Script_Algo - ORB Strategy with Filters🔍 Core Concept: This strategy combines three powerful technical analysis tools: Range Breakout, the SuperTrend indicator, and a volume filter. Additionally, it features precise customization of the number of candles used to construct the breakout range, enabling optimized performance for specific assets.
🎯 How It Works:
The strategy defines a trading range at the beginning of the trading session based on a selected number of candles.
It waits for a breakout above the upper or below the lower boundary of this range, requiring a candle close.
It filters signals using the SuperTrend indicator for trend confirmation.
It utilizes trading volume to filter out false breakouts.
⚡ Strategy Features
📈 Entry Points:
Long: Candle close above the upper range boundary + SuperTrend confirmation
Short: Candle close below the lower range boundary + SuperTrend confirmation
🛡️ Risk Management:
Stop-Loss: Set at the opposite range boundary.
Take-Profit: Calculated based on a risk/reward ratio (3:1 by default).
Position Size: 10 contracts (configurable).
⚠️ IMPORTANT SETTINGS
🕐 Time Parameters:
Set the correct time and time zone!
❕ATTENTION: The strategy works ONLY with correct time settings! Set the time corresponding to your location and trading session.
📊 This strategy is optimized for trading TESLA stock!
Parameters are tailored to TESLA's volatility, and trading volumes are adequate for signal filtering. Trading time corresponds to the American session.
📈 If you look at the backtesting results, you can see that the strategy could potentially have generated about 70 percent profit on Tesla stock over six months on 5m timeframe. However, this does not guarantee that results will be repeated in the future; remain vigilant.
⚠️ For other assets, the following is required:
Testing and parameter optimization
Adjustment of time intervals and the number of candles forming the range
Calibration of stop-loss and take-profit levels
⚠️ Limitations and Drawbacks
🔗 Automation Constraints:
❌ Cannot be directly connected via Webhook to CFD brokers!
Additional IT solutions are required for automation, thus only manual trading based on signals is possible.
📉 Risk Management:
Do not risk more than 2-3% of your account per trade.
Test on historical data before live use.
Start with a demo account.
💪 Strategy Advantages
✅ Combined approach – multiple signal filters
✅ Clear entry and exit rules
✅ Visual signals on the chart
✅ Volume-based false breakout filtering
✅ Automatic position management
🎯 Usage Recommendations
Always test the strategy on historical data.
Start with small trading volumes.
Ensure time settings are correct.
Adapt parameters to current market volatility.
Use only for stocks – futures and Forex require adaptation.
📚 Suitable Timeframes - M1-M15
Only highly liquid stocks
🍀 I wish all subscribers good luck in trading and steady profits!
📈 May your charts move in the right direction!
⚠️ Remember: Trading involves risk. Do not invest money you cannot afford to lose!
Bande e canali
Twin Range Filter StrategyClarity Over Confusion: See price action through a全新的 lens. Watch as erratic, choppy movements are smoothed into a clear, actionable trajectory. The path of least resistance becomes obvious.
Confidence Over Hesitation: Receive high-probability entry and exit signals with a proven logic that waits for the market to commit before you do. No more second-guessing.
Discipline Over Emotion: Our algorithm enforces a systematic approach, helping you avoid emotional FOMO chasing and panic selling. Stick to the plan and execute with precision.
What Can You Expect?
Dynamic Adaptability: Unlike static indicators, continuously adapts to volatility. It widens its filter in turbulent markets to avoid whipsaws and tightens it in trending markets to capture more of the move.
The Power of Two: By synthesizing data from two distinct market perspectives, it confirms strength and filters out weakness, providing a confluence that standalone indicators simply cannot match.
Clean, Unambiguous Signals: We’ve eliminated the clutter. The software provides clear visual alerts (Green Arrows for Long, Red Arrows for Short) right on your chart, telling you exactly when the equilibrium has shifted.
Who is this for?
Swing Traders looking to capture the heart of a trend and avoid false breakouts.
Day Traders needing a reliable filter to navigate volatile intraday action.
Systematic Traders seeking a robust logic layer to add to their automated strategy.
Anyone overwhelmed by indicator overload and craving a single, trusted source of truth on their chart
Estrategy EURUSD M3 Scalping Estrategia para operar el EURUSD en temp de 3 min, indica sl y tp 6 pips sl y 10 pips tp
MA20 Crossover Strategy with Threshold and Color ChangeMột chiến lược cơ bản dựa trên EMA20. Giá cắt lên MA20 hay EMA20 thi báo mua và ngược lại
Trading Advice By RajTrading Advice Strategy
This strategy is based on a simple moving average crossover system using the 50 EMA and the 200 EMA.
Buy Signal (Long): When the 50 EMA crosses above the 200 EMA, a bullish trend is detected and a BUY signal is generated.
Sell Signal (Short): When the 200 EMA crosses above the 50 EMA, a bearish trend is detected and a SELL signal is generated.
EMA lines are hidden on the chart for a clean look. Only BUY and SELL signals are shown as labels.
Suitable for trend-following traders who want clear entry signals without noise.
Can be combined with risk management tools like Stop Loss & Take Profit for better results. youtube.com BINANCE:BTCUSDT
BTCUSD Daily Nexus Protocol Robot [AlgoChadLin]The BTCUSD Daily Nexus Protocol Robot is a sophisticated, multi-faceted trading system designed for the Bitcoin Daily (D1) timeframe . It operates by integrating a diverse set of technical indicators to form a robust, rule-based trading protocol. This strategy focuses on identifying high-conviction trade setups and managing them with precision.
Strategy Logic
Entry Confirmation: The strategy uses a powerful combination of multiple indicators. Entry signals are confirmed when the closing price moves relative to the VWAP, indicating a shift in momentum.
Targeted Entries: To pinpoint optimal entry points, the system utilizes Keltner Channels and Average True Range (ATR). A long entry is placed as a limit order above the upper Keltner Channel, while a short entry is set below the lower channel.
Dynamic Exits: Risk and reward are managed through a dual-layered exit approach. The strategy uses a dynamic SuperTrend value and ATR to set a trailing stop-loss, protecting capital and locking in profits. Additionally, a time-based exit and an Ichimoku signal provide alternative exit conditions to ensure positions are closed under specific market circumstances.
Parameters
VWAP Period: Defines the lookback period for the VWAP indicator.
Keltner Channel Period: Sets the period for the Keltner Channel, which helps define entry levels.
Entry ATR Multiplier: Adjusts the distance of the limit order from the Keltner Channel.
Stop-Loss ATR Period & Multiplier: Configures the dynamic stop-loss based on the SuperTrend and ATR.
Exit After Bars: Specifies the maximum duration a trade can be open.
Pending
Order Valid Bars: Determines how long a pending order remains active.
Setup
Timeframe: Daily (D1)
Asset: BTCUSD (Not BTCUSDT. If you want to trade BTCUSDT you have to modify the parameters.)
Bollinger Bandit + TP EscalonadoDescription:
The Bollinger Bandit is a clean, visual mean reversion strategy designed to help traders identify potential reversal opportunities using Bollinger Bands. This strategy offers two distinct exit methods, giving you the flexibility to choose between classic band-based exits or precise fixed take-profit/stop-loss levels.
How It Works (Simple Explanation):
Basic Concept:
Prices often tend to return to their average after moving too far away. Bollinger Bands help identify these extreme moments.
Entry Signals:
BUY (Green Triangle): When price crosses above the lower Bollinger Band
SELL (Red Triangle): When price crosses below the upper Bollinger Band
Exit Options (CHOOSE ONE ONLY):
Option 1: Band & Mean Exits (Traditional)
Exit when price touches the opposite band
Optional exit at the middle moving average
Option 2: Fixed SL/TP Exits (Precise Risk Management)
Stop Loss: Fixed points from entry
Take Profit 1: First profit target (closes 50% of position)
Take Profit 2: Second profit target (closes remaining 50%)
Key Features:
Clear Visual Signals - Easy-to-see triangles for entries
Color-Coded Levels - Instant visual understanding
Fully Customizable - Adjust everything to your preference
Two Exit Strategies - Choose what works for your style
Risk Management - Fixed SL/TP with proper risk-reward ratios
Input Settings:
Bollinger Bands Configuration:
Period (20): Length of the moving average
Multiplier (1.0): Band width adjustment
Exit Strategy Selection:
Use Custom SL/TP - Switch between exit methods
Close on Moving Average - Enable/disable mean exits
Risk Management (SL/TP Mode):
SL Points (5): Stop Loss distance in points
TP1 Points (3): First Take Profit target
TP2 Points (5): Second Take Profit target
Important Notes:
CHOOSE ONLY ONE EXIT METHOD:
You can use EITHER Band/Mean exits OR Fixed SL/TP exits
Never enable both simultaneously
Ideal Market Conditions:
Works best in ranging markets
May give false signals in strong trends
Test different timeframes (1H-4H recommended)
How to Use:
Add the strategy to your chart
Choose your preferred exit method
Adjust settings to match your risk tolerance
Observe the visual signals on your chart
Practice with historical data first
Risk Disclaimer:
Trading involves significant risk of loss. This is not financial advice. Past performance is not indicative of future results. Test thoroughly before live trading. Only risk capital you can afford to lose.
This strategy is for educational purposes only. Always understand how any strategy works before using real capital.
Recommended Settings for Beginners:
Timeframe: 5M
SL: 5 points, TP1: 3 points, TP2: 5 points
Start with small position sizes
VWAP Executor — v6 (VWAP fix)tarek helishPractical scalping plan with high-rate (sometimes reaching 70–85% in a quiet market)
Concept: “VWAP bounce with a clear trend.”
Tools: 1–3-minute chart for entry, 5-minute trend filter, VWAP, EMA(50) on 5M, ATR(14) on 1M, volume.
When to trade: London session or early New York session; avoid 10–15 minutes before/after high-impact news.
Entry rules (buy for example):
Trend: Price is above the EMA(50) on 5M and has an upward trend.
Entry zone: First bounce to VWAP (or a ±1 standard deviation channel around it).
Signal: Bullish rejection/engulfing candle on 1M with increasing volume, and RSI(2) has exited oversold territory (optional).
Order: Entry after the confirmation candle closes or a limit close to VWAP.
Trade Management:
Stop: Below the bounce low or 0.6xATR(1M) (strongest).
Target: 0.4–0.7xATR(1M) or the previous micro-high (small return to increase success rate).
Trigger: Move the stop to breakeven after +0.25R; close manually if the 1M candle closes strongly against you.
Filter: Do not trade if the spread widens, or the price "saws" around VWAP without a trend.
Sell against the rules in a downtrend.
Why this plan raises the heat-rate? You buy a "small discount" within an existing trend and near the institutional average price (VWAP), with a small target price.
مواقعي شركة الماسة للخدمات المنزلية
شركة تنظيف بالرياض
نقل عفش بالرياض
Range FinderRange Finder Strategy for TradingView
Overview
The Range Finder Strategy is a sophisticated trading system designed for forex and cryptocurrency markets, leveraging dynamic range detection, wick-based rejection patterns, and EMA confluence to execute high-probability trades. This strategy identifies key price ranges using pivot points and triggers trades when price rejects from these boundaries with significant wick formations, aligning with the broader market trend as confirmed by EMA crossovers. It incorporates robust risk management, customizable parameters, and visual aids for clear trade visualization, making it suitable for both manual and automated trading on platforms like Bitget via webhook alerts.
Strategy Components
1. Dynamic Range Detection
Pivot Points: The strategy identifies range boundaries using pivot highs and lows, calculated with a user-defined Pivot Length (default: 5 bars left/right). These pivots mark significant swing points, defining the upper (range high) and lower (range low) boundaries of the price range.
Visualization: The range high is plotted as an orange line, and the range low as a purple line, using a broken line style (plot.style_linebr) to show only confirmed pivot levels, providing a clear visual of the trading range.
2. Wick-Based Rejection Pattern
Wick Detection: The strategy looks for rejection candles at the range boundaries, characterized by significant wicks. A wick is considered valid if its size is at least the user-defined Wick to Body Ratio (default: 1.1, or 10% larger than the candle body).
Sell Signal: Triggered when the high exceeds the range high, the candle closes bearish (close < open), and the upper wick meets the ratio requirement.
Buy Signal: Triggered when the low falls below the range low, the candle closes bullish (close > open), and the lower wick meets the ratio requirement.
Purpose: These wicks indicate strong rejection at key levels, often signaling a reversal back into the range, providing high-probability entry points.
3. EMA Trend Confirmation
EMA Calculation: Uses two Exponential Moving Averages (EMAs) calculated on a user-selectable timeframe (default: 5-minute):
EMA 200: Long-term trend indicator (plotted in red).
EMA 50: Short-term trend indicator (plotted in green).
Crossover Logic:
A bullish trend is confirmed when the EMA 50 crosses above the EMA 200 (ema_trend_up = true).
A bearish trend is confirmed when the EMA 50 crosses below the EMA 200 (ema_trend_down = true).
Confluence Requirement: Trades are only executed when the wick rejection aligns with the EMA trend (e.g., sell signals require close < ema200 and bearish trend; buy signals require close > ema200 and bullish trend).
4. Risk Management
Position Sizing: Calculated based on the user-defined Account Balance (default: $10,000) and Risk Per Trade (default: 2%). The position size is determined as risk_amount / stop_distance, where stop_distance is derived from the Average True Range (ATR, default period: 14).
Stop Loss (SL): Set using an ATR-based multiplier (SL Multiplier, default: 9.0). For sells, SL is placed above the high; for buys, below the low.
Take Profit (TP): Set using an ATR-based multiplier (TP Multiplier, default: 6.0) scaled by the Risk:Reward Ratio (default: 6.0), ensuring a favorable reward-to-risk profile.
Example: For a $10,000 account with 2% risk, if ATR is 0.5, the position size is 400 units, with SL and TP dynamically adjusted to market volatility.
5. Trade Execution
Sell Entry: Triggered on a wick rejection above the range high, with bearish EMA confluence (ema_trend_down and close < ema200). Enters a short position with calculated SL and TP.
Buy Entry: Triggered on a wick rejection below the range low, with bullish EMA confluence (ema_trend_up and close > ema200). Enters a long position with calculated SL and TP.
Exit Logic: Uses strategy.exit to set SL and TP levels, closing trades when either is hit.
6. Visual Feedback
Lines and Labels: Upon trade entry, the strategy plots:
Red SL line and label (e.g., "SL: 123.45").
Green TP line and label (e.g., "TP: 120.00").
Entry line (red for sell, green for buy) labeled with "Sell (Range Rejection)" or "Buy (Range Rejection)".
Customization: Users can adjust the Line Length (default: 25 bars) for how long lines persist and Label Position (left or right) for optimal chart visibility.
7. Alert Conditions
Webhook Integration: Generates alerts for Bitget webhook integration, providing JSON-formatted messages with trade details (action, contracts, market position, size, price, symbol, and timestamp).
Usage: Traders can set up automated trading by connecting these alerts to trading bots or platforms supporting webhooks.
Imbalance RSI Divergence Strategy# Imbalance RSI Divergence Strategy - User Guide
## What is This Strategy?
This strategy identifies **imbalance** zones in the market and combines them with **RSI divergence** to generate trading signals. It aims to capitalize on price gaps left by institutional investors and large volume movements.
### Main Settings
- **RSI Period (14)**: Period used for RSI calculation. Lower values = more sensitive, higher values = more stable signals.
- **ATR Period (10)**: Period for volatility measurement using Average True Range.
- **ATR Stop Loss Multiplier (2.0)**: How many ATR units to use for stop loss calculation.
- **Risk:Reward Ratio (4.0)**: Risk-reward ratio. 2.0 = 2 units of reward for 1 unit of risk.
- **Use RSI Divergence Filter (true)**: Enables/disables the RSI divergence filter.
### Imbalance Filters
- **Minimum Imbalance Size (ATR) (0.3)**: Minimum imbalance size in ATR units to filter out small imbalances.
- **Enable Lookback Limit (false)**: Activates historical lookback limitations.
- **Maximum Lookback Bars (300)**: Maximum number of bars to look back.
### Visual Settings
- **Show Imbalance Size**: Displays imbalance size in ATR units.
- **Show RSI Divergence Lines**: Shows/hides divergence lines.
- **Divergence Line Colors**: Colors for bullish/bearish divergence lines.
### Volatility-Based Adjustments
- **Low volatility markets**:
- Minimum Imbalance Size: 0.2-0.4 ATR
- ATR Stop Loss Multiplier: 1.5-2.0
- **High volatility markets**:
- Minimum Imbalance Size: 0.5-1.0 ATR
- ATR Stop Loss Multiplier: 2.5-3.5
### Risk Tolerance
- **Conservative approach**:
- Risk:Reward Ratio: 2.0-3.0
- RSI Divergence Filter: Enabled
- Minimum Imbalance Size: Higher (0.5+ ATR)
- **Aggressive approach**:
- Risk:Reward Ratio: 4.0-6.0
- Minimum Imbalance Size: Lower (0.2-0.3 ATR)
###Market Conditions
- **Trending markets**: Higher RSI Period (21-28)
- **Sideways markets**: Lower RSI Period (10-14)
- **Volatile markets**: Higher ATR Multiplier
## Recommended Testing Procedure
1. **Start with default settings** and backtest on 3-6 months of historical data
2. **Adjust RSI Period** to see which value produces better results
3. **Optimize ATR Multiplier** for stop loss levels
4. **Test different Risk:Reward ratios** comparatively
5. **Fine-tune Minimum Imbalance Size** to improve signal quality
## Important Considerations
- **False positive signals**: Imbalances may be less reliable during low volatility periods
- **Market openings**: First hours often produce more imbalances but can be riskier
- **News events**: Consider disabling strategy during major news releases
- **Backtesting**: Test across different market conditions (trending, sideways, volatile)
## Recommended Settings for Beginners
**Safe settings for new users:**
- RSI Period: 14
- ATR Period: 14
- ATR Stop Loss Multiplier: 2.5
- Risk:Reward Ratio: 3.0
- Minimum Imbalance Size: 0.5 ATR
- RSI Divergence Filter: Enabled
## Advanced Tips
### Signal Quality Improvement
- **Combine with market structure**: Look for imbalances near key support/resistance levels
- **Volume confirmation**: Higher volume during imbalance formation increases reliability
- **Multiple timeframe analysis**: Confirm signals on higher timeframes
### Risk Management
- **Position sizing**: Never risk more than 1-2% of account per trade
- **Maximum drawdown**: Set overall stop loss for the strategy
- **Market hours**: Consider avoiding low liquidity periods
### Performance Monitoring
- **Win rate**: Track percentage of profitable trades
- **Average R:R**: Monitor actual risk-reward achieved vs. target
- **Maximum consecutive losses**: Set alerts for strategy review
This strategy works best when combined with proper risk management and market analysis. Always backtest thoroughly before using real money and adjust parameters based on your specific market and trading style.
Keltner Alım Stratejisi v6 (10, 0.5)sadece keltner kanal girdilerinin değiştirilmesiyle oluşturulmuş bir göstergedir
The Barking Rat LiteMomentum & FVG Reversion Strategy
The Barking Rat Lite is a disciplined, short-term mean-reversion strategy that combines RSI momentum filtering, EMA bands, and Fair Value Gap (FVG) detection to identify short-term reversal points. Designed for practical use on volatile markets, it focuses on precise entries and ATR-based take profit management to balance opportunity and risk.
Core Concept
This strategy seeks potential reversals when short-term price action shows exhaustion outside an EMA band, confirmed by momentum and FVG signals:
EMA Bands:
Parameters used: A 20-period EMA (fast) and 100-period EMA (slow).
Why chosen:
- The 20 EMA is sensitive to short-term moves and reflects immediate momentum.
- The 100 EMA provides a slower, structural anchor.
When price trades outside both bands, it often signals overextension relative to both short-term and medium-term trends.
Application in strategy:
- Long entries are only considered when price dips below both EMAs, identifying potential undervaluation.
- Short entries are only considered when price rises above both EMAs, identifying potential overvaluation.
This dual-band filter avoids counter-trend signals that would occur if only a single EMA was used, making entries more selective..
Fair Value Gap Detection (FVG):
Parameters used: The script checks for dislocations using a 12-bar lookback (i.e. comparing current highs/lows with values 12 candles back).
Why chosen:
- A 12-bar displacement highlights significant inefficiencies in price structure while filtering out micro-gaps that appear every few bars in high-volatility markets.
- By aligning FVG signals with candle direction (bullish = close > open, bearish = close < open), the strategy avoids random gaps and instead targets ones that suggest exhaustion.
Application in strategy:
- Bullish FVGs form when earlier lows sit above current highs, hinting at downward over-extension.
- Bearish FVGs form when earlier highs sit below current lows, hinting at upward over-extension.
This gives the strategy a structural filter beyond simple oscillators, ensuring signals have price-dislocation context.
RSI Momentum Filter:
Parameters used: 14-period RSI with thresholds of 80 (overbought) and 20 (oversold).
Why chosen:
- RSI(14) is a widely recognized momentum measure that balances responsiveness with stability.
- The thresholds are intentionally extreme (80/20 vs. the more common 70/30), so the strategy only engages at genuine exhaustion points rather than frequent minor corrections.
Application in strategy:
- Longs trigger when RSI < 20, suggesting oversold exhaustion.
- Shorts trigger when RSI > 80, suggesting overbought exhaustion.
This ensures entries are not just technically valid but also backed by momentum extremes, raising conviction.
ATR-Based Take Profit:
Parameters used: 14-period ATR, with a default multiplier of 4.
Why chosen:
- ATR(14) reflects the prevailing volatility environment without reacting too much to outliers.
- A multiplier of 4 is a pragmatic compromise: wide enough to let trades breathe in volatile conditions, but tight enough to enforce disciplined exits before mean reversion fades.
Application in strategy:
- At entry, a fixed target is set = Entry Price ± (ATR × 4).
- This target scales automatically with volatility: narrower in calm periods, wider in explosive markets.
By avoiding discretionary exits, the system maintains rule-based discipline.
Visual Signals on Chart
Blue “▲” below candle: Potential long entry
Orange/Yellow “▼” above candle: Potential short entry
Green “✔️”: Trade closed at ATR take profit
Blue (20 EMA) & Orange (100 EMA) lines: Dynamic channel reference
⚙️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: HYPEUSDT
Backtesting range: Jul 28, 2025 — Aug 17, 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 Lite strategy is very selective, filtering out over 90% of market noise. 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 Barking Rat Lite valuable
Combines multiple layers of confirmation: EMA bands + FVG + RSI
Adaptive to volatility: ATR-based exits scale with market conditions
Clear, actionable visuals: Easy to monitor and manage trades
Crypto Gann Channel Strategy (Long Bias, fixed)This is Gann Strategy Cody with Long Bias. Please try and let me know if can be improved.
DCA Strategy on Steroids for CryptoThis strategy getting only in Long position for Crypto
Using Fast and Slow moving Averages and Stochastic RSI to get in Long position
Fast and Slow moving Averages - cross-under - I Prefer - or opposite for Bull Market
Stochastic RSI cross-over - 5 and Trend Determined by the Fast moving Average
There is no Stop loss is not for one with small tolerance to getting under
Fast and Slow moving Averages and Stochastic RSI Parameters can be adjust
The bot Use Safe Trades and Price Deviation Determined from the User
Max Safe Trades = 10
Take profit Parameters can be adjust in %
Pepe-USDC is just a example What the bot Can do
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
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.
ZapTeam Pro Strategy v6 — EMA The Pro Strategy v6 script is a versatile trading strategy for TradingView that combines trend indicators, filters, and levels.
Main features:
EMA 21, EMA 50, EMA 200 — trend detection and entry signals via EMA crossovers.
Ichimoku Cloud (optional) — trend filtering and price position relative to the cloud.
ETH Dominance filter (optional) — filters trades based on Ethereum dominance (ETH.D).
ATR Stop-Loss — dynamic stop-loss based on volatility.
Two take-profits (TP1 and TP2) with optional 50/50 split.
Dynamic Fibonacci Levels — automatic or manual swings, with 1.272 and 1.618 extensions.
Custom S/R Levels — user-defined support/resistance levels.
Level lines extend across the chart and automatically adjust when zooming or panning.
Designed for trading in trending market conditions on any timeframe.
The strategy calculates position size based on percentage risk per equity.
BB & RSI Trailing Stop StrategySimple BB & RSI generated using AI, gets 60% on S&P 500 with the right settings
Keltner Channel Based Grid Strategy # KC Grid Strategy - Keltner Channel Based Grid Trading System
## Strategy Overview
KC Grid Strategy is an innovative grid trading system that combines the power of Keltner Channels with dynamic position sizing to create a mean-reversion trading approach. This strategy automatically adjusts position sizes based on price deviation from the Keltner Channel center line, implementing a systematic grid-based approach that capitalizes on market volatility and price oscillations.
## Core Principles
### Keltner Channel Foundation
The strategy builds upon the Keltner Channel indicator, which consists of:
- **Center Line**: Moving average (EMA or SMA) of the price
- **Upper Band**: Center line + (ATR/TR/Range × Multiplier)
- **Lower Band**: Center line - (ATR/TR/Range × Multiplier)
### Grid Trading Logic
The strategy implements a sophisticated grid system where:
1. **Position Direction**: Inversely correlated to price position within the channel
- When price is above center line → Short positions
- When price is below center line → Long positions
2. **Position Size**: Proportional to distance from center line
- Greater deviation = Larger position size
3. **Grid Activation**: Positions are adjusted only when the difference exceeds a predefined grid threshold
### Mathematical Foundation
The core calculation uses the KC Rate formula:
```
kcRate = (close - ma) / bandWidth
targetPosition = kcRate × maxAmount × (-1)
```
This creates a mean-reversion system where positions increase as price moves further from the mean, expecting eventual return to equilibrium.
## Parameter Guide
### Time Range Settings
- **Start Date**: Beginning of strategy execution period
- **End Date**: End of strategy execution period
### Core Parameters
1. **Number of Grids (NumGrid)**: Default 12
- Controls grid sensitivity and position adjustment frequency
- Higher values = More frequent but smaller adjustments
- Lower values = Less frequent but larger adjustments
2. **Length**: Default 10
- Period for moving average and volatility calculations
- Shorter periods = More responsive to recent price action
- Longer periods = Smoother, less noisy signals
3. **Grid Coefficient (kcRateMult)**: Default 1.33
- Multiplier for channel width calculation
- Higher values = Wider channels, less frequent trades
- Lower values = Narrower channels, more frequent trades
4. **Source**: Default Close
- Price source for calculations (Close, Open, High, Low, etc.)
- Close price typically provides most reliable signals
5. **Use Exponential MA**: Default True
- True = Uses EMA (more responsive to recent prices)
- False = Uses SMA (equal weight to all periods)
6. **Bands Style**: Default "Average True Range"
- **Average True Range**: Smoothed volatility measure (recommended)
- **True Range**: Current bar's volatility only
- **Range**: Simple high-low difference
## How to Use
### Setup Instructions
1. **Apply to Chart**: Add the strategy to your desired timeframe and instrument
2. **Configure Parameters**: Adjust settings based on market characteristics:
- Volatile markets: Increase Grid Coefficient, reduce Number of Grids
- Stable markets: Decrease Grid Coefficient, increase Number of Grids
3. **Set Time Range**: Define your backtesting or live trading period
4. **Monitor Performance**: Watch strategy performance metrics and adjust as needed
### Optimal Market Conditions
- **Range-bound markets**: Strategy performs best in sideways trending markets
- **High volatility**: Benefits from frequent price oscillations around the mean
- **Liquid instruments**: Ensures efficient order execution and minimal slippage
### Position Management
The strategy automatically:
- Calculates optimal position sizes based on account equity
- Adjusts positions incrementally as price moves through grid levels
- Maintains risk control through maximum position limits
- Executes trades only during specified time periods
## Risk Warnings
### ⚠️ Important Risk Considerations
1. **Trending Market Risk**:
- Strategy may underperform or generate losses in strong trending markets
- Mean-reversion assumption may fail during sustained directional moves
- Consider market regime analysis before deployment
2. **Leverage and Position Size Risk**:
- Strategy uses pyramiding (up to 20 positions)
- Large positions may accumulate during extended moves
- Monitor account equity and margin requirements closely
3. **Volatility Risk**:
- Sudden volatility spikes may trigger multiple rapid position adjustments
- Consider volatility filters during high-impact news events
- Backtest across different volatility regimes
4. **Execution Risk**:
- Strategy calculates on every tick (calc_on_every_tick = true)
- May generate frequent orders in volatile conditions
- Ensure adequate execution infrastructure and consider transaction costs
5. **Parameter Sensitivity**:
- Performance highly dependent on parameter optimization
- Over-optimization may lead to curve-fitting
- Regular parameter review and adjustment may be necessary
## Suitable Scenarios
### Ideal Market Conditions
- **Sideways/Range-bound markets**: Primary use case
- **Mean-reverting instruments**: Forex pairs, some commodities
- **Stable volatility environments**: Consistent ATR patterns
- **Liquid markets**: Major currency pairs, popular stocks/indices
## Important Notes
### Strategy Limitations
1. **No Stop Loss**: Strategy relies on mean reversion without traditional stop losses
2. **Capital Requirements**: Requires sufficient capital for grid-based position sizing
3. **Market Regime Dependency**: Performance varies significantly across different market conditions
## Disclaimer
This strategy is provided for educational and research purposes only. Past performance does not guarantee future results. Trading involves substantial risk of loss and is not suitable for all investors. Users should thoroughly test the strategy and understand its mechanics before risking real capital. The author assumes no responsibility for trading losses incurred through the use of this strategy.
---
# KC网格策略 - 基于肯特纳通道的网格交易系统
## 策略概述
KC网格策略是一个创新的网格交易系统，它将肯特纳通道的力量与动态仓位调整相结合，创建了一个均值回归交易方法。该策略根据价格偏离肯特纳通道中心线的程度自动调整仓位大小，实施系统化的网格方法，利用市场波动和价格振荡获利。
## 核心原理
### 肯特纳通道基础
该策略建立在肯特纳通道指标之上，包含：
- **中心线**: 价格的移动平均线（EMA或SMA）
- **上轨**: 中心线 + (ATR/TR/Range × 乘数)
- **下轨**: 中心线 - (ATR/TR/Range × 乘数)
### 网格交易逻辑
该策略实施复杂的网格系统：
1. **仓位方向**: 与价格在通道中的位置呈反向关系
- 当价格高于中心线时 → 空头仓位
- 当价格低于中心线时 → 多头仓位
2. **仓位大小**: 与距离中心线的距离成正比
- 偏离越大 = 仓位越大
3. **网格激活**: 只有当差异超过预定义的网格阈值时才调整仓位
### 数学基础
核心计算使用KC比率公式：
```
kcRate = (close - ma) / bandWidth
targetPosition = kcRate × maxAmount × (-1)
```
这创建了一个均值回归系统，当价格偏离均值越远时仓位越大，期望最终回归均衡。
## 参数说明
### 时间范围设置
- **开始日期**: 策略执行期间的开始时间
- **结束日期**: 策略执行期间的结束时间
### 核心参数
1. **网格数量 (NumGrid)**: 默认12
- 控制网格敏感度和仓位调整频率
- 较高值 = 更频繁但较小的调整
- 较低值 = 较少频繁但较大的调整
2. **长度**: 默认10
- 移动平均线和波动率计算的周期
- 较短周期 = 对近期价格行为更敏感
- 较长周期 = 更平滑，噪音更少的信号
3. **网格系数 (kcRateMult)**: 默认1.33
- 通道宽度计算的乘数
- 较高值 = 更宽的通道，较少频繁的交易
- 较低值 = 更窄的通道，更频繁的交易
4. **数据源**: 默认收盘价
- 计算的价格来源（收盘价、开盘价、最高价、最低价等）
- 收盘价通常提供最可靠的信号
5. **使用指数移动平均**: 默认True
- True = 使用EMA（对近期价格更敏感）
- False = 使用SMA（对所有周期等权重）
6. **通道样式**: 默认"平均真实范围"
- **平均真实范围**: 平滑的波动率测量（推荐）
- **真实范围**: 仅当前K线的波动率
- **范围**: 简单的高低价差
## 使用方法
### 设置说明
1. **应用到图表**: 将策略添加到您所需的时间框架和交易品种
2. **配置参数**: 根据市场特征调整设置：
- 波动市场：增加网格系数，减少网格数量
- 稳定市场：减少网格系数，增加网格数量
3. **设置时间范围**: 定义您的回测或实盘交易期间
4. **监控表现**: 观察策略表现指标并根据需要调整
### 最佳市场条件
- **区间震荡市场**: 策略在横盘趋势市场中表现最佳
- **高波动性**: 受益于围绕均值的频繁价格振荡
- **流动性强的品种**: 确保高效的订单执行和最小滑点
### 仓位管理
策略自动：
- 根据账户权益计算最优仓位大小
- 随着价格在网格水平移动逐步调整仓位
- 通过最大仓位限制维持风险控制
- 仅在指定时间段内执行交易
## 风险警示
### ⚠️ 重要风险考虑
1. **趋势市场风险**:
- 策略在强趋势市场中可能表现不佳或产生损失
- 在持续方向性移动期间均值回归假设可能失效
- 部署前考虑市场制度分析
2. **杠杆和仓位大小风险**:
- 策略使用金字塔加仓（最多20个仓位）
- 在延长移动期间可能积累大仓位
- 密切监控账户权益和保证金要求
3. **波动性风险**:
- 突然的波动性激增可能触发多次快速仓位调整
- 在高影响新闻事件期间考虑波动性过滤器
- 在不同波动性制度下进行回测
4. **执行风险**:
- 策略在每个tick上计算（calc_on_every_tick = true）
- 在波动条件下可能产生频繁订单
- 确保充足的执行基础设施并考虑交易成本
5. **参数敏感性**:
- 表现高度依赖于参数优化
- 过度优化可能导致曲线拟合
- 可能需要定期参数审查和调整
## 适用场景
### 理想市场条件
- **横盘/区间震荡市场**: 主要用例
- **均值回归品种**: 外汇对，某些商品
- **稳定波动性环境**: 一致的ATR模式
- **流动性市场**: 主要货币对，热门股票/指数
## 注意事项
### 策略限制
1. **无止损**: 策略依赖均值回归而无传统止损
2. **资金要求**: 需要充足资金进行基于网格的仓位调整
3. **市场制度依赖性**: 在不同市场条件下表现差异显著
## 免责声明
该策略仅供教育和研究目的。过往表现不保证未来结果。交易涉及重大损失风险，并非适合所有投资者。用户应在投入真实资金前彻底测试策略并理解其机制。作者对使用此策略产生的交易损失不承担任何责任。
---
**Strategy Version**: Pine Script v6
**Author**: Signal2Trade
**Last Updated**: 2025-8-9
**License**: Open Source (Mozilla Public License 2.0)
