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光速量化-头皮策略v1.1Version: Unlimited trial version.
Principle: RSI and moving average complement each other, taking a bite of both oscillation and trend.
Disadvantage: High drawdown.
Disclaimer: The scalp strategy v1.1 of Lightspeed Quantification is designed for trial users. Those who use this strategy are responsible for their own assets, and any losses incurred are not the responsibility of the author.
版本:无期限试用版。
原理:RSI与均线配合,震荡与趋势都吃一口。
缺点:回撤高。
声明:光速量化的头皮策略v1.1是面向试用者体验的,使用该策略的人请为自己的资产负责,产生任何损失与作者无关。
The Barking Rat PercentilesPercentile Reversion with Multi-Layered Smoothing
The Barking Rat Percentiles is a multi-tiered reversion strategy based on fixed percentage movements away from the mean, designed to capture price extremes through a structured, practical approach. It combines statistically derived percentile bands, RSI momentum filtering, and ATR-driven exits to identify potential turning points while managing opportunity with precision. The aim is to isolate high-quality reversal opportunities at progressively deeper extremes while avoiding noise and low-conviction setups.
At its core, the strategy measures the current market position relative to long-term percentile thresholds. When price moves significantly beyond these smoothed levels and momentum shows signs of exhaustion, staged entries are triggered. Exits are managed using independent ATR-based take profit and stop loss logic to adapt to varying volatility conditions.
🧠 Core Logic: Tiered Extremes & Structured Management
This strategy is intentionally methodical, layering multiple thresholds and validation checks before highlighting potential setups. By combining percentile-based extremes with momentum confirmation and adaptive trade management, it offers a disciplined and repeatable framework for mean reversion trading.
1. Percentile Thresholds as the Primary Framework
The script calculates the highest high and lowest low over a long lookback period of more than 1000 candles to define the overall price range. It then derives upper and lower percentile thresholds to determine extreme price levels. These thresholds are smoothed using a simple moving average to filter out short-term noise, ensuring that only statistically significant deviations from the mean are considered for potential trades.
2. Multi-Tier Entry Levels
Based on the percentile distance away from the mean, the script plots and references five discrete trigger levels beyond the primary thresholds for both long and short positions. Each tier represents progressively deeper extremes, typically 1–3% beyond the smoothed threshold, balancing the benefits of early entries with the safety of more confirmed extremes. Custom logic ensures only one signal is generated per threshold level, avoiding duplicate entries in the same zone.
3. RSI Momentum Filter
A 14-period RSI filter is applied to prevent entering trades against strong momentum. Long trades are only triggered when RSI falls below 30 (oversold), and short trades only when RSI rises above 70 (overbought). This helps align entries with potential exhaustion points, reducing the risk of entering prematurely into a strong ongoing trend.
4. ATR-Based Trade Management
For each trade sequence, the strategy will exit on the first exit condition met: either the take profit (TP) or the stop loss (SL). Because the TP uses a smaller ATR multiplier, it’s generally closer to the entry price, so most trades will hit the TP before reaching the SL. The SL is intentionally set with a larger ATR multiplier to give the trade room to develop, acting as a protective fallback rather than a frequent exit.
So in practice, you’ll usually see the TP executed for a trade, and the SL only triggers in cases where price moves further against the position than expected.
5. Position Reset Logic
Once price returns to the smoothed threshold region, all entry tiers in that direction are reset. This allows the system to prepare for new opportunities if the market revisits extreme levels, without triggering duplicate trades at the same threshold.
Why These Parameters Were Chosen
Multi-tier thresholds ensure that only meaningful extremes are acted upon, while the long-range SMA provides historical context and filters out noise. The staged entry logic per level balances the desire for early participation with the discipline of risk management. ATR-based TP and SL levels adapt to changing volatility, while the RSI filter improves timing by aligning trades with potential exhaustion points. Together, these elements create a balanced, structured, and repeatable approach to mean reversion trading.
📈 Chart Visuals: Clear & Intuitive
Green “▲” below a candle: Potential long entry
Red “▼” above a candle: Potential short entry
Blue “✔️”: Exit when ATR take profit is hit
Orange “✘”: Exit when ATR stop loss is hit
Tier threshold lines (smoothed upper/lower bounds)
🔔Alerts: Stay Notified Without Watching
The strategy supports real-time alerts on candle close, ensuring that signals are only triggered once fully confirmed.
You must manually set up alerts within your TradingView account. Once configured, you’ll be able to set up one alert per instrument. This one alert covers all relevant signals and exits — ideal for hands-free monitoring.
⚙️Strategy report properties
Position size: 25% equity per trade
Initial capital: 10,000.00 USDT
Pyramiding: 10 entries per direction
Slippage: 2 ticks
Commission: 0.055% per side
Backtest timeframe: 1-minute
Backtest instrument: SOLUSDT
Backtesting range: Jul 28, 2025 — Aug 14, 2025
Note on Sample Size:
You’ll notice the report displays fewer than the ideal 100 trades in the strategy report above. This is intentional. The goal of the script is to isolate high-quality, short-term reversal opportunities while filtering out low-conviction setups. This means that the Barking Rat Percentiles strategy is ultra-selective, filtering out over 90% of market noise by enforcing multiple validation layers. The brief timeframe shown in the strategy report here illustrates its filtering logic over a short window — not its full capabilities. As a result, even on lower timeframes like the 1-minute chart, signals are deliberately sparse — each one must pass all criteria before triggering.
For a larger dataset:
Once the strategy is applied to your chart, users are encouraged to expand the lookback range or apply the strategy to other volatile pairs to view a full sample.
💡Why 25% Equity Per Trade?
While it's always best to size positions based on personal risk tolerance, we defaulted to 25% equity per trade in the backtesting data — and here’s why:
Backtests using this sizing show manageable drawdowns even under volatile periods
The strategy generates a sizeable number of trades, reducing reliance on a single outcome
Combined with conservative filters, the 25% setting offers a balance between aggression and control
Users are strongly encouraged to customize this to suit their risk profile.
🔍 What Makes This Strategy Unique?
Multi-Tier Percentile Triggers – Instead of relying on a single overbought/oversold zone, this strategy uses five distinct entry tiers per direction, allowing for staged, precision entries at progressively deeper extremes.
Long-Term Percentile Smoothing – By calculating extremes over a 1000+ candle range and smoothing them with a moving average, the strategy focuses only on statistically significant deviations.
Custom One-Signal-Per-Tier Logic – Prevents duplicate trades at the same threshold level, reducing overtrading and noise.
Dual ATR Exit System – Independent TP and SL levels adapt to volatility. TP uses a smaller ATR multiplier for realistic, achievable exits and generally executes first, while the SL has a larger ATR multiplier to provide protective breathing room if the trade moves further against the position.
Momentum-Aware Filtering – A 14-period RSI filter ensures trades are only taken when momentum is likely exhausted, avoiding entries into strong trends.
Automatic Position Reset – Once price normalizes, tiers reset, allowing for fresh entries without interference from previous trades.
No Wick Strategy (No-wick candles) — by Sh1n1gam1**No Wick Strategy - Momentum Trading System**
This strategy identifies and trades "no wick" or "minimal wick" candles, which often indicate strong directional momentum and conviction in the market.
**STRATEGY CONCEPT:**
The No Wick Strategy capitalizes on candles that show strong directional commitment - bullish candles with little to no bottom wick (buyers in control from the start) and bearish candles with little to no top wick (sellers dominating from the open).
**HOW IT WORKS:**
📈 **LONG ENTRIES:**
- Identifies bullish candles with minimal/no bottom wick
- Places buy limit order slightly below the signal candle's open
- Enters only during specified trading session
📉 **SHORT ENTRIES:**
- Identifies bearish candles with minimal/no top wick
- Places sell limit order slightly above the signal candle's close
- Enters only during specified trading session
**KEY FEATURES:**
✅ Customizable trading session (New York timezone)
✅ Flexible wick threshold (0% for strict, up to X% for flexibility)
✅ ATR-based stop loss for dynamic risk management
✅ Configurable risk-reward ratio via TP multiplier
✅ Auto-cancellation of unfilled orders after X bars
✅ Body size filters (minimum and maximum)
✅ Visual signals and pending order levels
✅ Position status display
**RISK MANAGEMENT:**
- Stop Loss: Based on ATR multiplier
- Take Profit: Multiple of stop loss distance
- One position at a time
- No pyramiding or position flipping
**RECOMMENDED TIMEFRAMES:**
- M1 and M5 for scalping
- M15 and H1 for day trading
- H4 and Daily for swing trading
**MARKETS:**
Suitable for forex pairs, indices (NQ, ES), commodities, and liquid stocks.
**DEFAULT SETTINGS:**
- Trading Session: 09:30-11:00 ET (NY morning session)
- ATR SL Multiplier: 1.5
- TP Multiplier: 2.0 (2:1 RR ratio)
- Wick Threshold: 5%
- Order Cancellation: 5 bars
**TIPS FOR OPTIMIZATION:**
1. Adjust trading session to match your market's most active hours
2. Test different wick thresholds (0-10%) based on market volatility
3. Optimize body size filters for your specific instrument
4. Backtest different ATR multipliers for your risk tolerance
5. Consider market conditions - works best in trending markets
**IMPORTANT NOTES:**
- Uses limit orders for better entry prices
- Does not close opposing positions (no position flipping)
- Respects trading session boundaries strictly
- All times are in America/New_York timezone
**AUTHOR:** Sh1n1gam1
**VERSION:** 1.0
**SUPPORT:** Comments and suggestions welcome!
Happy Trading! 📊
Breakout asia USD/CHF1 — Customizable Parameters
sess1 & sess2: The two time ranges that define the Asian session (e.g., 20:00–23:59 and 00:00–08:00).
Important: format is HHMM-HHMM.
rr: The risk/reward ratio (default = 3.0, meaning TP = 3× risk size).
onePerSess: Toggle to allow only one trade per Asian session or multiple.
bufTicks: Extra margin for the SL beyond the signal candle.
2 — Detecting the Asian Session
The script checks if the candle’s time is inside the first range (sess1) or inside the second range (sess2).
While inside the Asian session, it updates the current high and low.
When the session ends, it locks in these levels as rangeHigh and rangeLow.
3 — Step 1: Detecting the Initial Breakout
Bullish breakout → close above rangeHigh → flag breakoutUp is set to true.
Bearish breakout → close below rangeLow → flag breakoutDown is set to true.
No trade yet — this is just the breakout signal.
4 — Step 2: Waiting for the Retest
If a bullish breakout occurred, wait for the price to return to or slightly below rangeHigh and then close back above it.
If a bearish breakout occurred, wait for the price to return to or slightly above rangeLow and then close back below it.
5 — Entry & Exit
When the retest is confirmed:
strategy.entry() is triggered.
SL = behind the retest confirmation candle (with optional bufTicks margin).
TP = entry price ± RR × risk size.
If onePerSess is enabled, no further trades happen until the next Asian session.
6 — Chart Display
Green line = locked Asian session high.
Red line = locked Asian session low.
Light blue background = active Asian session hours.
Trade entries are shown on the chart when retests occur.
Open Range Breakout Strategy With Multi TakeProfitHello everyone,
For a while, I’ve been wanting to develop new scripts, but I couldn’t decide what to create. Eventually, I came up with the idea of coding traditional and well-known trading strategies—while adding modern features such as multi–take profit options. For the first strategy in this series, I chose the Open Range Strategy .
For those unfamiliar with it, the Open Range Strategy is a trading approach where you define a specific time period at the beginning of a trading session—such as the first 15 minutes, 30 minutes, or 1 hour—and mark the highest and lowest prices within that range. These levels then act as reference points for potential breakouts: if the price breaks above the range, it may signal a long entry; if it breaks below, it may indicate a short entry. This method is popular among day traders for capturing early momentum in the market.
Since this strategy is generally used as an intraday strategy , I added a Trade Session feature. This allows you to define the exact time window during which trades can be opened. Once the session ends, all positions are automatically closed, ensuring trades remain within your chosen intraday period.
Even though it’s a relatively simple concept, I’ve come across many different variations of it. That’s why I created a highly customizable project. Under the Session Settings, you can select the time window you want to define as your range. Whether it’s the first 15-minute candle or the entire first hour, the choice is entirely yours.
For stop-loss placement, there are two different options:
Middle of the Range – The stop loss is placed at the midpoint between the high and low of the defined range, offering a balanced buffer for both bullish and bearish setups.
Top/Bottom of the Range – The stop loss is placed just beyond the range’s high for short trades or just below the range’s low for long trades, providing a more conservative risk approach.
I’ve always been a big fan of the multi take-profit feature, so I added two different take-profit targets to this project. Take profits are calculated based on a Risk-to-Reward Ratio, which you can adjust in the settings. You can also set different position sizes for each target, allowing you to scale out of trades in a way that suits your strategy.
The result is a flexible, user-friendly strategy script that brings together a classic approach with modern risk management tools—ready to be tailored to your trading style
Backtest - Strategy Builder [AlgoAlpha]🟠 OVERVIEW
This script by AlgoAlpha is a modular Strategy Builder designed to let traders test custom trade entry and exit logic on TradingView without writing their own Pine code. It acts as a framework where users can connect multiple external signals, chain them in sequences, and run backtests with built-in leverage, margin, and risk controls. Its main strength is flexibility—you can define up to five sequential steps for entry and exit conditions on both long and short sides, with logic connectors (AND/OR) controlling how conditions combine. This lets you test complex multi-step confirmation workflows in a controlled, visual backtesting environment.
🟠 CONCEPTS
The system works by linking external signals —these can be values from other indicators, and/or custom sources—to conditional checks like “greater than,” “less than,” or “crossover.” You can stack these checks into steps , where all conditions in a step must pass before the sequence moves to the next. This creates a chain of logic that must be completed before a trade triggers. On execution, the strategy sizes positions according to your chosen leverage mode ( Cross or Isolated ) and allocation method ( Percent of equity or absolute USD value]). Liquidation prices are simulated for both modes, allowing realistic margin behaviour in testing. The script also tracks performance metrics like Sharpe, Sortino, profit factor, drawdown, and win rate in real time.
🟠 FEATURES
Up to 5 sequential steps for both long and short entries, each with multiple conditions linked by AND/OR logic.
Two leverage modes ( Cross and Isolated ) with independent long/short leverage multipliers.
Separate multi-step exit triggers for longs and shorts, with optional TP/SL levels or opposite-side triggers for flipping positions.
Position sizing by equity percent or fixed USD amount, applied before leverage.
Realistic liquidation price simulation for margin testing.
Built-in trade gating and validation—prevents trades if configuration rules aren’t met (e.g., no exit defined for an active side).
Full performance dashboard table showing live strategy status, warnings, and metrics.
Configurable bar coloring based on position side and TP/SL level drawing on chart.
Integration with TradingView's strategy backtester, allowing users to view more detailed metrics and test the strategy over custom time horizons.
🟠 USAGE
Add the strategy to your chart. In the settings, under Master Settings , enable longs/shorts, select leverage mode, set leverage multipliers, and define position sizing. Then, configure your Long Trigger and Short Trigger groups: turn on conditions, pick which external signal they reference, choose the comparison type, and assign them to a sequence step. For exits, use the corresponding Exit Long Trigger and Exit Short Trigger groups, with the option to link exits to opposite-side entries for auto-flips. You can also enable TP and/or SL exits with custom sources for the TP/SL levels. Once set, the strategy will simulate trades, show performance stats in the on-chart table, and highlight any configuration issues before execution. This makes it suitable for testing both simple single-signal systems and complex, multi-filtered strategies under realistic leverage and margin constraints.
🟠 EXAMPLE
The backtester on its own does not contain any indicator calculation; it requires input from external indicators to function. In this example, we'll be using AlgoAlpha's Smart Signals Assistant indicator to demonstrate how to build a strategy using this script.
We first define the conditions beforehand:
Entry :
Longs – SSA Bullish signal (strong OR weak)
Shorts – SSA Bearish signal (strong OR weak)
Exit
Longs/Shorts: (TP/SL hit OR opposing signal fires)
Other Parameters (⚠️Example only, tune this based on proper risk management and settings)
Long Leverage: default (3x)
Short Leverage: default (3x)
Position Size: default (10% of equity)
Steps
Load up the required indicators (in this example, the Smart Signals Assistant).
Ensure the required plots are being output by the indicator properly (signals and TP/SL levels are being plotted).
Open the Strategy Builder settings and scroll down to "CONDITION SETUP"; input the signals from the external indicator.
Configure the exit conditions, add in the TP/SL levels from the external indicator, and add an additional exit condition → {{Opposite Direction}} Entry Trigger.
After configuring the entry and exit conditions, the strategy should now be running. You can view information on the strategy in TradingView's backtesting report and also in the Strategy Builder's information table (default top right corner).
It is important to note that the strategy provided above is just an example, and the complexity of possible strategies stretches beyond what was shown in this short demonstration. Always incorporate proper risk management and ensure thorough testing before trading with live capital.
Spread Mean Reversion Strategy [SciQua]╭───────────────────────────────────────╮
Spread Mean Reversion Strategy
╰───────────────────────────────────────╯
This invite-only futures spread strategy applies a statistical mean reversion framework, executing limit orders exclusively at calculated Z-score thresholds for precise, rules-based entries and exits. It is designed for CME-style spreads and synthetic instruments with well-defined reversion tendencies.
╭────────────╮
Core Concept
╰────────────╯
The strategy calculates a rolling mean and standard deviation of a chosen spread or synthetic price series, then computes the Z-score to measure deviation from the mean in standard deviation units.
Long entries trigger when Z crosses upward through a negative entry threshold (`-devEnter`). A buy limit is placed exactly at the price corresponding to that Z-score, optionally offset by a configurable tick amount.
Short entries trigger when Z crosses downward through a positive entry threshold (`+devEnter`). A sell limit is placed at the corresponding threshold price, also with optional offset.
Exits use the same threshold method, with an independent `Close Limit Offset` to fine-tune exit placement.
╭────────────╮
Key Features
╰────────────╯
Persistence filter – Requires the Z-score to remain beyond threshold for a configurable number of bars before entry.
Cooldown after exits – Prevents immediate re-entry to reduce over-trading.
Daily and weekend flattening – Force-flattens positions via limit orders before exchange maintenance breaks and weekend closes.
Auto-rollover detection with persistence – Detects when the second contract month’s daily volume exceeds the first for a set number of days, then blocks new entries (optional).
Configurable tick offsets – Independently adjust entry and exit levels relative to threshold prices.
Minimum spread width filter – Blocks trades when long/short entry thresholds are too close together.
Contract multiplier override – Allows correct sizing for synthetic symbols where `syminfo.pointvalue` is incorrect or missing.
Limit-only execution – All entries, exits, and forced-flat actions are executed with limit orders for price control.
╭────────────────────╮
Entry Blocking Rules
╰────────────────────╯
New trades are blocked:
During daily maintenance break pre-windows
During weekend close pre-windows
After rollover triggers, if `Block After Roll` is enabled
╭────────────────────────╮
Intended Markets & Usage
╰────────────────────────╯
Built for futures spreads and synthetic instruments , including calendar spreads.
Performs best in markets with clear seasonal or statistical mean-reverting tendencies.
Not designed for strongly trending, non-reverting markets.
╭──────────────────────────╮
Risk Management & Defaults
╰──────────────────────────╯
Fixed default position size of 1 contract (qty calc function available for customization).
Realistic commission and slippage assumptions pre-set.
Pyramiding disabled by default.
Default Z-score levels: Entry at ±2.0, Exit at ±0.5.
Separate tick offset controls for entries and exits.
Note: This strategy is for research and backtesting purposes only. Past performance does not guarantee future results. All use is subject to explicit written permission from the author.
Market Open Impulse [LuciTech]Market Open Impulse Strategy
The Market Open Impulse Strategy is designed to capture significant price movements that occur at market open (2:30 PM UK time). This strategy identifies impulsive candles with high volatility and enters trades based on the direction and strength of the initial market reaction.
How It Works:
The strategy activates exclusively at 2:30 PM UK time during market open sessions. It uses ATR-based volatility filtering to identify impulsive candles that exceed a configurable multiplier (default 1.5x ATR). Long entries are triggered when an impulsive candle closes above its midpoint and above the opening price, while short entries occur when an impulsive candle closes below its midpoint and below the opening price.
Risk management is handled through precise stop loss placement at the opposite extreme of the impulse candle (high for short positions, low for long positions). Take profit levels are calculated using a configurable risk-reward ratio with a default setting of 3:1. Position sizing is automatically calculated based on the percentage risk per trade, and an optional breakeven feature can move the stop loss to the entry price at specified profit levels.
The strategy incorporates time-based filtering to ensure trades only occur during the specified market open window. Visual indicators highlight qualifying impulsive candles and plot all entry and exit levels for clear trade management. The system offers flexible risk management with customizable risk percentage, risk-reward ratios, and breakeven settings, along with multiple stop loss calculation methods including both ATR-based and candle-based options.
Key Parameters:
Market open timing is fully configurable through hour and minute settings for strategy activation. The impulse ATR multiple sets the minimum volatility threshold required for trade qualification, with visual highlighting available for qualifying setups. Risk management parameters include the percentage of account equity to risk per trade, target profit multiples relative to initial risk, and the profit level threshold for breakeven stop loss adjustment. Users can choose between ATR-based or candle-based stop loss calculation methods and adjust technical parameters for volatility calculation including ATR length and smoothing methods.
Applications:
This strategy is particularly effective for trading market open volatility and momentum, capturing institutional order flow during key timing windows, executing short-term swing trades on significant price impulses, and trading markets with predictable opening patterns and consistent volatility characteristics.
EMA20 Anti-Whipsaw Strategy - Clean Entry & Exit LabelsCrypto Strategy named EMA20 Anti-Whipsaw Strategy - Clean Entry & Exit Labels
ALMA & UT Bot Confluence StrategyALMA & UT Bot Confluence Strategy
This is a comprehensive trend-following and momentum strategy designed to identify high-probability trade setups by combining multiple layers of confirmation. It is built around an ALMA (Arnaud Legoux Moving Average) and a long-term EMA, and then enhances signal quality with the popular UT Bot indicator, a Volume Filter, and an adaptive hold mechanism.
The primary goal of this strategy is to filter out market noise, avoid low liquidity traps, and provide more robust and selective trading logic by adapting its timing to changing market volatility.
Key Features and How It Works
This strategy is not a simple crossover system. An entry signal is generated by the confluence of only a few conditions:
Underlying Trend and Signal Engine:
ALMA (Arnaud Legoux Moving Average): Provides a responsive, low-latency signal line for entries. EMA (Exponential Moving Average): A longer-term EMA acts as a primary trend filter, ensuring trades are executed only in line with the overall market trend.
Confirmation Layer:
UT Bot Confirmation: A trade is considered valid only when the UT Bot indicator provides a relevant buy or sell signal. This acts as a strong secondary confirmation, reducing false entries.
Advanced Filters for Signal Quality:
Volume Filter: This is an important safety mechanism that prevents trades from being executed in low-volume, illiquid markets where price action can be erratic and unreliable.
Momentum Filter (ADX and RSI): The strategy uses the ADX to check for sufficient market momentum and the RSI to ensure it doesn't enter overbought/oversold zones.
Volatility Filter (Bollinger Bands): This helps prevent entries when the price deviates too far from its average, preventing "buying at the top" or "selling at the bottom." Adaptive Timing (Dynamic Cool-Down):
Instead of a fixed waiting period between trades, this strategy uses a dynamic cooling-down period based on the ATR. It automatically waits longer during periods of high volatility (to prevent volatility) and becomes more responsive in calmer markets. How to Use This Strategy:
Long Entry (BUY): When all bullish conditions align, a green "BUY" triangle appears below the price.
Short Entry (SELL): When all bearish conditions align, a red "SELL" triangle appears above the price.
Trend Visualization: The chart background is color-coded according to UT Bot's trend direction (Green for an uptrend, Red for a downtrend), allowing for at-a-glance market analysis.
Double Exit Strategy Options
You have full control over how you exit trades:
Classic SL/TP: Use a standard Stop-Loss and Take-Profit order based on ATR (Average True Range) multipliers. UT Bot Trailing Stop (Recommended): A dynamic exit mechanism that follows the price allows your winning trades to catch up to larger trends while protecting your profits.
Disclaimer
This script is for educational purposes only and should not be construed as financial advice. Past performance is not indicative of future results. All trades involve risk. Before risking any capital, we strongly recommend extensively backtesting this strategy across your preferred assets and timeframes to understand its behavior and find settings that suit your personal trading style.
The author recommends using this strategy with Heikin-Ashi candlesticks. Using this method will significantly increase the strategy's trading success rate and profitability in backtests.
You should change the settings according to your preferred chart time range. You can find the best value for you by observing the value changes you make on the chart.
EMA20/50/200 + RSI Swing (Trend Filter)Using three different MA to identify the trend and enter when RSI under 70 or over 30
Commander Sparks | 1:1 Daily Core (Prop-Mode Overnight)Features
Trend Filter: EMA50 > EMA200 (long bias), EMA50 < EMA200 (short bias).
VWAP Filter: Only buys above VWAP, sells below VWAP.
Bollinger Band Filter: Avoids chop — enters only when price is outside BB midline in trend direction.
MACD Momentum: Entry only when MACD line crosses signal line in trend direction.
Risk Control: ATR-based stop, exactly 1:1 target, fixed full exit.
Time Filter: Trades 24/5 — including overnight & Sunday reopen.
No pyramiding — 1 trade per signal.
Entries allowed: 6:00 PM → 3:55 PM ET (1800-1555)
Auto-flat: 3:55–4:00 PM ET (so you’re flat before the 4:00 PM cutoff)
Toggle Prop Mode OFF anytime to trade 24/5 with no time limits.
Recovery Zone Hedging [Starbots]Recovery Zone Hedging Strategy — Advanced Adaptive Hedge Recovery System
This strategy introduces an innovative zone-based hedge recovery approach tailored to TradingView’s single-direction trading model. Designed for serious traders and professionals, it combines multiple technical indicators with dynamic position sizing and adaptive take-profit mechanisms to manage drawdowns and maximize recovery efficiency.
How Recovery Zones Are Calculated
The strategy defines recovery zones as a configurable percentage distance from the last executed trade price. This percentage can be adjusted to suit different market volatility environments — wider zones for volatile assets, tighter zones for stable ones. When price moves into a recovery zone against the open position, the strategy places a hedge trade in the opposite direction to help recoup losses.
Dynamic Take-Profit Calculation
Take-profit targets are not fixed. Instead, they increase dynamically based on any accumulated losses from previous hedge trades. For example, if your initial target is 2%, but you have a $5 loss from prior hedges, the next take-profit target adjusts upward to cover both the loss and your profit goal, ensuring the entire hedge sequence closes in net profit.
Originality & Value
Unlike traditional hedging or recovery scripts that rely on static stop losses and fixed trade sizing, this strategy offers:
- Dynamic Hedge Entry Zones: Uses configurable percentage-based recovery zones that adapt to price volatility, allowing precise placement of hedge trades at meaningful reversal levels.
- Multi-Indicator Signal Fusion: Integrates MACD and Directional Movement Index (DMI) signals to confirm trade entries, improving signal accuracy and reducing false triggers.
- Exponential Position Sizing: Each hedge trade’s size grows exponentially using a customizable multiplier, accelerating loss recovery while carefully balancing capital usage.
- Adaptive Take-Profit Logic: The take-profit target adjusts dynamically based on accumulated losses and profit margins, ensuring that the entire hedge sequence closes with a net gain.
- Capital Usage Monitoring: A built-in dashboard tracks real-time equity consumption, preventing over-leveraging by highlighting critical capital thresholds.
- Fail-Safe Exit Mechanism: An optional forced exit beyond the last hedge zone protects capital in extreme market scenarios.
This strategy’s layered design and adaptive mechanisms provide a unique and powerful tool for traders seeking robust recovery systems beyond standard hedge or martingale methods.
How Components Work Together
- Entry Signals: The script listens for MACD line crossovers and DMI directional crosses to open an initial trade.
- Recovery Zones: If the market moves against the initial position, the strategy calculates a recovery zone a set percentage away and places a hedge trade in the opposite direction.
- Position Scaling: Each subsequent hedge trade increases in size exponentially according to the hedge multiplier, designed to recover all previous losses plus a profit.
- Take-Profit Target: Rather than a fixed target, the TP level is dynamically calculated considering current drawdown and desired profit margin, ensuring the entire hedge sequence closes profitably.
- Cycle Management: Trades alternate direction following the recovery zones until profit is realized or a maximum hedge count is reached. If needed, a forced stop-out limits risk exposure.
Key Benefits for Professional Traders
- Enhanced Risk Management: Real-time capital usage visualization helps maintain safe exposure levels.
- Strategic Hedge Recovery: The adaptive recovery zones and exponential sizing accelerate loss recoupment more efficiently than traditional fixed-step systems.
- Multi-Indicator Confirmation: Combining MACD and DMI reduces false signals and improves hedge timing accuracy.
- Versatility: Suitable for multiple timeframes and asset classes with adjustable parameters.
- Comprehensive Visuals: On-chart recovery zones, hedge levels, dynamic take-profits, and equity usage tables enable informed decision-making.
Recommended Settings & Use Cases
- Initial Position Size: 0.1–1% of account equity
- Recovery Zone Distance: 2–5% price movement
- Hedge Multiplier: 1.5–1.85x growth per hedge step
- Max Hedge Steps: 5–10 for controlled risk exposure
Ideal for trending markets where price retracements create viable recovery opportunities. Use caution in sideways markets to avoid extended hedge sequences.
Important Notes
- TradingView’s single-direction model means hedging is simulated via alternating trades.
- Position sizes grow rapidly—proper parameter tuning is essential to avoid over-leveraging.
This script is designed primarily for professional traders seeking an advanced, automated hedge recovery framework, offering superior capital efficiency and loss management.
Supertrend EMA Vol Strategy V5### Supertrend EMA Strategy V5
**Overview**
This is a trend-following strategy designed for cryptocurrency markets like BTC/USD on daily timeframes, combining the Supertrend indicator for dynamic trailing stops with an EMA filter for trend confirmation. It aims to capture strong uptrends while avoiding counter-trend trades, with optional volume filtering for high-conviction entries and ATR-based stop-loss to manage risk. Ideal for long-only setups in bullish assets, it visually highlights trends with green/red bands and fills for easy interpretation. Backtested on BTC from 2024-2025, it shows potential for outperforming buy-and-hold in trending markets, but always use with proper risk management—past performance isn't indicative of future results.
**Key Features**
- **Supertrend Core**: Uses ATR to plot adaptive uptrend (green) and downtrend (red) lines, flipping on closes beyond prior bands for buy/sell signals.
- **EMA Trend Filter**: Entries require price above the EMA (default 21-period) for longs, ensuring alignment with the broader trend.
- **Volume Confirmation**: Optional filter only allows entries when volume exceeds its EMA (default 20-period), reducing false signals in low-activity periods.
- **Risk Controls**: Built-in ATR-multiplier stop-loss (default 2x) to cap losses; exits on Supertrend flips for trailing profits.
- **Visuals**: Green/red lines and highlighter fills for up/down trends, plus buy/sell labels and circles for signals.
- **Customizable Inputs**: Tweak ATR period (default 10), multiplier (default 3), EMA length, start date, long/short toggles, SL, and volume filter.
- **Alerts**: Built-in for buy/sell and direction changes.
**How to Use**
1. Add to your TradingView chart (e.g., BTC/USD 1D).
2. Adjust inputs: Start with defaults for trend-following; increase multiplier for fewer trades/higher win rate. Enable volume filter for volatile assets.
3. Monitor signals: Green "Buy" for long entries (if close > EMA and conditions met); red "Sell" for exits.
4. Backtest in Strategy Tester: Focus on equity curve, win rate (~50-60% in tests), and drawdown (<15% with SL).
5. Live Trading: Use small position sizes (1-2% risk per trade); combine with your analysis. Shorts disabled by default for bull-biased markets.
EMA Deviation Strategy📌 Strategy: EMA Deviation Strategy
The EMA Deviation Strategy identifies potential reversal points by measuring how far the current price deviates from its Exponential Moving Average (EMA). It dynamically tracks the minimum and maximum deviation levels over a user-defined lookback period, and enters trades when price reaches extreme zones.
🔍 Core Logic:
• Buy Entry: When price deviates significantly below the EMA, approaching the historical minimum deviation — signaling a potential rebound.
• Sell Entry: When price deviates significantly above the EMA, nearing the historical maximum deviation — signaling a possible pullback.
• Optional Take Profit / Stop Loss: Manage risk with customizable exit levels.
⚙️ Customizable Inputs:
• EMA length and lookback period
• Threshold sensitivity for entry signals
• Take profit and stop loss percentages
📈 Best Used For:
• Mean reversion setups
• Assets with cyclical or range-bound behavior
• Identifying short-term overbought/oversold conditions
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استراتژی ساز نئو 01 🇮🇷
A **Strategy Builder** is a tool or framework that lets you **design, test, and optimize** a trading strategy based on predefined rules and conditions.
**Purpose**
The main goal is to remove emotional decision-making from trading by replacing it with systematic, rule-based execution.
**How it works**
1. **Define rules** – You set entry, exit, and risk management conditions (e.g., *Buy when the 50-period moving average crosses above the 200-period moving average*).
2. **Choose parameters** – Such as indicator periods, stop-loss levels, take-profit targets, or position sizing methods.
3. **Backtesting** – The builder tests these rules on historical price data to show how the strategy would have performed in the past.
4. **Optimization** – Adjust the parameters to find the most effective setup while avoiding overfitting.
5. **Deployment** – Use the final strategy either for manual trading or connect it to an automated trading bot.
**Key Benefits**
* **Consistency** – Eliminates impulsive trades.
* **Data-driven decisions** – Every trade is based on tested rules, not guesswork.
* **Time-saving** – Once the rules are set, execution can be automated.
* **Scalability** – You can create multiple strategies for different markets or timeframes.
**Example**
Imagine you want to trade EUR/USD:
* **Entry rule:** Buy when RSI < 30 and the price is above the 50 SMA.
* **Exit rule:** Sell when RSI > 70 or price falls below the 50 SMA.
* **Risk control:** Risk 2% of account balance per trade.
A Strategy Builder lets you input those rules, run them on 5 years of EUR/USD historical data, and see metrics like win rate, maximum drawdown, and profit factor before risking real money.
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If you want, I can give you a **visual diagram** showing how the process flows from idea → testing → optimization → execution. That makes the concept much easier to grasp.
Trend Impulse Tester | Trend–Impulse–No-Chop (In development) Trend strategy. Regulate your entry and make the drawdown less than 3%, entry at % of capital. Currently under development.
Used on cryptocurrency. The 30 min timeframe was used. Adjust the values yourself, settings are provided
EMA Analysis for NasdaqThis TradingView strategy provides buy and sell entries based on EMA crossovers. It is designed for NASDAQ on the 1-minute timeframe and has high effectiveness. Testing shows that 40% of the entries result in trades with a 4-to-1 ratio of winners to losers.
ADX Phantom SniperADX Phantom Sniper is a precision trend-following tool that combines three powerful forces:
1. ADX & DI Crossover Trigger – Detects strong directional moves only when the trend strength exceeds a defined threshold.
2. Multi-Timeframe (MTF) Confirmation – Executes on the current chart timeframe (e.g., M15) only if the higher timeframe (H1) confirms the same trend direction.
3. Force Index Momentum Filter – Filters entries based on bullish/bearish momentum to avoid weak signals.
Signal Logic:
BUY: EMA14 > EMA100, price above EMA14, +DI crosses above -DI, ADX > threshold, Stochastic crosses above signal line in the bullish zone (>50), MTF trend aligned, Force Index > 0 (optional).
SELL: EMA14 < EMA100, price below EMA14, -DI crosses above +DI, ADX > threshold, Stochastic crosses below signal line in the bearish zone (<50), MTF trend aligned, Force Index < 0 (optional).
Features:
Noise filtering with trend structure + higher timeframe alignment
On-chart BUY/SELL labels for easy signal spotting
Optional Force Index filter toggle
Adjustable ADX threshold, EMA lengths, Stochastic settings, and higher timeframe choice
Suitable for scalping and swing entries depending on timeframe
Recommended Setup:
Primary chart: M15
Higher timeframe confirmation: H1
Combine with your preferred risk management rules.
Disclaimer:
This tool is for educational purposes only and is not financial advice. Past performance does not guarantee future results. Use at your own risk.
Nova Futures PRO (SAFE v6) — HTF + Choppiness + CooldownNova Futures PRO (SAFE v6) — HTF + Choppiness + Cooldown