:
This script is a strategy based on the Supertrend indicator combined with volume analysis, candle strength, and RSI. Its goal is to identify potential entry points for buy and sell trades based on technical criteria, without promising profitability or guaranteed results.
Script Components:
Supertrend: Used as the main trend compass. When the trend is positive (direction = 1), buy signals are considered; when negative (direction = -1), sell signals are considered.
Volume: Entries are only validated if the volume is above the average of the last 20 candles, adjusted with a 1.2 multiplier.
Candle Body: The candle body must be larger than a certain percentage of the ATR, ensuring sufficient strength and volatility.
RSI: Used as a filter to avoid trades in extreme overbought or oversold zones.
Support and Resistance: Identified based on simple pivots (5 periods before and after).
Customizable Parameters:
ATR Length and Multiplier: Controls the sensitivity of the Supertrend.
RSI Period: Adjusts the relative strength filter.
Minimum Volume and Candle Body: Settings to validate entry signals.
Entry Conditions:
Buy: Positive trend + strong candle + high volume + RSI below 70.
Sell: Negative trend + strong candle + high volume + RSI above 30.
Exit Conditions:
The trade is closed upon the appearance of an opposite signal.
Notes:
This is a technical system with no profit guarantees.
It is recommended to test with realistic capital values and parameters suited to your risk management.
The script is not optimized for specific profitability, but rather to support study and the construction of setups with objective criteria.
DEMA Trend Oscillator Strategy📌 Overview
The DEMA Trend Oscillator Strategy is a dynamic trend-following approach based on the Normalized DEMA Oscillator SD.
It adapts in real-time to market volatility with the goal of improving entry accuracy and optimizing risk management.
⚠️ This strategy is provided for educational and research purposes only.
Past performance does not guarantee future results.
🎯 Strategy Objectives
The main goal of this strategy is to respond quickly to sudden price movements and trend reversals,
by combining momentum-based signals with volatility filters.
It is designed to be user-friendly for traders of all experience levels.
✨ Key Features
Normalized DEMA Oscillator: A momentum indicator that normalizes DEMA values on a 0–100 scale, allowing intuitive identification of trend strength
Two-Bar Confirmation Filter: Requires two consecutive bullish or bearish candles to reduce noise and enhance entry reliability
ATR x2 Trailing Stop: In addition to fixed stop-loss levels, a trailing stop based on 2× ATR is used to maximize profits during strong trends
📊 Trading Rules
Long Entry:
Normalized DEMA > 55 (strong upward momentum)
Candle low is above the upper SD band
Two consecutive bullish candles appear
Short Entry:
Normalized DEMA < 45 (downward momentum)
Candle high is below the lower SD band
Two consecutive bearish candles appear
Exit Conditions:
Take-profit at a risk-reward ratio of 1.5
Stop-loss triggered if price breaks below (long) or above (short) the SD band
Trailing stop activated based on 2× ATR to secure and extend profits
💰 Risk Management Parameters
Symbol & Timeframe: Any (AUDUSD 5M example)
Account size (virtual): $3000
Commission: 0.4PIPS(0.0004)
Slippage: 2 pips
Risk per trade: 5%
Number of trades (backtest):534
All parameters can be adjusted based on broker specifications and individual trading profiles.
⚙️ Trading Parameters & Considerations
Indicator: Normalized DEMA Oscillator SD
Parameter settings:
DEMA Period (len_dema): 40
Base Length: 20
Long Threshold: 55
Short Threshold: 45
Risk-Reward Ratio: 1.5
ATR Multiplier for Trailing Stop: 2.0
🖼 Visual Support
The chart displays the following visual elements:
Upper and lower SD bands (±2 standard deviations)
Entry signals shown as directional arrows
🔧 Strategy Improvements & Uniqueness
This strategy is inspired by “Normalized DEMA Oscillator SD” by QuantEdgeB,
but introduces enhancements such as a two-bar confirmation filter and an ATR-based trailing stop.
Compared to conventional trend-following strategies, it offers superior noise filtering and profit optimization.
✅ Summary
The DEMA Trend Oscillator Strategy is a responsive and practical trend-following method
that combines momentum detection with adaptive risk management.
Its visual clarity and logical structure make it a powerful and repeatable tool
for traders seeking consistent performance in trending markets.
⚠️ Always apply appropriate risk management. This strategy is based on historical data and does not guarantee future results.
Dskyz (DAFE) AI Adaptive Regime - Beginners VersionDskyz (DAFE) AI Adaptive Regime - Pro: Revolutionizing Trading for All
Introduction
In the fast-paced world of financial markets, traders need tools that can keep up with ever-changing conditions while remaining accessible. The Dskyz (DAFE) AI Adaptive Regime - Pro is a groundbreaking TradingView strategy that delivers advanced, AI-driven trading capabilities to everyday traders. Available on TradingView (TradingView Scripts), this Pine Script strategy combines sophisticated market analysis with user-friendly features, making it a standout choice for both novice and experienced traders.
Core Functionality
The strategy is built to adapt to different market regimes—trending, ranging, volatile, or quiet—using a robust set of technical indicators, including:
Moving Averages (MA): Fast and slow EMAs to detect trend direction.
Average True Range (ATR): For dynamic stop-loss and volatility assessment.
Relative Strength Index (RSI) and MACD: Multi-timeframe confirmation of momentum and trend.
Average Directional Index (ADX): To identify trending markets.
Bollinger Bands: For assessing volatility and range conditions.
Candlestick Patterns: Recognizes patterns like bullish engulfing, hammer, and double bottoms, confirmed by volume spikes.
It generates buy and sell signals based on a scoring system that weighs these indicators, ensuring trades align with the current market environment. The strategy also includes dynamic risk management with ATR-based stops and trailing stops, as well as performance tracking to optimize future trades.
What Sets It Apart
The Dskyz (DAFE) AI Adaptive Regime - Pro distinguishes itself from other TradingView strategies through several unique features, which we compare to common alternatives below:
| Feature | Dskyz (DAFE) | Typical TradingView Strategies|
|---------|-------------|------------------------------------------------------------|
| Regime Detection | Automatically identifies and adapts to **four** market regimes | Often static or limited to trend/range detection |
| Multi‑Timeframe Analysis | Uses higher‑timeframe RSI/MACD for confirmation | Rarely incorporates multi‑timeframe data |
| Pattern Recognition | Detects candlestick patterns **with volume confirmation** | Limited or no pattern recognition |
| Dynamic Risk Management | ATR‑based stops and trailing stops | Often uses fixed stops or basic risk rules |
| Performance Tracking | Adjusts thresholds based on past performance | Typically static parameters |
| Beginner‑Friendly Presets | Aggressive, Conservative, Optimized profiles | Requires manual parameter tuning |
| Visual Cues | Color‑coded backgrounds for regimes | Basic or no visual aids |
The Dskyz strategy’s ability to integrate regime detection, multi-timeframe analysis, and user-friendly presets makes it uniquely versatile and accessible, addressing the needs of everyday traders who want professional-grade tools without the complexity.
-Key Features and Benefits
[Why It’s Ideal for Everyday Traders
⚡The Dskyz (DAFE) AI Adaptive Regime - Pro democratizes advanced trading by offering professional-grade tools in an accessible package. Unlike many TradingView strategies that require deep technical knowledge or fail in changing market conditions, this strategy simplifies complex analysis while maintaining robustness. Its presets and visual aids make it easy for beginners to start, while its adaptive features and performance tracking appeal to advanced traders seeking an edge.
🔄Limitations and Considerations
Market Dependency: Performance varies by market and timeframe. Backtesting is essential to ensure compatibility with your trading style.
Learning Curve: While presets simplify use, understanding regimes and indicators enhances effectiveness.
No Guaranteed Profits: Like all strategies, success depends on market conditions and proper execution. The Reddit discussion highlights skepticism about TradingView strategies’ universal success (Reddit Discussion).
Instrument Specificity: Optimized for futures (e.g., ES, NQ) due to fixed tick values. Test on other instruments like stocks or forex to verify compatibility.
📌Conclusion
The Dskyz (DAFE) AI Adaptive Regime - Pro is a revolutionary TradingView strategy that empowers everyday traders with advanced, AI-driven tools. Its ability to adapt to market regimes, confirm signals across timeframes, and manage risk dynamically. sets it apart from typical strategies. By offering beginner-friendly presets and visual cues, it makes sophisticated trading accessible without sacrificing power. Whether you’re a novice looking to trade smarter or a pro seeking a competitive edge, this strategy is your ticket to mastering the markets. Add it to your chart, backtest it, and join the elite traders leveraging AI to dominate. Trade like a boss today! 🚀
Use it with discipline. Use it with clarity. Trade smarter.
**I will continue to release incredible strategies and indicators until I turn this into a brand or until someone offers me a contract.
-Dskyz
Moving Average Shift WaveTrend StrategyMoving Average Shift WaveTrend Strategy
🧭 Overview
The Moving Average Shift WaveTrend Strategy is a trend-following and momentum-based trading system designed to be overlayed on TradingView charts. It executes trades based on the confluence of multiple technical conditions—volatility, session timing, trend direction, and oscillator momentum—to deliver logical and systematic trade entries and exits.
🎯 Strategy Objectives
Enter trades aligned with the prevailing long-term trend
Exit trades on confirmed momentum reversals
Avoid false signals using session timing and volatility filters
Apply structured risk management with automatic TP, SL, and trailing stops
⚙️ Key Features
Selectable MA types: SMA, EMA, SMMA (RMA), WMA, VWMA
Dual-filter logic using a custom oscillator and moving averages
Session and volatility filters to eliminate low-quality setups
Trailing stop, configurable Take Profit / Stop Loss logic
“In-wave flag” prevents overtrading within the same trend wave
Visual clarity with color-shifting candles and entry/exit markers
📈 Trading Rules
✅ Long Entry Conditions:
Price is above the selected MA
Oscillator is positive and rising
200-period EMA indicates an uptrend
ATR exceeds its median value (sufficient volatility)
Entry occurs between 09:00–17:00 (exchange time)
Not currently in an active wave
🔻 Short Entry Conditions:
Price is below the selected MA
Oscillator is negative and falling
200-period EMA indicates a downtrend
All other long-entry conditions are inverted
❌ Exit Conditions:
Take Profit or Stop Loss is hit
Opposing signals from oscillator and MA
Trailing stop is triggered
🛡️ Risk Management Parameters
Pair: ETH/USD
Timeframe: 4H
Starting Capital: $3,000
Commission: 0.02%
Slippage: 2 pips
Risk per Trade: 2% of account equity (adjustable)
Total Trades: 224
Backtest Period: May 24, 2016 — April 7, 2025
Note: Risk parameters are fully customizable to suit your trading style and broker conditions.
🔧 Trading Parameters & Filters
Time Filter: Trades allowed only between 09:00–17:00 (exchange time)
Volatility Filter: ATR must be above its median value
Trend Filter: Long-term 200-period EMA
📊 Technical Settings
Moving Average
Type: SMA
Length: 40
Source: hl2
Oscillator
Length: 15
Threshold: 0.5
Risk Management
Take Profit: 1.5%
Stop Loss: 1.0%
Trailing Stop: 1.0%
👁️ Visual Support
MA and oscillator color changes indicate directional bias
Clear chart markers show entry and exit points
Trailing stops and risk controls are transparently managed
🚀 Strategy Improvements & Uniqueness
In-wave flag avoids repeated entries within the same trend phase
Filtering based on time, volatility, and trend ensures higher-quality trades
Dynamic high/low tracking allows precise trailing stop placement
Fully rule-based execution reduces emotional decision-making
💡 Inspirations & Attribution
This strategy is inspired by the excellent concept from:
ChartPrime – “Moving Average Shift”
It expands on the original idea with advanced trade filters and trailing logic.
Source reference:
📌 Summary
The Moving Average Shift WaveTrend Strategy offers a rule-based, reliable approach to trend trading. By combining trend and momentum filters with robust risk controls, it provides a consistent framework suitable for various market conditions and trading styles.
⚠️ Disclaimer
This script is for educational purposes only. Trading involves risk. Always use proper backtesting and risk evaluation before applying in live markets.
Dskyz (DAFE) MAtrix with ATR-Powered Precision Dskyz (DAFE) MAtrix with ATR-Powered Precision
This cutting‐edge futures trading strategy built to thrive in rapidly changing market conditions. Developed for high-frequency futures trading on instruments such as the CME Mini MNQ, this strategy leverages a matrix of sophisticated moving averages combined with ATR-based filters to pinpoint high-probability entries and exits. Its unique combination of adaptable technical indicators and multi-timeframe trend filtering sets it apart from standard strategies, providing enhanced precision and dynamic responsiveness.
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Core Functional Components
1. Advanced Moving Averages
A distinguishing feature of the DAFE strategy is its robust, multi-choice moving averages (MAs). Clients can choose from a wide array of MAs—each with specific strengths—in order to fine-tune their trading signals. The code includes user-defined functions for the following MAs:
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Hull Moving Average (HMA):
The hma(src, len) function calculates the HMA by using weighted moving averages (WMAs) to reduce lag considerably while smoothing price data. This function computes an intermediate WMA of half the specified length, then a full-length WMA, and finally applies a further WMA over the square root of the length. This design allows for rapid adaptation to price changes without the typical delays of traditional moving averages.
Triple Exponential Moving Average (TEMA):
Implemented via tema(src, len), TEMA uses three consecutive exponential moving averages (EMAs) to effectively cancel out lag and capture price momentum. The final formula—3 * (ema1 - ema2) + ema3—produces a highly responsive indicator that filters out short-term noise.
Double Exponential Moving Average (DEMA):
Through the dema(src, len) function, DEMA calculates an EMA and then a second EMA on top of it. Its simplified formula of 2 * ema1 - ema2 provides a smoother curve than a single EMA while maintaining enhanced responsiveness.
Volume Weighted Moving Average (VWMA):
With vwma(src, len), this MA accounts for trading volume by weighting the price, thereby offering a more contextual picture of market activity. This is crucial when volume spikes indicate significant moves.
Zero Lag EMA (ZLEMA):
The zlema(src, len) function applies a correction to reduce the inherent lag found in EMAs. By subtracting a calculated lag (based on half the moving average window), ZLEMA is exceptionally attuned to recent price movements.
Arnaud Legoux Moving Average (ALMA):
The alma(src, len, offset, sigma) function introduces ALMA—a type of moving average designed to be less affected by outliers. With parameters for offset and sigma, it allows customization of the degree to which the MA reacts to market noise.
Kaufman Adaptive Moving Average (KAMA):
The custom kama(src, len) function is noteworthy for its adaptive nature. It computes an efficiency ratio by comparing price change against volatility, then dynamically adjusts its smoothing constant. This results in an MA that quickly responds during trending periods while remaining smoothed during consolidation.
Each of these functions—integrated into the strategy—is selectable by the trader (via the fastMAType and slowMAType inputs). This flexibility permits the tailored application of the MA most suited to current market dynamics and individual risk management preferences.
2. ATR-Based Filters and Risk Controls
ATR Calculation and Volatility Filter:
The strategy computes the Average True Range (ATR) over a user-defined period (atrPeriod). ATR is then used to derive both:
Volatility Assessment: Expressed as a ratio of ATR to closing price, ensuring that trades are taken only when volatility remains within a safe, predefined threshold (volatilityThreshold).
ATR-Based Entry Filters: Implemented as atrFilterLong and atrFilterShort, these conditions ensure that for long entries the price is sufficiently above the slow MA and vice versa for shorts. This acts as an additional confirmation filter.
Dynamic Exit Management:
The exit logic employs a dual approach:
Fixed Stop and Profit Target: Stops and targets are set at multiples of ATR (fixedStopMultiplier and profitTargetATRMult), helping manage risk in volatile markets.
Trailing Stop Adjustments: A trailing stop is calculated using the ATR multiplied by a user-defined offset (trailOffset), which captures additional profits as the trade moves favorably while protecting against reversals.
3. Multi-Timeframe Trend Filtering
The strategy enhances its signal reliability by leveraging a secondary, higher timeframe analysis:
15-Minute Trend Analysis:
By retrieving 15-minute moving averages (fastMA15m and slowMA15m) via request.security, the strategy determines the broader market trend. This secondary filter (enabled or disabled through useTrendFilter) ensures that entries are aligned with the prevailing market direction, thereby reducing the incidence of false signals.
4. Signal and Execution Logic
Combined MA Alignment:
The entry conditions are based primarily on the alignment of the fast and slow MAs. A long condition is triggered when the current price is above both MAs and the fast MA is above the slow MA—complemented by the ATR filter and volume conditions. The reverse applies for a short condition.
Volume and Time Window Validation:
Trades are permitted only if the current volume exceeds a minimum (minVolume) and the current hour falls within the predefined trading window (tradingStartHour to tradingEndHour). An additional volume spike check (comparing current volume to a moving average of past volumes) further filters for optimal market conditions.
Comprehensive Order Execution:
The strategy utilizes flexible order execution functions that allow pyramiding (up to 10 positions), ensuring that it can scale into positions as favorable conditions persist. The use of both market entries and automated exits (with profit targets, stop-losses, and trailing stops) ensures that risk is managed at every step.
5. Integrated Dashboard and Metrics
For transparency and real-time analysis, the strategy includes:
On-Chart Visualizations:
Both fast and slow MAs are plotted on the chart, making it easy to see the market’s technical foundation.
Dynamic Metrics Dashboard:
A built-in table displays crucial performance statistics—including current profit/loss, equity, ATR (both raw and as a percentage), and the percentage gap between the moving averages. These metrics offer immediate insight into the health and performance of the strategy.
Input Parameters: Detailed Breakdown
Every input is meticulously designed to offer granular control:
Fast & Slow Lengths:
Determine the window size for the fast and slow moving averages. Smaller values yield more sensitivity, while larger values provide a smoother, delayed response.
Fast/Slow MA Types:
Choose the type of moving average for fast and slow signals. The versatility—from basic SMA and EMA to more complex ones like HMA, TEMA, ZLEMA, ALMA, and KAMA—allows customization to fit different market scenarios.
ATR Parameters:
atrPeriod and atrMultiplier shape the volatility assessment, directly affecting entry filters and risk management through stop-loss and profit target levels.
Trend and Volume Filters:
Inputs such as useTrendFilter, minVolume, and the volume spike condition help confirm that a trade occurs in active, trending markets rather than during periods of low liquidity or market noise.
Trading Hours:
Restricting trade execution to specific hours (tradingStartHour and tradingEndHour) helps avoid illiquid or choppy markets outside of prime trading sessions.
Exit Strategies:
Parameters like trailOffset, profitTargetATRMult, and fixedStopMultiplier provide multiple layers of risk management and profit protection by tailoring how exits are generated relative to current market conditions.
Pyramiding and Fixed Trade Quantity:
The strategy supports multiple entries within a trend (up to 10 positions) and sets a predefined trade quantity (fixedQuantity) to maintain consistent exposure and risk per trade.
Dashboard Controls:
The resetDashboard input allows for on-the-fly resetting of performance metrics, keeping the strategy’s performance dashboard accurate and up-to-date.
Why This Strategy is Truly Exceptional
Multi-Faceted Adaptability:
The ability to switch seamlessly between various moving average types—each suited to particular market conditions—enables the strategy to adapt dynamically. This is a testament to the high level of coding sophistication and market insight infused within the system.
Robust Risk Management:
The integration of ATR-based stops, profit targets, and trailing stops ensures that every trade is executed with well-defined risk parameters. The system is designed to mitigate unexpected market swings while optimizing profit capture.
Comprehensive Market Filtering:
By combining moving average crossovers with volume analysis, volatility thresholds, and multi-timeframe trend filters, the strategy only enters trades under the most favorable conditions. This multi-layered filtering reduces noise and enhances signal quality.
-Final Thoughts-
The Dskyz Adaptive Futures Elite (DAFE) MAtrix with ATR-Powered Precision strategy is not just another trading algorithm—it is a multi-dimensional, fully customizable system built on advanced technical principles and sophisticated risk management techniques. Every function and input parameter has been carefully engineered to provide traders with a system that is both powerful and transparent.
For clients seeking a state-of-the-art trading solution that adapts dynamically to market conditions while maintaining strict discipline in risk management, this strategy truly stands in a class of its own.
****Please show support if you enjoyed this strategy. I'll have more coming out in the near future!!
-Dskyz
Caution
DAFE is experimental, not a profit guarantee. Futures trading risks significant losses due to leverage. Backtest, simulate, and monitor actively before live use. All trading decisions are your responsibility.
