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.
Trend Analizi
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。
%-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.
Seasonal Strategies V1Seasonal Strategies V1 is a rule-based futures seasonality framework built around predefined calendar windows per asset.
The strategy automatically detects the current symbol and activates long or short trading phases strictly based on historically observed seasonal tendencies. All entries and exits are fully time-based — no indicators, no predictions, no discretionary input.
Key Features
Asset-specific seasonal windows (MMDD-based)
Automatic long and short activation
Fully time-based entries and exits
One position at a time (no pyramiding)
Clean chart visualization using subtle background shading
No indicators, no filters, no curve fitting
Philosophy:
This strategy is designed as a structural trading tool, not a forecasting model.
It focuses on when a market historically shows seasonal tendencies — not why or how far price might move.
Seasonal Strategies V1 intentionally keeps the chart clean and minimal, making it suitable as a baseline framework for research, portfolio-style seasonal approaches, or further extensions in later versions.
Intended Use:
Futures and commodity markets
Seasonality research and testing
Systematic, calendar-driven strategies
Educational and analytical purposes
Disclaimer
This script is provided for educational and research purposes only.
Past seasonal tendencies do not guarantee future performance.
Risk management, position sizing, and portfolio decisions are the responsibility of the user.
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.
Efy60mEfy60m Strategy Analysis Report (Product Analysis)
Efy60m 策略分析報告
Strategy Name: Efy60m
策略名稱：Efy60m
Instrument: Taiwan Index Futures (TXF) / Continuous Contract | Timeframe: 60-minute Chart
適用商品：台指期 (TXF) / 連續月 | 適用週期：60 分鐘 K 線
1. Core Philosophy
核心邏輯
Efy60m is a trend-following strategy based on "Asymmetric Volatility Breakout". It does not predict the market but waits for the trend to initiate.
Efy60m 是一套基於 「非對稱波動率突破」 的趨勢策略。它不預測行情，而是等待行情發動。
Asymmetry: Recognizes the "slow rise, sharp drop" characteristic of TXF. It uses different parameters for Long and Short positions to avoid slow reactions in bear markets or getting whipsawed during bull market corrections.
非對稱性：承認台指期「緩漲急跌」的特性，多空使用不同的參數，避免在空頭市場反應過慢，或在多頭回檔時被洗出場。
Anti-Chop Mechanism: Built-in ADX momentum filter. It automatically stays idle during low momentum periods (sideways markets) and only executes trades when significant profit potential exists.
抗盤整機制：內建 ADX 動能濾網，在市場動能不足（死魚盤）時自動休眠，只在有大肉吃的時候才出手。
Triple Risk Management: Features "Channel Reversal Exit," "Fixed Stop Loss," and "Trailing Take Profit" to effectively secure and lock in profits.
三重風控：具備「通道反向出場」、「固定停損」與「移動停利」，確保獲利落袋為安。
2. Competitiveness
市場競爭力
Profit Factor > 2.1: This represents a Tier 1 (Top-tier) level among commercial strategies. While most strategies pass with a PF of 1.5~1.6, Efy60m demonstrates exceptional efficiency.
獲利因子 > 2.1：這在市售策略中屬於 Tier 1 (頂級) 水準。大部分市售策略 PF 能到 1.5~1.6 就算及格，Efy60m 的獲利效率極高。
High Average Trade (> $16,000 TWD): This is its strongest competitive moat. Even with increased slippage or higher commissions in the future, the strategy remains profitable because it captures major trends rather than marginal gains.
高平均獲利 (Avg Trade > $16,000)：這是最強的護城河。即便未來滑價變大、手續費變貴，這套策略依然能獲利，因為它抓的是大波段，而非蠅頭小利。
Avoid Settlement Risk: Executes early settlement on Tuesdays to avoid the volatility and turbulence of Wednesday's settlement day.
避開結算風險：週二提前結算，避開了週三的結算亂流。
3. Rating
評級
Profitability: ⭐⭐⭐⭐⭐
獲利能力：⭐⭐⭐⭐⭐
Stability: ⭐⭐⭐⭐
穩定性：⭐⭐⭐⭐
Risk Profile: Medium-High Risk (Swing trading strategy; sufficient margin is required).
風險屬性：中高風險 (屬於波段策略，需準備足夠保證金)
Disclaimer: "Past performance is not indicative of future results. This swing trading strategy has a maximum drawdown of approximately 400,000 TWD. It is recommended to have a capital reserve of 800,000 to 1,000,000 TWD per Large TXF contract."
警語：「過去績效不代表未來獲利，波段策略最大回撤約 40 萬，建議操作大台本金需備足 80-100 萬/口」。
Redheal V19 (BTC - VER 1.0 Final)"Redheal V19: Professional Trading Algorithm with Transparent Performance Data"
Redheal V19 is built on rigorous backtesting that accounts for the harshest real-world trading conditions. We provide transparent data based on different slippage scenarios to ensure reliability.
Performance by Slippage Condition (Late 2019 – Present):
At 30 Ticks Slippage: Over 6,000% Total Profit
At 100 Ticks Slippage: Over 3,000% Total Profit (Proven stability even under extreme execution errors)
Technical Integrity: Zero Repainting and No Look-ahead bias. High-fidelity signals that match live trading 100%.
Rigorous Backtesting Parameters:
Commission: 0.05% (Round-turn) included
Pyramiding: 1 (Strict position management)
Risk Control: 22% MDD maintained through various market cycles over 6 years
How to Request Access: Send a DM on TradingView or contact via email (cth7623@gmail.com) / Telegram (@master4967) with your .
"Redheal V19: 압도적인 데이터와 투명한 성과로 증명된 트레이딩 알고리즘"
본 전략은 실전 매매의 가혹한 환경을 단계별로 검증하여 설계되었습니다. 단순히 높은 수익률을 보여주는 것에 그치지 않고, 체결 오차(Slippage)에 따른 성과를 투명하게 공개합니다.
슬리피지 조건별 수익률 (2019 하반기 ~ 현재):
슬리피지 30 Ticks 적용 시: 총 수익률 6,000% 이상
슬리피지 100 Ticks 적용 시: 총 수익률 3,000% 이상 (극도의 체결 오차 상황에서도 안정적 수익 입증)
기술적 정직함: 리페인팅(Repainting) 및 룩어헤드(Look-ahead) 편향이 전혀 없으며, 실시간 신호와 백테스트가 100% 일치합니다.
엄격한 실전 파라미터: * 수수료: 왕복 0.05% 포함
피라미딩: 1 (단일 포지션 관리)
리스크 관리: 6년 이상의 전 장세 경험 및 MDD 22% 수준 유지
권한 요청 방법: 트레이딩뷰 메시지(DM) 또는 이메일(cth7623@gmail.com) / 텔레그램(@master4967)으로 을 보내주십시오.
Gold DipperDescription: The Gold Dipper is not just a simple EMA crossover; it is a comprehensive trend-following system designed to filter out market noise and capture entries during price retracements.
How the logic works together:
Trend Confirmation: The script utilizes a dual-layered filtering process. It compares the interaction between a fast-response EMA (20) and a baseline EMA (50) to establish the primary trend direction.
Volume/Momentum Filter (The "Dip" Detection): The script identifies a "Dip" by monitoring price action proximity to the baseline. A signal is only triggered when price 'kisses' the EMA 20 zone while the 50 EMA slope remains positive, ensuring we are not catching a falling knife but buying a controlled pullback.
Dynamic Risk Control: Unlike standard static SL/TP, this script calculates exit points based on recent Swing Lows/Highs within a specific look-back period, allowing the stop loss to adapt to current market volatility (ATR-like behavior).
Why this Mashup is Useful: This script solves the "Late Entry" problem common in crossover strategies. By merging trend detection with a precise pullback trigger and dynamic risk levels, it provides a complete trading plan in one tool, reducing the need for multiple cluttered indicators.
How to Use:
Best for XAUUSD on 15M.
Wait for the background/trend color to confirm an uptrend.
Execute when the "Buy" label appears at the touch of the EMA 20 line.
NQ/MNQ 5min BotThis invite-only strategy is built for traders who want a systematic approach to Nasdaq futures (NQ/MNQ). It combines VWAP (Volume Weighted Average Price), EMA (Exponential Moving Average), and ATR (Average True Range) filters to identify high-probability intraday setups.
🔑 Key Features
Trend Confirmation: Multi-timeframe EMA signals for directional bias.
VWAP Integration: Anchored VWAP zones act as dynamic support/resistance.
ATR-Based Risk Management: Stops and targets adapt to market volatility.
Intraday Focus: Designed for day traders and scalpers in NQ/MNQ futures.
Backtested Logic: Strategy has been optimized with robust historical testing.
✅ Who This Is For
Futures traders looking for consistency on Nasdaq contracts.
Traders who want clear entry and exit rules without second-guessing.
Those seeking scalable risk management that adapts to volatility.
EMA MACD Swing Set upUsed EMA and MACD, Targeted to help you simply identify the trending stocks. Can be used for Buy and Sell side trades
Bull Market Pro Trend Strategy proBull Market Pro Trend Strategy is a trend-following trading system specifically optimized for bullish market conditions. It is designed to help traders enter trends more efficiently, reduce unnecessary stop-outs, and systematically capture extended bullish moves.
The strategy features loose yet structured entry conditions, allowing participation in early or mid-stage trends without being overly restrictive. Risk management is handled through an ATR-based dynamic stop-loss, which adapts to market volatility and provides more realistic and flexible protection compared to fixed stop levels.
As the trend develops, the strategy supports scaled position building, enabling gradual position increases under controlled risk, aiming to maximize gains during sustained bullish trends.
This strategy is best suited for:
Clear bullish trend environments
Markets with moderate to high volatility
Traders seeking rule-based and systematic trend-following approaches
It can be used for live market analysis, strategy backtesting, and trend trading studies.
Disclaimer:
This strategy is for educational and research purposes only.
Past performance does not guarantee future results.
Always apply proper risk management when using any trading strategy.
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.
Adaptive Cycle & Trend StrategyThe Adaptive Cycle & Trend Strategy is a fully rules-based trading strategy designed to adapt dynamically to changing market conditions.
Instead of relying on a single static exit model, the strategy continuously evaluates market volatility and trend structure to determine the most appropriate exit behavior for the current regime. This allows it to respond differently in trending environments than in high-volatility or corrective phases.
The strategy is optimized for the 1W timeframe and focuses on capturing meaningful market cycles rather than short-term noise. Entries and exits are generated algorithmically and remain consistent across assets, making the system applicable to both low-volatility markets (such as Bitcoin) and higher-volatility instruments.
Key characteristics:
Adaptive exit logic based on volatility regimes
Cycle- and trend-aware trade management
Fully rule-based, no discretionary inputs
Designed for higher timeframes (1W, 1M) and long-term market structure
No indicators required for interpretation
This strategy is intended for systematic analysis and backtesting purposes only. It does not constitute financial or investment advice.
DAX-30 ATRX V2Updated DAX-30 ATRX strategy with visuals to manually trade the strategy.
FX:GER30
Optimized settings:
HTF timeframe for trend bias: 4 hours
HTF EMA length: 24
Min HA body size (pts): 0.5
- Use RSI filter
RSI length: 14
RSI threshold: 50
- Use Fisher filter
Fisher length: 18
- Use Volume filter
Volume lookback: 20
Volume spike multiplier: 1.2
ATR length: 13
ATR mean length: 80
SL = ATR x: 0.9
TP = Risk x: 2.1
- Use NY session filter
NY session start hour: 9
NY session end hour: 18
Max trades per day: 2
☑ Show SL/TP Boxes
☑ Show Entry Label
SL/TP Line Length (bars): 5
Swing Momentum TrendSwing Momentum Trend - Confirm Momentum Strategy Concept
English (English)
Core Concept: Confirm Momentum Trading
The Swing Momentum Trend strategy is not about catching falling knives or finding the exact bottom. Instead, it focuses on "Confirmation." It waits for both price action and momentum to align in an uptrend, ensuring a high-probability environment for trend-following entries.
Momentum Confirmation via Indicators
The strategy explains momentum by looking at the synergy between various technical tools:
1. Trend Zone Confirmation (EMA High/Low Switch) :
- Utilizes EMA calculated from Highs and Lows to define a "Trend Territory."
- Bullish momentum is confirmed when the price closes above the EMA High band, signalling that the market has transitioned into a strong trending phase.
2. Momentum Engine (RSI Smoothing MA) :
- RSI is treated as a momentum engine rather than a simple oscillator.
- Strength is confirmed when RSI remains above its own Smoothing Moving Average (MA), and that MA exhibits a positive upward slope, indicating accelerating buying pressure.
3. Structural Integrity (HH/HL Swings) :
- The strategy monitors market structure (Higher Highs and Higher Lows) on both Daily and Weekly timeframes.
- True momentum must be supported by a trend that builds higher floors and ceilings, distinguishing a sustainable trend from a temporary price spike.
4. Relative Strength Analysis (Trend Cycle Logic) :
- Current momentum is validated against the previous uptrend cycle's performance.
- By requiring the price to stay above the previous cycle's average close or low, the strategy ensures the current move has sufficient structural backing.
5. Visual Momentum Feedback (Bar Coloring) :
- Dynamic bar coloring provides instant clarity. Strong momentum is visually represented (e.g., Blue), while fading strength is flagged (e.g., Yellow), allowing for a quick assessment of momentum health at a glance.
Summary : This approach emphasizes "Patience for Confirmation" — entering only when all layers of momentum are in sync, thereby riding the strongest part of the trend.
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ภาษาไทย (Thai)
แนวคิดหลัก: การเทรดด้วยการยืนยันโมเมนตัม (Confirm Momentum)
กลยุทธ์ Swing Momentum Trend ไม่ใช่การพยายามหาจุดต่ำสุดเพื่อเข้าซื้อ (Bottom Fishing) แต่เป็นกลยุทธ์ที่เน้น "ความชัวร์" โดยการรอให้ราคาและแรงส่ง (Momentum) ยืนยันแนวโน้มขาขึ้นอย่างชัดเจนก่อนที่จะเข้าเกาะไปกับเทรน (Trend Following)
การยืนยันโมเมนตัมผ่านตัวชี้วัด (Indicator-Based Confirmation)
บทสรุปของแนวคิดนี้คือการใช้ความสอดคล้องของ Indicator หลายตัวในการอธิบายพลังของ Momentum:
1. การยืนยันโซนแนวโน้ม (EMA High/Low Switch) :
- ใช้เส้น EMA ของราคา High และ Low เพื่อสร้าง "เขตแดน" ของเทรน
- การยืนยัน Momentum ขาขึ้นจะเกิดขึ้นเมื่อราคาปิดสามารถยืนเหนือเส้น EMA High ได้อย่างมั่นคง ซึ่งถือเป็นด่านแรกของการคอนเฟิร์มว่าแนวโน้มหลักกำลังเปลี่ยนเป็นขาขึ้น
2. พลังของแรงส่ง (RSI Smoothing MA) :
- ไม่ได้มอง RSI เพียงแค่การ Overbought/Oversold แต่ใช้ RSI ร่วมกับเส้นค่าเฉลี่ย (Smoothing MA)
- โมเมนตัมจะถูกคอนเฟิร์มเมื่อ RSI อยู่เหนือเส้นค่าเฉลี่ยของตนเอง และเส้นค่าเฉลี่ยนั้นมีความชันเป็นบวก (Slope Up) แสดงถึงแรงซื้อที่กำลังเร่งเครื่อง (Acceleration)
3. โครงสร้างราคาเพื่อความยั่งยืน (HH/HL Structure) :
- มีการตรวจสอบโครงสร้างราคา (Market Structure) ทั้งในระดับวันและระดับสัปดาห์
- Momentum ที่แข็งแกร่งต้องมาพร้อมกับโครงสร้างที่ "ยกตัว" คือการทำจุดสูงสุดใหม่ที่สูงขึ้น (Higher High) และจุดต่ำสุดใหม่ที่สูงขึ้น (Higher Low) เพื่อยืนยันว่าไม่ใช่เพียงการรีบาวด์ระยะสั้น
4. การเปรียบเทียบกับรอบก่อนหน้า (Trend Cycle Analysis) :
- วิเคราะห์ความแข็งแกร่งโดยเทียบกับรอบขาขึ้นก่อนหน้า (Previous Up Trend Cycle)
- ราคาปัจจุบันควรยืนเหนือระดับราคาเฉลี่ยหรือฐานราคาต่ำสุดของรอบก่อน เพื่อยืนยันว่าแรงส่งในรอบนี้มีคุณภาพมากกว่ารอบที่ผ่านมา
5. การตอบสนองผ่านสีแท่งเทียน (Visual Bar Coloring) :
- ใช้สีช่วยในการตัดสินใจแบบ Real-time เช่น สีน้ำเงินเมื่อโมเมนตัมแข็งแกร่ง (RSI > Smoothing MA) และสีเหลืองเพื่อเตือนเมื่อแรงส่งเริ่มอ่อนกำลังลง (Momentum Weak)
--- PLAN ---
Contact us for a 7-day free trial.
Monthly Plan: $100 per month ($1,200 billed annually)
Annual Plan: $1,000 per year
Bull Market Pro Trend StrategyBull Market Pro Trend Strategy is a trend-following trading system specifically optimized for bullish market conditions. It is designed to help traders enter trends more efficiently, reduce unnecessary stop-outs, and systematically capture extended bullish moves.
The strategy features loose yet structured entry conditions, allowing participation in early or mid-stage trends without being overly restrictive. Risk management is handled through an ATR-based dynamic stop-loss, which adapts to market volatility and provides more realistic and flexible protection compared to fixed stop levels.
As the trend develops, the strategy supports scaled position building, enabling gradual position increases under controlled risk, aiming to maximize gains during sustained bullish trends.
This strategy is best suited for:
Clear bullish trend environments
Markets with moderate to high volatility
Traders seeking rule-based and systematic trend-following approaches
It can be used for live market analysis, strategy backtesting, and trend trading studies.
Disclaimer:
This strategy is for educational and research purposes only.
Past performance does not guarantee future results.
Always apply proper risk management when using any trading strategy.
Liquidity Retest Strategy (Apicode) - TP/SL Lines FixedTechnical Documentation:
1. Purpose and underlying concept
This strategy targets a common behavior in liquid markets: liquidity sweeps around meaningful support/resistance levels, followed by a retest and rejection (reversal) with confirmation.
The core thesis is that many initial “breaks” are not continuation moves, but rather stop-runs and order harvesting. After the sweep, price reclaims the level and closes back on the opposite side, offering a structured entry with defined risk.
The strategy includes:
Support/Resistance detection via pivots
Dynamic selection of the “working” level using an ATR-based proximity window
Rejection validation via candle structure (wick + close)
Optional filters: volume, VWAP-like bias, and EMA trend
Risk management with static TP/SL (ATR-based or %), plus trailing stop (ATR-based or %), with per-trade lines plotted
2. Main components
2.1. Volatility metric: ATR
atr = ta.atr(atrLength) is used in two essential places:
Level selection (proximity to S/R): prevents trading levels that are too far from current price.
Sweep validation (minimum wick size): requires the wick to extend beyond the level by a volatility-relative amount.
Optionally, ATR can also be used for:
Static TP/SL (when usePercent = false)
Trailing stop (when useTrailPercent = false)
2.2. Building S/R levels with pivots
Pivots are detected using:
pivotHigh = ta.pivothigh(pivotLookback, rightBars)
pivotLow = ta.pivotlow(pivotLookback, rightBars)
Each confirmed pivot is stored in arrays:
resistanceLevels for resistance
supportLevels for support
The array size is capped by maxLevels, which reduces noise and manages chart resource usage (lines).
2.3. Selecting the “best” level each bar
On each bar, a single support S and/or resistance R candidate is chosen:
Support: nearest level below price (L < price)
Resistance: nearest level above price (L > price)
Only levels within atr * maxDistATR are considered
This produces dynamic “working levels” that adapt to price location and volatility.
2.4. Rejection pattern (retest + sweep)
After selecting the working level:
Support rejection (long setup)
Conditions:
Low touches/crosses support: low <= S
Close reclaims above: close > S
Bullish candle: close > open
Sufficient wick below the level (liquidity sweep): (S - low) >= atr * minWickATR
This aims to capture a stop sweep below support followed by immediate recovery.
Resistance rejection (short setup)
Symmetric conditions:
High touches/crosses resistance: high >= R
Close rejects back below: close < R
Bearish candle: close < open
Sufficient wick above the level: (high - R) >= atr * minWickATR
2.5. Optional filters
Final signals are the rejection pattern AND enabled filters:
1.- Volume filter
High volume is defined as: volume > SMA(volume, 20) * volMult
When useVolFilter = true, setups require relatively elevated participation
2.- VWAP-like bias filter
A VWAP-like series is computed over vwapLength (typical price weighted by volume)
When useVWAPFilter = true:
- Longs only if close > vwap
- Shorts only if close < vwap
3.- EMA trend filter
Uptrend if EMA(fast) > EMA(slow)
When useTrendFilter = true:
- Longs only in uptrend
- Shorts only in downtrend
2.6. Backtest time window (time filter)
To keep testing focused and reduce long-history noise:
useMaxLookbackDays enables the filter
maxLookbackDays defines how many days back from timenow entries are allowed
Entries are permitted only when time >= startTime.
3. Entry rules and position control
3.1. Entries
strategy.entry('Long', strategy.long) when longSetup and no long position is open
strategy.entry('Short', strategy.short) when shortSetup and no short position is open
No pyramiding is allowed (pyramiding = 0). Position gating is handled by:
Long allowed if strategy.position_size <= 0
Short allowed if strategy.position_size >= 0
4. Risk management: TP/SL and trailing (with plotted lines)
4.1. Detecting entry/exit events
Events are identified via changes in strategy.position_size:
LongEntry: transition into a long
shortEntry: transition into a short
flatExit: transition back to flat
This drives per-trade line creation, updates, and cleanup of state variables.
4.2. Static TP/SL
On entry, entryPrice := strategy.position_avg_price is stored.
Percent mode (usePercent = true)
Long:
staticSL = entryPrice*(1 - slPerc/100)
staticTP = entryPrice*(1 + tpPerc/100)
Short:
staticSL = entryPrice*(1 + slPerc/100)
staticTP = entryPrice*(1 - tpPerc/100)
ATR mode (usePercent = false)
Long:
staticSL = entryPrice - atrAtEntry*slATR
staticTP = entryPrice + atrAtEntry*tpATR
Short:
staticSL = entryPrice + atrAtEntry*slATR
staticTP = entryPrice - atrAtEntry*tpATR
4.3. Trailing stop (custom)
While a position is open, the script tracks the most favorable excursion:
Long: hhSinceEntry = highest high since entry
Short: llSinceEntry = lowest low since entry
A trailing candidate is computed:
Percent trailing (useTrailPercent = true)
Long: trailCandidate = hhSinceEntry*(1 - trailPerc/100)
Short: trailCandidate = llSinceEntry*(1 + trailPerc/100)
ATR trailing (useTrailPercent = false)
Long: trailCandidate = hhSinceEntry - atr*trailATR
Short: trailCandidate = llSinceEntry + atr*trailATR
Then the effective stop is selected:
Long: slUsed = max(staticSL, trailCandidate) when useTrail is enabled
Short: slUsed = min(staticSL, trailCandidate) when useTrail is enabled
If useTrail is disabled, slUsed remains the static stop.
Take profit remains static:
tpUsed = staticTP
Exit orders are issued via:
strategy.exit(..., stop=slUsed, limit=tpUsed)
4.4. Per-trade TP/SL lines
On each entry, two lines are created (SL and TP) via f_createLines().
During the trade, the SL line updates when trailing moves the stop; TP remains fixed.
On exit (flatExit), both lines are finalized on the exit bar and left on the chart as historical references.
This makes it straightforward to visually audit each trade: entry context, intended TP, and trailing evolution until exit.
5. Visualization and debugging
BUY/SELL labels with configurable size (xsize)
Debug mode (showDebug) plots the chosen working support/resistance level each bar
Stored pivot levels are drawn using reusable line slots, projected a fixed 20 bars to the right to keep the chart readable and efficient
6. Parameter guidance and practical notes
pivotLookback / rightBars: controls pivot significance vs responsiveness. Lower rightBars confirms pivots earlier but can increase noise.
maxDistATR: too low may reject valid levels; too high may select distant, less relevant levels.
minWickATR: key quality gate for “real” sweeps. Higher values reduce frequency but often improve signal quality.
Filters:
Volume filter tends to help in ranges and active sessions.
VWAP bias is useful intraday to align trades with session positioning.
EMA trend filter is helpful in directional markets but may remove good mean-reversion setups.
Percent TP/SL: provides consistent behavior across assets with variable volatility, but is less adaptive to sudden regime shifts.
Percent trailing: can capture extensions well; calibrate trailPerc per asset/timeframe (too tight = premature exits).
7. Known limitations
Pivot-derived levels are a heuristic; in strong trends, valid retests may be limited.
The time filter uses timenow; behavior may vary depending on historical context and how the platform evaluates “current time.”
TP/SL and trailing are computed from bar OHLC; in live trading, intrabar sequencing and fills may differ from bar-close simulation.
ERAK Quantitative Gaussian Edge [Pro Math Model]Overview
The ERAK Quantitative Gaussian Edge is not a traditional trading indicator; it is a probabilistic mathematical model designed to identify statistical anomalies in asset prices. Unlike classical indicators (RSI, MACD) that rely on lagging price derivatives, this algorithm utilizes Linear Regression Analysis and Gaussian Distribution (Normal Distribution) theory to determine the probability of a Mean Reversion event.
Core Philosophy
Markets are stochastic, but they exhibit "Fat Tail" behavior. This strategy operates on the principle that while prices wander, they are mathematically tethered to a "Center of Gravity" (Mean). When the price deviates significantly (Z-Score > 2.5 Sigma) from this mean without fundamental justification, it presents a high-probability arbitrage opportunity to trade back toward equilibrium.
Key Features & Mathematical Logic:
1. Dynamic Linear Regression Channel: Instead of simple Moving Averages (which lag significantly), we use a Linear Regression Curve to establish the "Fair Value" of the asset in real-time.
2. Statistical Z-Score Trigger: Entries are not based on arbitrary levels but on Standard Deviation (Sigma).
• Entry: Occurs when price hits ±2.5 Sigma (Statistically, this represents the outer ~1% of price occurrences).
• Exit: Occurs when price reverts to the mean (Expected Value).
3. R-Squared (R^2) Trend Filter: To avoid "catching a falling knife," the algorithm calculates the Coefficient of Determination (R^2).
• If R^2 > 0.80, it implies a strong deterministic trend. The system blocks counter-trend trades to prevent fighting strong momentum.
4. Volatility Regime Detection: Uses ATR analysis to detect "Fat Tail" events (Black Swans). If volatility expands beyond 2.5x the norm, the system pauses to protect capital from chaotic market conditions.
5. Advanced Money Management (Kelly Criterion): Includes a live dashboard that calculates the Half-Kelly Criterion, offering a mathematically optimal position size suggestion based on the strategy's real-time Win Rate and Payoff Ratio.
How to Use the Dashboard:
• Live Z-Score: Shows how many deviations the current price is from the mean. (Red values indicate extreme anomalies).
• Trend Strength (R^2): If this is Red (>0.80), do NOT open counter-trend positions manually.
• Kelly Rec %: Suggests the optimal % of equity to risk for the next trade to maximize geometric growth while minimizing the risk of ruin.
Disclaimer: This is a quantitative tool for statistical analysis. Past performance in backtests does not guarantee future results. Always manage your risk.
Kohen Dive V3.7 Strategy (Backtest)⚠️ DISCLAIMER & RISK WARNING
This Strategy Script is for EDUCATIONAL and BACKTESTING purposes only. Past performance does not guarantee future results. This script is designed to test the mathematical probability of the "Kohen Dive" logic.
📊 KOHEN DIVE V3.7 STRATEGY (Backtest Edition)
Concept: Automated Mean Reversion System
This is the Strategy (Backtest) version of the "Kohen Dive V4.6" indicator. While the indicator visualizes the market tension, this script executes automated trades based on specific rules to test the profitability of the "Spring Tension" logic.
The Core Philosophy: It uses a Contrarian approach. It looks for "Overextended" market conditions (Neon Candles) to enter trades against the crowd, targeting a snap-back move.
⚙️ TRADE RULES (Entry Logic)
The strategy waits for a confluence of 3 Conditions:
1. 📉 SHORT ENTRY (Sell High)
⚙︎ Zone: Price must be in the Premium (Red) zone (Above 100-period average).
⚙︎ Tension: Momentum must hit NEON GREEN (Max Upside Tension) and sustain it for at least 5 bars.
⚙︎ Trigger: Enters Short when momentum starts to cool down.
2. 📈 LONG ENTRY (Buy Low)
⚙︎ Zone: Price must be in the Discount (Green) zone (Below 100-period average).
⚙︎ Tension: Momentum must hit NEON RED (Max Downside Tension) and sustain it for at least 5 bars.
⚙︎ Trigger: Enters Long when momentum starts to recover.
🛡️ RISK MANAGEMENT (Set & Forget)
This strategy is strictly rule-based with fixed Stop Loss and Take Profit levels to remove emotional trading.
⚙︎ Take Profit (TP): 6.0%
⚙︎ Stop Loss (SL): 2.5%
⚙︎ Risk/Reward Ratio: 1:2.4
⚙︎ Optimization: Default settings are optimized for ETH/USDT 15-Minute timeframe.
🔧 KEY SETTINGS
⚙︎ Gamma Value (0.8): Filters out weak signals. Higher values = Fewer but higher quality trades.
⚙︎ PD Lookback (100): Defines the "Cheap/Expensive" range based on the last ~24 hours (on 15m chart).
⚙︎ Min Peak Bars (5): Prevents entering on sudden wicks/fake-outs. Requires sustained tension.
MGC 5 POINT WIN NY SESSION🚀 EMA Crossover Strategy (MGC) — Precision Trend Trading With Smart Risk Control
Unlock a cleaner, more consistent way to trade Micro Gold Futures (MGC) with this trend‑powered EMA crossover system. Designed for traders who want high‑probability entries, tight risk management, and automated profit protection, this strategy blends simplicity with powerful trade logic.
If you’re tired of chop, fakeouts, and inconsistent setups — this is built for you.
🔥 Why This Strategy Works
Gold loves structure. This system takes advantage of that by combining:
✅ Trend‑Aligned Entries
Trades only trigger when the fast EMA crosses the mid or slow EMA in the direction of the dominant trend. No counter‑trend guessing. No fighting momentum.
✅ 5‑Point Take Profit (Optimized for MGC)
A realistic, repeatable target that fits MGC’s intraday volatility. With 3 micro contracts, that’s roughly $150 per trade.
✅ Break‑Even Protection (+2 Points)
Once the trade moves +2 points in your favor, the stop snaps to break‑even. Your downside risk instantly drops to zero.
✅ Trailing Stop Engine (+3 Points)
At +3 points, a dynamic trailing stop activates — letting winners run while locking in gains. Perfect for catching those extended gold pushes.
⚙️ What’s Under the Hood
This strategy uses:
9 EMA → short‑term momentum
20 EMA → medium‑term structure
55 EMA → trend filter
Crossover logic → precise entries
Dollar‑based initial stop → consistent risk
Break‑even + trailing stop → automated profit protection
Everything is built to keep you on the right side of the market while minimizing unnecessary losses.
📈 Who This Strategy Is For
This system is ideal for traders who want:
Clean, rules‑based entries
Trend‑only setups
Fast break‑even protection
A realistic, repeatable profit target
A strategy that works across Asia, London, and NY sessions
A simple but powerful framework that doesn’t require indicators all over the chart
If you scalp or intraday trade MGC, this fits your workflow perfectly.
🧪 Backtest Behavior
In testing, this strategy consistently shows:
Fewer false signals due to trend filtering
Stronger win rate thanks to the 5‑point TP
Reduced drawdowns from early break‑even logic
Better performance in choppy conditions
Smooth equity curves during trending sessions
It’s built for stability — not lottery‑ticket trades.
🎯 Recommended Settings
Timeframe: 5‑minute
Symbol: MGC1!
Fast EMA: 9
Mid EMA: 20
Slow EMA: 55
Take Profit: 5 points
Break‑Even Trigger: +2 points
Trailing Trigger: +3 points
Trailing Distance: 1 point
Risk per Trade: $100
💡 Final Notes
This strategy is designed to give you structure, consistency, and confidence in the gold market. It removes emotion, avoids chop, and automates the parts of trading that humans tend to mess up.
If you want a clean, disciplined approach to MGC — this is it.
MGC 5POINT WIN(Asia + London Optimized, BE + Trail + ATR Filter)📌 Strategy Description (Asia + London + NY Optimized Version)
This strategy is designed specifically for MGC (Micro Gold Futures) and optimized to perform consistently across Asia, London, and New York sessions. Gold behaves differently in each global session, so this system uses volatility‑adaptive logic, trend confirmation, and dynamic stop management to maintain stable performance 24 hours a day.
The goal is simple: Capture clean, trend‑aligned moves while avoiding low‑quality chop and protecting profits early.
🔶 Core Logic
The strategy uses a 9/20/55 EMA structure to identify trend direction and momentum shifts. Entries occur only when the fast EMA crosses the mid or slow EMA in the direction of the prevailing trend, filtering out counter‑trend signals.
🔶 Trend Filter
To improve accuracy and reduce noise:
Longs only when price is above the 55 EMA
Shorts only when price is below the 55 EMA
This keeps the system aligned with broader directional bias.
🔶 Volatility Filter (ATR‑Based)
Asia session often has low volatility and choppy price action. To avoid low‑quality setups, the strategy requires ATR to be above a minimum threshold before allowing entries.
This dramatically improves performance during Asia and stabilizes results across all sessions.
🔶 EMA Slope Filter
Sideways markets are filtered out by requiring the slow EMA to have a minimum slope. This ensures trades only occur when the market is actually moving.
🔶 Profit Target
The strategy uses a 5‑point take‑profit, which is ideal for MGC’s intraday volatility. With 3 micro contracts, this equals approximately $150 per trade.
This TP level provides:
High win rate
Frequent opportunities
Realistic movement across all sessions
🔶 Dynamic Stop Management
Break‑Even Stop (+2 Points)
Once price moves +2 points in profit, the stop is moved to the entry price. This eliminates downside risk and protects against reversals.
Trailing Stop (+3 Points)
After price reaches +3 points in profit, a trailing stop activates. This allows the strategy to lock in gains while still giving room for the move to reach the 5‑point target.
📊 Backtest Notes
During backtesting, the following behaviors were observed:
ATR filter removes 40–60% of losing trades during Asia session
EMA slope filter significantly reduces chop entries
London session performance improves due to cleaner trend confirmation
New York session performance remains strong and unaffected
Drawdowns are reduced across all sessions
Win rate increases due to trend‑aligned entries and early risk removal
Trailing stop captures extended moves without sacrificing consistency
🔧 Recommended Settings
Fast EMA: 9
Mid EMA: 20
Slow EMA: 55
Take Profit: 5 points
Break‑Even Trigger: +2 points
Trailing Stop Trigger: +3 points
Trailing Distance: 1 point
ATR Length: 14
Minimum ATR: 0.25–0.35
EMA Slope Minimum: 0.02–0.05
Timeframe: 5‑minute chart
Symbol: MGC1! or continuous MGC contract
🎯 Best Use Case
This strategy is ideal for traders who operate during:
Asia session (low volatility)
London session (medium volatility)
New York session (high volatility)
The system adapts automatically to volatility conditions, making it suitable for 24‑hour trading.
Supertrend + VWAP Strategy [Smart Safety Exit] by StoxxoAutomated Nifty/BankNifty strategy combining Supertrend for trend direction and VWAP for validation. Features a unique "Safety Exit" mechanism that closes trades immediately if price fails to hold the VWAP level. Ready for Stoxxo Bridge automation.
