Seawolf Pivot Hunter [Strategy]Overview
Seawolf Pivot Hunter is a practical trading strategy that enhances the classic pivot-box breakout system with a structured risk-management framework. Using ATR-based stop loss and take-profit calculations, position sizing, multi-layer filtering, and daily loss-limit protection, it provides a stable and sustainable trading environment. It preserves the strengths of the original version while adding systems designed to manage real-market risks more effectively.
Core Philosophy
The most important element in trading is not generating profits but controlling losses. Even the best entry signals cannot compensate for a single large loss that wipes out accumulated gains. This strategy precisely calculates the risk exposure for every trade and includes multiple layers of protection to safeguard the account under worst-case scenarios.
Indicator Setup Link
kr.tradingview.com
Example of Optimal Parameter Settings
Asset (Exchange): ETH/USDT (Binance)
Timeframe: 15-minute chart
Pivot Detection Length: 5
Upper Box Width: 2
Lower Box Width: 2
Enable Risk Management: False
Use Trailing Stop: False
Use Volume Filter
-Min Buy Volume % for Long: 50
-Min Sell Volume % for Short: 50
Use Trend Filter (EMA): False
Enable Max Loss Protection
-Max Daily Loss ($): 200
-Max Trades Per Day: 10
Calculated Bars: 50,000
Risk-Management System
Every trade automatically receives a stop-loss level at the moment of entry. The stop is calculated using ATR, adjusting dynamically to market volatility. When volatility increases, the stop widens; in stable conditions, it tightens to reduce unnecessary exits. The default distance is set to twice the ATR.
The standard take-profit level is set to four times the ATR, providing a 1:2 risk-reward structure. With this ratio, even a 50 percent win rate can produce profitability—while the typical trade structure aims for small losses and larger gains to support long-term performance.
A trailing-stop option is also available. Once the trade moves into profit, the stop level automatically trails behind price action, protecting gains while allowing the position to expand when momentum continues.
Position size is calculated automatically based on the selected risk percentage. For example, with a 2 percent risk setting, each stop-loss hit would result in exactly 2 percent of the account balance being lost. This ensures a consistent risk profile regardless of account size.
The daily loss-limit function prevents excessive drawdown by halting new trades once a predefined loss threshold is reached. This helps avoid emotional decision-making after consecutive losses.
A daily trade-limit feature is included as well. The default is 10 trades per day, protecting traders from overtrading and unnecessary fees.
Filtering System
The volume filter analyzes buying and selling pressure within the pivot box. Long trades are allowed only when buy volume exceeds a specified percentage; shorts require sell-volume dominance. The default threshold is 55 percent.
The trend filter uses an EMA to determine market direction. When price is above the 200-EMA, only long signals are permitted; when below, only shorts are allowed. This ensures alignment with the broader trend and reduces counter-trend risk.
Each filter can be toggled independently. More filters generally reduce trade frequency but improve signal quality.
Real-Time Monitoring
A real-time statistics panel displays daily profit/loss, the number of trades taken, the maximum allowed trades, and whether new trades are currently permitted. When daily limits are reached, the panel provides clear visual warnings.
Entry Logic
A trade is validated only after a pivot-box breakout occurs and all active filters—volume, trend, daily loss limit, and daily trade limit—are satisfied. Position size, stop loss, and take-profit levels are then calculated automatically. Entry arrows and labels on the chart help with later review and analysis.
Setup Guide
Risk percentage is the most critical setting. Beginners should start at 1 percent. Anything above 3 percent becomes aggressive.
ATR stop-loss multipliers should reflect asset volatility.
ATR take-profit multipliers determine reward ratio; 4.0 is the standard.
Volume thresholds are typically set between 50–60 percent depending on market conditions.
Daily loss limits are typically 2–5 percent of the account.
Trading Strategy
This strategy performs best in trending environments and works especially well on the 4-hour and daily charts. New users should begin with all filters enabled and trade conservatively. A minimum of one month of paper trading is recommended before committing real capital.
Suitable Users
The strategy is ideal for beginners who lack risk-management experience as well as advanced traders seeking a customizable structure. It is particularly helpful for traders who struggle with emotional decision-making, as pre-defined limits and rules enforce discipline.
Backtesting Guide
Use at least 2–3 years of historical data that includes bullish, bearish, and sideways conditions.
Target metrics:
Sharpe ratio: 1.5 or higher
Maximum drawdown: below 25 percent
Win rate: 40 percent or higher
Total trades: at least 100 for statistical relevance
Optimization Precautions
Avoid over-fitting parameters. Always test values around the “best” setting to verify stability.
Out-of-sample testing is essential for confirming robustness.
Test across multiple assets and timeframes to ensure consistency.
Live Deployment Roadmap
After successful backtesting, follow a gradual rollout:
Paper trading for at least one month
Small-account live testing
Slow scaling as performance stabilizes
Continuous Improvement
Keep a detailed trading journal and evaluate performance each quarter using recent data.
Adapt settings as market conditions evolve.
Conclusion
Seawolf Pivot Hunter aims to provide more than simple trade signals—it is designed to create a stable and sustainable trading system built on disciplined risk management. No strategy is perfect, and long-term success depends on consistency, patience, and strict adherence to rules. Start small, verify results, and scale progressively.
Disclaimer
This strategy is for educational and research purposes only. Past performance does not guarantee future results. All trading decisions are the responsibility of the user.
개요
Seawolf Pivot Hunter는 기본 피봇 박스 브레이크아웃 전략에 전문적인 리스크 관리 시스템을 더한 실전형 트레이딩 전략입니다. ATR 기반의 손절매와 목표가 설정, 포지션 사이징, 다층 필터링 시스템, 일일 손실 제한 기능을 통해 안정적이고 지속 가능한 트레이딩 환경을 제공합니다. 기본 버전의 장점은 유지하면서 실제 시장에서 발생할 수 있는 위험을 체계적으로 관리할 수 있도록 설계되었습니다.
핵심 철학
트레이딩에서 가장 중요한 것은 수익이 아니라 손실 관리입니다. 아무리 훌륭한 진입 조건이 있어도 한 번의 큰 손실로 모든 수익이 사라질 수 있습니다. 이 전략은 각 거래마다 감수할 리스크를 명확히 계산하고, 최악의 상황에서도 계좌를 보호하기 위한 다양한 안전장치를 제공합니다.
지표 적용 링크 공유
kr.tradingview.com
최적 조건값 설정(예시)
"종목(거래소): ETH/USDT(Binance)", "15 분봉 기준"
-Pivot Detection Length: 5
-Upper Box width: 2
-Lower Box width: 2
-Enable Risk Management: False
-Use Trailing Stop: False
-Use Volume Filter
-Min Buy Volume % for Long: 50
-Min Buy Volume % for Long: 50
-Use Trend Filter(EMA): False
-Enable Max Loss Protection
-Max Daily Loss($): 200
-Max Trades Per Day: 10
-Calucated bars: 50000
리스크 관리 시스템
모든 거래는 진입과 동시에 손절매 주문이 자동 설정됩니다. 손절가는 ATR을 기준으로 계산되며, 시장의 변동성에 따라 자동으로 조정됩니다. 변동성이 큰 시장에서는 넓은 손절폭을, 안정적인 시장에서는 좁은 손절폭을 사용해 불필요한 청산을 줄입니다. 기본값은 ATR의 2배입니다.
목표가는 ATR의 4배를 기본값으로 설정하여 손익비 1:2 구조를 유지합니다. 승률이 50퍼센트만 되어도 수익성이 가능하며, 실제로는 손절은 짧고 이익은 길게 가져가는 방식으로 장기 성과를 확보합니다.
트레일링 스톱 기능도 제공됩니다. 포지션이 수익 구간에 들어서면 손절가가 자동으로 함께 움직이며 수익을 보호합니다. 이 기능은 사용자가 켜거나 끌 수 있습니다.
포지션 크기는 리스크 퍼센트 기반으로 자동 계산됩니다. 예를 들어 리스크를 2퍼센트로 설정하면 손절 시 계좌 자산의 2퍼센트만 잃도록 수량이 조절됩니다. 계좌 크기와 무관하게 항상 일정한 비율의 리스크만 감수하게 되는 방식입니다.
일일 손실 제한 기능은 하루에 허용 가능한 최대 손실을 초과하지 않도록 합니다. 지정 금액에 도달하면 당일 거래는 더 이상 실행되지 않습니다. 감정적 거래를 막고 일정한 규율을 유지하도록 돕습니다.
일일 거래 횟수 제한 기능도 제공됩니다. 기본값은 하루 10회로, 과매매와 수수료 증가를 방지합니다.
필터링 시스템
볼륨 필터는 박스 구간 내 매수·매도 압력을 분석해 진입 신호를 검증합니다. 롱은 매수 볼륨이 일정 비율 이상일 때, 숏은 매도 볼륨이 우세할 때만 진입합니다. 기본값은 55퍼센트입니다.
추세 필터는 EMA를 사용하며, 가격이 200EMA 위에 있을 때는 롱 신호만, 아래에서는 숏 신호만 허용합니다. 큰 추세 방향에만 거래하여 역추세 리스크를 줄입니다.
필터는 독립적으로 켜고 끌 수 있으며, 필터가 많을수록 거래 횟수는 줄지만 신호 품질은 향상됩니다.
실시간 모니터링
화면에 실시간 통계 테이블이 표시되며, 일일 손익, 거래 횟수, 최대 허용 횟수, 현재 거래 가능 여부가 즉시 확인됩니다. 손실 제한 또는 거래 제한 도달 시 시각적으로 표시됩니다.
진입 로직
피봇 박스 브레이크아웃 발생 후 볼륨 필터, 추세 필터, 일일 손실·거래 제한을 모두 통과하면 포지션 크기를 계산하고 손절·목표가를 설정한 뒤 진입합니다. 진입 지점에는 화살표와 레이블이 표시되어 분석에 도움을 줍니다.
설정 가이드
리스크 퍼센트는 가장 중요한 설정입니다. 초보자는 1퍼센트를 추천하며 3퍼센트 이상은 위험합니다.
손절 ATR 배수는 자산 특성에 맞게 조절합니다.
목표가 ATR 배수는 손익비를 결정하며 기본값은 4.0입니다.
볼륨 비율은 시장 상황에 따라 50~60퍼센트 내외로 조정합니다.
일일 손실 제한은 계좌의 2~5퍼센트 수준이 적절합니다.
사용 전략
추세가 명확한 시장에서 가장 효과적이며, 4시간봉 또는 일봉을 추천합니다. 초반에는 모든 필터를 켜고 보수적으로 시작하며, 최소 한 달간 페이퍼 트레이딩을 권장합니다.
적합한 사용자
리스크 관리 경험이 부족한 초보자부터, 커스터마이징을 원하는 경험자까지 폭넓게 적합합니다. 감정적 트레이딩을 억제하는 기능이 있어 규율 유지가 어렵던 트레이더에게 특히 유용합니다.
백테스트 가이드
최소 2~3년 데이터로 테스트하며, 상승·하락·횡보 모두 포함해야 합니다.
샤프비율 1.5 이상, 최대 낙폭 25퍼센트 이하를 목표로 합니다.
승률은 40퍼센트 이상이면 충분합니다.
최소 100회 이상 거래가 있어야 통계적으로 의미가 있습니다.
최적화 주의사항
과최적화를 피하고 주변 값도 테스트해야 합니다.
샘플 외 기간 검증은 필수입니다.
여러 자산·여러 시간대에서 테스트하여 일관성을 확인해야 합니다.
실전 적용 로드맵
백테스트 후 바로 실전 투입하지 말고, 한 달 이상의 페이퍼 트레이딩 → 소액 실전 → 점진적 확대 순으로 진행합니다.
지속적 개선
일지를 기록하고 분기마다 최신 데이터로 점검합니다.
시장 변화에 따라 유연하게 조정해야 합니다.
마치며
Seawolf Pivot Hunter는 단순 신호 제공을 넘어, 안전하고 지속 가능한 트레이딩 환경 구축을 목표로 합니다. 어떤 전략도 완벽할 수 없으며, 장기적 성공을 위해서는 규칙 준수와 인내가 가장 중요합니다. 충분한 검증을 거쳐 작은 금액으로 시작하고 점진적으로 확장해나가는 접근을 추천합니다.
면책 조항
이 전략은 교육 및 연구 목적이며, 과거 성과는 미래를 보장하지 않습니다. 모든 투자 결정은 본인의 판단과 책임 하에 이루어져야 합니다.
Göstergeler ve stratejiler
Bitcoin & Ethereum Profitable Crypto Investor – FREE EditionBitcoin & Ethereum Profitable Crypto Investor – FREE Edition
by RustyTradingScripts
This is the free, simplified edition of my long-term crypto trend-following strategy designed for Bitcoin, Ethereum, and other major assets. It provides an accessible introduction to the core concepts behind the full version while remaining easy to use, transparent, and beginner-friendly.
This FREE edition focuses on a single technical component: a 102-period Simple Moving Average trend model. When price moves above the SMA, the script considers it a potential long trend environment. When the slope begins to turn down, the strategy exits the position. This creates a straightforward, rules-based framework for identifying trend shifts without emotional or discretionary decision-making.
The goal of this simplified version is to help users understand how a structured trend approach behaves during different market conditions. It demonstrates how using a slow, objective indicator can reduce noise and provide clearer long-term directional context on higher timeframes such as the 10-hour BTC chart shown in the backtest example.
What This FREE Version Includes
- Trend-based entries using a 102-period SMA
- Automatic exits when the SMA slope turns down
- Clean visual plot of the moving average
- No repainting — signals are based on confirmed bar data
- Works on BTC, ETH, and other major crypto assets
- User-adjustable SMA length for customization
What’s Not Included in This Version:
This edition intentionally focuses on the essential trend logic only.
It does NOT include the following components found in the full investor strategy:
- Linear regression smoothing
- Seasonal filters
- Price-extension filtering
- Volume-based protection
- Partial stop-loss and partial take-profit systems
- Cooldown logic after profitable trades
- RSI-based extended exits
- Multi-layered trade management modules
The purpose of this free version is to provide a clear, functional introduction to the underlying trend concept without the advanced filters and risk-management features that are part of the complete system.
How to Use It
Apply the script to your preferred asset and timeframe (commonly higher timeframes such as 4H, 8H, 10H, 12H, or 1D). The script will enter long positions when the market is trading above the SMA and exit when the slope of the average begins to point downward. Users may adjust the SMA length to match their preferred level of responsiveness.
Important Notes
This script is for educational and analytical purposes.
Historical results are not guarantees of future performance.
Always practice proper risk management and perform your own testing.
This script does not repaint.
This FREE version is meant as a helpful starting point for those exploring long-term crypto trend strategies. If you find it useful and wish to explore more advanced tools, feel free to reach out for additional information.
RSI BREAKOUT SIGNALSThis BB + RSI Breakout indicator is designed to help traders identify potential buy and sell opportunities based on price movements relative to the Donchian channel (or Bollinger-type channel) and momentum conditions. It calculates the highest high and lowest low over a user-defined length to form a dynamic channel, and then it checks whether the current price breaks above the upper band (for a buy signal) or below the lower band (for a sell signal). To avoid repeated signals in a row, the indicator uses a state system: after a buy signal occurs, it will not generate another buy until a sell occurs, and vice versa. When a buy signal is triggered, it automatically calculates a take-profit price a certain percentage above the buy candle and displays this price below the candle as a “TP” label. Sell signals are displayed above the candle, and any previous TP label is cleared. The indicator updates in real time, so the signals move with the chart, giving a clear and lag-free visualization of entry points and potential profit targets.
BTC EMA 5-9 Flip Strategy AutobotThis strategy is designed for fast and accurate trend-following trades on Bitcoin.
It uses a crossover between EMA 5 and EMA 9 to detect instant trend reversals and automatically flips between Long and Short positions.
How the strategy works
EMA 5 crossing above EMA 9 → Long
EMA 5 crossing below EMA 9 → Short
Automatically closes the opposite trade during a flip
Executes trades only on candle close
Prevents double entries with internal position-state logic
Fully compatible with automated trading via webhooks (Delta Exchange)
Why this strategy works
EMA 5–9 is extremely responsive for BTC’s volatility
Captures trend reversals early
Works best on 15-minute timeframe
Clean, simple logic without over-filtering reduces missed opportunities
Performs well in both uptrends and downtrends
Automation Ready
This strategy includes alert conditions and webhook-ready JSON for automated execution.
This is a fast-reacting BTC bot designed for intraday and swing crypto trend trading.
TradeX Labs Pivot MasterLucrorStrategies — Automated Price Action Execution Framework
This indicator-strategy automation is built for traders who want a simple, consistent, and rules-based trading system—no multi-timeframe chaos or overcomplicated confirmation layers. It trades purely from prior-day price action, keeping volatility, structure, and logic constant across all sessions.
Every entry, stop, and target comes directly from the same volatility-adjusted model. If the trade can’t fit your defined dollar risk, it simply won’t execute or plot.
⸻
IMPORTANT NOTE
***Since TradingView utilizes close of bar for plots, this is best utilized for real time entry/exit signals on 1 second charts or lower. If you do not have 1 second charts we can not recommend you to upgrade your subscription but we HIGHLY recommend utilizing this script on a 1 second chart. If utilizing on any higher time frame any signals or trade logic will be delayed and inaccurate or signals can be entirely skipped altogether and populate incorrect entries***
⸻
Purpose & Core Design
The framework is anchored to prior-day settlement data and mathematically transforms it into real-time, session-specific trading levels. This creates a daily map of opportunity that evolves with volatility while maintaining a consistent structure.
This approach eliminates guesswork and ensures the same conditions that produced historical edge apply to every live session.
⸻
Key Inputs & Control
1. Dollar Risk
Set your maximum dollar risk per trade. The system automatically sizes positions to stay at or below that risk limit based on stop distance.
• If the trade qualifies: a red-to-green gradient fill and entry label appear.
• If not: no fill, no entry, no false visual signals.
2. Timer Exit (Default: 30 Minutes)
The strategy is designed for momentum capture in the first 30 minutes after market open. If a trade remains active beyond that time, it is closed automatically.
All back tests and live reports reference this same window to maintain integrity. (Adjustable if you wish.)
3. Days to Keep Lines
Controls how many sessions of plotted levels and fills stay visible (up to 10).
To explore further back, use TradingView’s replay mode. The indicator will continue plotting as far as platform data allows.
4. Font & Label Size
• Price Label Size: Adjusts the numerical price levels beside pivots for manual pre-market entries.
• Level Label Size: Controls the on-chart text size for active trade signals. Both fully customizable.
⸻
Level Structure & Trade Mechanics
All plotted levels originate from a proprietary prior-day volatility formula. You will see:
• Middle Green Horizontal Lines — Support Levels
These mark historically reactive zones where price has a higher probability of holding or bouncing.
• Middle Blue Horizontal Lines — Resistance Levels
These represent opposing zones where price tends to reject or stall.
(Solid and dotted variants handle different roles in execution logic.)
• Red Horizontal Lines — Points of Control (POC Zones)
These are high-impact levels where price historically either rejects violently or breaks with strength.
⸻
Trade Logic
Long Trades
• Trigger: The solid blue line above the current structure acts as the long trigger.
• Stop: The solid blue line below is the stop-loss.
• Target: The next solid blue line above serves as the target.
Long trades are executed when price hits the solid blue trigger above the current level, using solid levels exclusively for entry, stop, and target.
Short Trades
• Trigger: The dotted blue line below the current structure is the short trigger.
• Stop: The dotted blue line above is the stop-loss.
• Target: The next dotted blue line below becomes the target.
Short trades use only dotted levels to define all key mechanics — entry, stop, and target — keeping short setups visually distinct and structurally independent from longs.
This dual structure allows for clean, symmetrical trade logic across both sides of the market, with consistent volatility mapping from prior-day data.
⸻
High-Priority Red Levels (Points of Control)
Red horizontal levels represent areas of major interest — typically where institutional activity concentrated previously. Price often reacts sharply here: either reversing instantly or breaking through with momentum.
These are optional reference points but often signal where the strongest reactions occur.
⸻
Visualization & Behavior
• Executed trades show the red-to-green gradient fill.
• Trades that exceed risk parameters simply do not appear.
• Levels remain clean and persistent day to day for back testing, journaling, or educational
use.
⸻
Disclaimer
This is a closed, proprietary LucrorStrategies tool. It is provided for analytical and educational use only. It does not predict price or guarantee profit. All trade execution, configuration, and outcomes remain the responsibility of the user.
CongTrader Strategy V1📈 CongTrader Strategy V1 — Official Overview
CongTrader Strategy V1 is a precision-built algorithm designed for intraday and swing traders who want a structured, rules-driven approach to capturing directional momentum while avoiding low-quality market conditions.
This strategy combines volatility-based logic, trend confirmation filters, and a market-conditioning engine to produce high-probability long and short signals with strictly candle-close confirmed entries (no intrabar repainting).
🔍 Core Philosophy
Modern markets move in bursts of volatility that are often preceded by subtle shifts in momentum and structure.
CongTrader V1 is engineered to:
identify emerging directional pressure early
filter out noise, consolidation, and choppy environments
only execute when multiple conditions align
maintain consistent, disciplined trade management
The result is a strategy that aims to trade quality over quantity, focusing on clear, structured setups rather than impulsive, intrabar signals.
🧠 Key Components (High-Level Explanation)
1️⃣ Directional Signal Engine (Trigger System)
The strategy uses a custom momentum-oscillation model to detect potential turning points and trend continuations.
This engine smooths price action, measures pressure extremes, and generates trigger crossovers that signal potential long or short opportunities.
(The exact formula and coefficients are proprietary and not displayed.)
2️⃣ ATR-Based Risk Management
Each trade is automatically paired with:
a volatility-adaptive stop loss, and
a volatility-adaptive profit target
This allows the strategy to adjust position management dynamically based on current market movement rather than fixed pip or dollar distances.
3️⃣ Trend Confirmation Filter (EMA)
A long-term EMA trend filter prevents counter-trend entries by ensuring:
Long positions trade only above trend
Short positions trade only below trend
This keeps signals aligned with higher-timeframe momentum.
4️⃣ VWAP Institutional Bias Filter
VWAP is used as a dynamic market fair-value reference.
The strategy only trades when price action shows favorable positioning relative to VWAP—helping avoid false moves and mean-reversion traps.
5️⃣ Range & Volatility Filter
A volatility/range filter avoids entering during tight consolidations.
If the market is not moving or lacks range expansion, the strategy waits patiently.
This significantly reduces chop and whipsaw trades.
6️⃣ RTH (Regular Trading Hours) Protection
Optionally limits trades to regular exchange hours for traders who avoid low-liquidity overnight sessions.
⏳ Candle-Close Entry Confirmation (No Repainting)
All entries are strictly confirmed after the bar closes, which means:
No intrabar fakeouts
No signal disappearance
No repainting
Cleaner, more realistic backtesting
This ensures the strategy behaves the same in backtests and in live charts.
🎯 Trade Logic Summary
A trade is only taken when:
✔ A directional trigger signal occurs
✔ Price meets VWAP bias conditions
✔ Price aligns with the long-term trend
✔ Sufficient volatility/range is present
✔ (Optional) Within regular trading hours
✔ The candle has fully confirmed
Every trade is managed automatically with ATR-based stop loss and take profit placement.
📊 Who This Strategy Is For
CongTrader V1 works well for:
Intraday traders (1–15m)
Swing traders (30m–4h)
Momentum and trend-followers
Algorithmic traders looking for disciplined, rules-based entries
Traders who want cleaner signals and less noise
Anyone who wants to avoid low-quality, choppy markets
🔔 Alerts Included
Built-in alerts notify you instantly when conditions for long or short entries are met, making it suitable for:
Manual execution
Automated trading systems
Signal services
🧩 Important Note
This strategy is designed for educational purposes and is not financial advice. Performance may vary depending on market conditions, broker feed, and instrument volatility. Always backtest thoroughly and use risk management.
Cognex Fibonacci Breakout StrategyTHE COMPLETE TRADE LOGIC (What We Want):
Step 1: Morning Session (9:30-10:30)
Track session high and low
Step 2: After 10:30 - Wait for Breakout
Bullish: Close above session high
Bearish: Close below session low
Step 3: Track Extreme After Breakout
Keep updating highest_after_breakout or lowest_after_breakout
This continuously updates as price makes new extremes
Step 4: Detect 28% Retracement (THE LOCK)
When price retraces to 28%, set last_extreme_for_retracement to the current extreme
This LOCKS the extreme for fibonacci calculations
fib_100 should use this locked value
Step 5: Place Limit Order EARLY (at 20% retracement)
When price retraces to 20%, place limit order at 28% entry
This is so the order is ready when price hits 28%
Step 6: Cancel & Recalculate if New Extreme
If price makes a NEW extreme AFTER the order is placed
Cancel the old order
Wait for new 20% retracement to place new order
Step 7: One Trade Per Day
Only ONE order placement attempt per day
Even if cancelled, don't try again
TSI.LTA | Base BTC 1DTSI.LTA | Base BTC 1D is a closed‑source trend‑following strategy designed for BTC on the 1D timeframe .
It focuses on participating in the main directional moves of the market while avoiding as much short‑term noise as possible.
📊 The script:
Uses a combination of moving‑average–based filters and volatility bands to define the active trend.
Applies optional volume filters to avoid low‑participation or exhausted moves.
Includes risk‑management controls (Stop Loss, Take Profit, Trailing Stop) that work on a per‑trade basis.
All entries and exits are confirmed at bar close and the script does not repaint .
This makes it suitable for backtesting, alerts and external automation.
█ 💡 CONCEPTS
This strategy is built around a few simple ideas:
1 — Trend first.
Positions are only taken when a group of smoothed trend filters agree on direction.
The goal is to ride larger swings, not to scalp each fluctuation.
2 — Volatility awareness.
Standard‑deviation–based bands help avoid entries in abnormal spikes or during very compressed ranges.
3 — Participation filter.
Optional volume‑based conditions (VWMA, OBV slope, MFI, volume Z‑score) try to ensure that entries occur when the market shows enough activity, not during dead phases.
4 — Risk defined in advance.
Stop‑loss and trailing‑stop inputs are expressed as percentages relative to entry price, so users can align them with their own risk tolerance.
The logic is purposely conservative: it is expected to stay flat during parts of the market where the trend is unclear or participation is weak.
█ ⚙️ FEATURES & INPUTS
This section follows approximately the order of the script’s inputs, so users can read here and then match what they see in the “Inputs” tab.
1 — 📐 Trend filters
These inputs control how the strategy detects the underlying trend:
DEMA / Gaussian / SMMA lengths
Control how fast or slow the trend reacts to price changes.
Shorter lengths → more responsive, more trades, more noise.
Longer lengths → slower reaction, fewer trades, more filtering.
Volatility Bands (SD length & multipliers)
Standard‑deviation bands around the smoothed price series.
They are used to avoid entries during extreme moves or very narrow ranges where a breakout is not yet confirmed.
In practice, these settings let the user choose between a more “aggressive” trend follower (shorter lengths, smaller bands) or a more “patient” one.
2 — 📊 Volume filters (optional)
These filters are meant to restrict trades to periods where the market shows meaningful participation:
VWMA filter
Requires price to be aligned with a Volume‑Weighted Moving Average, which de‑emphasizes moves on very low volume.
OBV slope filter
Uses the slope of On‑Balance Volume to check that net volume flow supports the direction of the trade.
MFI band filter
Uses the Money Flow Index to avoid taking new entries in zones that often correspond to exhaustion (extreme values defined by the user).
Volume Z‑Score
Compares current volume to its recent history. Trades can be restricted when volume is unusually low or out of character for that period.
When any of these filters are turned off, the strategy relies only on price‑based trend and volatility logic.
When they are on, trades are more selective and may be fewer.
3 — 🛡️ Risk management
These inputs define how individual trades are managed once entered.
They do not change the trend logic itself:
Stop Loss (%)
A percentage move against the entry price that will close the position.
Typical values on BTC 1D remain in the single‑digit range so that no single trade risks an unrealistic portion of equity.
Take Profit (%)
An optional fixed target that closes the trade when price has moved a chosen percentage in favor.
This can be disabled if the user prefers to let the trend filters perform the exit.
Trailing Stop (%)
A stop that follows the most favorable price reached since entry.
When the “use lower timeframe peak” option is enabled, peaks can be detected on a lower timeframe for more granular trailing, while decisions still occur at the close of the 1D bar.
Fixed SL/TP Price and Activation Date
Allow defining absolute price levels and a date from which they start applying.
This is useful when the user wants structural protection around known price zones.
The combination of these controls determines how deep a pullback the user is willing to tolerate and how much profit they are prepared to give back in order to stay in trends.
4 — 🚫 Filter failure & cooldown
To avoid over‑trading in difficult environments, the script can:
Automatically exit when filters remain unfavorable for a configurable number of bars.
Enter a cooldown period, during which no new trades are taken, even if some conditions improve.
These mechanisms are intended to protect capital during choppy or low‑quality phases rather than force constant exposure.
█ 📚 HOW TO USE
A suggested process for using this strategy as a study tool:
1 — Start on BTC 1D.
Apply the script to BTCUSD or BTC/USDT on the 1D timeframe, with default inputs.
2 — Open the Strategy Tester.
Choose a time window (for example a full halving cycle, a crash + recovery period, or just the most recent bull leg).
3 — Compare with Buy & Hold.
For the same window, look at:
Net profit of the strategy vs Buy & Hold.
Max drawdown of the strategy vs Buy & Hold.
The goal is not to hit a particular number, but to see whether, in that window, the strategy manages to:
Provide a smoother equity curve (lower drawdown),
While still performing at least as well as, or better than, simply holding the asset.
4 — Experiment with risk inputs.
Vary Stop Loss, Trailing Stop and the volume filters.
After each change, re‑check the same two questions above. This should make clear how each input affects the trade‑off between participation and risk.
5 — Forward‑test.
Before using any configuration with real capital, let it run for a while in paper‑trading or demo conditions.
█ 🚧 LIMITATIONS
The strategy is built and tuned primarily for BTC on 1D.
It can be used on other symbols and timeframes, but behavior may differ and requires new testing.
In very tight ranges or during event‑driven gaps, trend logic may enter later than discretionary trading would. This is expected for a conservative trend‑following approach.
Results from historical backtests depend on data quality, broker settings, fees and slippage configured in the Strategy Tester.
█ 📝 NOTES
Signals are generated on bar close.
The script is closed‑source, but the description explains the main ideas so users and moderators can understand what it does and how to use it.
The HUD on the chart is meant as a compact summary of the same statistics available in the Strategy Tester; it simply makes comparisons quicker.
█ ⚠️ DISCLAIMER
This strategy is provided for educational and research purposes only .
It is not financial advice and does not recommend any specific trades, assets, position sizes, or risk levels.
Users are fully responsible for:
Choosing their own risk parameters (Stop Loss, Take Profit, Trailing Stop, position sizing, etc.).
Testing the script on the markets and timeframes they intend to trade.
Verifying that any configuration is appropriate for their capital, risk tolerance and jurisdiction.
Past performance in backtests or examples does not guarantee future results.
Always test carefully before considering any live deployment.
RubberBand Scalp NQ Strategy (V6 - High PF Focus)
================================================================================
RUBBERBAND SCALP NQ (V6 - HIGH PF FOCUS)
================================================================================
// STRATEGY OVERVIEW
// -----------------
// Instrument: NQ (Nasdaq 100 E-mini Futures)
// Style: Intraday mean-reversion scalping
// Core Idea: Price "stretches" away from VWAP, then "snaps back" → enter on strong reversal
// Session: 9:00 AM – 2:30 PM CST (America/Chicago)
// Timeframe: 1–5 min (ideal: 2–3 min)
// Position: 2 contracts, pyramiding = 0
// Commission: $2.00 per contract
// Goal: High Profit Factor via asymmetric exits (1R fixed + unlimited runner)
// KEY FILTERS
// -----------
// • Only trade when ATR(15) > 5.0 points (~$100 range) → avoids chop
// • Must be in session → forces flat at 2:30 PM
// • VWAP proximity: price must touch within 0.5 × ATR of VWAP
// ENTRY LOGIC (LONG)
// -----------------
// 1. In session & no position
// 2. Close > Open (bullish bar)
// 3. Close > highest high of last 4 bars → momentum confirmation
// 4. Close > VWAP
// 5. Low < VWAP + (0.5 × ATR) → pullback reached VWAP zone
// 6. ATR > 5.0
// 7. Bar confirmed
// → Plot green triangle below bar
// ENTRY LOGIC (SHORT) – Symmetric
// -----------------
// 1. Close < Open
// 2. Close < lowest low of last 4 bars
// 3. Close < VWAP
// 4. High > VWAP - (0.5 × ATR)
// 5. ATR > 5.0
// → Plot red triangle above bar
// STOP LOSS – DUAL SYSTEM (Widest Stop Wins)
// -----------------------------------------
// VWAP Stop (Long): VWAP - 0.20
// ATR Stop (Long): Close - min(ATR × 1.0, 15.0)
// Final Stop: MAX(VWAP Stop, ATR Stop) → then CAP at Close - 0.20
// Short: MIN of both → FLOOR at Close + 0.20
// → Max buffer: 0.20 pts = $20 (4 ticks)
// → Risk = |Entry – Final Stop|
// PROFIT TAKING – 2 CONTRACTS
// ---------------------------
// Contract #1: Fixed 1R → limit = entry + risk (long) / entry - risk (short)
// Contract #2: Trailing stop only → trail_points = risk, trail_offset = 0
// NO FIXED TAKE PROFIT ON RUNNER → lets 3R, 5R, 10R+ winners run
// BUG: Short runner uses trail_offset = 1.5 → CHANGE TO 0
// V6 IMPROVEMENTS
// ---------------
// 1. ATR_STOP_MULTIPLIER reduced from 1.5 → 1.0 → tighter average loss
// 2. Removed fixed 2R cap on runner → unlimited upside
// 3. Widest-stop logic → prevents premature stop-outs
// TRADE EXAMPLE (LONG)
// -------------------
// Entry: 18,125 (2 contracts)
// Stop: 18,110 → Risk = $300/contract
// 1R: 18,155 → Contract #1 exits (+$600)
// Runner trails by $300 → exits at 18,425 (+$6,000)
// Total P&L: +$6,600
// PERFORMANCE EXPECTATIONS
// ------------------------
// Win Rate: 40–50%
// Avg Winner: >3× avg loser
// Profit Factor: 2.0–3.5+
// Max Drawdown: <5% (with risk controls)
// DAILY CHECKLIST
// ---------------
// 2–3 min NQ chart
// Timezone: America/Chicago
// ATR > 5.0
// Price touched VWAP zone
// 4-bar breakout confirmed
// trail_offset = 0 (both sides)
// Alerts on
// Log R-multiple
// FINAL NOTES
// -----------
// This is a PROFIT FACTOR system — not a high win-rate system.
// Success = discipline + volatility + clean execution.
================================================================================
GOLDM Dow Theory – 1H Trend + 5m Pullback1. Strategy Overview
Instrument: MCX GOLDM
Chart timeframe: 5 minutes
Side: Long-only
Position size: Fixed 3 lots
Core idea:
Trade only in 1H uptrend, enter after a 5m pullback and breakout, with basic volume/volatility filters and ATR-based SL/TP.
2. High-Level Logic Flow (Per Bar)
On every 5-minute bar, the script does this:
Update session/time, volume, and ATR filters
Read 1H trend from higher timeframe
Update 5m pullback state (whether a valid dip happened)
Check if there is a valid breakout back in the direction of the 1H trend
If all filters + conditions align → enter Long (3 lots)
While in a trade:
Manage SL/TP using ATR
Close trade if 1H trend flips down or price closes below 5m EMA
Everything else (plots, alerts) is just for visibility and convenience.
3. Inputs & Configuration
Main inputs:
pullbackLookback – how many 5m bars to look back to detect a pullback
breakoutLookback – how many bars to consider for recent swing high
emaLenTrendFast / emaLenTrendSlow – 1H EMAs (50/200) for trend
emaLenPullback – 5m EMA used for pullback logic (default 20)
tradeSession – default "0900-2315" (you can change)
volLookback, volMult – volume filter
atrLen, atrSmaLen – ATR filter
slATRmult (1.4), tpATRmult (3.0) – ATR multiples → ~1.4 : 3 RR
4. Session / Time Filter
tradeSession = "0900-2315"
inSession = not useSessionFilter or not na(time(timeframe.period, tradeSession))
Only allows entries when the current bar’s time is inside 09:00–23:15.
If useSessionFilter is false, this filter is ignored.
No trade opens outside this window, but existing trades can still exit.
5. Volume & Volatility Filters
Volume Filter
avgVol = ta.sma(volume, volLookback)
highVolume = not useVolumeFilter or (volume > avgVol * volMult)
If enabled, current bar’s volume must be greater than average volume × multiplier.
Purpose: avoid thin, illiquid periods.
ATR Filter
atr5 = ta.atr(atrLen)
atrSma = ta.sma(atr5, atrSmaLen)
goodATR = not useATRFilter or (atr5 > atrSma)
If enabled, current ATR must be above its own moving average.
Purpose: avoid flat / extremely low-volatility periods.
Only if both highVolume and goodATR are true, the system considers entering.
6. Higher Timeframe Trend (1H)
emaFast1h = request.security(syminfo.tickerid, "60", ta.ema(close, emaLenTrendFast), ...)
emaSlow1h = request.security(syminfo.tickerid, "60", ta.ema(close, emaLenTrendSlow), ...)
trendUp = emaFast1h > emaSlow1h
trendDown = emaFast1h < emaSlow1h
On the 1-hour timeframe:
If EMA Fast (50) > EMA Slow (200) → trendUp = true
If EMA Fast (50) < EMA Slow (200) → trendDown = true
This is the core trend filter:
We only look for longs when trendUp is true.
7. 5-Minute Structure Logic (Dow-style)
7.1 Pullback Detection
emaPull = ta.ema(close, emaLenPullback)
pulledBackLong = ta.lowest(close, pullbackLookback) < emaPull
A pullback is defined as:
In the last pullbackLookback bars, price closed below the 5m EMA (emaPull) at least once.
This indicates a dip against the 1H uptrend.
A state flag tracks this:
var bool hadLongPullback = false
hadLongPullback := trendUp and pulledBackLong ? true : (not trendUp ? false : hadLongPullback)
When:
trendUp AND pulledBackLong → hadLongPullback = true.
If the trend stops being up (trendUp = false), flag resets to false.
So the system remembers:
“There has been a proper dip while the 1H uptrend is active.”
7.2 Breakout Confirmation
recentHigh = ta.highest(high, pullbackLookback)
breakoutUp = close > recentHigh
After a pullback, we wait for price to close above the highest high of recent bars (excluding the current one).
This mimics:
“Higher high after a higher low” → breakout in Dow Theory terms.
8. Final Long Entry Logic
The base entry condition:
baseLongEntry =
trendUp and
hadLongPullback and
breakoutUp and
close > emaPull
Translated:
1H trend is up (trendUp).
A valid pullback happened recently (hadLongPullback).
Current candle broke above the recent swing high (breakoutUp).
Price is now back above the 5m EMA (pullback is resolving, not deepening).
Then filters are applied:
longEntryCond =
baseLongEntry and
inSession and
highVolume and
goodATR and
not isLong
So a long entry only occurs if:
Core structure conditions (baseLongEntry) are true
Time is within session
Volume is high enough
ATR is healthy
You are not already in a long
When longEntryCond is true:
if longEntryCond
strategy.entry("Long", strategy.long, comment = "Dow Long: Trend+PB+BO")
hadLongPullback := false
Enters 3 lots long (as per default_qty_type + default_qty_value).
Resets hadLongPullback so we don’t re-use the same pullback.
9. Exit Logic
There are two exit layers:
9.1 Logical Exit (Trend or Structure Change)
exitLongTrendFlip = trendDown
exitLongEMA = ta.crossunder(close, emaPull)
longExitCond = isLong and (exitLongTrendFlip or exitLongEMA)
If in a long:
Exit when trend flips down (1H EMA50 < EMA200), OR
Price crosses below 5m EMA (pullback may be turning into reversal).
Then:
if longExitCond
strategy.close("Long", comment = "Exit Long: Trend flip / EMA break")
This closes the position at market (on bar close).
9.2 ATR-based Stop Loss & Take Profit
if useSLTP and isLong
longStop = strategy.position_avg_price - atr5 * slATRmult
longLimit = strategy.position_avg_price + atr5 * tpATRmult
strategy.exit("Long SLTP", "Long", stop = longStop, limit = longLimit)
SL = entry price – 1.4 × ATR(14, 5m)
TP = entry price + 3.0 × ATR(14, 5m)
This gives roughly 1.4 : 3 RR.
If SL or TP is hit, strategy.exit will close the trade.
So exits can come from:
Hitting Stop Loss
Hitting Take Profit
OR logic-based exit (trend flip / EMA break)
10. Alerts
Two alertconditions:
alertcondition(longEntryCond, title="Long Entry Signal",
message="GOLDM LONG: 1H Uptrend + 5m Pullback Breakout + Filters OK")
alertcondition(longExitCond, title="Long Exit Signal",
message="GOLDM LONG EXIT: Trend flip or EMA break")
You can set TradingView alerts based on:
“Long Entry Signal” → tells you when all entry conditions align.
“Long Exit Signal” → tells you when the logic-based exit triggers.
(ATR SL/TP exits won’t auto-alert unless you separately set price alerts or add extra conditions.)
11. Mental Model Summary (How YOU should think about it)
For every trade, the system is basically doing this:
Is GOLDM in an uptrend on 1H?
→ If no: do nothing
Did we get a clear dip below 5m EMA in that uptrend?
→ If no: wait
Did price then break above recent highs and reclaim EMA20?
→ If yes: this is our Dow-style continuation entry
Is market liquid and moving (volume + ATR)?
→ If yes: go Long with 3 lots
Manage with:
ATR SL & TP
Exit early if 1H trend flips or price falls back below EMA20
SP500 Session Gap Fade StrategySummary in one paragraph
SPX Session Gap Fade is an intraday gap fade strategy for index futures, designed around regular cash sessions on five minute charts. It helps you participate only when there is a full overnight or pre session gap and a valid intraday session window, instead of trading every open. The original part is the gap distance engine which anchors both stop and optional target to the previous session reference close at a configurable flat time, so every trade’s risk scales with the actual gap size rather than a fixed tick stop.
Scope and intent
• Markets. Primarily index futures such as ES, NQ, YM, and liquid index CFDs that exhibit overnight gaps and regular cash hours.
• Timeframes. Intraday timeframes from one minute to fifteen minutes. Default usage is five minute bars.
• Default demo used in the publication. Symbol CME:ES1! on a five minute chart.
• Purpose. Provide a simple, transparent way to trade opening gaps with a session anchored risk model and forced flat exit so you are not holding into the last part of the session.
• Limits. This is a strategy. Orders are simulated on standard candles only.
Originality and usefulness
• Unique concept or fusion. The core novelty is the combination of a strict “full gap” entry condition with a session anchored reference close and a gap distance based TP and SL engine. The stop and optional target are symmetric multiples of the actual gap distance from the previous session’s flat close, rather than fixed ticks.
• Failure mode it addresses. Fixed sized stops do not scale when gaps are unusually small or unusually large, which can either under risk or over risk the account. The session flat logic also reduces the chance of holding residual positions into late session liquidity and news.
• Testability. All key pieces are explicit in the Inputs: session window, minutes before session end, whether to use gap exits, whether TP or SL are active, and whether to allow candle based closes and forced flat. You can toggle each component and see how it changes entries and exits.
• Portable yardstick. The main unit is the absolute price gap between the entry bar open and the previous session reference close. tp_mult and sl_mult are multiples of that gap, which makes the risk model portable across contracts and volatility regimes.
Method overview in plain language
The strategy first defines a trading session using exchange time, for example 08:30 to 15:30 for ES day hours. It also defines a “flat” time a fixed number of minutes before session end. At the flat bar, any open position is closed and the bar’s close price is stored as the reference close for the next session. Inside the session, the strategy looks for a full gap bar relative to the prior bar: a gap down where today’s high is below yesterday’s low, or a gap up where today’s low is above yesterday’s high. A full gap down generates a long entry; a full gap up generates a short entry. If the gap risk engine is enabled and a valid reference close exists, the strategy measures the distance between the entry bar open and that reference close. It then sets a stop and optional target as configurable multiples of that gap distance and manages them with strategy.exit. Additional exits can be triggered by a candle color flip or by the forced flat time.
Base measures
• Range basis. The main unit is the absolute difference between the current entry bar open and the stored reference close from the previous session flat bar. That value is used as a “gap unit” and scaled by tp_mult and sl_mult to build the target and stop.
Components
• Component one: Gap Direction. Detects full gap up or full gap down by comparing the current high and low to the previous bar’s high and low. Gap down signals a long fade, gap up signals a short fade. There is no smoothing; it is a strict structural condition.
• Component two: Session Window. Only allows entries when the current time is within the configured session window. It also defines a flat time before the session end where positions are forced flat and the reference close is updated.
• Component three: Gap Distance Risk Engine. Computes the absolute distance between the entry open and the stored reference close. The stop and optional target are placed as entry ± gap_distance × multiplier so that risk scales with gap size.
• Optional component: Candle Exit. If enabled, a bullish bar closes short positions and a bearish bar closes long positions, which can shorten holding time when price reverses quickly inside the session.
• Session windows. Session logic uses the exchange time of the chart symbol. When changing symbols or venues, verify that the session time string still matches the new instrument’s cash hours.
Fusion rule
All gates are hard conditions rather than weighted scores. A trade can only open if the session window is active and the full gap condition is true. The gap distance engine only activates if a valid reference close exists and use_gap_risk is on. TP and SL are controlled by separate booleans so you can use SL only, TP only, or both. Long and short are symmetric by construction: long trades fade full gap downs, short trades fade full gap ups with mirrored TP and SL logic.
Signal rule
• Long entry. Inside the active session, when the current bar shows a full gap down relative to the previous bar (current high below prior low), the strategy opens a long position. If the gap risk engine is active, it places a gap based stop below the entry and an optional target above it.
• Short entry. Inside the active session, when the current bar shows a full gap up relative to the previous bar (current low above prior high), the strategy opens a short position. If the gap risk engine is active, it places a gap based stop above the entry and an optional target below it.
• Forced flat. At the configured flat time before session end, any open position is closed and the close price of that bar becomes the new reference close for the following session.
• Candle based exit. If enabled, a bearish bar closes longs, and a bullish bar closes shorts, regardless of where TP or SL sit, as long as a position is open.
What you will see on the chart
• Markers on entry bars. Standard strategy entry markers labeled “long” and “short” on the gap bars where trades open.
• Exit markers. Standard exit markers on bars where either the gap stop or target are hit, or where a candle exit or forced flat close occurs. Exit IDs “long_gap” and “short_gap” label gap based exits.
• Reference levels. Horizontal lines for the current long TP, long SL, short TP, and short SL while a position is open and the gap engine is enabled. They update when a new trade opens and disappear when flat.
• Session background. This version does not add background shading for the session; session logic runs internally based on time.
• No on chart table. All decisions are visible through orders and exit levels. Use the Strategy Tester for performance metrics.
Inputs with guidance
Session Settings
• Trading session (sess). Session window in exchange time. Typical value uses the regular cash session for each contract, for example “0830-1530” for ES. Adjust if your broker or symbol uses different hours.
• Minutes before session end to force exit (flat_before_min). Minutes before the session end where positions are forced flat and the reference close is stored. Typical range is 15 to 120. Raising it closes trades earlier in the day; lowering it allows trades later in the session.
Gap Risk
• Enable gap based TP/SL (use_gap_risk). Master switch for the gap distance exit engine. Turning it off keeps entries and forced flat logic but removes automatic TP and SL placement.
• Use TP limit from gap (use_gap_tp). Enables gap based profit targets. Typical values are true for structured exits or false if you want to manage exits manually and only keep a stop.
• Use SL stop from gap (use_gap_sl). Enables gap based stop losses. This should normally remain true so that each trade has a defined initial risk in ticks.
• TP multiplier of gap distance (tp_mult). Multiplier applied to the gap distance for the target. Typical range is 0.5 to 2.0. Raising it places the target further away and reduces hit frequency.
• SL multiplier of gap distance (sl_mult). Multiplier applied to the gap distance for the stop. Typical range is 0.5 to 2.0. Raising it widens the stop and increases risk per trade; lowering it tightens the stop and may increase the number of small losses.
Exit Controls
• Exit with candle logic (use_candle_exit). If true, closes shorts on bullish candles and longs on bearish candles. Useful when you want to react to intraday reversal bars even if TP or SL have not been reached.
• Force flat before session end (use_forced_flat). If true, guarantees you are flat by the configured flat time and updates the reference close. Turn this off only if you understand the impact on overnight risk.
Filters
There is no separate trend or volatility filter in this version. All trades depend on the presence of a full gap bar inside the session. If you need extra filtering such as ATR, volume, or higher timeframe bias, they should be added explicitly and documented in your own fork.
Usage recipes
Intraday conservative gap fade
• Timeframe. Five minute chart on ES regular session.
• Gap risk. use_gap_risk = true, use_gap_tp = true, use_gap_sl = true.
• Multipliers. tp_mult around 0.7 to 1.0 and sl_mult around 1.0.
• Exits. use_candle_exit = false, use_forced_flat = true. Focus on the structured TP and SL around the gap.
Intraday aggressive gap fade
• Timeframe. Five minute chart.
• Gap risk. use_gap_risk = true, use_gap_tp = false, use_gap_sl = true.
• Multipliers. sl_mult around 0.7 to 1.0.
• Exits. use_candle_exit = true, use_forced_flat = true. Entries fade full gaps, stops are tight, and candle color flips flatten trades early.
Higher timeframe gap tests
• Timeframe. Fifteen minute or sixty minute charts on instruments with regular gaps.
• Gap risk. Keep use_gap_risk = true. Consider slightly higher sl_mult if gaps are structurally wider on the higher timeframe.
• Note. Expect fewer trades and be careful with sample size; multi year data is recommended.
Properties visible in this publication
• On average our risk for each position over the last 200 trades is 0.4% with a max intraday loss of 1.5% of the total equity in this case of 100k $ with 1 contract ES. For other assets, recalculations and customizations has to be applied.
• Initial capital. 100 000.
• Base currency. USD.
• Default order size method. Fixed with size 1 contract.
• Pyramiding. 0.
• Commission. Flat 2 USD per order in the Strategy Tester Properties. (2$ buying + 2$selling)
• Slippage. One tick in the Strategy Tester Properties.
• Process orders on close. ON.
Realism and responsible publication
• No performance claims are made. Past results do not guarantee future outcomes.
• Costs use a realistic flat commission and one tick of slippage per trade for ES class futures.
• Default sizing with one contract on a 100 000 reference account targets modest per trade risk. In practice, extreme slippage or gap through events can exceed this, so treat the one and a half percent risk target as a design goal, not a guarantee.
• All orders are simulated on standard candles. Shapes can move while a bar is forming and settle on bar close.
Honest limitations and failure modes
• Economic releases, thin liquidity, and limit conditions can break the assumptions behind the simple gap model and lead to slippage or skipped fills.
• Symbols with very frequent or very large gaps may require adjusted multipliers or alternative risk handling, especially in high volatility regimes.
• Very quiet periods without clean gaps will produce few or no trades. This is expected behavior, not a bug.
• Session windows follow the exchange time of the chart. Always confirm that the configured session matches the symbol.
• When both the stop and target lie inside the same bar’s range, the TradingView engine decides which is hit first based on its internal intrabar assumptions. Without bar magnifier, tie handling is approximate.
Legal
Education and research only. This strategy is not investment advice. You remain responsible for all trading decisions. Always test on historical data and in simulation with realistic costs before considering any live use.
MSB Trend Breakout Strategy V7**MSB Trend Breakout Strategy V7**
This is the full, high-precision automated strategy designed for disciplined traders who understand directional price action. The script functions as a robust **entry and trade management tool** following two proprietary concepts:
**1. Trend Confirmation:** A customized Moving Average filter is utilized to ensure entries strictly align with the dominant market flow.
**2. Momentum Confirmation:** The system uses a specific short-term **multi-bar breakout range** to pinpoint high-probability entries at the start of a momentum shift, avoiding choppy market conditions.
**Key Features:**
* **Automated Risk Management:** Includes complete dynamic Stop Loss (SL) and Take Profit (TP) order management to ensure capital preservation.
* **Time Filter:** Optimizes performance by filtering signals to the most liquid Forex trading hours (01:00 to 19:00, broker time).
**PREREQUISITE FOR ACCESS:**
This is an advanced tool. To utilize the strategy effectively, the user should have a foundational understanding of directional bias and trade management principles.
---
**Important Note & Risk Disclosure:**
This strategy is published under **Invite-only** protection. The script does not provide financial advice or guarantee profits. Past performance is not indicative of future results.
ETH SuperTrend Hull Strategy - 15min Futures(重制版)🟠 ETH SuperTrend Hull Strategy - 15min Futures
Strategy Overview
The "ETH SuperTrend Hull Strategy" is a sophisticated 15-minute trading system specifically designed for Bitcoin perpetual contracts. This advanced algorithm integrates SuperTrend indicators with Hull moving averages to deliver high-precision trend following through a triple-confirmation mechanism, featuring intelligent position management and multi-level take-profit systems.
Core Value Proposition
Triple Trend Confirmation: SuperTrend + Hull MA + ATR volatility filtering
Adaptive Take-Profit System: 6-level dynamic profit targets adjusted to market conditions
Smart Position Management: Three martingale modes with automatic sizing
Real-time Webhook Integration: Direct exchange connectivity for automated execution
🟠 Technical Framework
Multi-Layer Trend Detection
Layer 1 - SuperTrend Filter
pinescript
= ta.supertrend(supertrend_factor, supertrend_atr_period)
is_supertrend_long = direction < 0 // Bullish trend line
is_supertrend_short = direction >= 0 // Bearish trend line
Layer 2 - Hull MA Confirmation
pinescript
HMA = HMA(close, 73) // Hull Moving Average
hull_is_green = HULL > HULL // Uptrend confirmation
hull_is_red = HULL <= HULL // Downtrend confirmation
Layer 3 - ATR Breakout Signals
pinescript
xATR = ta.atr(5)
nLoss = key_value * xATR // Dynamic stop distance
Entry Conditions
Long Entry:
Price breaks above ATR trailing stop
Hull MA shows green uptrend
SuperTrend indicates bullish momentum
Price positioned above Hull MA
Short Entry:
Price breaks below ATR trailing stop
Hull MA shows red downtrend
SuperTrend indicates bearish momentum
Price positioned below Hull MA
🟠 Risk Management System
Position Sizing
text
Base Position = Initial Capital × Risk % / Entry Price × Leverage
Actual Position = Base Position × Martingale Multiplier (1.0-5.0x)
Martingale Modes
4x Mode: Conservative approach, maximum 4x position scaling
5x Mode: Balanced risk management, maximum 5x scaling
5x Big Mode: Aggressive growth with faster position increases
Dynamic Take-Profit System
6-Level Profit Targets:
TP1: 2.2×ATR (Close 30%)
TP2: 4.5×ATR (Close 25%)
TP3: 7.5×ATR (Close 20%)
TP4: 10.5×ATR (Close 10%)
TP5: 15.5×ATR (Close 7%)
TP6: 20.5×ATR (Close 3%)
ATR Adaptive Adjustment:
Short-term ATR > Long-term ATR: TP distance +0.5
Short-term ATR < Long-term ATR: TP distance -0.5
🟠 Configuration Parameters
Core Settings
pinescript
// Trend Sensitivity
key_value = 2.0 // ATR multiplier (lower = more sensitive)
supertrend_factor = 3.0 // SuperTrend factor
// Risk Management
risk_percent = 19.9 // Per trade risk %
leverage = 1.0 // Leverage multiplier
Hull MA Configuration
pinescript
length = 73 // Hull period (55-200)
modeSwitch = "Hma" // Hull variant (Hma/Thma/Ehma)
🟠 Quick Start Guide
Initial Setup
Apply to BTCUSDT perpetual 15-minute chart
Configure Webhook Signal ID and User ID
Adjust position parameters according to risk preference
Signal Monitoring
Long Signals: Green arrows with Hull MA turning green
Short Signals: Red arrows with Hull MA turning red
Trend Direction: SuperTrend line color changes
Execution Workflow
Wait for triple-signal confluence
Confirm all entry conditions met
System automatically calculates position size and TP levels
Webhook sends trade instructions to connected platform
Advanced Features
Heikin-Ashi Mode: Smooth price data using Heikin-Ashi candles
Fixed Position Mode: Disable martingale, use fixed sizing
Multi-Timeframe: Higher timeframe confirmation integration
🟠 ETH SuperTrend Hull Strategy - 15min Futures
策略概述
"ETH超级趋势Hull策略"是一款专为比特币永续合约设计的15分钟短线交易系统。该策略融合超级趋势指标与Hull均线，通过三重过滤机制实现高精度趋势跟踪，具备智能仓位管理和多级止盈体系。
核心价值
三重趋势确认：Supertrend + Hull均线 + ATR波动过滤
自适应止盈系统：6级动态止盈，根据市场波动调整目标
智能仓位管理：支持三种倍投模式，自动调整仓位规模
实时Webhook通知：直连交易平台，实现自动化执行
🟠 策略原理
趋势识别系统
第一层 - 超级趋势过滤
pinescript
= ta.supertrend(supertrend_factor, supertrend_atr_period)
is_supertrend_long = direction < 0 // 绿色趋势线
is_supertrend_short = direction >= 0 // 红色趋势线
第二层 - Hull均线确认
pinescript
HMA = HMA(close, 73) // Hull移动平均线
hull_is_green = HULL > HULL // 上升趋势
hull_is_red = HULL <= HULL // 下降趋势
第三层 - ATR突破信号
pinescript
xATR = ta.atr(5)
nLoss = key_value * xATR // 动态止损距离
入场条件
多头入场：
价格突破ATR追踪止损
Hull均线呈绿色上升趋势
超级趋势显示看涨信号
价格位于Hull均线上方
空头入场：
价格跌破ATR追踪止损
Hull均线呈红色下降趋势
超级趋势显示看跌信号
价格位于Hull均线下方
🟠 风险管理
仓位计算
text
基础仓位 = 初始资金 × 风险比例% / 入场价格 × 杠杆倍数
实际仓位 = 基础仓位 × 倍投系数 (1.0-5.0倍)
倍投模式
4倍模式：保守型，最大4倍加仓
5倍模式：均衡型，最大5倍加仓
5倍大模式：激进型，更快仓位增长
动态止盈系统
6级止盈目标：
TP1: 2.2×ATR (平仓30%)
TP2: 4.5×ATR (平仓25%)
TP3: 7.5×ATR (平仓20%)
TP4: 10.5×ATR (平仓10%)
TP5: 15.5×ATR (平仓7%)
TP6: 20.5×ATR (平仓3%)
ATR自适应调整：
短期ATR > 长期ATR：止盈距离+0.5
短期ATR < 长期ATR：止盈距离-0.5
🟠 参数配置
核心参数
pinescript
// 趋势敏感度
key_value = 2.0 // ATR乘数，值越小越敏感
supertrend_factor = 3.0 // 超级趋势因子
// 风险管理
risk_percent = 19.9 // 单次交易风险%
leverage = 1.0 // 杠杆倍数
Hull均线设置
pinescript
length = 73 // Hull周期 (55-200)
modeSwitch = "Hma" // Hull变体 (Hma/Thma/Ehma)
🟠 使用指南
初始设置
添加到BTCUSDT永续合约15分钟图表
配置Webhook信号ID和用户ID
根据风险偏好调整仓位参数
信号监控
多单信号：绿色箭头，Hull均线转绿
空单信号：红色箭头，Hull均线转红
趋势方向：超级趋势线颜色变化
执行流程
等待三重信号共振
确认入场条件满足
系统自动计算仓位和止盈
通过Webhook发送交易指令
高级功能
K线均线模式：使用Heikin-Ashi平滑价格
固定仓位模式：禁用倍投，固定仓位大小
多时间框架：集成更高时间框架确认
Moving Average Band StrategyOverview
The Moving Average Band Strategy is a fully customizable breakout and trend-continuation system designed for traders who need both simplicity and control.
The strategy creates adaptive bands around a user-selected moving average and executes trades when price breaks out of these bands, with advanced risk-management settings including optional Risk:Reward targets.
This script is suitable for intraday, swing, and positional traders across all markets — equities, futures, crypto, and forex.
Key Features
✔ Six Moving Average Types
Choose the MA that best matches your trading style:
SMA
EMA
WMA
HMA
VWMA
RMA
✔ Dynamic Bands
Upper Band built from MA of highs
Lower Band built from MA of lows
Adjustable band offset (%)
Color-coded band fill indicating price position
✔ Configurable Strategy Preferences
Toggle Long and/or Short trades
Toggle Risk:Reward Take-Profit
Adjustable Risk:Reward Ratio
Default position sizing: % of equity (configurable via strategy settings)
Entry Conditions
Long Entry
A long trade triggers when:
Price crosses above the Upper Band
Long trades are enabled
No existing long position is active
Short Entry
A short trade triggers when:
Price crosses below the Lower Band
Short trades are enabled
No existing short position is active
Clear entry markers and price labels appear on the chart.
Risk Management
This strategy includes a complete set of risk-controls:
Stop-Loss (Fixed at Entry)
Long SL: Lower Band
Short SL: Upper Band
These levels remain constant for the entire trade.
Optional Risk:Reward Take-Profit
Enabled/disabled using a toggle switch.
When enabled:
Long TP = Entry + (Risk × Risk:Reward Ratio)
Short TP = Entry – (Risk × Risk:Reward Ratio)
When disabled:
Exits are handled by reverse crossover signals.
Exit Conditions
Long Exit
Stop-Loss Hit (touch-based)
Take-Profit Hit (if enabled)
Reverse Band Crossover (if TP disabled)
Short Exit
Stop-Loss Hit (touch-based)
Take-Profit Hit (if enabled)
Reverse Band Crossover (if TP disabled)
Exit markers and price labels are plotted automatically.
Visual Tools
To improve clarity:
Upper & Lower Band (blue, adjustable width)
Middle Line
Dynamic band fill (green/red/yellow)
SL & TP line plotting when in position
Entry/Exit markers
Price labels for all executed trades
These are built to help users visually follow the strategy logic.
Alerts Included
Every trading event is covered:
Long Entry
Short Entry
Long SL / TP / Cross Exit
Short SL / TP / Cross Exit
Combined Alert for webhook/automation (JSON-formatted)
Perfect for algo trading, Discord bots, or automation platforms.
Best For
This strategy performs best in:
Trending markets
Breakout environments
High-momentum instruments
Clean intraday swings
Works seamlessly on:
Stocks
Index futures
Commodities
Crypto
Forex
⚠️ Important Disclaimer
This script is for educational purposes only.
Trading involves risk. Backtest results are not indicative of future performance.
Always validate settings and use proper position sizing.
Bank nifty with RSI + SMA (Bli-Rik)best to trade for 100 points on 15 mins time frame, very rarly fails
EMA VIP STRThis strategy works on EMAS and standard deviation on both sides , the tp is decided on RSI levels. the strategy is a systematic trading setup
Adaptive Volatility StrategyHere's a professional description for publishing your indicator:
Adaptive Volatility Strategy - Multi-Indicator Confirmation System
A comprehensive trading strategy that combines multiple technical indicators with adaptive volatility filtering to identify high-probability trade setups while managing risk effectively.
Key Features:
Multi-Indicator Confirmation: Combines RSI, MACD, and ADX signals with trend analysis (20/50/200 EMAs) to reduce false signals and improve entry quality
Adaptive Volatility Filter: Intelligent volatility detection using ATR that can filter trades based on either fixed percentage thresholds or multiples of average volatility, helping avoid unstable market conditions
Flexible Session Filtering: Optional time-based trading windows with customizable hours and trading days to align with your preferred market sessions
Smart Signal Generation: Requires minimum signal confirmations before entering trades, with separate tracking for directional and confirmation signals
Comprehensive Risk Management: Configurable take profit and stop loss percentages with automatic position exits on signal reversals
Real-Time Dashboard: Visual display showing current indicator values, signals, volatility levels, and trend direction for quick market assessment
Strategy Logic:
Enters long when bullish signals outnumber bearish signals (minimum 2 signals) with ADX confirmation
Enters short when bearish signals outnumber bullish signals with ADX confirmation
All trades must pass volatility and session filters when enabled
Exits on take profit, stop loss, or signal reversal
Best Used For:
Swing trading on 1H to daily timeframes
Markets with clear trending behavior
Traders who prefer multiple confirmations before entering positions
Note: This is a complete strategy with entry/exit logic. Backtest thoroughly and adjust parameters for your specific instrument and timeframe before live trading.
FX Swing — Compact Auto-Sizing (Fixed)A compact Forex swing-trading strategy that combines higher-timeframe EMA trend bias, EMA pullback confirmation, and RSI momentum filtering. It automatically sizes positions using either risk-percentage or fixed-risk, adapts pip values for JPY and non-JPY pairs, and generates clear SL/TP levels with partial take-profit exits. The script also sends structured JSON alerts for webhooks or WhatsApp automation, making it ideal for fast, disciplined, and risk-controlled swing entries.
MOMO – Imbalance Trend (SIMPLE BUY/SELL)MOMO – Imbalance Trend (SIMPLE BUY/SELL)
This strategy combines trend breaks, imbalance detection, and first-tap supply/demand entries to create a clean and disciplined trading model.
It automatically highlights imbalance candles, draws fresh zones, and waits for the first retest to deliver precise BUY and SELL signals.
Performance
On optimized settings, this strategy shows an estimated 57%–70% win-rate, depending on the asset and timeframe.
Actual performance may vary, but the model is built for consistency, discipline, and improved decision-making.
How it works
Detects trend structure shifts (BOS / Break of Trend)
Identifies displacement (imbalance) candles
Creates supply and demand zones from imbalance origin
Waits for first tap only (no second chances)
Confirms direction using trend logic
Generates clean BUY/SELL arrows
Automatic SL/TP based on user settings
Features
Clean BUY/SELL markers
Auto-drawn supply & demand zones
Trend break markers
Imbalance tags
Smart first-tap confirmation
Customizable stop loss & take profit
Works on crypto, gold, forex, indices
Best on M5–H1 for day trading
Note
This strategy is designed for day traders who want clarity, structure, and zero emotional trading.
Use it with discipline — and it will serve you well.
Good luck, soldier.
Fractional Candlestick Long Only Experimental V10Fractional Candlestick Long-Only Strategy – Technical Description
This document provides a professional English description of the "Fractional Candlestick Long Only Experimental V6" strategy using pure CF/AB fractional kernels and wavelet-based filtering.
1. Fractional Candlesticks (CF / AB)
The strategy computes two fractional representations of price using Caputo–Fabrizio (CF) and Atangana–Baleanu (AB) kernels. These provide long-memory filtering without EMA approximations. Both CF and AB versions are applied to O/H/L/C, producing fractional candlesticks and fractional Heikin-Ashi variants.
2. Trend Stack Logic
Trend confirmation is based on a 4-component stack:
- CF close > AB close
- HA_CF close > HA_AB close
- HA_CF bullish
- HA_AB bullish
The user selects how many components must align (4, 3, or any 2).
3. Wavelet Filtering
A wavelet transform (Haar, Daubechies-4, Mexican Hat) is applied to a chosen source (e.g., HA_CF close). The wavelet response is used as:
- entry filter (4 modes)
- exit filter (4 modes)
Wavelet modes: off, confirm, wavelet-only, block adverse signals.
4. Trailing System
Trailing stop uses fractional AB low × buffer, providing long-memory dynamic trailing behavior. A fractional trend channel (CF/AB lows vs HA highs) is also plotted.
5. Exit Framework
Exit options include: stack flip, CF
Positional Supertrend Strategy (1D Filter + 2H Entry)Positional Supertrend Strategy (1D Filter + 2H Entry)
