VWAP Trend GuardVWAP Trend Guard – Built by CodaPro.ai x ARiS
Prompt-Based Strategy Creation
“I have FOMO and want to buy gold and oil. I don’t have a lot of trading experience — I just want to make 1–3% profit every month. Can you build me anything so that I can trade MCG and MCL?”
That was the only input.
From that simple, human, emotionally honest prompt — ARiS, the AI strategy copilot inside CodaPro.ai, generated a fully automated trading strategy built for real markets.
This wasn’t hand-coded. It wasn’t based on a template.
It was built from scratch — by AI — using smart defaults, embedded risk logic, and live-execution hooks.
Prompt Interpretation by ARiS
To translate that raw FOMO-fueled question into structured trading logic, ARiS asked back:
“Should we trade with or against the trend?” → Let the AI decide
“Should we confirm trades with VWAP?” → Let the AI decide
“Should this be long-only or also short?” → Both
“What stop loss method should I use?” → User didn’t know what a stop loss is
“How much risk per trade?” → 1%
“Should I auto-close trades by end of day?” → Yes
“What timeframe should we trade?” → Whichever is safest for a beginner
Based on that, ARiS produced a complete day-trading strategy, wrapped in clean logic, with:
+ Trend-following entry using EMA + VWAP
+ ATR-based stop, target, and optional trailing stop
+ Risk-based position sizing (auto-calculated by equity %)
+ End-of-session flattening (no overnight exposure)
+ Full webhook alert system for live broker automation
Strategy Profile
Category Details
Markets MCL (Micro Crude), MGC (Micro Gold)
Timeframe Intraday (5–15 minute default)
Style Day trading (flat by session end)
Direction Long & Short
Indicators Used EMA(20), EMA(50), VWAP, ATR
Position Sizing Based on 1% equity risk
Stops & Targets ATR-multiplied SL/TP + optional trailing
Exit Triggers Target hit, stop loss hit, trend flip, or session end
Automation Includes JSON webhooks for entry/exit signals
Platform TradingView Pine Script v6
Disclaimer: Slippage, Backtesting, and Live Use
This strategy runs in TradingView’s strategy tester, where backtested fills assume ideal executions.
In real-world trading, you may encounter:
Slippage (especially on fast contracts like MCL)
Missed limits or early stop-outs
Trailing stop misfires or duplicates
These can be addressed by regenerating the strategy with:
Buffer logic
Slippage simulation
Broker-linked execution systems (e.g., Tradovate or IBKR)
The real magic is that this strategy didn’t come from a coder. It came from a conversation.
You say what you want — ARiS builds it. Instantly. Safely. Logically.
Who This Is For
This strategy is ideal for:
New traders who want a safe, day-only framework
Anyone trading gold (MGC) or oil (MCL) with micro contracts
Beginners who want to learn trading logic from what ARiS built
Professionals who want to convert human prompts into real algo logic
移動平均線
ilker %90This strategy is a short-term momentum approach based on moving averages and volume. Studies show it performs more effectively on the 1-hour and 4-hour timeframes. Take-profit and stop-loss distances are kept short, resulting in a high win rate, while the profit factor ranges between 1.4 and 2.
40 SMA Scaling StrategyThis trend-following strategy focuses on capturing momentum when price breaks above the 40-period Simple Moving Average (SMA) while utilizing a systematic scale-out (Take Profit) approach to lock in gains during extended runs.
Strategy Logic
Entry: Opens a Long position with 100% of current equity when the price closes above the 40 SMA. This ensures maximum capital efficiency at the start of a new perceived trend.
Scaling Take Profits: To reduce risk as the trade progresses, the strategy automatically closes 25% of the initial position for every 1% increase in price from the entry point.
Exit: The entire remaining position is closed immediately if the price closes below the 40 SMA, acting as a trailing stop that adapts to the moving average.
Key Features
Capital-Efficient: Starts with a full account allocation to maximize exposure to the initial breakout.
Systematic De-risking: By scaling out in 25% increments, the strategy banks profits early while leaving a portion of the trade active for potential "moon shots."
Trend-Following Exit: Uses a classic SMA filter to exit, aiming to stay in the trade as long as the medium-term trend remains bullish.
%-to-Tick Trailing Stop & VisualizerPercent-to-Tick Trailing Stop (strategy.exit Framework + Visualizer)
Overview
This script focuses on exit management and visualization, not entry performance. The included MA crossover entry is intentionally simple and replaceable.
Core idea (Percent → Tick conversion)
strategy.exit() trailing parameters are tick-based (trail_points, trail_offset, and loss).
This script lets you input distances in percent (%) and converts them into integer ticks using syminfo.mintick, making the same exit logic portable across most tick-based symbols/exchanges with different tick sizes.
//==What it provides==//
1. % → tick conversion for:
- Fixed stop loss (loss)
- Trailing activation distance (trail_points)
- Trailing offset distance (trail_offset)
2. On-chart visualization:
- Entry average price
- Trailing activation threshold
- Fixed stop-loss line
- Trailing stop line (with an exit-bar alignment attempt to reduce gaps)
//==How to use==//
1. Keep the included MA crossover entries, or replace them with your own entries.
2. Configure:
- Fixed Stop Loss % (loss_pct)
- Trailing Activation % (t_points_pct)
- Trailing Offset % (t_offset_pct)
3. Adjust commission/slippage defaults to match your market.
//==Important limitations (must read)==//
- calc_on_every_tick=true recalculates on realtime bars only; historical bars are evaluated differently. Backtests can differ from realtime behavior and may change after reload.
- Tick rounding: percent distances are rounded to integer ticks, so small differences can occur depending on tick size and price level.
- For more realistic intrabar backtesting, consider enabling Bar Magnifier in Strategy Properties (if available).
# Average Entry Price (Basis):
"Calculations are based on the position's average entry price (strategy.position_avg_price)."
# Pine Script v6:
"Written in the latest Pine Script v6."
요약
이 스크립트의 핵심은 “진입 전략”이 아니라 **strategy.exit()의 tick 기반 트레일링 파라미터를 % 입력으로 일반화(%→ticks 변환)**하여, 다양한 심볼/거래소의 서로 다른 tick size 환경에서도 동일한 exit 로직을 재사용할 수 있게 만든 “청산 프레임워크”입니다. 또한 calc_on_every_tick=true 환경에서 트리거/손절/트레일 라인을 실시간에 가깝게 시각화하는 데 중점을 두었습니다.
단, calc_on_every_tick은 실시간 바에서만 틱 단위 재계산이 적용되며, 히스토리 바/백테스트는 평가 방식이 달라 결과가 다를 수 있습니다.
SMAcross-mvrOverview
SMAcross-mvrNew is a flexible, non-repainting moving-average strategy designed for clarity, configurability, and reliable backtesting.
It supports multiple entry styles, optional layered exits, and full-capital position sizing, while remaining stable during chart zooming and dragging.
🚀 What’s New in v2
✅ Multiple Entry Modes
You can now choose how trades are entered:
Entry Mode A: Short SMA crosses Long SMA
Entry Mode B: Price crosses Long SMA
This allows both classic MA-crossover trading and trend-continuation pullback entries using the same strategy.
✅ Modular Exit System (Checkbox-Based)
Exit logic is now fully modular using independent checkboxes:
☑ Exit on opposite signal
☑ Exit when price closes beyond Short SMA
You may enable one, both, or neither.
If both are enabled, the strategy exits on whichever condition occurs first.
✅ Terminology Clarity
All labels, inputs, and alerts now use semantic naming:
Short SMA (formerly 13 SMA)
Long SMA (formerly 30 SMA)
This makes the strategy easier to understand and future-proof if SMA lengths are changed.
✅ Full-Capital Position Sizing
Each trade uses 100% of available equity, allowing performance to naturally compound over time during backtests.
✅ Optional Visual Enhancements
Optional cross price labels (can be toggled on/off)
Color-filled zone between Short and Long SMAs for quick trend recognition
Optional 200 SMA (off by default) for higher-timeframe context
✅ Alert-Ready (TV-Safe)
All alerts use static messages compatible with TradingView’s alert system, making the strategy suitable for:
Manual trade notifications
Webhook-based automation
Broker integrations
🔒 Design Principles
No repainting
No line continuations (TradingView-safe formatting)
Stable behavior when zooming or scrolling
Clear separation of entry logic, exit logic, and visuals
⚠️ Notes
This script is intended for educational and research purposes.
Always forward-test and apply proper risk management before live trading.
EMA and Dow Theory Strategies V2 DOGE Current Optimum Value
📘 Overview
These are the current optimal values for DOGE.
They are intended for use on the 2‑hour timeframe.
This script requires complex configuration, but there is an optimal set of values somewhere.
Here, I’m sharing the settings that I personally use at the moment.
Turning Take Profit off can lead to higher profits, but it also increases risks such as a lower win rate.
With Take Profit on, you can adjust the settings by increasing the values.
I have been trading using Dow Theory for many years.
Trading with Dow Theory and EMA has been my main strategy.
Although it has been profitable, I have long struggled with its low win rate.
The issue lies in the immaturity of the exit strategy, and I’m currently experimenting to see if I can solve that.
In V2, I added three take‑profit lines, securing 30% of the profit at each level to ensure a minimum level of gain.
Additionally, when the trend weakens, half of the position is closed.
In all scenarios, the remaining position is held until the trend reverses.
The system provides precise entries, adaptive exits, and highly visual guidance that helps traders understand trend structure at a glance.
🧠 Key Features
🔹 1. Dual‑EMA Trend Logic (Symbol + External Index)
Both the chart symbol and an external index (OTHERS.D) are evaluated using fast/slow EMAs to determine correlation‑based trend bias.
🔹 2. Dow Theory Swing Detection (Real‑time)
The script identifies swing highs/lows and updates trend direction when price breaks them. This creates a structural trend model that reacts faster than EMAs alone.
🔹 3. Gradient Trend Zones (Visual Trend Strength)
When trend is up or down, the area between price and the latest swing level is filled with a multi‑step gradient. This makes trend strength and distance-to-structure visually intuitive.
🔹 4. Higher‑Timeframe Swing Trend (htfTrend)
Swing highs/lows from a higher timeframe (e.g., 4H) are plotted to show macro structure. Used only for visual context, not for filtering entries.
🔹 5. RSI‑Based Entry Protection
RSI prevents entries during extreme overbought/oversold conditions.
🔹 6. Dynamic Exit System
Includes:
Custom stop‑loss (%)
Partial take‑profit (TP1/TP2/TP3)
Automatic scale‑out when trend color weakens
“Color‑change lockout” to prevent immediate re‑entry
Real‑time PnL tracking and labels
🔹 7. Alerts for All Key Events
Entry, stop‑loss, partial exits, and trend‑change exits all generate structured JSON alerts.
🔹 8. Visual PnL Labels & Equity Tracking
PnL for the latest trade is displayed directly on the chart, including scale‑out adjustments.
⚙️ Input Parameters
Parameter Description
Fast EMA / Slow EMA EMAs used for symbol trend detection
Index Fast / Slow EMA EMAs applied to external index
StopLoss (%) Custom stop‑loss threshold
Scale‑Out % Portion to exit when trend color weakens
RSI Period / Levels Overbought/oversold filters
Swing Detection Length Bars used to detect swing highs/lows
Stats Display Position of statistics table
🧭 About htfTrend (Higher Timeframe Trend)
The higher‑timeframe swing trend is displayed visually but not used for entry logic.
Why? Strict HTF filtering reduces trade frequency and often removes profitable setups. By keeping it visual‑only, traders retain flexibility while still benefiting from macro structure awareness.
Use it as a contextual guide, not a constraint.
📘 概要
DOGEの現在の最適値です。
2時間足での使用を想定しています。
このスクリプトは複雑な設定が必要ですが、どこかに最適値が存在します。
今回は現在私が個人的に使っている設定値の公開です。
Take ProfitをOFFにするとさらなる利益が望めますが、勝率が下がるなどのリスクが上がります。
ONにした状態で数値を上げることによって調整することが可能です。
私はダウ理論を使ったトレードを長年続けてきました。
ダウ理論とEMAを使ったトレードが私の主力です。
しかし利益は出るものの、長年その勝率の低さに悩んでいました。
問題は出口戦略が未熟なためで、現在はそれらの解決ができないかと試行錯誤を続けています。
V2では3本の利益確定ラインを引き、それぞれ30%ずつ利益を確定し、最低限の利益がでるようにしました。
それ以外にはトレンドが弱まったタイミングで半分の利益確定をし、どのパターンでも残ったポジションはトレンド転換まで持ち続けます。
🧠 主な機能
🔹 1. 銘柄＋外部インデックスの EMA クロス判定
対象銘柄と OTHERS.D の EMA を比較し、相関を考慮したトレンド方向を判定します。
🔹 2. ダウ理論に基づくスイング高値・安値の自動検出
スイング更新によりトレンド方向を切り替える、構造ベースのトレンド判定を採用。
🔹 3. グラデーション背景によるトレンド強度の可視化
スイングラインから現在価格までを段階的に塗り分け、 「どれだけトレンドが伸びているか」を直感的に把握できます。
🔹 4. 上位足スイングトレンド（htfTrend）の表示
4H などの上位足でのスイング高値・安値を表示し、 大局的なトレンド構造を視覚的に把握できます（ロジックには未使用）。
🔹 5. RSI による過熱・売られすぎフィルター
極端な RSI 状態でのエントリーを防止。
🔹 6. 動的イグジットシステム
カスタム損切り（％）
TP1/TP2/TP3 の段階的利確
トレンド色の弱まりによる自動スケールアウト
色変化後の再エントリー制限（waitForColorChange）
リアルタイム PnL の追跡とラベル表示
🔹 7. アラート完備（JSON 形式）
エントリー、損切り、部分利確、トレンド反転などすべてに対応。
🔹 8. 損益ラベル・統計表示
直近トレードの損益をチャート上に表示し、視覚的に把握できます。
⚙️ 設定項目
設定項目名 説明
Fast / Slow EMA 銘柄の EMA 設定
Index Fast / Slow EMA 外部インデックスの EMA 設定
損切り（％） カスタム損切りライン
部分利確割合 トレンド弱化時のスケールアウト割合
RSI 期間・水準 過熱/売られすぎフィルター
スイング検出期間 スイング高値・安値の検出に使用
統計表示位置 テーブルの表示位置
🧭 上位足トレンド（htfTrend）について
上位足スイングの更新に基づくトレンド判定を表示しますが、 エントリー条件には使用していません。
理由： 上位足を厳密にロジックへ組み込むと、トレード機会が大幅に減るためです。
本ストラテジーでは、 「大局の把握は視覚で、エントリーは柔軟に」 という設計思想を採用しています。
→ 裁量で利確判断や逆張り回避に活用できます。
Quality-Controlled Trend Strategy v2 (Expectancy Focused)This script focuses on quality control rather than curve-fitting.
No repainting, no intrabar tricks, no fake equity curves.
It uses confirmed-bar entries, ATR-based risk, and clean trend logic so backtests reflect what could actually be traded live.
If you publish scripts, this is the minimum structure worth sharing.
Why this script exists
TradingView’s public scripts are flooded with:
repainting indicators
no stop-loss logic
curve-fit entries that collapse live
strategies that look good only in hindsight
This script is intentionally boring but honest.
No repainting.
No intrabar tricks.
No fake equity curves
The goal is quality control, not hype.
What this strategy enforces
✔ Confirmed bars only
✔ Single source of truth for indicators
✔ Fixed risk structure
✔ No signal repainting
✔ Clean exits with unique IDs
✔ Works on any liquid market
Trading Logic (simple & auditable)
Trend filter
EMA 50 vs EMA 200
Entry
Pullback to EMA 50
RSI confirms momentum (not oversold/overbought)
Risk
ATR-based stop
Fixed R:R
One position at a time
This is the minimum bar for a strategy to be considered publish-worthy.
Why this helps TradingView quality
Most low-value scripts fail because they:
hide repainting logic
skip exits entirely
use inconsistent calculations
rely on hindsight candles
This strategy forces discipline:
every signal is confirmed
every trade has defined risk
behavior is repeatable across symbols & timeframes
If more scripts followed this baseline, TradingView’s public library would be far more usable.
Commodity Channel Index CCI + EMA strategy
================================================================================
COMMODITY CHANNEL INDEX CCI + EMA STRATEGY - STRATEGY GUIDE 📊
================================================================================
💡 COLLABORATION & SUPPORT
---------------------------
If you want to collaborate, have an idea for a strategy, or need help writing
or customizing code, send an email to burdytrader@gmail.com or send me a
message. Suggestions, ideas, and comments are always welcome! 🤝
I also develop automated trading codes for other trading platforms including:
- CTrader (C#)
- MetaTrader 4 (MQL4)
- MetaTrader 5 (MQL5)
If you need a strategy converted or developed for any of these platforms, feel
free to contact me!
================================================================================
⚠️ IMPORTANT: INSTRUMENT SELECTION 📈
-------------------------------------
This strategy performs BEST with currency pairs (forex). The CCI indicator
works particularly well in the forex market due to the nature of currency
movements and the effectiveness of the CCI in identifying overbought and
oversold conditions in trending markets.
Why Currency Pairs? 🎯
- CCI is highly effective in identifying reversals in forex markets
- Currency pairs show clear overbought/oversold patterns
- EMA filter (50/200) aligns well with major forex trends
- High liquidity ensures reliable signal execution
Performance Highlights:
In specific currency pairs, when properly configured, this strategy can achieve:
- Profit Factor: Over 2.0
- Win Rate: Up to 70%
- Particularly effective pairs: USDCAD, EURUSD, GBPJPY
While the strategy can work with other instruments (stocks, indices, commodities),
currency pairs provide the most consistent and reliable results. For optimal
performance, focus on major forex pairs with good liquidity and clear trending
characteristics.
================================================================================
WHAT DOES THIS STRATEGY DO? 🎯
---------------------------
This strategy combines the Commodity Channel Index (CCI) with Exponential
Moving Averages (EMA) to identify high-probability trading opportunities.
The strategy uses CCI crossovers with a smoothing moving average and filters
signals using EMA trend confirmation. The strategy automatically enters trades
when CCI crosses the smoothing MA in specific zones, indicating potential trend
reversals or continuations.
HOW IT WORKS? ⚙️
---------------
1. CCI CALCULATION 📈
The strategy calculates the Commodity Channel Index using:
- CCI = (Price - SMA(Price, length)) / (0.015 × Deviation(Price, length))
- Default length: 20 periods
- Source: HLC3 (typical price)
The CCI shows:
- Values above +100 = Overbought conditions
- Values below -100 = Oversold conditions
- Values around 0 = Neutral conditions
2. SMOOTHING MOVING AVERAGE 📊
A moving average is applied to the CCI to smooth out fluctuations:
- Types available: SMA, EMA, SMMA (RMA), WMA, VWMA
- Default: SMA with length 14
- Can be disabled (set to "None")
This smoothed line acts as a reference for crossover signals.
3. EMA TREND FILTER 🎯
Two EMAs are calculated on the CCI:
- EMA 50 (fast EMA)
- EMA 200 (slow EMA)
When the EMA filter is enabled:
- LONG signals only occur when EMA50 > EMA200 (uptrend confirmation)
- SHORT signals only occur when EMA50 < EMA200 (downtrend confirmation)
This filter can be enabled/disabled via the "Use EMA Filter" option.
4. ENTRY CONDITIONS 🎲
LONG ENTRY (Buy Signal):
- CCI crosses ABOVE the Smoothing MA (crossover)
- CCI is between Lower Level (-100) and Middle Level (0)
- EMA Filter: EMA50 > EMA200 (if filter enabled)
- No existing positions (or close opposite positions first)
SHORT ENTRY (Sell Signal):
- CCI crosses BELOW the Smoothing MA (crossunder)
- CCI is between Middle Level (0) and Upper Level (+100)
- EMA Filter: EMA50 < EMA200 (if filter enabled)
- No existing positions (or close opposite positions first)
5. POSITION MANAGEMENT 💰
The strategy uses a simple position management approach:
- Only ONE position at a time (no pyramiding)
- If a signal occurs in the opposite direction, closes existing position first
- Then opens new position in the new direction
- This prevents overexposure and simplifies risk management
6. TAKE PROFIT & STOP LOSS SETTINGS 🎯
The strategy uses percentage-based TP/SL:
- Take Profit: 1.0% (default, configurable)
- Stop Loss: 0.5% (default, configurable)
- Risk/Reward Ratio: 2:1 (TP is double the SL)
TP/SL are calculated once when the position opens and remain fixed.
AVAILABLE PARAMETERS ⚙️
-----------------------
CCI SETTINGS:
1. CCI Length (Default: 20)
- Period for CCI calculation
- Lower values = More sensitive to recent price action
- Higher values = More smoothed, less sensitive
2. CCI Source (Default: HLC3)
- Price source for CCI calculation
- Options: close, open, high, low, hlc3, hlcc4, ohlc4
3. CCI Lower Level (Default: -100)
- Lower boundary for LONG entry zone
- Typically -100 for oversold conditions
4. CCI Middle Level (Default: 0)
- Neutral level separating LONG and SHORT zones
5. CCI Upper Level (Default: +100)
- Upper boundary for SHORT entry zone
- Typically +100 for overbought conditions
SMOOTHING MA:
6. Type (Default: SMA)
- Moving average type: None, SMA, EMA, SMMA (RMA), WMA, VWMA
- Set to "None" to disable smoothing
7. Length (Default: 14)
- Period for smoothing MA
- Range: 7-28, step 7
EMA FILTER:
8. EMA 1 Length (Default: 50)
- Fast EMA period applied to CCI
9. EMA 2 Length (Default: 200)
- Slow EMA period applied to CCI
10. Use EMA Filter (Default: true)
- Enable/disable EMA trend filter
- When enabled: LONG only if EMA50 > EMA200, SHORT only if EMA50 < EMA200
RISK MANAGEMENT:
11. Take Profit (%) (Default: 1.0%)
- Profit target as percentage of entry price
- For LONG: Entry × (1 + TP%)
- For SHORT: Entry × (1 - TP%)
12. Stop Loss (%) (Default: 0.5%)
- Stop loss as percentage of entry price
- For LONG: Entry × (1 - SL%)
- For SHORT: Entry × (1 + SL%)
VISUALIZATION 📊
---------------
The strategy displays in a separate panel below the price chart:
1. CCI LINE
- Blue line showing the CCI value
- Oscillates around zero
2. SMOOTHING MA LINE
- Yellow line showing the smoothed CCI
- Reference line for crossover signals
3. CCI LEVEL LINES
- Red dashed line: Upper Level (+100)
- Green dashed line: Lower Level (-100)
- Yellow dashed line: Middle Level (0)
4. ENTRY SIGNALS
- Green cross: LONG entry signal (when CCI crosses above MA)
- Red cross: SHORT entry signal (when CCI crosses below MA)
RECOMMENDED SETTINGS 🎯
-----------------------
To get started, you can use these settings:
CCI SETTINGS:
- CCI Length: 20 (default)
- CCI Source: HLC3 (default)
- CCI Lower Level: -100 (default)
- CCI Middle Level: 0 (default)
- CCI Upper Level: +100 (default)
SMOOTHING MA:
- Type: SMA (default) or EMA for faster response
- Length: 14 (default)
EMA FILTER:
- EMA 1 Length: 50 (default)
- EMA 2 Length: 200 (default)
- Use EMA Filter: true (recommended for better signal quality)
RISK MANAGEMENT:
- Take Profit (%): 1.0% (adjust based on your risk/reward preference)
- Stop Loss (%): 0.5% (adjust based on your risk tolerance)
For more aggressive trading:
- Reduce CCI Length to 14-16
- Reduce Smoothing MA Length to 7
- Disable EMA Filter
For more conservative trading:
- Increase CCI Length to 24-30
- Increase Smoothing MA Length to 21-28
- Keep EMA Filter enabled
RECOMMENDED CURRENCY PAIRS 💱
------------------------------
This strategy is optimized for currency pairs and performs exceptionally well
on the following pairs when properly configured:
TOP PERFORMING PAIRS:
- USDCAD: Can achieve Profit Factor > 2.0 and Win Rate up to 70%
- EURUSD: Excellent performance with consistent signals
- GBPJPY: Strong results with proper EMA filter configuration
These pairs have shown the best historical performance due to:
- Clear trending characteristics
- Good response to CCI overbought/oversold levels
- Strong alignment with EMA 50/200 trend filter
- High liquidity ensuring reliable execution
When trading these pairs, use the default settings or slightly adjusted
parameters based on the pair's volatility. Always backtest on historical
data before using real money to find the optimal configuration for each
specific pair.
PRACTICAL EXAMPLE 📝
--------------------
Scenario: LONG Entry on EUR/USD
1. Market conditions:
- Price: 1.1000
- CCI: -80 (in oversold zone)
- Smoothing MA: -90
- CCI crosses above Smoothing MA (crossover occurs)
- EMA50: -50, EMA200: -70 (EMA50 > EMA200, uptrend confirmed)
2. Strategy checks conditions:
✓ Smoothing MA enabled: Yes
✓ Crossover: Yes (CCI crosses above MA)
✓ CCI in range: Yes (-100 <= -80 <= 0)
✓ EMA Filter: Yes (EMA50 > EMA200)
✓ No existing position: Yes
3. Strategy opens position:
- Direction: LONG (Buy)
- Entry: 1.1000 (current close)
- Take Profit: 1.1110 (1.0% above entry)
- Stop Loss: 1.0945 (0.5% below entry)
- Risk/Reward: 2:1
4. Outcome scenarios:
- If price rises to 1.1110 → Take Profit hit (profit)
- If price falls to 1.0945 → Stop Loss hit (loss limited)
IMPORTANT NOTE ⚠️
-----------------
This strategy is a technical analysis tool based on CCI and EMA indicators.
Like all trading strategies, it does NOT guarantee profits. Trading involves
significant risks and you can lose money, including your entire investment.
Past performance does not guarantee future results.
Always:
- Use appropriate risk management
- Never risk more than you can afford to lose
- Test the strategy on historical data (backtesting) before using real money
- Start with small position sizes or paper trading
- Understand that no strategy works 100% of the time
- Consider market conditions, news events, and other factors
- Keep a trading journal to learn and improve
The author and contributors are NOT responsible for any losses incurred from
using this strategy. Trading decisions are your own responsibility. Profits
are NOT guaranteed, and losses are possible.
LICENSE 📄
----------
This code is open source and available for modification. You are free to use,
modify, and distribute this strategy. If you republish or share a modified
version, please kindly mention the original author.
================================================================================
Delta Volume EMA Strategy
================================================================================
DELTA VOLUME EMA STRATEGY - STRATEGY GUIDE 📊
================================================================================
💡 COLLABORATION & SUPPORT
---------------------------
If you want to collaborate, have an idea for a strategy, or need help writing
or customizing code, send an email to burdytrader@gmail.com or send me a
message. Suggestions, ideas, and comments are always welcome! 🤝
================================================================================
⚠️ IMPORTANT: INSTRUMENT SELECTION 📈
-------------------------------------
This strategy performs BEST with instruments that have a centralized data flow,
such as Futures contracts. Centralized markets provide more accurate and
reliable volume data, which is essential for Volume Delta analysis to work
effectively.
Why Futures? 🎯
- Centralized exchange = Accurate volume data
- All trades flow through a single exchange
- Volume reflects true buying/selling pressure
- Better correlation between volume and price movements
While the strategy can work with other instruments (stocks, forex, etc.),
volume data quality may vary, which can affect the reliability of Volume Delta
signals. For optimal performance, use Futures contracts or other instruments
with centralized, high-quality volume data.
================================================================================
WHAT DOES THIS STRATEGY DO? 🎯
---------------------------
This strategy uses Volume Delta analysis combined with Exponential Moving
Averages (EMA) to identify high-probability trading opportunities. The Volume
Delta measures the difference between buying and selling pressure, helping to
identify when strong institutional or smart money movements occur. The strategy
automatically enters trades when volume delta reaches extreme levels, indicating
potential trend continuation or reversal points.
HOW IT WORKS? ⚙️
---------------
1. VOLUME DELTA CALCULATION 📈
The strategy calculates the Volume Delta using the following formula:
- Volume Ratio (v) = Current Volume / Previous Volume
- EMA of Close (mac) = EMA(Close, MA Length) × Volume Ratio
- EMA of Open (mao) = EMA(Open, MA Length) × Volume Ratio
- Volume Delta (vd) = mac - mao
The Volume Delta shows:
- Positive values (green) = Buying pressure (buyers are more active)
- Negative values (red) = Selling pressure (sellers are more active)
2. VOLUME DELTA MOVING AVERAGE 📊
The strategy calculates an EMA of the Volume Delta (vdma) to smooth out
fluctuations and identify the overall trend of buying/selling pressure:
- vdma = EMA(Volume Delta, EMA Length)
- When vdma is above zero = Overall buying pressure
- When vdma is below zero = Overall selling pressure
3. PERCENTILE-BASED ENTRY CONDITIONS 🎲
Instead of using fixed thresholds, the strategy uses percentile analysis to
identify extreme volume delta movements:
For LONG entries:
- Analyzes seller volumes (negative volume delta) over the lookback period
- Calculates the percentile threshold (default: 80th percentile)
- Enters LONG when volume delta becomes positive AND exceeds the threshold
- This indicates a strong shift from selling to buying pressure
For SHORT entries:
- Analyzes buyer volumes (positive volume delta) over the lookback period
- Calculates the percentile threshold (default: 80th percentile)
- Enters SHORT when volume delta becomes negative AND exceeds the threshold
- This indicates a strong shift from buying to selling pressure
4. POSITION SIZING 💰
The strategy offers two position sizing methods:
a) RISK VALUE (Fixed Risk in Dollars):
- Calculates position size based on a fixed dollar risk amount
- Formula: Position Size = Risk Amount / (Entry Price × Stop Loss %)
- Ensures consistent risk per trade regardless of price level
b) LOTS SIZE:
- Uses a fixed lot size for all trades
- Simple and straightforward approach
- Useful when you want consistent position sizes
5. TAKE PROFIT & STOP LOSS SETTINGS 🎯
The strategy offers flexible TP/SL configuration in three modes:
a) PERCENTAGE (%):
- TP/SL calculated as a percentage of entry price
- Example: 2% TP means entry price × 1.02 (for LONG) or × 0.98 (for SHORT)
- Adapts automatically to different price levels
b) CURRENCY:
- TP/SL set as a fixed currency amount
- Example: $100 TP means entry price + $100 (for LONG) or - $100 (for SHORT)
- Useful for instruments with consistent price movements
c) PIPS:
- TP/SL set as a fixed number of pips
- Automatically converts pips to price using the instrument's minimum tick
- Ideal for forex and other pip-based instruments
6. AUTOMATIC TRADE EXECUTION ⚡
When entry conditions are met:
- Opens a position (LONG or SHORT) at market price
- Automatically sets Take Profit and Stop Loss based on selected mode
- Sends an alert with all trade information
- Only one position at a time (waits for current position to close)
AVAILABLE PARAMETERS ⚙️
----------------------
1. MA LENGTH (Default: 10)
- Length of the Exponential Moving Average used for close and open prices
- Lower values = More sensitive to recent price action
- Higher values = More smoothed, less sensitive
2. EMA LENGTH (Default: 20)
- Length of the EMA applied to Volume Delta
- Controls the smoothing of the volume delta signal
- Lower values = Faster signals, more trades
- Higher values = Slower signals, fewer but potentially more reliable trades
3. POSITION SIZE MODE
- "Risk Value": Calculate position size based on fixed dollar risk
- "Lots Size": Use fixed lot size for all trades
4. FIXED RISK IN $ (Default: 50)
- Only used when Position Size Mode = "Risk Value"
- The dollar amount you're willing to risk per trade
- Strategy calculates position size automatically
5. LOT SIZE (Default: 0.01)
- Only used when Position Size Mode = "Lots Size"
- Fixed lot size for all trades
6. TAKE PROFIT MODE
- "%": Percentage of entry price
- "Currency": Fixed currency amount
- "Pips": Fixed number of pips
7. STOP LOSS MODE
- "%": Percentage of entry price
- "Currency": Fixed currency amount
- "Pips": Fixed number of pips
8. TAKE PROFIT / STOP LOSS VALUES
- Different input fields appear based on selected mode
- Configure TP and SL independently
9. VOLUME LOOKBACK PERIOD (Default: 20)
- Number of bars used to calculate percentile thresholds
- Lower values = More sensitive, adapts faster to recent conditions
- Higher values = More stable, uses longer-term statistics
10. PERCENTILE THRESHOLD (Default: 80%)
- The percentile level used to identify extreme volume delta movements
- 80% means: only enter when volume delta exceeds 80% of recent values
- Higher values = Fewer but potentially stronger signals
- Lower values = More frequent signals
VISUALIZATION 📊
---------------
The strategy displays on the chart:
1. VOLUME DELTA COLUMNS
- Green columns = Positive volume delta (buying pressure)
- Red columns = Negative volume delta (selling pressure)
- Height represents the magnitude of buying/selling pressure
2. VOLUME DELTA MA AREA
- Two overlapping area plots showing the smoothed volume delta
- Black area (base layer) for overall visualization
- Green area (when positive) = Overall buying pressure trend
- Red area (when negative) = Overall selling pressure trend
- Helps identify the dominant market sentiment
3. ZERO LINE
- Horizontal line at zero
- Helps visualize when buying/selling pressure crosses the neutral point
ALERTS 🔔
--------
When enabled, the strategy sends alerts when a trade is opened. The alert
message includes:
- Direction: "Buy" for LONG positions or "Sell" for SHORT positions
- Entry Price: The price at which the position was opened
- TP (Take Profit): The target profit price
- SL (Stop Loss): The stop loss price
Example alert message:
"Buy | Entry: 1.2050 | TP: 1.2250 | SL: 1.1950"
Alerts can be configured in TradingView to send notifications via email,
SMS, webhooks, or other platforms.
RECOMMENDED SETTINGS 🎯
-----------------------
To get started, you can use these settings:
STRATEGY PARAMETERS:
- MA Length: 10 (default)
- EMA Length: 20 (default)
- Volume Lookback Period: 20 (default)
- Percentile Threshold: 80% (default)
POSITION SIZING:
- Position Size Mode: "Risk Value" (for risk management)
- Fixed Risk in $: Adjust based on your account size (e.g., 1-2% of account)
- OR use "Lots Size" with 0.01 lots for small accounts
TAKE PROFIT & STOP LOSS:
- TP Mode: "%" (recommended for most instruments)
- SL Mode: "%" (recommended for most instruments)
- Take Profit (%): 2.0% (adjust based on your risk/reward preference)
- Stop Loss (%): 1.0% (adjust based on your risk tolerance)
For Forex:
- Consider using "Pips" mode for TP/SL
- Typical values: 20-50 pips TP, 10-30 pips SL
For Stocks/Indices:
- Use "%" mode for TP/SL
- Typical values: 2-5% TP, 1-2% SL
PRACTICAL EXAMPLE 📝
-------------------
Scenario: LONG Entry on EUR/USD
1. Market conditions:
- Price: 1.1000
- Volume Delta becomes strongly positive
- Volume Delta exceeds 80th percentile of recent seller volumes
2. Strategy calculates:
- Entry Price: 1.1000 (current close)
- Position Size Mode: "Risk Value"
- Fixed Risk: $50
- Stop Loss Mode: "%"
- Stop Loss: 1.0%
- Position Size = $50 / (1.1000 × 0.01) = 4.55 lots
3. Strategy opens position:
- Direction: LONG (Buy)
- Entry: 1.1000
- Take Profit: 1.1220 (2% above entry)
- Stop Loss: 1.0890 (1% below entry)
- Alert sent: "Buy | Entry: 1.1000 | TP: 1.1220 | SL: 1.0890"
4. Outcome scenarios:
- If price rises to 1.1220 → Take Profit hit (profit)
- If price falls to 1.0890 → Stop Loss hit (loss limited to $50)
IMPORTANT NOTE ⚠️
-----------------
This strategy is a technical analysis tool based on volume delta analysis.
Like all trading strategies, it does NOT guarantee profits. Trading involves
significant risks and you can lose money, including your entire investment.
Past performance does not guarantee future results.
Always:
- Use appropriate risk management
- Never risk more than you can afford to lose
- Test the strategy on historical data (backtesting) before using real money
- Start with small position sizes or paper trading
- Understand that no strategy works 100% of the time
- Consider market conditions, news events, and other factors
- Keep a trading journal to learn and improve
The author and contributors are NOT responsible for any losses incurred from
using this strategy. Trading decisions are your own responsibility. Profits
are NOT guaranteed, and losses are possible.
LICENSE 📄
---------
This code is open source and available for modification. You are free to use,
modify, and distribute this strategy. If you republish or share a modified
version, please kindly mention the original author.
================================================================================
Golden Vector Trend Orchestrator (GVTO)Golden Vector Trend Orchestrator (GVTO) is a composite trend-following strategy specifically engineered for XAUUSD (Gold) and volatile assets on H4 (4-Hour) and Daily timeframes.
This script aims to solve a common problem in trend trading: "Whipsaws in Sideways Markets." Instead of relying on a single indicator, GVTO employs a Multi-Factor Confluence System that filters out low-probability trades by requiring alignment across Trend Structure, Momentum, and Volatility.
🛠 Methodology & Logic
The strategy executes trades only when four distinct technical conditions overlap (Confluence). If any single condition is not met, the trade is filtered out to preserve capital.
1. Market Structure Filter (200 EMA)
Indicator: Exponential Moving Average (Length 200).
Logic: The 200 EMA acts as the baseline for the long-term trend regime.
Bullish Regime: Price must close above the 200 EMA.
Bearish Regime: Price must close below the 200 EMA.
Purpose: Prevents counter-trend trading against the macro direction.
2. Signal Trigger & Trailing Stop (Supertrend)
Indicator: Supertrend (ATR Length 14, Factor 3.5).
Logic: Uses Average True Range (ATR) to detect trend reversals while accounting for volatility.
Purpose: Provides the specific entry signal and acts as a dynamic trailing stop-loss to let profits run while cutting losses when the trend invalidates.
3. Volatility Gatekeeper (ADX Filter)
Indicator: Average Directional Index (Length 14).
Threshold: > 25.
Logic: A high ADX value indicates a strong trend presence, regardless of direction.
Purpose: This is the most critical filter. It prevents the strategy from entering trades during "choppy" or ranging markets (consolidation zones) where trend-following systems typically fail.
4. Momentum Confirmation (DMI)
Indicator: Directional Movement Index (DI+ and DI-).
Logic: Checks if the buying pressure (DI+) is physically stronger than selling pressure (DI-), or vice versa.
Purpose: Ensures that the price movement is backed by genuine momentum, not just a momentary price spike.
📋 How to Use This Strategy
🟢 LONG (BUY) Setup
A Buy signal is generated only when ALL of the following occur simultaneously:
Price Action: Price closes ABOVE the 200 EMA (Orange Line).
Trigger: Supertrend flips to GREEN (Bullish).
Strength: ADX is greater than 25 (Strong Trend).
Momentum: DI+ (Plus Directional Indicator) is greater than DI- (Minus).
🔴 SHORT (SELL) Setup
A Sell signal is generated only when ALL of the following occur simultaneously:
Price Action: Price closes BELOW the 200 EMA (Orange Line).
Trigger: Supertrend flips to RED (Bearish).
Strength: ADX is greater than 25 (Strong Trend).
Momentum: DI- (Minus Directional Indicator) is greater than DI+ (Plus).
🛡 Exit Strategy
Stop Loss / Take Profit: The strategy utilizes the Supertrend Line as a dynamic Trailing Stop.
Exit Long: When Supertrend turns Red.
Exit Short: When Supertrend turns Green.
Note: Traders can also use the real-time P/L Dashboard included in the script to manually secure profits based on their personal Risk:Reward ratio.
📊 Included Features
Real-Time P/L Dashboard: A table in the top-right corner displays the current trend status, ADX strength, and the Unrealized Profit/Loss % of the current active position.
Smart Labeling: Buy/Sell labels are coded to appear only on the initial entry trigger. They do not repaint and do not spam the chart if the trend continues (no pyramiding visualization).
Visual Aids: Background color changes (Green/Red) to visually represent the active trend based on the Supertrend status.
⚠️ Risk Warning & Best Practices
Asset Class: Optimized for XAUUSD (Gold) due to its high volatility nature. It also works well on Crypto (BTC, ETH) and Major Forex Pairs.
Timeframe: Highly recommended for H4 (4 Hours) or D1 (Daily). Using this on lower timeframes (M5, M15) may result in false signals due to market noise.
News Events: Automated strategies cannot predict economic news (CPI, NFP). Exercise caution or pause trading during high-impact economic releases.
Algomist.app v1.0🚀 WMA Crossover Momentum Scalper: Algomist.app AUTO-EXECUTION
This strategy is a momentum-based trend-following system optimized for fully automated, high-frequency trade execution via algomist.app webhooks. It systematically enters trades based on a powerful moving average crossover, confirmed by both volume and volatility filters.
⚙️ Core Strategy Logic
This script is designed to capture short- to medium-term moves in trending markets by combining three key indicators:
Trend Confirmation (WMA Crossover): The primary signal is generated when a Fast WMA (50-period) crosses the Slow WMA (100-period). This crossover confirms the shift in the prevailing trend direction.
Volume Filter (VWAP): The trade is only taken if the price is trading above the VWAP for Long entries, or below the VWAP for Short entries. This ensures the trade is aligned with the asset's average price relative to trading volume.
Volatility Filter (ATR): A minimum Average True Range (ATR) filter is applied. This is critical for avoiding entries during periods of extreme low volatility ("chop"), ensuring the market has enough movement to justify the trade.
🔗 Algomist.app Automation Ready
This is the most important feature. The script contains custom-coded alert() functions that output a perfect JSON payload, making it 100% compatible with the algomist.app webhook infrastructure.
Seamless Execution: The strategy instantly transmits all required parameters—symbol, side, entry_price, dynamic stop_loss, and dynamic take_profit—directly to your MT5 terminal through the algomist.app connector.
Simple Setup: To enable live automation, you only need to configure a TradingView alert using the provided webhook URL and the {{strategy.order.alert_message}} placeholder on the bar's close.
Default Asset: The webhook is pre-configured to trade the ETHUSDC symbol. This can be easily adapted to other crypto or Forex pairs within the algomist.app settings.
🛡️ Dynamic Risk Management (ATR-Based)
Risk management is dynamic, ensuring the Stop Loss and Take Profit levels automatically adapt to current market volatility:
Stop Loss (SL): Placed at a customizable (x) * ATR distance from the entry price. The default setting is 3.0x ATR.
Take Profit (TP): Placed at a customizable (x) * ATR distance from the entry price. The default setting is 9.0x ATR, offering a fixed Reward-to-Risk ratio of 3:1 (9.0 / 3.0).
Position Sizing: The script uses strategy.percent_of_equity = 10% for backtesting, but the algomist.app execution is based on an internal calculation using a small percentage (e.g., 5%) of a leveraged notional value for illustrative purposes. Users must set their risk size within the algomist.app platform.
Disclaimer: This script is provided as an example for Algomist.app users and is NOT financial advice. Backtest thoroughly across various assets and timeframes. Past performance is not indicative of future results. The user assumes all responsibility for live trading risk.
HMA 9/50 Crossover + RSI 50 Filter1. The Core Indicators
HMA 9 (Fast): Acts as the primary trigger line. Its unique calculation minimizes lag compared to standard moving averages, allowing for faster entries.
HMA 50 (Slow): Defines the medium-term trend direction and acts as the "anchor" for crossover signals.
RSI 14: Serves as a "momentum gate." Instead of traditional overbought/oversold levels, we use the 50 midline to confirm that the directional strength supports the crossover.
2. Entry Conditions
Long Entry: Triggered when the HMA 9 crosses above the HMA 50 AND the RSI is greater than 50.
Short Entry: Triggered when the HMA 9 crosses below the HMA 50 AND the RSI is less than 50.
3. Execution & Reversal
This strategy is currently configured as an Always-in-the-Market system.
A "Long" position is automatically closed when a "Short" signal is triggered.
To prevent "pyramiding" (buying multiple positions in one direction), the script checks the current position_size before opening new entries.
How to Use
Timeframe: Optimized for 3-minute (3m) candles but can be tuned for 1m to 15m scalping.
Settings: Use the Inputs panel to adjust HMA lengths based on the volatility of your specific asset (e.g., shorter for stable stocks, longer for volatile crypto).
Visuals:
Aqua Line: HMA 9
Orange Line: HMA 50
Green Background: Bullish RSI Momentum (> 50)
Red Background: Bearish RSI Momentum (< 50)
Risk Disclosure
Whipsaws: This strategy is likely to underperform in sideways markets.
Backtesting: Past performance does not guarantee future results. Always test this strategy in the Strategy Tester with appropriate commission and slippage settings before live use.
CryptoFlux Dynamo [JOAT]CryptoFlux Dynamo: Velocity Scalping Strategy
WHAT THIS STRATEGY IS
CryptoFlux Dynamo is an open-source Pine Script v6 strategy designed for momentum-based scalping on cryptocurrency perpetual futures. It combines multiple technical analysis methods into a unified system that adapts its behavior based on current market volatility conditions.
This script is published open-source so you can read, understand, and modify the complete logic. The description below explains everything the strategy does so that traders who cannot read Pine Script can fully understand how it works before using it.
HOW THIS STRATEGY IS ORIGINAL AND WHY THE INDICATORS ARE COMBINED
This strategy uses well-known indicators (MACD, EMA, RSI, MFI, Bollinger Bands, Keltner Channels, ATR). The originality is not in the individual indicators themselves, but in the specific way they are integrated into a regime-adaptive system. Here is the detailed justification for why these components are combined and how they work together:
The Problem Being Solved:
Standard indicator-based strategies use fixed thresholds. For example, a typical MACD strategy might enter when the histogram crosses above zero. However, in cryptocurrency markets, volatility changes dramatically throughout the day and week. A MACD crossover during a low-volatility consolidation period has very different implications than the same crossover during a high-volatility trending period. Using the same entry thresholds and stop distances in both conditions leads to either:
Too many false signals during consolidation (if thresholds are loose)
Missing valid opportunities during expansion (if thresholds are tight)
Stops that are too tight during volatility spikes (causing premature exits)
Stops that are too wide during compression (giving back profits)
The Solution Approach:
This strategy first classifies the current volatility regime using normalized ATR (ATR as a percentage of price), then dynamically adjusts ALL other parameters based on that classification. This creates a context-aware system rather than a static threshold comparison.
How Each Component Contributes to the System:
ATR-Based Regime Classification (The Foundation)
The strategy calculates ATR over 21 periods, smooths it with a 13-period EMA to reduce noise from wicks, then divides by price to get a normalized percentage. This ATR% is classified into three regimes:
- Compression (ATR% < 0.8%): Market is consolidating, breakouts are more likely but false signals are common
- Expansion (ATR% 0.8% - 1.6%): Normal trending conditions
- Velocity (ATR% > 1.6%): High volatility, larger moves but also larger adverse excursions
This regime classification then controls stop distances, profit targets, trailing stop offsets, and signal strength requirements. The regime acts as a "meta-parameter" that tunes the entire system.
EMA Ribbon (8/21/34) - Trend Structure Detection
The three EMAs establish trend direction and structure. When EMA 8 > EMA 21 > EMA 34, the trend structure is bullish. The slope of the middle EMA (21) is calculated over 8 bars and converted to degrees using arctangent. This slope measurement quantifies trend strength, not just direction.
Why these specific periods? The 8/21/34 sequence follows Fibonacci-like spacing and provides good separation on 5-minute cryptocurrency charts. The fast EMA (8) responds to immediate price action, the mid EMA (21) represents the short-term trend, and the slow EMA (34) acts as a trend filter.
The EMA ribbon works with the regime classification: during compression regimes, the strategy requires stronger ribbon alignment before entry because false breakouts are more common.
MACD (8/21/5) - Momentum Measurement
The MACD uses faster parameters (8/21/5) than the standard (12/26/9) because cryptocurrency markets move faster than traditional markets. The histogram is smoothed with a 5-period EMA to reduce noise.
The key innovation is the adaptive histogram baseline. Instead of using a fixed threshold, the strategy calculates a rolling baseline from the smoothed absolute histogram value, then multiplies by a sensitivity factor (1.15). This means the threshold for "significant momentum" automatically adjusts based on recent momentum levels.
The MACD works with the regime classification: during velocity regimes, the histogram baseline is effectively higher because recent momentum has been stronger, preventing entries on relatively weak momentum.
RSI (21 period) and MFI (21 period) - Independent Momentum Confirmation
RSI measures momentum using price changes only. MFI (Money Flow Index) measures momentum using price AND volume. By requiring both to confirm, the strategy filters out price moves that lack volume support.
The 21-period length is longer than typical (14) to reduce noise on 5-minute charts. The trigger threshold (55 for longs, 45 for shorts) is slightly offset from 50 to require momentum in the trade direction, not just neutral readings.
These indicators work together: a signal requires RSI > 55 AND MFI > 55 for longs. This dual confirmation reduces false signals from price manipulation or low-volume moves.
Bollinger Bands (1.5 mult) and Keltner Channels (1.8 mult) - Squeeze Detection
When Bollinger Bands contract inside Keltner Channels, volatility is compressing and a breakout is likely. This is the "squeeze" condition. When the bands expand back outside the channels, the squeeze "releases."
The strategy uses a 1.5 multiplier for Bollinger Bands (tighter than standard 2.0) and 1.8 for Keltner Channels. These values were chosen to identify meaningful squeezes on 5-minute cryptocurrency charts without triggering too frequently.
The squeeze detection works with the regime classification: squeeze releases during compression regimes receive additional signal strength points because breakouts from consolidation are more significant.
Volume Impulse Detection - Institutional Participation Filter
The strategy calculates a volume baseline (34-period SMA) and standard deviation. A "volume impulse" is detected when current volume exceeds the baseline by 1.15x OR when the volume z-score exceeds 0.5.
This filter ensures entries occur when there is meaningful market participation, not during low-volume periods where price moves are less reliable.
Volume impulse is required for all entries and adds points to the composite signal strength score.
Cycle Oscillator - Trend Alignment Filter
The strategy calculates a 55-period EMA as a cycle basis, then measures price deviation from this basis as a percentage. When price is more than 0.15% above the cycle basis, the cycle is bullish. When more than 0.15% below, the cycle is bearish.
This filter prevents counter-trend entries. Long signals require bullish cycle alignment; short signals require bearish cycle alignment.
BTC Dominance Filter (Optional) - Market Regime Filter
The strategy can optionally use BTC.D (Bitcoin Dominance) as a market regime filter. When BTC dominance is rising (slope > 0.12), the market is in "risk-off" mode and long entries on altcoins are filtered. When dominance is falling (slope < -0.12), short entries are filtered.
This filter is optional because the BTC.D data feed may lag during low-liquidity periods.
How The Components Work Together (The Mashup Justification):
The strategy uses a composite scoring system where each signal pathway contributes points:
Trend Break pathway (30 points): Requires EMA ribbon alignment + positive slope + price breaks above recent structure high
Momentum Surge pathway (30 points): Requires MACD histogram > adaptive baseline + MACD line > signal + RSI > 55 + MFI > 55 + volume impulse
Squeeze Release pathway (25 points): Requires BB inside KC (squeeze) then release + momentum bias + histogram confirmation
Micro Pullback pathway (15 points): Requires shallow retracement to fast EMA within established trend + histogram confirmation + volume impulse
Additional modifiers:
+5 points if volume impulse is present, -5 if absent
+5 points in velocity regime, -2 in compression regime
+5 points if cycle is aligned, -5 if counter-trend
A trade only executes when the composite score reaches the minimum threshold (default 55) AND all filters agree (session, cycle bias, BTC dominance if enabled).
This scoring system is the core innovation: instead of requiring ALL conditions to be true (which would generate very few signals) or ANY condition to be true (which would generate too many false signals), the strategy requires ENOUGH conditions to be true, with different conditions contributing different weights based on their reliability.
HOW THE STRATEGY CALCULATES ENTRIES AND EXITS
Entry Logic:
1. Calculate current volatility regime from ATR%
2. Calculate all indicator values (MACD, EMA, RSI, MFI, squeeze, volume)
3. Evaluate each signal pathway and sum points
4. Check all filters (session, cycle, dominance, kill switch)
5. If composite score >= 55 AND all filters pass, generate entry signal
6. Calculate position size based on risk per trade and regime-adjusted stop distance
7. Execute entry with regime name as comment
Position Sizing Formula:
RiskCapital = Equity * (0.65 / 100)
StopDistance = ATR * StopMultiplier(regime)
RawQuantity = RiskCapital / StopDistance
MaxQuantity = Equity * (12 / 100) / Price
Quantity = min(RawQuantity, MaxQuantity)
Quantity = round(Quantity / 0.001) * 0.001
This ensures each trade risks approximately 0.65% of equity regardless of volatility, while capping total exposure at 12% of equity.
Stop Loss Calculation:
Stop distance is ATR multiplied by a regime-specific multiplier:
Compression regime: 1.05x ATR (tighter stops because moves are smaller)
Expansion regime: 1.55x ATR (standard stops)
Velocity regime: 2.1x ATR (wider stops to avoid premature exits during volatility)
Take Profit Calculation:
Target distance is ATR multiplied by regime-specific multiplier and base risk/reward:
Compression regime: 1.6x ATR * 1.8 base R:R * 0.9 regime bonus = approximately 2.6x ATR
Expansion regime: 2.05x ATR * 1.8 base R:R * 1.0 regime bonus = approximately 3.7x ATR
Velocity regime: 2.8x ATR * 1.8 base R:R * 1.15 regime bonus = approximately 5.8x ATR
Trailing Stop Logic:
When adaptive trailing is enabled, the strategy calculates a trailing offset based on ATR and regime:
Compression regime: 1.1x base offset (looser trailing to avoid noise)
Expansion regime: 1.0x base offset (standard)
Velocity regime: 0.8x base offset (tighter trailing to lock in profits during fast moves)
The trailing stop only activates when it would be tighter than the initial stop.
Momentum Fail-Safe Exits:
The strategy closes positions early if momentum reverses:
Long positions close if MACD histogram turns negative OR EMA ribbon structure breaks (fast EMA crosses below mid EMA)
Short positions close if MACD histogram turns positive OR EMA ribbon structure breaks
This prevents holding through momentum reversals even if stop loss hasn't been hit.
Kill Switch:
If maximum drawdown exceeds 6.5%, the strategy disables new entries until manually reset. This prevents continued trading during adverse conditions.
HOW TO USE THIS STRATEGY
Step 1: Apply to Chart
Use a 5-minute chart of a high-liquidity cryptocurrency perpetual (BTC/USDT, ETH/USDT recommended)
Ensure at least 200 bars of history are loaded for indicator stabilization
Use standard candlestick charts only (not Heikin Ashi, Renko, or other non-standard types)
Step 2: Understand the Visual Elements
EMA Ribbon: Three lines (8/21/34 periods) showing trend structure. Bullish when stacked upward, bearish when stacked downward.
Background Color: Shows current volatility regime
- Indigo/dark blue = Compression (low volatility)
- Purple = Expansion (normal volatility)
- Magenta/pink = Velocity (high volatility)
Bar Colors: Reflect signal strength divergence. Brighter colors indicate stronger directional bias.
Triangle Markers: Entry signals. Up triangles below bars = long entry. Down triangles above bars = short entry.
Dashboard (top-right): Real-time display of regime, ATR%, signal strengths, position status, stops, targets, and risk metrics.
Step 3: Interpret the Dashboard
Regime: Current volatility classification (Compression/Expansion/Velocity)
ATR%: Normalized volatility as percentage of price
Long/Short Strength: Current composite signal scores (0-100)
Cycle Osc: Price deviation from 55-period EMA as percentage
Dominance: BTC.D slope and filter status
Position: Current position direction or "Flat"
Stop/Target: Current stop loss and take profit levels
Kill Switch: Status of drawdown protection
Volume Z: Current volume z-score
Impulse: Whether volume impulse condition is met
Step 4: Adjust Parameters for Your Needs
For more conservative trading: Increase "Minimum Composite Signal Strength" to 65 or higher
For more aggressive trading: Decrease to 50 (but expect more false signals)
For higher timeframes (15m+): Increase "Structure Break Window" to 12-15, increase "RSI Momentum Trigger" to 58
For lower liquidity pairs: Increase "Volume Impulse Multiplier" to 1.3, increase slippage in strategy properties
To disable short selling: Uncheck "Enable Short Structure"
To disable BTC dominance filter: Uncheck "BTC Dominance Confirmation"
STRATEGY PROPERTIES (BACKTEST SETTINGS)
These are the exact settings used in the strategy's Properties dialog box. You must use these same settings when evaluating the backtest results shown in the publication:
Initial Capital: $100,000
Justification: This amount is higher than typical retail accounts. I chose this value to demonstrate percentage-based returns that scale proportionally. The strategy uses percentage-based position sizing (0.65% risk per trade), so a $10,000 account would see the same percentage returns with 10x smaller position sizes. The absolute dollar amounts in the backtest should be interpreted as percentages of capital.
Commission: 0.04% (commission_value = 0.04)
Justification: This reflects typical perpetual futures exchange fees. Major exchanges charge between 0.02% (maker) and 0.075% (taker). The 0.04% value is a reasonable middle estimate. If your exchange charges different fees, adjust this value accordingly. Higher fees will reduce net profitability.
Slippage: 1 tick
Justification: This is conservative for liquid pairs like BTC/USDT on major exchanges during normal conditions. For less liquid altcoins or during high volatility, actual slippage may be higher. If you trade less liquid pairs, increase this value to 2-3 ticks for more realistic results.
Pyramiding: 1
Justification: No position stacking. The strategy holds only one position at a time. This simplifies risk management and prevents overexposure.
calc_on_every_tick: true
Justification: The strategy evaluates on every price update, not just bar close. This is necessary for scalping timeframes where waiting for bar close would miss opportunities. Note that this setting means backtest results may differ slightly from bar-close-only evaluation.
calc_on_order_fills: true
Justification: The strategy recalculates immediately after order fills for faster response to position changes.
RISK PER TRADE JUSTIFICATION
The default risk per trade is 0.65% of equity. This is well within the TradingView guideline that "risking more than 5-10% on a trade is not typically considered viable."
With the 12% maximum exposure cap, even if the strategy takes multiple consecutive losses, the total risk remains manageable. The kill switch at 6.5% drawdown provides additional protection by halting new entries during adverse conditions.
The position sizing formula ensures that stop distance (which varies by regime) is accounted for, so actual risk per trade remains approximately 0.65% regardless of volatility conditions.
SAMPLE SIZE CONSIDERATIONS
For statistically meaningful backtest results, you should select a dataset that generates at least 100 trades. On 5-minute BTC/USDT charts, this typically requires:
2-3 months of data during normal market conditions
1-2 months during high-volatility periods
3-4 months during low-volatility consolidation periods
The strategy's selectivity (requiring 55+ composite score plus all filters) means it generates fewer signals than less filtered approaches. If your backtest shows fewer than 100 trades, extend the date range or reduce the minimum signal strength threshold.
Fewer than 100 trades produces statistically unreliable results. Win rate, profit factor, and other metrics can vary significantly with small sample sizes.
STRATEGY DESIGN COMPROMISES AND LIMITATIONS
Every strategy involves trade-offs. Here are the compromises made in this design and the limitations you should understand:
Selectivity vs. Opportunity Trade-off
The 55-point minimum threshold filters many potential trades. This reduces false signals but also misses valid setups that don't meet all criteria. Lowering the threshold increases trade frequency but decreases win rate. There is no "correct" threshold; it depends on your preference for fewer higher-quality signals vs. more signals with lower individual quality.
Regime Classification Lag
The ATR-based regime detection uses historical data (21 periods + 13-period smoothing). It cannot predict sudden volatility spikes. During flash crashes or black swan events, the strategy may be classified in the wrong regime for several bars before the classification updates. This is an inherent limitation of any lagging indicator.
Indicator Parameter Sensitivity
The default parameters (MACD 8/21/5, EMA 8/21/34, RSI 21, etc.) are tuned for BTC/ETH perpetuals on 5-minute charts during 2024 market conditions. Different assets, timeframes, or market regimes may require different parameters. There is no guarantee that parameters optimized on historical data will perform similarly in the future.
BTC Dominance Filter Limitations
The CRYPTOCAP:BTC.D data feed may lag during low-liquidity periods or weekends. The dominance slope calculation uses a 5-bar SMA, adding additional delay. If you notice the filter behaving unexpectedly, consider disabling it.
Backtest vs. Live Execution Differences
TradingView backtesting does not replicate actual broker execution. Key differences:
Backtests assume perfect fills at calculated prices; real execution involves order book depth, latency, and partial fills
The calc_on_every_tick setting improves backtest realism but still cannot capture sub-bar price action or order book dynamics
Commission and slippage settings are estimates; actual costs vary by exchange, time of day, and market conditions
Funding rates on perpetual futures are not modeled in backtests and can significantly impact profitability over time
Exchange-specific limitations (position limits, liquidation mechanics, order types) are not modeled
Market Condition Dependencies
This strategy is designed for trending and breakout conditions. During extended sideways consolidation with no clear direction, the strategy may generate few signals or experience whipsaws. No strategy performs well in all market conditions.
Cryptocurrency-Specific Risks
Cryptocurrency markets operate 24/7 without session boundaries. This means:
No natural "overnight" risk reduction
Volatility can spike at any time
Liquidity varies significantly by time of day
Exchange outages or issues can occur at any time
WHAT THIS STRATEGY DOES NOT DO
To be straightforward about limitations:
This strategy does not guarantee profits. Past backtest performance does not indicate future results.
This strategy does not predict the future. It reacts to current conditions based on historical patterns.
This strategy does not account for funding rates, which can significantly impact perpetual futures profitability.
This strategy does not model exchange-specific execution issues (partial fills, requotes, outages).
This strategy does not adapt to fundamental news events or black swan scenarios.
This strategy is not optimized for all market conditions. It may underperform during extended consolidation.
IMPORTANT RISK WARNINGS
Past performance does not guarantee future results. The backtest results shown reflect specific historical market conditions and parameter settings. Markets change constantly, and strategies that performed well historically may underperform or lose money in the future. A single backtest run does not constitute proof of future profitability.
Trading involves substantial risk of loss. Cryptocurrency derivatives are highly volatile instruments. You can lose your entire investment. Only trade with capital you can afford to lose completely.
This is not financial advice. This strategy is provided for educational and informational purposes only. It does not constitute investment advice, trading recommendations, or any form of financial guidance. The author is not a licensed financial advisor.
You are responsible for your own decisions. Before using this strategy with real capital:
Thoroughly understand the code and logic by reading the open-source implementation
Forward test with paper trading or very small positions for an extended period
Verify that commission, slippage, and execution assumptions match your actual trading environment
Understand that live results will differ from backtest results
Consider consulting with a qualified financial advisor
No guarantees or warranties. This strategy is provided "as is" without any guarantees of profitability, accuracy, or suitability for any purpose. The author is not responsible for any losses incurred from using this strategy.
OPEN-SOURCE CODE STRUCTURE
The strategy code is organized into these sections for readability:
Configuration Architecture: Input parameters organized into logical groups (Core Controls, Optimization Constants, Regime Intelligence, Signal Pathways, Risk Architecture, Visualization)
Helper Functions: calcQty() for position sizing, clamp01() and normalize() for value normalization, calcMFI() for Money Flow Index calculation
Core Indicator Engine: EMA ribbon, ATR and regime classification, MACD with adaptive baseline, RSI, MFI, volume analytics, cycle oscillator, BTC dominance filter, squeeze detection
Signal Pathway Logic: Trend break, momentum surge, squeeze release, micro pullback pathways with composite scoring
Entry/Exit Orchestration: Signal filtering, position sizing, entry execution, stop/target calculation, trailing stop logic, momentum fail-safe exits
Visualization Layer: EMA plots, regime background, bar coloring, signal labels, dashboard table
You can read and modify any part of the code. Understanding the logic before deployment is strongly recommended.
- Made with passion by officialjackofalltrades
LR Candles V2.1IMPORTANT: Use this strategy only with Heikin Ashi candles; otherwise, the results will be negative.
The use of this strategy is solely and exclusively under the responsibility of the operator.
To perform testing correctly and as close to market reality as possible, we suggest setting the strategy preferences as follows:
Slippage = 3
Using bar magnifico = Enabled
Commission = Completed
Detail: It is important to include at least 1,000 trades in the test. This provides a certain robustness in the historical analysis of a strategy. Values lower than this may alter the expected results when trading in real life.
Tip:
Play around with different time frames and calibrations on the strategic indicator. Examples include unchecking Ling-Reg, unchecking EMA, or using both in combination. Look for the best probability and results for a specific asset.
The strategy usually performs well on time frames longer than 1 hour; this is what has been observed.
Elite MTF EMA Reclaim StrategyThis script is a 6-minute execution MTF EMA “retest → reclaim” strategy. It looks for trend-aligned pullbacks into fast EMAs, then enters when price reclaims and (optionally) retests the reclaim level—while filtering out chop (low trend strength/volatility or recent EMA20/50 crosses) and enforcing higher-timeframe alignment (Daily + 1H, or whichever you select).
How to use
Run it on a 6-minute chart (that’s what the presets are tuned for).
Pick your Market (Forex / XAUUSD / Crypto / Indices) and a Preset:
Elite = strictest, cleanest (fewer signals)
Balanced = middle ground
Aggressive = most signals, loosest filters
Set HTF Alignment Mode:
D + H1 (recommended) for highest quality
Off if you want more trades / LTF-only testing
Leave Kill Chop = ON (recommended). If you’re not getting trades, this is usually the blocker.
Choose entry behavior:
If Require Retest = true, entries happen on the retest after reclaim (cleaner, later).
If Require Retest = false, entries trigger on reclaim using Reclaim Timing Default:
“Preset” uses the strategy’s recommended default per market/preset
or force Reclaim close / Next bar confirmation
For backtesting, keep Mode = Strategy (Backtest). For alerts/visual-only, set Mode = Indicator (Signals Only).
Use Show Signals (All Modes) to toggle triangles on/off without affecting trades.
Tip: If TradingView says “not enough data,” switch symbol history to “All,” reduce HTF alignment (try H1 only), or backtest a more recent date range.
A-Share Broad-Based ETF Dual-Core Timing System1. Strategy Overview
The "A-Share Broad-Based ETF Dual-Core Timing System" is a quantitative trading strategy tailored for the Chinese A-share market (specifically for broad-based ETFs like CSI 300, CSI 500, STAR 50). Recognizing the market's characteristic of "short bulls, long bears, and sharp bottoms," this strategy employs a "Left-Side Latency + Right-Side Full Position" dual-core driver. It aims to safely bottom-fish during the late stages of a bear market and maximize profits during the main ascending waves of a bull market.
2. Core Logic
A. Left-Side Latency (Rebound/Bottom Fishing)
Capital Allocation: Defaults to 50% position.
Philosophy: "Buy when others fear." Seeks opportunities in extreme panic or momentum divergence.
Entry Signals (Triggered by any of the following):
Extreme Panic: RSI Oversold (<30) + Price below Bollinger Lower Band + Bullish Candle Close (Avoid catching falling knives).
Oversold Bias: Price deviates more than 15% from the 60-day MA (Life Line), betting on mean reversion.
MACD Bullish Divergence: Price makes a new low while MACD histogram does not, accompanied by strengthening momentum.
B. Right-Side Full Position (Trend Following)
Capital Allocation: Aggressively scales up to Full Position (~99%) upon signal trigger.
Philosophy: "Follow the trend." Strike heavily once the trend is confirmed.
Entry Signals (All must be met):
Upward Trend: MACD Golden Cross + Price above 20-day MA.
Breakout Confirmation: CCI indicator breaks above 100, confirming a main ascending wave.
Volume Support: Volume MACD Golden Cross, ensuring price increase is backed by volume.
C. Smart Risk Control
Bear Market Exhaustion Exit: In a bearish trend (MA20 < MA60), the strategy does not "hold and hope." It immediately liquidates left-side positions upon signs of rebound exhaustion (breaking below MA20, touching MA60 resistance, or RSI failure).
ATR Trailing Stop: Uses Average True Range (ATR) to calculate a dynamic stop-profit line that rises with the price to lock in profits.
Hard Stop Loss: Forces a stop-loss if the left-side bottom fishing fails and losses exceed a set ATR multiple, preventing deep drawdowns.
3. Recommendations
Target Assets: High liquidity broad-based ETFs such as CSI 300 ETF (510300), CSI 500 ETF (510500), ChiNext ETF (159915), STAR 50 ETF (588000).
Timeframe: Daily Chart.
Liquidity Maxing [JOAT]Liquidity Maxing - Institutional Liquidity Matrix
Introduction
Liquidity Maxing is an open-source strategy for TradingView built around institutional market structure concepts. It identifies structural shifts, evaluates trades through multi-factor confluence, and implements layered risk controls.
The strategy is designed for swing trading on 4-hour timeframes, focusing on how institutional order flow manifests in price action through structure breaks, inducements, and liquidity sweeps.
Core Functionality
Liquidity Maxing performs three primary functions:
Tracks market structure to identify when control shifts between buyers and sellers
Scores potential trades using an eight-factor confluence system
Manages position sizing and risk exposure dynamically based on volatility and user-defined limits
The goal is selective trading when multiple conditions align, rather than frequent entries.
Market Structure Engine
The structure engine tracks three key events:
Break of Structure (BOS): Price pushes beyond a prior pivot in the direction of trend
Change of Character (CHoCH): Control flips from bullish to bearish or vice versa
Inducement Sweeps (IDM): Market briefly runs stops against trend before moving in the real direction
The structure module continuously updates strong highs and lows, labeling structural shifts visually. IDM markers are optional and disabled by default to maintain chart clarity.
The trade engine requires valid structure alignment before considering entries. No structure, no trade.
Eight-Factor Confluence System
Instead of relying on a single indicator, Liquidity Maxing uses an eight-factor scoring system:
Structure alignment with current trend
RSI within healthy bands (different ranges for up and down trends)
MACD momentum agreement with direction
Volume above adaptive baseline
Price relative to main trend EMA
Session and weekend filter (configurable)
Volatility expansion/contraction via ATR shifts
Higher-timeframe EMA confirmation
Each factor contributes one point to the confluence score. The default minimum confluence threshold is 6 out of 8, but you can adjust this from 1-8 based on your preference for trade frequency versus selectivity.
Only when structure and confluence agree does the strategy proceed to risk evaluation.
Dynamic Risk Management
Risk controls are implemented in multiple layers:
ATR-based stops and targets with configurable risk-to-reward ratio (default 2:1)
Volatility-adjusted position sizing to maintain consistent risk per trade as ranges expand or compress
Daily and weekly risk budgets that halt new entries once thresholds are reached
Correlation cooldown to prevent clustered trades in the same direction
Global circuit breaker with maximum drawdown limit and emergency kill switch
If any guardrail is breached, the strategy will not open new positions. The dashboard clearly displays risk state for transparency.
Market Presets
The strategy includes configuration presets optimized for different market types:
Crypto (BTC/ETH): RSI bands 70/30, volume multiplier 1.2, enhanced ATR scaling
Forex Majors: RSI bands 75/25, volume multiplier 1.5
Indices (SPY/QQQ): RSI bands 70/30, volume multiplier 1.3
Custom: Default values for user customization
For crypto assets, the strategy automatically applies ATR volatility scaling to account for higher volatility characteristics.
Monitoring and Dashboards
The strategy includes optional monitoring layers:
Risk Operations Dashboard (top-right):
Trend state
Confluence score
ATR value
Current position size percentage
Global drawdown
Daily and weekly risk consumption
Correlation guard state
Alert mode status
Performance Console (top-left):
Net profit
Current equity
Win rate percentage
Average trade value
Sharpe-style ratio (rolling 50-bar window)
Profit factor
Open trade count
Optional risk tint on chart background provides visual indication of "safe to trade" versus "halted" state.
All visualization elements can be toggled on/off from the inputs for clean chart viewing or full telemetry during parameter tuning.
Alerts and Automation
The strategy supports alert integration with two formats:
Standard alerts: Human-readable messages for long, short, and risk-halt conditions
Webhook format: JSON-formatted payloads ready for external execution systems (optional)
Alert messages are predictable and unambiguous, suitable for manual review or automated forwarding to execution engines.
Built-in Validation Suite
The strategy includes an optional validation layer that can be enabled from inputs. It checks:
Internal consistency of structure and confluence metrics
Sanity and ordering of risk parameters
Position sizing compliance with user-defined floors and caps
This validation is optional and not required for trading, but provides transparency into system operation during development or troubleshooting.
Strategy Parameters
Market Presets:
Configuration Preset: Choose between Crypto (BTC/ETH), Forex Majors, Indices (SPY/QQQ), or Custom
Market Structure Architecture:
Pivot Length: Default 5 bars
Filter by Inducement (IDM): Default enabled
Visualize Structure: Default enabled
Structure Lookback: Default 50 bars
Risk & Capital Preservation:
Risk:Reward Ratio: Default 2.0
ATR Period: Default 14
ATR Multiplier (Stop): Default 2.0
Max Drawdown Circuit Breaker: Default 10%
Risk per Trade (% Equity): Default 1.5%
Daily Risk Limit: Default 6%
Weekly Risk Limit: Default 12%
Min Position Size (% Equity): Default 0.25%
Max Position Size (% Equity): Default 5%
Correlation Cooldown (bars): Default 3
Emergency Kill Switch: Default disabled
Signal Confluence:
RSI Length: Default 14
Trend EMA: Default 200
HTF Confirmation TF: Default Daily
Allow Weekend Trading: Default enabled
Minimum Confluence Score (0-8): Default 6
Backtesting Considerations
When backtesting this strategy, consider the following:
Commission: Default 0.05% (adjustable in strategy settings)
Initial Capital: Default $100,000 (adjustable)
Position Sizing: Uses percentage of equity (default 2% per trade)
Timeframe: Optimized for 4-hour charts, though can be tested on other timeframes
Results will vary significantly based on:
Market conditions and volatility regimes
Parameter settings, especially confluence threshold
Risk limit configuration
Symbol characteristics (crypto vs forex vs equities)
Past performance does not guarantee future results. Win rate, profit factor, and other metrics should be evaluated in context of drawdown periods, trade frequency, and market conditions.
How to Use This Strategy
This is a framework that requires understanding and parameter tuning, not a one-size-fits-all solution.
Recommended workflow:
Start on 4-hour timeframe with default parameters and appropriate market preset
Run backtests and study performance console metrics: focus on drawdown behavior, win rate, profit factor, and trade frequency
Adjust confluence threshold to match your risk appetite—higher thresholds mean fewer but more selective trades
Set realistic daily and weekly risk budgets appropriate for your account size and risk tolerance
Consider ATR multiplier adjustments based on market volatility characteristics
Only connect alerts or automation after thorough testing and parameter validation
Treat this as a risk framework with an integrated entry engine, not merely an entry signal generator. The risk controls are as important as the trade signals.
Strategy Limitations
Designed for swing trading timeframes; may not perform optimally on very short timeframes
Requires sufficient market structure to identify pivots; may struggle in choppy or low-volatility environments
Crypto markets require different parameter tuning than traditional markets
Risk limits may prevent entries during favorable setups if daily/weekly budgets are exhausted
Correlation cooldown may delay entries that would otherwise be valid
Backtesting results depend on data quality and may not reflect live trading with slippage
Design Philosophy
Many indicators tell you when price crossed a moving average or RSI left oversold. This strategy addresses questions institutional traders ask:
Who is in control of the market right now?
Is this move structurally significant or just noise?
Do I want to add more risk given what I've already done today/week?
If I'm wrong, exactly how painful can this be?
The strategy provides disciplined, repeatable answers to these questions through systematic structure analysis, confluence filtering, and multi-layer risk management.
Technical Implementation
The strategy uses Pine Script v6 with:
Custom types for structure, confluence, and risk state management
Functional programming approach for reusable calculations
State management through persistent variables
Optional visual elements that can be toggled independently
The code is open-source and can be modified to suit individual needs. All important logic is visible in the source code.
Disclaimer
This script is provided for educational and informational purposes only. It is not intended as financial, investment, trading, or any other type of advice or recommendation. Trading involves substantial risk of loss and is not suitable for all investors. Past performance, whether real or indicated by historical tests of strategies, is not indicative of future results.
No representation is being made that any account will or is likely to achieve profits or losses similar to those shown. In fact, there are frequently sharp differences between backtested results and actual results subsequently achieved by any particular trading strategy.
The user should be aware of the risks involved in trading and should trade only with risk capital. The authors and publishers of this script are not responsible for any losses or damages, including without limitation, any loss of profit, which may arise directly or indirectly from use of or reliance on this script.
This strategy uses technical analysis methods and indicators that are not guaranteed to be accurate or profitable. Market conditions change, and strategies that worked in the past may not work in the future. Users should thoroughly test any strategy in a paper trading environment before risking real capital.
Commission and slippage settings in backtests may not accurately reflect live trading conditions. Real trading results will vary based on execution quality, market liquidity, and other factors not captured in backtesting.
The user assumes full responsibility for all trading decisions made using this script. Always consult with a qualified financial advisor before making investment decisions.
Enjoy - officialjackofalltrades
EMA and Dow Theory Strategies V2📘 Overview
This strategy is an advanced evolution of the original EMA × Dow Theory hybrid model. V2 introduces true swing‑based trend detection, gradient trend‑zones, higher‑timeframe swing overlays, and dynamic exit logic designed for intraday to short‑term trading across crypto, forex, stocks, and indices.
The system provides precise entries, adaptive exits, and highly visual guidance that helps traders understand trend structure at a glance.
🧠 Key Features
🔹 1. Dual‑EMA Trend Logic (Symbol + External Index)
Both the chart symbol and an external index (OTHERS.D) are evaluated using fast/slow EMAs to determine correlation‑based trend bias.
🔹 2. Dow Theory Swing Detection (Real‑time)
The script identifies swing highs/lows and updates trend direction when price breaks them. This creates a structural trend model that reacts faster than EMAs alone.
🔹 3. Gradient Trend Zones (Visual Trend Strength)
When trend is up or down, the area between price and the latest swing level is filled with a multi‑step gradient. This makes trend strength and distance-to-structure visually intuitive.
🔹 4. Higher‑Timeframe Swing Trend (htfTrend)
Swing highs/lows from a higher timeframe (e.g., 4H) are plotted to show macro structure. Used only for visual context, not for filtering entries.
🔹 5. RSI‑Based Entry Protection
RSI prevents entries during extreme overbought/oversold conditions.
🔹 6. Dynamic Exit System
Includes:
Custom stop‑loss (%)
Partial take‑profit (TP1/TP2/TP3)
Automatic scale‑out when trend color weakens
“Color‑change lockout” to prevent immediate re‑entry
Real‑time PnL tracking and labels
🔹 7. Alerts for All Key Events
Entry, stop‑loss, partial exits, and trend‑change exits all generate structured JSON alerts.
🔹 8. Visual PnL Labels & Equity Tracking
PnL for the latest trade is displayed directly on the chart, including scale‑out adjustments.
⚙️ Input Parameters
Parameter Description
Fast EMA / Slow EMA EMAs used for symbol trend detection
Index Fast / Slow EMA EMAs applied to external index
StopLoss (%) Custom stop‑loss threshold
Scale‑Out % Portion to exit when trend color weakens
RSI Period / Levels Overbought/oversold filters
Swing Detection Length Bars used to detect swing highs/lows
Stats Display Position of statistics table
🧭 About htfTrend (Higher Timeframe Trend)
The higher‑timeframe swing trend is displayed visually but not used for entry logic.
Why? Strict HTF filtering reduces trade frequency and often removes profitable setups. By keeping it visual‑only, traders retain flexibility while still benefiting from macro structure awareness.
Use it as a contextual guide, not a constraint.
📘 概要
本ストラテジーは、V1 を大幅に拡張した EMA × ダウ理論 × スイング構造 × 上位足トレンド可視化 の複合型モデルです。 短期〜デイトレード向けに最適化されており、仮想通貨・FX・株式・指数など幅広いアセットで利用できます。
V2 では、スイング構造の自動検出、グラデーションによるトレンド強度の可視化、上位足スイングライン、動的な利確/損切りロジック が追加され、視覚的にもロジック的にも大幅に強化されています。
🧠 主な機能
🔹 1. 銘柄＋外部インデックスの EMA クロス判定
対象銘柄と OTHERS.D の EMA を比較し、相関を考慮したトレンド方向を判定します。
🔹 2. ダウ理論に基づくスイング高値・安値の自動検出
スイング更新によりトレンド方向を切り替える、構造ベースのトレンド判定を採用。
🔹 3. グラデーション背景によるトレンド強度の可視化
スイングラインから現在価格までを段階的に塗り分け、 「どれだけトレンドが伸びているか」を直感的に把握できます。
🔹 4. 上位足スイングトレンド（htfTrend）の表示
4H などの上位足でのスイング高値・安値を表示し、 大局的なトレンド構造を視覚的に把握できます（ロジックには未使用）。
🔹 5. RSI による過熱・売られすぎフィルター
極端な RSI 状態でのエントリーを防止。
🔹 6. 動的イグジットシステム
カスタム損切り（％）
TP1/TP2/TP3 の段階的利確
トレンド色の弱まりによる自動スケールアウト
色変化後の再エントリー制限（waitForColorChange）
リアルタイム PnL の追跡とラベル表示
🔹 7. アラート完備（JSON 形式）
エントリー、損切り、部分利確、トレンド反転などすべてに対応。
🔹 8. 損益ラベル・統計表示
直近トレードの損益をチャート上に表示し、視覚的に把握できます。
⚙️ 設定項目
設定項目名 説明
Fast / Slow EMA 銘柄の EMA 設定
Index Fast / Slow EMA 外部インデックスの EMA 設定
損切り（％） カスタム損切りライン
部分利確割合 トレンド弱化時のスケールアウト割合
RSI 期間・水準 過熱/売られすぎフィルター
スイング検出期間 スイング高値・安値の検出に使用
統計表示位置 テーブルの表示位置
🧭 上位足トレンド（htfTrend）について
上位足スイングの更新に基づくトレンド判定を表示しますが、 エントリー条件には使用していません。
理由： 上位足を厳密にロジックへ組み込むと、トレード機会が大幅に減るためです。
本ストラテジーでは、 「大局の把握は視覚で、エントリーは柔軟に」 という設計思想を採用しています。
→ 裁量で利確判断や逆張り回避に活用できます。
10>20,p>50 DEMARenders daily EMA, 10, 20 and 50 on any timeframe below 1D
30m timeframe works well.
Use trend of 10 > 20 + price > 50 for long and 10 < 20 + price < 50 for shorts or exits.
225 SMA CrossoverWell-known strategy from Zahlengraf from the Mauerstrassenwetten subreddit for you to test yourself.
You can change the length of the SMA and whether to trade long, short or both directions.
Buy the dips StrategyThis strategy getting in long position only after the price drop- Buy the dips
The % of the drop is Determined by SMA for the first trade
The inputs of SMA and % of the drop can be adjust from the User
After that Strategy start taking safe trades if not take profit from the first trade
The safe trades are Determined by step down deviation % and by quantity
There is no Stop loss is not for one with small tolerance to getting under
if any question ask
Estrategia Momentum Seguro (EMS) Entry and exit signals, this indicator helps or suggests where to enter, exit, or place a stop loss.
Hybrid Trend-Following Inside Bar BreakoutHybrid Trend-Following Inside Bar Breakout Strategy
The Hybrid Trend-Following Inside Bar Breakout Strategy is a rule-based trading system designed to capture strong directional moves while controlling risk during uncertain market conditions. It combines trend-following, price action, and volatility-based risk management into a single robust framework.
Core Concept
The strategy trades inside bar breakouts only in the direction of the dominant market trend. Inside bars represent periods of consolidation, and when price breaks out of this consolidation in a trending market, it often leads to impulsive moves with favorable risk–reward characteristics.
Key Components
1. Trend Filter
Uses 50 EMA and 200 EMA to define the market trend.
Bullish bias: 50 EMA above 200 EMA
Bearish bias: 50 EMA below 200 EMA
This filter prevents counter-trend trades and improves trade quality.
2. Volatility Filter
Compares fast ATR (14) with slow ATR (50).
Trades are taken only when volatility is expanding or above a minimum threshold.
This avoids low-volatility, choppy market conditions.
3. Inside Bar Breakout
An inside bar forms when the current candle’s high is lower than the previous candle’s high and the low is higher than the previous candle’s low.
A trade is triggered only when price breaks above or below the inside bar range in the direction of the trend.
4. Candle Quality Filter
Requires a minimum body-to-range ratio, ensuring that the breakout candle has strong momentum and is not driven by weak wicks.
Risk Management & Trade Management
Stop Loss (SL)
Placed using ATR-based dynamic stops, adapting to current market volatility.
Prevents tight stops in volatile conditions and wide stops in calm markets.
Partial Profit Taking
50% of the position is exited at 1.5R, locking in profits early.
This reduces psychological pressure and improves equity stability.
Trailing Stop
After partial profit is taken, the remaining position is managed with an ATR-based trailing stop.
Allows the strategy to capture large trend moves while protecting gains.
Cooldown Mechanism
After a losing trade, the system enters a cooldown period and skips a fixed number of bars.
This helps avoid revenge trading and overtrading during unfavorable market phases.
Why This Strategy Works
Trades only high-probability breakouts in trending markets
Adapts automatically to changing volatility
Combines price action precision with systematic risk control
Designed for consistent performance over long historical periods
