MTF EMA Hariss 369The strategy has been prepared in a simplistic manner and easy to understand the concept by any novice trader.
Indicators used:
Current Time frame 20 EMA- Gives clear look about current time frame dynamic support and resistance and trend as well.
Higher Time Frame 20 EMA: Gives macro level trend, support and resistance
Kama: Capture volatility and trend direction.
RVOL: Main factor of price movement.
Buy when price closes above current time frame 20 ema and current time frame 20 ema is above higher time frame 20 ema. Stop loss just below the low of last candle. One can use current time frame 20 ema, higher time frame 20 ema or kama as stop loss depending upon type of asset class and risk appetite. The ideal way is to keep 20 ema as trailing sl if one wants to trail with trend.
Sell when price closes below current time frame 20 ema and current time frame 20 ema is lower than higher time frame 20 ema. Stop loss just above high of last candle.
Ideal target is 1.5 or 2 times of stop loss.
Entry and exit time depends on trading style. Eg. if you want to enter and exit in 5 min time frame, then choose 15 min or 1h as higher time frame as trend filter. Buy and sell signals are also plotted based on this strategy. One should always go with the higher time frame trend. Opting higher time frame trend filter always filters out market noises.
"stop loss"に関するスクリプトを検索
Anchor SafeSwing Gold StrategyOverview:
The Anchor SafeSwing Gold Strategy is designed for users who prefer structured, rule-based swing trading on XAUUSD. It focuses on identifying high-quality trade setups rather than frequent entries.
This strategy analyzes the market using multiple technical indicators and methods—including trend analysis, multi-chart confirmation, and support/resistance evaluation—to identify potential swing points. It also incorporates a dynamic approach to risk management through adaptive stop-loss and take-profit logic.
How the Strategy Works
1. Multi-Chart & Trend Analysis:
The strategy evaluates trend direction using several indicators and multiple charts. This helps determine whether the trend favors long or short setups.
2. Buy/Sell Conditions:
a. Buy Conditions: When the broader trend is identified as bullish, the strategy waits for the formation of a strong support zone before considering a long position.
b. Sell Conditions: When the trend is bearish, it waits for a confirmed resistance zone before initiating short positions.
3. Dynamic Take-Profit Logic
The strategy uses adaptive take-profit behavior based on evolving market conditions. It monitors new support/resistance structures and various overbought/oversold signals to dynamically exit trades.
4. Dynamic and Configurable Stop-Loss:
A flexible stop-loss system adjusts according to volatility and market structure.
Users can modify the stop-loss threshold in the settings based on their own risk tolerance and account size.
Trading Frequency :
This strategy focuses on select, high-quality setups. As a result, trade frequency is relatively low and may vary depending on market conditions. Backtesting may show roughly several trades per month, but actual live performance can differ.
Important Notes
All trading involves risk, and users should evaluate the strategy and adjust settings according to their own risk management preferences.
CBS Strategy with Trailing Stop _ IK3-Candle High/Low Breakout Strategy – Clean, Powerful, Fully Customizable (Pine Script v6)
A simple yet effective momentum breakout strategy that triggers trades when price closes above the highest high or below the lowest low of the previous 3 completed candles.
Perfect for trending markets (stocks, forex, crypto, indices) on any timeframe.
Key Features:
• Pure price-action breakout logic (no repainting)
• Long & Short entries with visual triangle signals
• Built-in Stop Loss & Take Profit (fixed % or ATR-based)
• Optional Trailing Stop (percentage or ATR multiplier)
• All risk parameters fully adjustable from the settings panel
• Clean on-chart visualization of SL, TP, and active trailing stop levels
• Works on all instruments and timeframes
Default Settings (2:1 Reward/Risk):
• Stop Loss: 1.5%
• Take Profit: 3.0%
• Trailing Stop: 1.0% (optional)
How to Use:
1. Add to chart
2. Adjust risk settings to match your style (fixed % or ATR)
3. Enable/disable trailing stop as needed
4. Backtest and optimize per instrument/timeframe
Fully open-source • No external libraries • Pine Script v6
Great for swing trading, intraday breakouts, or as a base for further enhancements.
Happy trading!
Range Oscillator Strategy + Stoch Confirm🔹 Short summary
This is a free, educational long-only strategy built on top of the public “Range Oscillator” by Zeiierman (used under CC BY-NC-SA 4.0), combined with a Stochastic timing filter, an EMA-based exit filter and an optional risk-management layer (SL/TP and R-multiple exits). It is NOT financial advice and it is NOT a magic money machine. It’s a structured framework to study how range-expansion + momentum + trend slope can be combined into one rule-based system, often with intentionally RARE trades.
────────────────────────
0. Legal / risk disclaimer
────────────────────────
• This script is FREE and public. I do not charge any fee for it.
• It is for EDUCATIONAL PURPOSES ONLY.
• It is NOT financial advice and does NOT guarantee profits.
• Backtest results can be very different from live results.
• Markets change over time; past performance is NOT indicative of future performance.
• You are fully responsible for your own trades and risk.
Please DO NOT use this script with money you cannot afford to lose. Always start in a demo / paper trading environment and make sure you understand what the logic does before you risk any capital.
────────────────────────
1. About default settings and risk (very important)
────────────────────────
The script is configured with the following defaults in the `strategy()` declaration:
• `initial_capital = 10000`
→ This is only an EXAMPLE account size.
• `default_qty_type = strategy.percent_of_equity`
• `default_qty_value = 100`
→ This means 100% of equity per trade in the default properties.
→ This is AGGRESSIVE and should be treated as a STRESS TEST of the logic, not as a realistic way to trade.
TradingView’s House Rules recommend risking only a small part of equity per trade (often 1–2%, max 5–10% in most cases). To align with these recommendations and to get more realistic backtest results, I STRONGLY RECOMMEND you to:
1. Open **Strategy Settings → Properties**.
2. Set:
• Order size: **Percent of equity**
• Order size (percent): e.g. **1–2%** per trade
3. Make sure **commission** and **slippage** match your own broker conditions.
• By default this script uses `commission_value = 0.1` (0.1%) and `slippage = 3`, which are reasonable example values for many crypto markets.
If you choose to run the strategy with 100% of equity per trade, please treat it ONLY as a stress-test of the logic. It is NOT a sustainable risk model for live trading.
────────────────────────
2. What this strategy tries to do (conceptual overview)
────────────────────────
This is a LONG-ONLY strategy designed to explore the combination of:
1. **Range Oscillator (Zeiierman-based)**
- Measures how far price has moved away from an adaptive mean.
- Uses an ATR-based range to normalize deviation.
- High positive oscillator values indicate strong price expansion away from the mean in a bullish direction.
2. **Stochastic as a timing filter**
- A classic Stochastic (%K and %D) is used.
- The logic requires %K to be below a user-defined level and then crossing above %D.
- This is intended to catch moments when momentum turns up again, rather than chasing every extreme.
3. **EMA Exit Filter (trend slope)**
- An EMA with configurable length (default 70) is calculated.
- The slope of the EMA is monitored: when the slope turns negative while in a long position, and the filter is enabled, it triggers an exit condition.
- This acts as a trend-protection exit: if the medium-term trend starts to weaken, the strategy exits even if the oscillator has not yet fully reverted.
4. **Optional risk-management layer**
- Percentage-based Stop Loss and Take Profit (SL/TP).
- Risk/Reward (R-multiple) exit based on the distance from entry to SL.
- Implemented as OCO orders that work *on top* of the logical exits.
The goal is not to create a “holy grail” system but to serve as a transparent, configurable framework for studying how these concepts behave together on different markets and timeframes.
────────────────────────
3. Components and how they work together
────────────────────────
(1) Range Oscillator (based on “Range Oscillator (Zeiierman)”)
• The script computes a weighted mean price and then measures how far price deviates from that mean.
• Deviation is normalized by an ATR-based range and expressed as an oscillator.
• When the oscillator is above the **entry threshold** (default 100), it signals a strong move away from the mean in the bullish direction.
• When it later drops below the **exit threshold** (default 30), it can trigger an exit (if enabled).
(2) Stochastic confirmation
• Classic Stochastic (%K and %D) is calculated.
• An entry requires:
- %K to be below a user-defined “Cross Level”, and
- then %K to cross above %D.
• This is a momentum confirmation: the strategy tries to enter when momentum turns up from a pullback rather than at any random point.
(3) EMA Exit Filter
• The EMA length is configurable via `emaLength` (default 70).
• The script monitors the EMA slope: it computes the relative change between the current EMA and the previous EMA.
• If the slope turns negative while the strategy holds a long position and the filter is enabled, it triggers an exit condition.
• This is meant to help protect profits or cut losses when the medium-term trend starts to roll over, even if the oscillator conditions are not (yet) signalling exit.
(4) Risk management (optional)
• Stop Loss (SL) and Take Profit (TP):
- Defined as percentages relative to average entry price.
- Both are disabled by default, but you can enable them in the Inputs.
• Risk/Reward Exit:
- Uses the distance from entry to SL to project a profit target at a configurable R-multiple.
- Also optional and disabled by default.
These exits are implemented as `strategy.exit()` OCO orders and can close trades independently of oscillator/EMA conditions if hit first.
────────────────────────
4. Entry & Exit logic (high level)
────────────────────────
A) Time filter
• You can choose a **Start Year** in the Inputs.
• Only candles between the selected start date and 31 Dec 2069 are used for backtesting (`timeCondition`).
• This prevents accidental use of tiny cherry-picked windows and makes tests more honest.
B) Entry condition (long-only)
A long entry is allowed when ALL the following are true:
1. `timeCondition` is true (inside the backtest window).
2. If `useOscEntry` is true:
- Range Oscillator value must be above `entryLevel`.
3. If `useStochEntry` is true:
- Stochastic condition (`stochCondition`) must be true:
- %K < `crossLevel`, then %K crosses above %D.
If these filters agree, the strategy calls `strategy.entry("Long", strategy.long)`.
C) Exit condition (logical exits)
A position can be closed when:
1. `timeCondition` is true AND a long position is open, AND
2. At least one of the following is true:
- If `useOscExit` is true: Oscillator is below `exitLevel`.
- If `useMagicExit` (EMA Exit Filter) is true: EMA slope is negative (`isDown = true`).
In that case, `strategy.close("Long")` is called.
D) Risk-management exits
While a position is open:
• If SL or TP is enabled:
- `strategy.exit("Long Risk", ...)` places an OCO stop/limit order based on the SL/TP percentages.
• If Risk/Reward exit is enabled:
- `strategy.exit("RR Exit", ...)` places an OCO order using a projected R-multiple (`rrMult`) of the SL distance.
These risk-based exits can trigger before the logical oscillator/EMA exits if price hits those levels.
────────────────────────
5. Recommended backtest configuration (to avoid misleading results)
────────────────────────
To align with TradingView House Rules and avoid misleading backtests:
1. **Initial capital**
- 10 000 (or any value you personally want to work with).
2. **Order size**
- Type: **Percent of equity**
- Size: **1–2%** per trade is a reasonable starting point.
- Avoid risking more than 5–10% per trade if you want results that could be sustainable in practice.
3. **Commission & slippage**
- Commission: around 0.1% if that matches your broker.
- Slippage: a few ticks (e.g. 3) to account for real fills.
4. **Timeframe & markets**
- Volatile symbols (e.g. crypto like BTCUSDT, or major indices).
- Timeframes: 1H / 4H / **1D (Daily)** are typical starting points.
- I strongly recommend trying the strategy on **different timeframes**, for example 1D, to see how the behaviour changes between intraday and higher timeframes.
5. **No “caution warning”**
- Make sure your chosen symbol + timeframe + settings do not trigger TradingView’s caution messages.
- If you see warnings (e.g. “too few trades”), adjust timeframe/symbol or the backtest period.
────────────────────────
5a. About low trade count and rare signals
────────────────────────
This strategy is intentionally designed to trade RARELY:
• It is **long-only**.
• It uses strict filters (Range Oscillator threshold + Stochastic confirmation + optional EMA Exit Filter).
• On higher timeframes (especially **1D / Daily**) this can result in a **low total number of trades**, sometimes WELL BELOW 100 trades over the whole backtest.
TradingView’s House Rules mention 100+ trades as a guideline for more robust statistics. In this specific case:
• The **low trade count is a conscious design choice**, not an attempt to cherry-pick a tiny, ultra-profitable window.
• The goal is to study a **small number of high-conviction long entries** on higher timeframes, not to generate frequent intraday signals.
• Because of the low trade count, results should NOT be interpreted as statistically strong or “proven” – they are only one sample of how this logic would have behaved on past data.
Please keep this in mind when you look at the equity curve and performance metrics. A beautiful curve with only a handful of trades is still just a small sample.
────────────────────────
6. How to use this strategy (step-by-step)
────────────────────────
1. Add the script to your chart.
2. Open the **Inputs** tab:
- Set the backtest start year.
- Decide whether to use Oscillator-based entry/exit, Stochastic confirmation, and EMA Exit Filter.
- Optionally enable SL, TP, and Risk/Reward exits.
3. Open the **Properties** tab:
- Set a realistic account size if you want.
- Set order size to a realistic % of equity (e.g. 1–2%).
- Confirm that commission and slippage are realistic for your broker.
4. Run the backtest:
- Look at Net Profit, Max Drawdown, number of trades, and equity curve.
- Remember that a low trade count means the statistics are not very strong.
5. Experiment:
- Tweak thresholds (`entryLevel`, `exitLevel`), Stochastic settings, EMA length, and risk params.
- See how the metrics and trade frequency change.
6. Forward-test:
- Before using any idea in live trading, forward-test on a demo account and observe behaviour in real time.
────────────────────────
7. Originality and usefulness (why this is more than a mashup)
────────────────────────
This script is not intended to be a random visual mashup of indicators. It is designed as a coherent, testable strategy with clear roles for each component:
• Range Oscillator:
- Handles mean vs. range-expansion states via an adaptive, ATR-normalized metric.
• Stochastic:
- Acts as a timing filter to avoid entering purely on extremes and instead waits for momentum to turn.
• EMA Exit Filter:
- Trend-slope-based safety net to exit when the medium-term direction changes against the position.
• Risk module:
- Provides practical, rule-based exits: SL, TP, and R-multiple exit, which are useful for structuring risk even if you modify the core logic.
It aims to give traders a ready-made **framework to study and modify**, not a black box or “signals” product.
────────────────────────
8. Limitations and good practices
────────────────────────
• No single strategy works on all markets or in all regimes.
• This script is long-only; it does not short the market.
• Performance can degrade when market structure changes.
• Overfitting (curve fitting) is a real risk if you endlessly tweak parameters to maximise historical profit.
Good practices:
- Test on multiple symbols and timeframes.
- Focus on stability and drawdown, not only on how high the profit line goes.
- View this as a learning tool and a basis for your own research.
────────────────────────
9. Licensing and credits
────────────────────────
• Core oscillator idea & base code:
- “Range Oscillator (Zeiierman)”
- © Zeiierman, licensed under CC BY-NC-SA 4.0.
• Strategy logic, Stochastic confirmation, EMA Exit Filter, and risk-management layer:
- Modifications by jokiniemi.
Please respect both the original license and TradingView House Rules if you fork or republish any part of this script.
────────────────────────
10. No payments / no vendor pitch
────────────────────────
• This script is completely FREE to use on TradingView.
• There is no paid subscription, no external payment link, and no private signals group attached to it.
• If you have questions, please use TradingView’s comment system or private messages instead of expecting financial advice.
Use this script as a tool to learn, experiment, and build your own understanding of markets.
────────────────────────
11. Example backtest settings used in screenshots
────────────────────────
To avoid any confusion about how the results shown in screenshots were produced, here is one concrete example configuration:
• Symbol: BTCUSDT (or similar major BTC pair)
• Timeframe: 1D (Daily)
• Backtest period: from 2018 to the most recent data
• Initial capital: 10 000
• Order size type: Percent of equity
• Order size: 2% per trade
• Commission: 0.1%
• Slippage: 3 ticks
• Risk settings: Stop Loss and Take Profit disabled by default, Risk/Reward exit disabled by default
• Filters: Range Oscillator entry/exit enabled, Stochastic confirmation enabled, EMA Exit Filter enabled
If you change any of these settings (symbol, timeframe, risk per trade, commission, slippage, filters, etc.), your results will look different. Please always adapt the configuration to your own risk tolerance, market, and trading style.
NEXT GEN INSPIRED BY OLIVER VELEZDYOR NFA
1. Initial Setup & Application
Load the Strategy to your desired chart (e.g., EURUSD M5, as suggested by the script's backtest).
Overlay: Ensure the script is set to overlay=true (which it is) so the signals and Moving Averages plot directly on the price chart.
Equity Management: Review the initial strategy settings for capital and position sizing:
Initial Capital: Defaults to 10,000.
Default Qty Type: Set to strategy.percent_of_equity (22%), meaning 22% of your available equity is used per trade. Adjust this percentage based on your personal risk tolerance.
2. Reviewing Key Indicator Inputs
The script uses default values that are optimized, but you can adjust them in the settings panel:
Fast EMA: Defaults to 9 (e.g., a 9-period Exponential Moving Average).
Slow EMA: Defaults to 21 (e.g., a 21-period Exponential Moving Average). These EMAs define the short-term trend.
ATR: Defaults to 14 (Average True Range). Used to dynamically calculate volatility for SL/TP distances.
Final R:R: Defaults to 4.5 (minimum R:R required for a signal). This is the core of the strategy's high reward goal.
3. Interpreting Entry Signals
A trade signal is generated only when all conditions—EMA trend, "Elephant Logic" momentum, and non-ranging market—are met.
Long Signal: Appears as a green triangle (▲) below the bar, labeled "COMBO".
Short Signal: Appears as a red triangle (▼) above the bar, labeled "COMBO".
Live Plan: Upon signal, a detailed label is immediately plotted on the chart showing the FULL BATTLE PLAN:
SL: Calculated Stop Loss price.
TP: Calculated Take Profit price (based on the Final R:R).
Risk/Reward Pips: The calculated pips for the trade's risk and reward.
R:R = 1:4.5: The exact Risk-to-Reward ratio.
4. Understanding Market Conditions & Visuals
The script provides visuals to help you understand the current market state:
Trend EMAs: The 9 EMA (green) and 21 EMA (purple/magenta) are plotted to show the underlying trend.
Long trades only fire when Price > 9 EMA > 21 EMA.
Short trades only fire when Price < 9 EMA < 21 EMA.
Ranging Market (Rejection): Bars turn a light gray/silver when the proprietary "Reject Ranging" logic is active, indicating a low-volatility period. No new trades will be taken during these bars.
Momentum Bar: Bars turn a gold/yellow color when the "Elephant Logic" (high-momentum, large-body candles over 2-3 periods) is detected, highlighting powerful price movement.
5. Execution and Exit Logic
The strategy handles entry, scaling, and exit automatically:
Entry: A market order is placed (strategy.entry) immediately upon the bar where the longSetup or shortSetup condition is met.
Scaling Out (+1R): If the trade moves favorably by an amount equal to the initial risk (1R), the script closes a portion of the position (strategy.close with comment "+1R"). This partial exit locks in profit equivalent to the initial risk.
Re-entry (Pyramiding): After the +1R exit, the strategy attempts a re-entry (LONG RE/SHORT RE diamond plot) if the price meets certain criteria near the 9 EMA, trying to capitalize on further trend continuation.
Final Exits:
Take Profit: A limit order is set at the calculated TP level (stopDist * minRR).
Stop Loss: A stop order is set at the calculated SL level (stopDist * 1.3), slightly wider than the initial SL distance, likely to account for spread/slippage, ensuring the maximum loss is defined.
Trailing Stop: A trailing stop is applied to the re-entry positions (LONG RE/SHORT RE) to protect profits as the market moves further in the direction of the trade.
PSAR with ATR Trailing Stop + SMA Filter📈 Strategy Overview: PSAR + 6×ATR Trailing Stop with SMA Filter
This strategy is built around the principle of “Cut the losers, let the winners run” — a disciplined, trend-following approach that combines the Parabolic SAR indicator with dynamic risk management and a Simple Moving Average (SMA) trend filter.
🔍 Strategy Logic
Trend Filter Trades are only taken in the direction of the prevailing trend, defined by a user-selected SMA (default: 100).
✅ Long trades only when price is above the SMA
✅ Short trades only when price is below the SMA
Entry Signal: A trade is triggered when the Parabolic SAR flips to the opposite side of the price bars, signaling a potential trend reversal.
Stop Loss: The stop loss is dynamically set at 6×ATR from the entry price. This adapts to market volatility and is recalculated every bar — effectively acting as a trailing stop.
Exit Logic: There is no fixed take profit. The trade remains open until the trailing stop is hit — allowing winners to run and losers to be cut quickly.
Risk Management: Each trade risks 0.5% of total equity, ensuring consistent position sizing and capital preservation.
📊 Visual Elements
PSAR dots mark trend direction changes
SMA line shows the broader trend filter
Trailing stop crosses (with 50% opacity) indicate the current stop level without cluttering the chart
⚙️ Customizable Inputs
PSAR parameters: Start, Increment, Maximum
ATR length and multiplier
SMA length
Risk percentage per trade
This strategy is ideal for traders who want to stay aligned with the trend, automate disciplined exits, and avoid emotional decision-making. Clean, simple, and powerful.
Wishing you calm and successful trades!
coinbot_mr_table이 스크립트는 **"MA 리본(Moving Average Ribbon) 기반 자동매매 전략"**입니다.
이름(coinbot_mr_table)에 모든 기능이 요약되어 있습니다.
coinbot: user_id, exchange, leverage 등 자동매매 봇과 연동하기 위한 웹훅(Webhook) 신호 전송 기능이 포함되어 있습니다.
mr (MA Ribbon): 18개(5~90)의 이동평균선(EMA 또는 SMA)이 100 이평선을 기준으로 정배열/역배열되는지를 색상(LIME/RUBI)으로 구분하여 추세를 판단합니다.
table: 전략의 백테스팅 성과(총 승률, 일일 수익률 등)를 차트 위에 '누적 통계'와 '일일 통계' 테이블로 시각화해 줍니다.
이 스크립트의 매매 로직과 자동매매 신호에 대한 자세한 설명을 한글과 영어로 각각 제공해 드립니다.
🇰🇷 한글 (Korean)
이 스크립트는 **"MA 리본(Moving Average Ribbon)"**을 핵심 엔진으로 사용하는 완전 자동매매(Autotrade) 전략 신호 생성기입니다.
이 지표의 목적은 차트에서 추세를 시각적으로 보여주는 것을 넘어, 구체적인 매매 신호(진입, 분할 익절, 손절)가 발생할 때마다 JSON 형식의 명령어를 자동매매 봇으로 전송하는 것입니다.
1. 📈 매매 전략: MA 리본 추세 추종
이 전략은 18개의 단기/중기 이동평균선(5~90)과 1개의 장기 이동평균선(100)을 사용하여 추세를 정의합니다.
100 이평선: 장기 추세를 가르는 기준선(강/약을 나누는 분수령)입니다.
18개 리본: 이 리본들이 100 이평선 위에서 모두 상승(LIME 색상)하면 '강세 추세', 아래에서 모두 하락(RUBI 색상)하면 '약세 추세'로 판단합니다.
2. 🚦 진입 및 청산 신호
이 전략은 '전환(Reversing)' 전략입니다. 즉, 롱 신호가 발생하면 숏 포지션을 종료하고 롱으로 진입하며, 그 반대도 마찬가지입니다. (항상 롱 또는 숏 포지션을 유지합니다.)
진입 신호 (Long):
추세 확정: 모든 리본이 100 이평선 위에서 '강세(LIME)'로 통일될 때.
재진입 (불타기): 강세 추세 중, 리본이 일시적으로 조정(GREEN)을 보이다가 다시 '강세(LIME)'로 복귀할 때.
진입 신호 (Short):
추세 확정: 모든 리본이 100 이평선 아래에서 '약세(RUBI)'로 통일될 때.
재진입 (물타기): 약세 추세 중, 리본이 일시적으로 반등(MAROON)하다가 다시 '약세(RUBI)'로 복귀할 때.
청산 신호 (자동매매):
진입 (ENTRY): 롱/숏 신호 발생 시, 설정한 user_id, exchange, leverage 등을 포함한 JSON 메시지를 전송합니다.
익절 (TAKE_PROFIT): 롱/숏 포지션이 사용자가 설정한 TP1, TP2, TP3 목표가에 도달하면, 설정된 물량(qty_percent)만큼 분할 익절하라는 JSON 메시지를 전송합니다.
손절 (CLOSE): 포지션이 설정한 sl_percent에 도달하면, 포지션을 즉시 종료하라는 JSON 메시지를 전송합니다.
3. 📊 핵심 기능: 통계 테이블
이 스크립트는 백테스팅 성과를 두 개의 테이블로 요약하여 차트에 실시간으로 표시합니다.
누적 통계 (Total Stats): 전체 기간의 총 진입 횟수, 승/패, 승률(Winrate), 총수익률(Total Profit) 등을 보여줍니다.
일일 통계 (Daily Stats): '오늘' 하루 동안 발생한 매매의 성과(승/패, 승률, 수익률)만 따로 집계하여 보여줍니다.
🇺🇸 영어 (English)
This script is an automated trading (Autotrade) strategy signal generator based on a "Moving Average (MA) Ribbon."
Its purpose extends beyond visual trend analysis; it is designed to generate specific JSON-formatted commands and send them to an automated trading bot whenever a trade signal (entry, take-profit, stop-loss) occurs.
1. 📈 Trading Strategy: MA Ribbon Trend Following
This strategy uses 18 short-to-mid-term Moving Averages (5 to 90) and one long-term Moving Average (100) to define the trend.
100-MA: This acts as the baseline filter, dividing the market into a long-term bull or bear state.
18-MA Ribbon: When all 18 ribbons are above the 100-MA and rising (LIME color), it defines a 'Strong Bull Trend'. When all are below the 100-MA and falling (RUBI color), it defines a 'Strong Bear Trend'.
2. 🚦 Entry and Exit Signals
This is a 'Reversing' strategy. This means when a long signal occurs, it closes any existing short position and enters long, and vice-versa. It is designed to hold a position (either long or short) at all times.
Long Entry Signals:
Trend Confirmation: When all ribbons unify into a 'Strong Bull' (LIME) state above the 100-MA.
Re-entry (Buy the Dip): During a bull trend, if the ribbon shows a temporary pullback (GREEN) and then flips back to 'Strong Bull' (LIME).
Short Entry Signals:
Trend Confirmation: When all ribbons unify into a 'Strong Bear' (RUBI) state below the 100-MA.
Re-entry (Sell the Rally): During a bear trend, if the ribbon shows a temporary rally (MAROON) and then flips back to 'Strong Bear' (RUBI).
Exit Signals (For Automation):
ENTRY: When a long/short signal occurs, it sends a JSON message with the user's user_id, exchange, leverage, etc.
TAKE_PROFIT: When a position reaches the user-defined TP1, TP2, or TP3 price targets, it sends a JSON message to take profit on the specified quantity (qty_percent) for that portion.
CLOSE (Stop-Loss): When a position hits the sl_percent threshold, it sends a JSON message to immediately close the entire position.
3. 📊 Key Feature: Statistics Tables
The script provides two real-time summary tables on the chart to visualize backtesting performance.
Cumulative Stats: Shows lifetime performance, including total trades, wins, losses, win rate, and total profit.
Daily Stats: Isolates and displays the performance metrics (wins, losses, win rate, profit) for "Today's" trading activity only.
Mean Reversion Trading V1Overview
This is a simple mean reversion strategy that combines RSI, Keltner Channels, and MACD Histograms to predict reversals. Current parameters were optimized for NASDAQ 15M and performance varies depending on asset. The strategy can be optimized for specific asset and timeframe.
How it works
Long Entry (All must be true):
1. RSI < Lower Threshold
2. Close < Lower KC Band
3. MACD Histogram > 0 and rising
4. No open trades
Short Entry (All must be true):
1. RSI > Upper Threshold
2. Close > Upper KC Band
3. MACD Histogram < 0 and falling
4. No open trades
Long Exit:
1. Stop Loss: Average position size x ( 1 - SL percent)
2. Take Profit: Average position size x ( 1 + TP percent)
3. MACD Histogram crosses below zero
Short Exit:
1. Stop Loss: Average position size x ( 1 + SL percent)
2. Take Profit: Average position size x ( 1 - TP percent)
3. MACD Histogram crosses above zero
Settings and parameters are explained in the tooltips.
Important
Initial capital is set as 100,000 by default and 100 percent equity is used for trades
Adaptive Trend 1m ### Overview
The "Adaptive Trend Impulse Parallel SL/TP 1m Realistic" strategy is a sophisticated trading system designed specifically for high-volatility markets like cryptocurrencies on 1-minute timeframes. It combines trend-following with momentum filters and adaptive parameters to dynamically adjust to market conditions, ensuring more reliable entries and risk management. This strategy uses SuperTrend for primary trend detection, enhanced by MACD, RSI, Bollinger Bands, and optional volume spikes. It incorporates parallel stop-loss (SL) and multiple take-profit (TP) levels based on ATR, with options for breakeven and trailing stops after the first TP. Optimized for realistic backtesting on short timeframes, it avoids over-optimization by adapting indicators to market speed and efficiency.
### Principles of Operation
The strategy operates on the principle of adaptive impulse trading, where entry signals are generated only when multiple conditions align to confirm a strong trend reversal or continuation:
1. **Trend Detection (SuperTrend)**: The core signal comes from an adaptive SuperTrend indicator. It calculates upper and lower bands using ATR (Average True Range) with dynamic periods and multipliers. A buy signal occurs when the price crosses above the lower band (from a downtrend), and a sell signal when it crosses below the upper band (from an uptrend). Adaptation is based on Rate of Change (ROC) to measure market speed, shortening periods in fast markets for quicker responses.
2. **Momentum and Trend Filters**:
- **MACD**: Uses adaptive fast and slow lengths. In "Trend Filter" mode (default when "Use MACD Cross" is false), it checks if the MACD line is above/below the signal for long/short. In cross mode, it requires a crossover/crossunder.
- **RSI**: Adaptive period RSI must be above 50 for longs and below 50 for shorts, confirming overbought/oversold conditions dynamically.
- **Bollinger Bands (BB)**: Depending on the mode ("Midline" by default), it requires the price to be above/below the BB midline for longs/shorts, or a breakout in "Breakout" mode. Deviation adapts to market efficiency.
- **Volume Spike Filter** (optional): Entries require volume to exceed an adaptive multiple of its SMA, signaling strong impulse.
3. **Volatility Filter**: Entries are only allowed if current ATR percentage exceeds a historical minimum (adaptive), preventing trades in low-volatility ranges.
4. **Risk Management (Parallel SL/TP)**:
- **Stop-Loss**: Set at an adaptive ATR multiple below/above entry for long/short.
- **Take-Profits**: Three levels at adaptive ATR multiples, with partial position closures (e.g., 51% at TP1, 25% at TP2, remainder at TP3).
- **Post-TP1 Features**: Optional breakeven moves SL to entry after TP1. Trailing SL uses BB midline as a dynamic trail.
- All levels are calculated per trade using the ATR at entry, making them "realistic" for 1m charts by widening SL and tightening initial TPs.
The strategy enters long on buy signals with all filters met, and short on sell signals. It uses pyramid margin (100% long/short) for full position sizing.
Adaptation is driven by:
- **Market Speed (normSpeed)**: Based on ROC, tightens multipliers in volatile periods.
- **Efficiency Ratio (ER)**: Measures trend strength, adjusting periods for trending vs. ranging markets.
This ensures the strategy "adapts" without manual tweaks, reducing false signals in varying conditions.
### Main Advantages
- **Adaptability**: Unlike static strategies, parameters dynamically adjust to market volatility and trend strength, improving performance across ranging and trending phases without over-optimization.
- **Realistic Risk Management for 1m**: Wider SL and tiered TPs prevent premature stops in noisy short-term charts, while partial profits lock in gains early. Breakeven/trailing options protect profits in extended moves.
- **Multi-Filter Confirmation**: Combines trend, momentum, and volume for high-probability entries, reducing whipsaws. The volatility filter avoids flat markets.
- **Debug Visualization**: Built-in plots for signals, levels, and component checks (when "Show Debug" is enabled) help users verify logic on charts.
- **Efficiency**: Low computational load, suitable for real-time trading on TradingView with alerts.
Backtesting shows robust results on volatile assets, with a focus on sustainable risk (e.g., SL at 3x ATR avoids excessive drawdowns).
### Uniqueness
What sets this strategy apart is its **fully adaptive framework** integrating multiple indicators with real-time market metrics (ROC for speed, ER for efficiency). Most trend strategies use fixed parameters, leading to poor adaptation; here, every key input (periods, multipliers, deviations) scales dynamically within bounds, creating a "self-tuning" system. The "parallel SL/TP with 1m realism" adds custom handling for micro-timeframes: tightened initial TPs for quick wins and adaptive min-ATR filter to skip low-vol bars. Unlike generic mashups, it justifies the combination—SuperTrend for trend, MACD/RSI/BB for impulse confirmation, volume for conviction—working synergistically to capture "trend impulses" while filtering noise. The post-TP1 breakeven/trailing tied to BB adds a unique profit-locking mechanism not common in open-source scripts.
### Recommended Settings
These settings are optimized and recommended for trading ASTER/USDT on Bybit, with 1-minute chart, x10 leverage, and cross margin mode. They provide a balanced risk-reward for this volatile pair:
- **Base Inputs**:
- Base ATR Period: 10
- Base SuperTrend ATR Multiplier: 2.5
- Base MACD Fast: 8
- Base MACD Slow: 17
- Base MACD Signal: 6
- Base RSI Period: 9
- Base Bollinger Period: 12
- Bollinger Deviation: 1.8
- Base Volume SMA Period: 19
- Base Volume Spike Multiplier: 1.8
- Adaptation Window: 54
- ROC Length: 10
- **TP/SL Settings**:
- Use Stop Loss: True
- Base SL Multiplier (ATR): 3
- Use Take Profits: True
- Base TP1 Multiplier (ATR): 5.5
- Base TP2 Multiplier (ATR): 10.5
- Base TP3 Multiplier (ATR): 19
- TP1 % Position: 51
- TP2 % Position: 25
- Breakeven after TP1: False
- Trailing SL after TP1: False
- Base Min ATR Filter: 0.001
- Use Volume Spike Filter: True
- BB Condition: Midline
- Use MACD Cross (false=Trend Filter): True
- Show Debug: True
For backtesting, use initial capital of 30 USD, base currency USDT, order size 100 USDT, pyramiding 1, commission 0.1%, slippage 0 ticks, long/short margin 0%.
Always backtest on your platform and use risk management—risk no more than 1-2% per trade. This is not financial advice; trade at your own risk.
AlgoIndex - All Stages (AM & Mid-Day Long/Short)Scope (read first)
ES1! on 5-minute only. The strategy backtests ES fills; alerts can post JSON messages to a Webhook URL you configure. Exits are target-based with ITTC - if ES touches target intra-bar, an exit alert is sent immediately. No fixed ES stop-loss. Positions can also exit at scheduled time-based safety closes (session end, holiday/half-day, or expiration end). You can always close manually.
What this is
One intraday engine with four session presets (“Stages”). Stages only change session windows, trade side, and a few risk/confirmation governors—the core logic is the same. Single invite-only listing; not a multi-post suite.
How it trades
Opening Range (OR): Each Stage begins with a short OR at its session start; that Stage won’t take entries until its OR closes.
VWAP alignment: Trade with flow. Price must align with VWAP (simple pass/fail; optional gap offset).
Real breakouts only: A composite “impulse” check looks for volume expansion, recent momentum, ATR-scaled range, body/range quality, and a clean OR break (or a gap-aware extension).
Entry & target: Entries occur on the signal bar’s close; targets are set in underlying (ES) units.
ITTC (close on touch): If ES touches target intra-bar, ITTC sends a one-shot exit.
Adds (preset by Stage): S1/S2/S3 allow up to two adds on defined ES retraces; S4 disables adds. Adds use a fixed scale-out policy handled internally—no user input required.
Time-based safety closes: At the configured session end (and on holiday/half-day or expiration when applicable), any open position is closed. These are time exits, not price stops.
Why traders use it
A progressive filter for intraday continuity: OR context → VWAP alignment → authentic breakout (impulse) → ITTC to sync ES triggers with options execution. Stage-governed adds keep scaled positions coherent from open to close.
Stages (session templates; one engine)
S1 — 09:30–11:20 NY, Long-only. Standard impulse; adds ON.
S2 — 09:30–11:30 NY, Short-only. Tighter breakout standard; adds ON.
S3 — 11:15–15:15 NY, Long-only. Trade-protection ON; slightly lower underlying target; adds ON.
S4 — 11:30–14:30 NY, Short-only. Alternative trigger governor; slightly lower underlying target; adds OFF.
You can replicate any Stage via session times, side, and thresholds; presets exist for convenience and auditability.
Public inputs (what you can adjust)
Contracts (order size)
TP (Underlying) and TP (Options)
Trade Limiter (toggle) + Max profitable trades per session
Session settings: Exchange Day Session times, optional Custom Time Zone, Session 1 times, optional Session 2, and day-of-week checkboxes
Visual overlays (display-only): VWAP, Prior-Day High/Low, Session High/Low, Round Numbers, Bias Banner, Trade Markers
Display: Inputs in status line
Alerts (how to use)
Create an alert on this strategy and select “Any alert() function call.” (Optional) add a Webhook URL you control to receive the JSON the script sends. Leave Message empty.
Backtest vs options (read carefully)
Backtests show ES fills on 5-minute bars; options pricing (IV, DTE, spreads, partial fills) isn’t simulated. Because live execution uses options, ES PnL is a directional proxy only.
Evaluate quality via: trade count (target ≥100), win rate, average time-in-trade, MAE/MFE, and holding-time distribution. Do not read ES $ PnL as expected options returns—actual options outcomes depend on strike/DTE, IV regime, spreads, and execution.
Defaults used in this publication (match these before interpreting results)
Dataset: last 12–24 months of ES1! 5-minute RTH (to ensure ≥100 trades)
Initial capital: $25,000
Commission: $1.00 per order per contract (≈ $2 round-trip)
Slippage: 1 tick
Order size: 1 contract; pyramiding only for Stage-governed adds
No fixed ES stop-loss; exits are target-based with ITTC and scheduled safety closes
Operating notes
ES1! symbol only; 5-minute resolution only
You can run multiple Stages in parallel via separate tabs/alerts; if you want a single net position across Stages, enforce it in your own tooling (e.g., ignore new orders while a position is open)
Use a clean chart when publishing (only this strategy active)
Keep results separate by using four TradingView tabs (one per Stage)
Disclosures
Educational research tool, not financial advice. Past or hypothetical performance does not guarantee future results. Trading involves risk, including the risk of loss. Test thoroughly and use at your own discretion.
SRFRZ EMA Crossover with RSI StrategySRFRZ EMA Crossover with RSI Strategy
1. Overview
Strategy Name: SRFRZ EMA Crossover with RSI Strategy
Summary: A trend-following strategy designed for Indian stock and index markets, operating on any timeframe (optimized for 1H or 4H charts). It combines a 9-period and 21-period EMA crossover with RSI confirmation to identify high-probability long entries during the Indian trading session (9:15 AM–3:25 PM IST). Backtested with a fixed 20% capital allocation per trade, 3% stop loss, and 50% take profit, it aims for consistent returns in trending markets.
Intended Audience: Intermediate traders familiar with EMA and RSI, seeking automated signals for Indian markets.
2. How It Works (Core Logic)
Entry Conditions (Long/Buy Signal):
Primary Trigger: A "Golden Cross" occurs when the 9-period EMA crosses above the 21-period EMA, signaling bullish momentum.
RSI Confirmation: RSI (14-period) must be above 55, or cross above 55, to confirm strong momentum.
Trend Filter: The 9-period EMA must remain above the 21-period EMA for delayed RSI-triggered entries.
Session Filter: Trades are only executed during the Indian market session (9:15 AM–3:25 PM IST, Monday–Friday).
Exit Conditions:
Take Profit (TP): Fixed at 50% above the entry price (e.g., entry at ₹100, TP at ₹150).
Stop Loss (SL): Fixed at 3% below the entry price (e.g., entry at ₹100, SL at ₹97).
Indicator-Based Exit: Close the position if a "Death Cross" occurs (21-period EMA crosses above 9-period EMA).
Position Sizing: Allocates 20% of initial capital (₹100,000 default) per trade, calculated as (initial_capital * 0.20) / entry_price.
3. Key Indicators & Parameters
Primary Indicators:
EMA (9-period): Fast-moving average to capture short-term trends (plotted in blue).
EMA (21-period): Slower-moving average for trend confirmation (plotted in red).
RSI (14-period): Measures momentum, with a threshold of 55 for bullish confirmation (plotted in purple).
Customizable Settings in Pine Script:
initial_capital: Default ₹100,000 (adjust based on your account size).
qty_percent: Default 20% of capital per trade (adjust for risk tolerance).
sl_percent: Default 3% stop loss (adjust for volatility).
tp_percent: Default 50% take profit (adjust for reward targets).
session_time: Default "0915-1525:1234567" (Indian session, adjustable for other markets).
Default Values: Optimized for Indian stocks/indices (e.g., NIFTY 50) on 1H or 4H charts.
Risk Management:
Always use the built-in 3% stop loss.
Avoid trading during major news events (e.g., RBI announcements), as Pine Script cannot filter these.
Risk only 20% of capital per trade to diversify exposure.
Pro Tips:
Combine with support/resistance levels for manual confirmation.
Test on a demo account to validate performance on your chosen asset.
Monitor RSI for overbought conditions (>70) to anticipate reversals.
4. Visuals on Chart
Plotted Indicators:
Blue line: 9-period EMA.
Red line: 21-period EMA.
Purple line: RSI (14-period) in a separate pane.
Trade Signals:
Green triangle (below bar): Long entry.
Red triangle (above bar): Long exit (via TP, SL, or Death Cross).
5. Disclaimer & Notes
Risk Warning: Past performance is not indicative of future results. Trading involves significant risk. This strategy is for educational purposes only and is not financial advice.
Customization: The script is open-source (modify freely). Fork it to add short-selling logic or additional filters.
Note: The strategy avoids trades during non-session hours but cannot filter news events. Manually check economic calendars.
Add the script to your chart and adjust inputs (e.g., capital, TP/SL percentages).
Enable alerts for "Long Entry" and "Long Exit TP/SL" or "EMA Exit" to automate signals.
Optionally, connect to a broker via webhooks for auto-trading (consult your broker’s API).
Intraday Momentum for Volatile Stocks 29.09The strategy targets intraday momentum breakouts in volatile stocks when the broader market (Nifty) is in an uptrend. It enters long positions when stocks move significantly above their daily opening price with sufficient volume confirmation, then manages the trade using dynamic ATR-based stops and profit targets.
Entry Conditions
Price Momentum Filter: The stock must move at least 2.5% above its daily opening price, indicating strong bullish momentum. This percentage threshold is customizable and targets gap-up scenarios or strong intraday breakouts.
Volume Confirmation: Daily cumulative volume must exceed the 20-day average volume, ensuring institutional participation and genuine momentum. This prevents false breakouts on low volume.
Market Regime Filter: The Nifty index must be trading above its 50-day SMA, indicating a favorable market environment for momentum trades. This macro filter helps avoid trades during bearish market conditions.
Money Flow Index: MFI must be above 50, confirming buying pressure and positive money flow into the stock. This adds another layer of momentum confirmation.
Time Restriction: Trades are only initiated before 3:00 PM to ensure sufficient time for position management and avoid end-of-day volatility.
Exit Management
ATR Trailing Stop Loss: Uses a 3x ATR multiplier for dynamic stop-loss placement that trails higher highs, protecting profits while giving trades room to breathe. The trailing mechanism locks in gains as the stock moves favorably.
Profit Target: Set at 4x ATR above the entry price, providing a favorable risk-reward ratio based on the stock's volatility characteristics. This adaptive approach adjusts targets based on individual stock behavior.
Position Reset: Both stops and targets reset when not in a position, ensuring fresh calculations for each new trade.
Key Strengths
Volatility Adaptation: The ATR-based approach automatically adjusts risk parameters to match current market volatility levels. Higher volatility stocks get wider stops, while calmer stocks get tighter management.
Multi-Timeframe Filtering: Combines intraday price action with daily volume patterns and market regime analysis for robust signal generation.
Risk Management Focus: The strategy prioritizes capital preservation through systematic stop-loss placement and position sizing considerations.
Considerations for NSE Trading
This strategy appears well-suited for NSE intraday momentum trading, particularly for mid-cap and small-cap stocks that exhibit high volatility. The Nifty filter helps align trades with broader market sentiment, which is crucial in the Indian market context where sectoral and index movements strongly influence individual stocks.
The 2.5% threshold above open price is appropriate for volatile NSE stocks, though traders might consider adjusting this parameter based on the specific stocks being traded. The strategy's emphasis on volume confirmation is particularly valuable in the NSE environment where retail participation can create misleading price movements without institutional backin
DEMARED with ATR StopLoss & Dynamic Risk (v5)DEMARED with ATR StopLoss & Dynamic Risk
This strategy combines Double Exponential Moving Averages (DEMA) with EMA and Donchian midline filters to capture trend-following signals. A long entry is triggered when both DEMA pairs are aligned bullishly, price is above EMA, and above the Donchian midpoint. Exits occur on opposite signals or when the ATR-based stop loss is hit.
Key features:
ATR Stop Loss: dynamic stop based on ATR with user-defined multiplier.
Dynamic Risk Management: position size is automatically calculated based on account equity and risk percentage.
Visualization: plots stop loss, EMA, Donchian midline, and optional bar coloring.
Flexible Display: toggle all indicator visuals on/off with a single input.
The goal is to provide a trend-following system with controlled risk and adaptability across different markets and timeframes.
Lavender Multi-Signal Momentum StrategyOverview
The Lavender strategy is a sophisticated momentum-based trading system specifically optimized for Tesla (TSLA) on the 15-minute timeframe. It combines multiple technical signals to identify high-probability long entries during strong trending conditions.
Key Features
🎯 Multi-Signal Entry System
The strategy uses 4 distinct signal types that can be enabled/disabled individually:
Supertrend Pullback (Default: ON)
Identifies pullbacks in uptrends using Supertrend (ATR: 9, Factor: 0.5)
Enters when price retests EMA9-20 zone during bullish Supertrend
Donchian Breakout + Z-Score Momentum (Default: ON)
53-period Donchian channel breakouts
Combined with 35-period Z-Score momentum filter
Only triggers with positive momentum confirmation
Keltner Squeeze Expansion (Default: OFF)
Detects volatility squeeze conditions
Enters on breakout above Keltner Channel after compression
Opening Range Breakout (ORB) (Default: ON)
Tracks first hour range (9:30-10:30 AM)
Triggers on breakout above opening range high
🧭 Trend Regime Filter
EMA Trend Filter: 20 EMA > 100 EMA (Default: ON)
ADX Strength Filter: ADX > 22 with 15/13 smoothing (Default: ON)
Only trades when both trend conditions align
💵 Advanced Risk Management
Risk per Trade: 2.0% of capital (Default)
ATR-Based Stop Loss: 15-period ATR × 1.6 multiplier
Risk/Reward Ratio: 4:1 (Default)
Position Sizing: Automatic based on stop distance
Capital Options: Dynamic equity or fixed capital ($200,000 default)
⚙️ Execution Control
Candle Close Entries: Prevents intrabar noise (Default: ON)
Candle Close Exits: Stop loss and take profit only at bar close (Default: ON)
Trading Session: 9:00 AM - 4:00 PM (Default)
Trading Days: Monday-Saturday (Default: 123456)
Default Settings Summary
ParameterDefault ValuePurposeRisk per Trade2.0%Capital risk percentageATR Length15Stop loss calculationATR Multiplier1.6Stop distance factorRisk/Reward4.0Take profit multiplierEMA Fast20Short-term trendEMA Slow100Long-term trendADX Threshold22Minimum trend strengthMin Signals Required1Entry trigger thresholdInitial Capital$200,000Backtesting capital
How It Works
Trend Confirmation: Checks EMA alignment and ADX strength
Signal Generation: Scans for active momentum signals
Entry Execution: Enters when minimum signal threshold is met
Risk Management: Calculates position size based on ATR stop
Exit Management: Manages trades with 4:1 risk/reward ratio
Best Use Cases
Tesla (TSLA) on 15-minute charts
Trending market conditions
Intraday momentum trading
Markets with clear directional bias
Visual Indicators
Blue Line: 100-period EMA (trend filter)
Green/Red Line: Supertrend indicator
Teal Line: Donchian channel high
Purple Triangles: Keltner breakout signals
Orange Arrows: Opening range breakouts
Green Dots: Combined entry signals
Red/Green Lines: Active stop loss and take profit levels
Risk Disclaimer
This strategy is optimized for Tesla's specific price behavior on 15-minute timeframes. Past performance does not guarantee future results. Always test thoroughly and manage risk appropriately.
Created by kevloewe - Specialized for TSLA 15M momentum trading
BDNS ORB Strategy v3BDNS Opening Range Breakout Strategy
What This Strategy Does This strategy implements an Opening Range Breakout (ORB) system that identifies the high and low prices during a customizable opening period, then trades breakouts above or below these levels with momentum confirmation. The strategy goes beyond basic ORB concepts by incorporating ADX momentum filtering, VWAP directional bias, dynamic position sizing, and sophisticated exit management including breakeven moves and trailing stops.
Core Strategy Logic
Opening Range Definition: The strategy tracks price action during a user-defined opening period (default: 9:30-9:35 AM ET for 5 minutes). During this time, blue horizontal lines appear marking the session high and low. A yellow background highlights this opening range period.
Breakout Detection: After the opening range completes, green and red horizontal lines appear showing the actual entry levels - these are offset from the range boundaries by a configurable number of ticks (default: 24 ticks) to filter out false breakouts and ensure committed moves.
Entry Conditions: Trades trigger when price breaks through these offset levels during the trading window (green background, default until 10:30 AM ET), but only when:
ADX momentum indicator exceeds threshold (default 24.0) in the breakout direction
Price relationship to VWAP confirms directional bias (when VWAP filter enabled)
Daily trade limits haven't been reached
Large range filtering conditions are met
Visual Elements and Usage
Range Lines: Blue lines show the actual opening range boundaries. These appear immediately when the opening session begins.
Entry Levels: Green (long) and red (short) lines show where trades will trigger, appearing after the opening range completes.
Information Table: A data table appears in the top-right showing real-time strategy status including range size in ticks, ADX readings, filter status, trade counts, and momentum conditions.
Position Management:
When in a trade, colored circles appear showing:
Lime circles: Long position targets (T1, T2, T3)
Orange circles: Short position targets
Red circles: Stop loss levels
Blue crosses: Breakeven levels (when that feature activates)
Purple lines: Trailing stop levels (when position 3 trailing activates)
Background Colors:
Yellow: Opening range session active
Green: Trading window active
Purple: Large range day detected
Gray: Large range day being skipped
Position Management System
The strategy uses a three-tier exit approach:
Position 1: Takes partial profits at first target (default 50% of range size)
Position 2: Exits at second target (default 100% of range size)
Position 3: Either exits at third target or uses trailing stop after Position 2 wins
Breakeven Feature: When enabled and price reaches the breakeven trigger level, all stop losses move to a more favorable breakeven level instead of the original stop, protecting against giving back profits.
Trailing Stop System: After Position 2 hits its target, Position 3 automatically switches to a trailing stop that moves in the trader's favor as price continues trending.
Customization for Different Instruments
The default settings are configured for MNQ (Micro NASDAQ futures) but the ORB concept is highly customizable for any futures instrument and timeframe. Range duration, breakout offsets, and filter thresholds should be adjusted based on the specific instrument's volatility characteristics and typical intraday patterns.
Filter Usage Guidelines
ADX Momentum Filter: Essential for avoiding breakouts during consolidation. Higher thresholds (30+) for trending markets, lower (20-25) for more opportunities.
VWAP Filter: Helpful in trending conditions but may reduce trade frequency. Better to disable during range-bound or mean-reverting periods.
Large Range Filter: Critical risk management tool. When the opening range exceeds your threshold:
Skip: Avoids trades when stops would be too large
Fade: Trades mean reversion back into the range
Trade: Takes breakouts regardless (higher risk)
Range Size Considerations: Setting a large range threshold (200-400 ticks) helps avoid days when both sides of the range get tested before any meaningful breakout occurs, which often leads to whipsaws.
Risk Management Features
Dynamic Stops and Targets: All exit levels scale with the opening range size, ensuring risk/reward remains consistent regardless of daily volatility. A 100-tick range day will have proportionally smaller stops than a 300-tick range day.
Position Sizing: Configure contract amounts for each position tier based on account size and risk tolerance.
Daily Trade Limits: Prevents overtrading by limiting trades per direction per day.
Breakout Offset: The tick offset from range boundaries is crucial - too small creates false signals, too large misses good moves. Test different values based on your instrument's typical noise levels.
Advanced Features
Large Third Target: Set Target 3 to 300-500% to essentially hold runners indefinitely, using the trailing stop as the primary exit method for capturing extended trends.
Fade Trading: On large range days, the strategy can trade mean reversion when initial breakouts fail, often providing good counter-trend opportunities.
Time-Based Exits: All positions close at the end of the trading window, preventing overnight risk.
Strategy Properties Used
Initial Capital: $5,000 (realistic for micro contract trading)
Commission: $0.50 per contract (realistic retail rates)
Position Size: 100% of equity (manages risk through contract quantities and stop placement)
Default quantities: 3/1/1 contracts across the three positions
The default settings assume larger account sizes or proprietary trading firm accounts where higher risk tolerance is acceptable. With MNQ at $0.50 per tick, a typical 200-tick opening range with 75% stop loss (150 ticks) would risk $375 on a 5-contract position. For smaller retail accounts, consider reducing position sizes significantly - using only Position 1 (3 contracts) would risk $225, or even reducing to 1-2 total contracts to maintain appropriate risk levels relative to account size.
Getting Started Apply the strategy to your preferred instrument
Adjust the opening range time and duration for your market
Set appropriate breakout offset based on typical noise levels
Configure large range threshold based on your risk tolerance
Test filter combinations to find what works best for your trading style
Adjust contract quantities based on your account size and risk management rules
The strategy works best on liquid instruments with clear opening sessions and sufficient volatility to generate meaningful ranges. Results will vary significantly based on market conditions, parameter settings, and the specific instrument traded.
I warrant that the information created and published by by me here on TradingView is not prohibited, doesn't constitute investment advice, and isn't created solely for qualified investors.
Canuck Trading Traders Strategy [Candle Entropy Edition]Canuck Trading Traders Strategy: A Unique Entropy-Based Day Trading System for Volatile Stocks
Overview
The Canuck Trading Traders Strategy is a custom, entropy-driven day trading system designed for high-volatility stocks like TSLA on short timeframes (e.g., 15m). At its core is CETP-Plus, a proprietary blended indicator that measures "order from chaos" in candle patterns using Shannon entropy, while embedding mathematical principles from EMA (recent weighting), RSI (momentum bias), ATR (volatility scaling), and ADX (trend strength) into a single score. This unique approach avoids layering multiple indicators, reducing complexity while improving timing for early trend detection and balanced long/short trades.
CETP-Plus calculates a score from weighted candle ratios (body, upper/lower wicks) binned into a 3D histogram for entropy (low entropy = strong pattern). The score is adjusted with momentum, volatility, and trend multipliers for robust signals. Entries occur when the score exceeds thresholds (positive for longs, negative for shorts), with exits on reversals or stops. The strategy is automatic—no manual bias needed—and optimized for margin accounts with equal long/short treatment.
Backtested on TSLA 15m (Jan 2015–Aug 2025), it targets +50,000% net profit (beating +1,478% buy-hold by 34x) with ~25,000 trades, 85-90% win rate, and <10% drawdown (with costs). Results vary by timeframe/period—test with your data and add slippage/commission for realism. Disclaimer: Past performance isn't indicative of future results; consult a financial advisor.
Key Features
CETP-Plus Indicator: Blends entropy with momentum/vol/trend for a single score, capturing bottoms/squeezes and trends without external tools.
Automatic Balance: Positive scores trigger longs in bull trends, negative scores trigger shorts in bear trends—no user input for direction.
Customizable Math: Tune weights and scales to adapt for different stocks (e.g., lower thresholds for NVDA's smoother trends).
Risk Controls: Stop-loss, trailing stops, and score strength filter to minimize drawdowns in volatile markets like TSLA.
Exit Debugging: Plots exit reasons ("Stop Loss", "Trail Stop", "CETP Exit") for analysis.
Input Settings and Purposes
All inputs are grouped in TradingView's Inputs tab for ease. Defaults are optimized for TSLA 15m day trading; adjust for other intervals or tickers (e.g., increase window for 1h, lower thresholds for NVDA).
CETP-Plus Settings
CETP Window (default: 5, min: 3, max: 20): Lookback bars for entropy/momentum. Short values (3-5) for fast sensitivity on short frames; longer (8-10) for stability on hourly+.
CETP Bins per Dimension (default: 3, min: 3, max: 10): Histogram granularity for entropy. Low (3) for speed/simple patterns; high (5+) for detail in complex markets.
Long Threshold (default: 0.15, min: 0.1, max: 0.8, step: 0.05): CETP score for long entries. Lower (0.1) for more longs in mild bull trends; higher (0.2) to filter noise.
Short Threshold (default: -0.05, min: -0.8, max: -0.1, step: 0.05): CETP score for short entries. Less negative (-0.05) for more shorts in mild bear trends; more negative (-0.2) for strong signals.
CETP Momentum Weight (default: 0.8, min: 0.1, max: 1.0, step: 0.1): Emphasizes momentum in score. High (0.9) for aggressive in fast moves; low (0.5) for entropy focus.
Momentum Scale (default: 1.6, min: 0.1, max: 2.0, step: 0.1): Amplifies momentum. High (2.0) for short intervals; low (1.0) for stability.
Body Ratio Weight (default: 1.2, min: 0.0, max: 2.0, step: 0.1): Weights candle body in entropy (trend focus). High (1.5) for strong trends; low (0.8) for wick emphasis.
Upper Wick Ratio Weight (default: 0.8, min: 0.0, max: 2.0, step: 0.1): Weights upper wick (reversal noise). Low (0.5) to reduce false ups.
Lower Wick Ratio Weight (default: 0.8, min: 0.0, max: 2.0, step=0.1): Weights lower wick. Low (0.5) to reduce false downs.
Trade Settings
Confirmation Bars (default: 0, min: 0, max: 5): Bars for sustained CETP signals. 0 for immediate entries (more trades); 1-2 for reliability (fewer but stronger).
Min CETP Score Strength (default: 0.04, min: 0.0, max: 0.5, step: 0.05): Min absolute score for entry. Low (0.04) for more trades; high (0.15) for quality.
Risk Management
Stop Loss (%) (default: 0.5, min: 0.1, max: 5.0, step: 0.1): % from entry for stop. Tight (0.4) for quick exits; wide (0.8) for trends.
ATR Multiplier (default: 1.5, min: 0.5, max: 3.0, step: 0.1): Scales ATR for stops/trails. Low (1.0) for tight; high (2.0) for room.
Trailing ATR Mult (default: 3.5, min: 0.5, max: 5.0, step: 0.1): ATR mult for trails. High (4.0) for longer holds; low (2.0) for profits.
Trail Start Offset (%) (default: 1.0, min: 0.5, max: 2.0, step: 0.1): % profit before trailing. Low (0.8) for early lock-in; high (1.5) for bigger moves.
These settings enable customization for intervals/tickers while CETP-Plus handles automatic balancing.
Risk Disclosure
Trading involves significant risk and may result in losses exceeding your initial capital. The Canuck Trading Trader Strategy is provided for educational and informational purposes only. Users are responsible for their own trading decisions and should conduct thorough testing before using in live markets. The strategy’s high trade frequency requires reliable execution infrastructure to minimize slippage and latency.
The SamuraiOverview
This strategy implements a session-based range breakout system specifically designed for GBP/JPY trading. The approach focuses on identifying key price ranges during specific market sessions and trading breakouts of these ranges during optimal trading windows. The strategy combines multi-timeframe analysis using 30-minute data with precise session timing to capture high-probability breakout moves.
Entry Logic
The strategy operates on a two-phase approach:
Range Collection Phase:
Monitors price action during a specified session window
Identifies session high and low levels
Only collects ranges on selected trading days
Trading Phase:
Long Entry: Price closes above the established session high
Short Entry: Price closes below the established session low
Entries only occur on valid trading days (day after range collection)
One trade per direction per session to prevent overtrading
Exit Conditions
Stop Loss: Set at a percentage of the session range below entry (long) or above entry (short)
Take Profit: Calculated using a Risk-Reward Ratio based on stop loss distance
Session Close: All positions are closed at the end of the trading window
Risk Management Features
Fixed risk-reward ratio of for consistent risk management
Stop loss calculated as percentage of session range for adaptive sizing
Visual risk/reward boxes display potential outcomes before entry
Daily session close protection prevents overnight exposure
Visual Features
Customizable Colors: Full control over line colors, styles, and box opacities
Risk/Reward Visualization: Color-coded boxes showing potential profit and loss zones
Take Profit Lines: TP level with different line styles for clarity
Stop Loss Line: Clear visual indication of risk level
Clean Interface: Streamlined settings focused on essential visual customization
Important Notes
Timeframe Dependency: Strategy uses 30-minute data regardless of chart timeframe for consistency
Session Timing: All times are in UTC - ensure proper timezone conversion for your location
Trading Days: Default setup trades Tuesday-Friday ranges (Monday-Thursday collection)
Single Position: Only one position per direction per session to maintain discipline
No Pyramiding: Strategy prevents position averaging to maintain clear risk parameters
Suggested Use
Recommended Pairs: Optimized for GBP/JPY but may work on other volatile pairs
Best Timeframes: Display on any timeframe (strategy uses 30m data internally)
Session Awareness: Most effective during high-volatility session transitions
Risk Management: Consider position sizing based on account risk tolerance
Market Conditions: Performs best in trending or breakout market environments
Backtesting Considerations
Strategy includes realistic entry/exit conditions based on closing prices
Visual elements help understand historical performance context
Built-in position management prevents unrealistic results
Session-based logic ensures trades align with actual market sessions
This strategy is designed for traders who prefer systematic, rule-based approaches to breakout trading with clear risk management parameters. The visual feedback helps in understanding market context and decision-making process.
Disclaimer: Past performance does not guarantee future results. Always test thoroughly on historical data and consider your risk tolerance before live trading.
Strategy Builder Pro [ChartPrime]ChartPrime Strategy Creator Overview
The ChartPrime Strategy Builder offers traders an innovative, structured approach to building and testing strategies. The Strategy Creator allows users to combine, test, and automate complex strategies with many parameters.
Key Features of the ChartPrime Strategy Builder
1. Customizable Buy and Sell Conditions
The Strategy Creator provides flexibility in establishing entry and exit rules, with separate sections for long and short strategies. Traders can combine multiple conditions in each section to fine-tune when positions are opened or closed. For instance, they might choose to only buy when the indicator signals a buy and the Dynamic Reactor (a low lag filter) indicator shows a bullish trend. Users are able to pick, mix and match the following list of features:
Signal Mode: Select the type of assistive signals you are requiring. Provided are both trend following signals with self optimization using backtest results as well as reversal signals, aiming to provide real time tops and bottoms in markets. Both these signal modes can be fine tuned using the tuning input to refine signals to a trader's liking. ChartPrime Trend Signals leverage audio engineering inspired techniques and low-pass filters in order to achieve and attempt to produce lower lag response times and therefore are designed to have a uniqueness when compared to more classical trend following approaches.
The Dynamic Reactor: provides a simple band passing through the chart. This can provide assistance in support and resistance locations as well as identifying the trend direction expressed via green and red colors. Taking a moving average and applying unique adaptivity calculations gives this plot a unique and fast behavior.
Candlestick structures: analyze candlestick formation putting a spin on classical candlestick patterns and provide the most relevant formations on the chart. These are not classical and are filtered by further analyzing market activity. A trader's classic with a spin.
The Prime Trend Assistant: provides a trend following dynamic support and resistance level. This makes it perfect to use in confluence or as a filter for other supporting indicators. This is an adaptive trend following system designed to handle volatility leveraging filter kernels as opposed to low pass filters.
Money Flow: with further filters applied for early response to money flow changes in the market. This can be a great filter in trends.
Oscillator reversals: are built in leveraging an oscillator focusing on market momentum allowing users to enter based on market shifts and trends along with reversals.
Volume-Inspired Signals: determine overbought and oversold conditions, adding another layer of analysis to the oscillator. These appear as orange labels, providing a simple reading into a possible reversal.
The Volume Matrix: is a volume oscillator that shows whether money is flowing into or out of the market. Green suggests an uptrend with buyers in control, while red indicates a majority of sellers. By incorporating smoothed volume analysis, it distinguishes between bullish and bearish volumes, offering an early indication of potential trend reversals.
The True 7: is a middle-ranking system that evaluates the strength of a move and the overall trend, offering a numeric or visual representation of trend strength. It can also indicate when a trend is starting to reverse, providing leading signals for potential market shifts. Rather than using an oscillator, this offers the unique edge of falling into set categories, making understanding it simple. This can be a great confluence point when designing a strategy.
Take profits: These offer real-time suggestions from our algorithm on when it might be a good time to take profit. Using these as part of a strategy allows for great entries at bottoms and tops of trends.
Using features such as the Dynamic reactor have dual purposes. Traders can use this as both a filter and an entry condition. This allows for true interoperability when using the Strategy Builder. The above conditions are duplicated for short entries too allowing for symmetrical trading systems. By disabling all of the entry conditions on either long or short areas of the settings will create a strategy that only takes a single type of position. For example; a trader that just wants to take longs can disable all short options.
2. Layered Entries
Layered entries, a feature to enhance the uniqueness in the tool. It allows traders to average into positions as the market moves, rather than committing all capital at once. This feature is particularly useful for volatile markets where prices may fluctuate substantially. The Strategy Builder lets users adjust the number of layered entries, which can help in managing risk and optimizing entry points as well as the aggressiveness of the safety orders. With each safety order placed the system will automatically and dynamically scale into positions reducing the average entry price and hence dynamically adjust the potential take profits. Due to the potential complexities of exiting during multiple orders, a smart system is employed to automatically take profits on the layered system aiming to take profits at peaks of trends.
Users are able to override this smart TP system at the bottom of the settings instead targeting percentage profits for both short and long positions.
Entries lowering average buy price
The ability to adjust how quickly the system layers into positions can also be adjusted via the layered entries drop down between fast and slow mode where the slow mode will be more cautious when producing new orders.
3. Flexible Take Profit (TP) and Stop Loss (SL) Options
Traders can set their TP and SL levels according to various parameters, including ATR (Average True Range), risk-reward ratio, trailing stops, or specific price changes. If layered entries are active, an automatic TP method is applied by default, though traders can manually specify TP values if they prefer. This setup allows for precise control over trade exits, tailored to the strategy’s risk profile.
Provided options
The ability to use external take profits and stop losses is also provided. By loading an indicator of your choice the plots will be added to the chart. By navigating to the external sources area of the settings, users can select this plot and use it as part of a wider trading system.
Example: Let’s say a user has entries based on the inbuilt trend signals and wishes to exit whenever the RSI crosses above 70, they can add RSI to the chart, select crossing up and enter the value of 70.
4. Integrated Reinvestment for Compounding Gains
The reinvestment option allows traders to reinvest a portion of their gains into future trades, increasing trade size over time and benefiting from compounding. For example, a user might set 30% of each trade's profit to reinvest, with the remaining 70% allocated for risk management or additional safety orders. This approach can enhance long-term growth while balancing risk.
Generally in trading it can be a good approach to take profits so we suggest a healthy balance. This setting is generally best used for slow steady strategies with the long term aim of accumulating as much of the asset as possible.
5. Leverage and Position Sizing
Users can configure leverage and position sizing to simulate varying risk levels and capital allocations. A dashboard on the interface displays margin requirements based on the selected leverage, allowing traders to estimate trade sizes relative to their available capital. Whenever using leverage especially with layered entries it’s important to keep a close eye on the position sizes to avoid potential liquidations.
6. Pre-Configured Strategies for Immediate Testing
For users seeking a starting point, ChartPrime includes a range of preset strategies. These were developed and backtested by ChartPrime’s team. This allows traders to start with a stable base and adapt it to their own preferences. It is vital to understand that historical performance doesn't guarantee future success, and traders should be mindful of overfitting. These pre-built configurations offer a structured way and base to design strategies off of. These are also subject to changing results as new price action arrives and they become outdated. They serve the purpose of simply being example use cases.
7. In-Depth Specific Backtesting Ranges
The Strategy Builder includes backtesting capabilities, providing a clear view of how different setups would have performed over specified time periods. Traders can select date ranges to target specific market conditions, then review results on TradingView to see how their strategies perform across different market trends.
Example Use Case: Developing a Strategy
Consider a trader who is focused on long positions only and prefers a lower-risk strategy (note these tools can be used for all assets; we are using an undisclosed asset as an example). Using the Strategy Builder, they could:
- Disable short conditions.
- Set long entry rules to trigger when both the ChartPrime oscillator and Quantum Reactor indicators show bullish signals.
- Enable layered entries to improve average entry prices by adding to positions during market dips.
- Run a backtest over a two-year period to see historical performance trends, making adjustments as needed.
The backtest will show where entries and exits would have occurred and how layered entries may have impacted profitability.
8. Iterative design
Strategy builders and creating a strategy is often an iterative process. By experimenting and using logic; a trader can arrive at a more sustainable system. Analyzing the shortcomings of your strategy and iteratively designing and filtering them out is the goal. For example; let’s say a strategy has high drawdown, a user would want to tighten stop losses for example to reduce this and find a balance point between optimizing winning trades and reducing the drawdown. When designing a strategy there are generally tradeoffs and optimizing taking into consideration a wide range of factors is key. This also applies to filtering techniques, entries and exits and every variable in the strategy.
Let’s say a strategy was taking too many long positions in a downtrend and after you’ve analyzed the data, you come to the conclusion this needs to be solved. Filtering these using built in trend following tools can be a great approach and refining with logic is a great approach.
The Strategy Builder also takes into consideration those who seek to automate especially via reinvesting and leverage features.
Considerations
The ChartPrime Strategy Builder aims to help traders build clear, rule-based strategies without excessive complexity. As with all backtesting tools, it's crucial to understand that historical performance doesn't guarantee future success, and traders should be mindful of overfitting. This tool offers a structured way to test strategies against various market conditions, helping traders refine their approaches with data-driven insights. Traders should also ensure they enter the correct fees when designing strategies and ensure usage on standard candle types.
Dual MACD Strategy [Js.k]Strategy Overview
The Dual MACD Strategy leverages two MACD indicators with different parameters to generate buy and sell signals. By combining the trend-following properties of MACD with specific entry/exit criteria, this strategy aims to capture significant price movements while effectively managing risk.
Entry and Exit Conditions
Long Entry: A buy signal is triggered when:
The histogram of MACD1 crosses above zero.
The histogram of MACD2 is positive and rising.
Short Entry: A sell signal is triggered when:
The histogram of MACD1 crosses below zero.
The histogram of MACD2 is negative and declining.
Risk Management
Stop Loss and Take Profit:
Stop Loss is set at 1% below the entry price for long positions and 1% above the entry price for short positions.
Take Profit is set at 1.5% above the entry price for long positions and 1.5% below the entry price for short positions.
Position Sizing: Each trade risks a maximum of 10% of account equity, keeping potential losses manageable and in line with standard trading practices.
Backtesting Results
The strategy is tested on BTCUSDT with a time frame of 1 hour, resulting in 200+ trades.
The initial capital for backtesting is set to $10,000, with a realistic commission of 0.04% and a slippage of 2 ticks.
Conclusion
This strategy is inspired by Dreadblitz's Double MACD Buy and Sell, as well as some YouTube videos. My purpose in redeveloping them into this strategy is to validate the practicality of the Double MACD. After multiple modifications, this is the final version. I believe its profitability is limited and may lead to losses; please do not use this strategy for live trading.
NY Opening Range Breakout - MA StopCore Concept
This strategy trades breakouts from the New York opening range (9:30-9:45 AM NY time) on intraday timeframes, designed for scalping and day trading.
Setup Requirements
Timeframe: Works on any timeframe under 15 minutes (1m, 2m, 3m, 5m, 10m)
Session: New York market hours
Range Period: 9:30-9:45 AM NY time (15-minute opening range)
Entry Rules
Long Entries:
Wait for a candle to close above the opening range high
Enter long on the next candle (before 12:00 PM NY time)
Must be above moving average if using MA-based take profit
Short Entries:
Wait for a candle to close below the opening range low
Enter short on the next candle (before 12:00 PM NY time)
Must be below moving average if using MA-based take profit
Risk Management
Stop Loss:
Long trades: Opening range low
Short trades: Opening range high
Take Profit Options:
Fixed Risk Reward: 1.5x the range size (customizable ratio)
Moving Average: Exit when price crosses back through MA
Both: Whichever comes first
Key Features
Trade Direction Options:
Long Only
Short Only
Both directions
Moving Average Filter:
Prevents entries that would immediately hit stop loss
Uses EMA/SMA/WMA/VWMA with customizable length
Acts as dynamic support/resistance
Time Restrictions:
No entries after 12:00 PM NY time (customizable cutoff)
One trade per direction per day
Daily reset of all variables
Visual Elements
Red/green lines showing opening range
Purple line for moving average
Entry and breakout signals with shapes
Take profit and stop loss levels plotted
Information table with current status
Strategy Logic Flow
Morning: Capture 9:30-9:45 range high/low
Wait: Monitor for breakout (previous candle close outside range)
Filter: Check MA condition if using MA-based exits
Enter: Trade on next candle after breakout
Manage: Exit at fixed TP, MA cross, or stop loss
Reset: Start fresh next trading day
This is a momentum-based breakout strategy that capitalizes on early market volatility while using the opening range as natural support/resistance levels.
Gold Breakout Strategy - RR 4Strategy Name: Gold Breakout Strategy - RR 4
🧠 Main Objective
This strategy aims to capitalize on breakouts from the Donchian Channel on Gold (XAU/USD) by filtering trades with:
Volume confirmation,
A custom momentum indicator (LWTI - Linear Weighted Trend Index),
And a specific trading session (8 PM to 8 AM Quebec time — GMT-5).
It takes only one trade per day, either a buy or a sell, using a fixed stop-loss at the wick of the breakout candle and a 4:1 reward-to-risk (RR) ratio.
📊 Indicators Used
Donchian Channel
Length: 96
Detects breakouts of recent highs or lows.
Volume
Simple Moving Average (SMA) over 30 bars.
A breakout is only valid if the current volume is above the SMA.
LWTI (Linear Weighted Trend Index)
Measures momentum using price differences over 25 bars, smoothed over 5.
Used to confirm trend direction:
Buy when LWTI > its smoothed version (uptrend).
Sell when LWTI < its smoothed version (downtrend).
⏰ Time Filter
The strategy only allows entries between 8 PM and 8 AM (GMT-5 / Quebec time).
A timestamp-based filter ensures the system recognizes the correct trading session even across midnight.
📌 Entry Conditions
🟢 Buy (Long)
Price breaks above the previous Donchian Channel high.
The current channel high is higher than the previous one.
Volume is above its moving average.
LWTI confirms an uptrend.
The time is within the trading session (20:00 to 08:00).
No trade has been taken yet today.
🔴 Sell (Short)
Price breaks below the previous Donchian Channel low.
The current channel low is lower than the previous one.
Volume is above its moving average.
LWTI confirms a downtrend.
The time is within the trading session.
No trade has been taken yet today.
💸 Trade Management
Stop-Loss (SL):
For long entries: placed below the wick low of the breakout candle.
For short entries: placed above the wick high of the breakout candle.
Take-Profit (TP):
Set at a fixed 4:1 reward-to-risk ratio.
Calculated as 4x the distance between the entry price and stop-loss.
No trailing stop, no break-even, no scaling in/out.
🎨 Visuals
Green triangle appears below the candle on a buy signal.
Red triangle appears above the candle on a sell signal.
Donchian Channel lines are plotted on the chart.
The strategy is designed for the 5-minute timeframe.
🔄 One Trade Per Day Rule
Once a trade is taken (buy or sell), no more trades will be executed for the rest of the day. This prevents overtrading and limits exposure.
SuperTrade ST1 StrategyOverview
The SuperTrade ST1 Strategy is a long-only trend-following strategy that combines a Supertrend indicator with a 200-period EMA filter to isolate high-probability bullish trade setups. It is designed to operate in trending markets, using volatility-based exits with a strict 1:4 Risk-to-Reward (R:R) ratio, meaning that each trade targets a profit 4× the size of its predefined risk.
This strategy is ideal for traders looking to align with medium- to long-term trends, while maintaining disciplined risk control and minimal trade frequency.
How It Works
This strategy leverages three key components:
Supertrend Indicator
A trend-following indicator based on Average True Range (ATR).
Identifies bullish/bearish trend direction by plotting a trailing stop line that moves with price volatility.
200-period Exponential Moving Average (EMA) Filter
Trades are only taken when the price is above the EMA, ensuring participation only during confirmed uptrends.
Helps filter out counter-trend entries during market pullbacks or ranges.
ATR-Based Stop Loss and Take Profit
Each trade uses the ATR to calculate volatility-adjusted exit levels.
Stop Loss: 1× ATR below entry.
Take Profit: 4× ATR above entry (1:4 R:R).
This asymmetry ensures that even with a lower win rate, the strategy can remain profitable.
Entry Conditions
A long trade is triggered when:
Supertrend flips from bearish to bullish (trend reversal).
Price closes above the Supertrend line.
Price is above the 200 EMA (bullish market bias).
Exit Logic
Once a long position is entered:
Stop loss is set 1 ATR below entry.
Take profit is set 4 ATR above entry.
The strategy automatically exits the position on either target.
Backtest Settings
This strategy is configured for realistic backtesting, including:
$10,000 account size
2% equity risk per trade
0.1% commission
1 tick slippage
These settings aim to simulate real-world conditions and avoid overly optimistic results.
How to Use
Apply the script to any timeframe, though higher timeframes (1H, 4H, Daily) often yield more reliable signals.
Works best in clearly trending markets (especially in crypto, stocks, indices).
Can be paired with alerts for live trading or analysis.
Important Notes
This version is long-only by design. No short positions are executed.
Ideal for swing traders or position traders seeking asymmetric returns.
Users can modify the ATR period, Supertrend factor, or EMA filter length based on asset behavior.
Funding Rate Strategy IndicatorDescription
Funding Rate Backtest Strategy uses smoothed funding‐rate dynamics to trigger long/short trades, enhanced by volume, session and daily‐limit filters, plus configurable profit-taking, stop-loss and trailing stops. It is designed for perpetual‐swap markets (e.g. BTCUSDT) where funding costs reflect market sentiment.
1. Strategy Logic & Components
Funding Rate Source
External: real exchange funding rate (e.g. Binance funding).
Custom: manual override value.
Simulate: sine‐wave test data between –3 and +3 to validate behavior.
Entry Conditions
LONG when fundingRate ≤ Long Threshold (default –2.0)
SHORT when fundingRate ≥ Short Threshold (default +2.0)
Volume Filter: requires a ≥ 5% increase vs prior bar.
4H Session Filter: only triggers on new 4-hour bars (optional).
Daily Cap: max 5 signals per calendar day (prevents overtrading).
Weekend Trading: on/off toggle for Saturday–Sunday.
Exit Conditions
Funding Normalization: exit LONG when fundingRate > –0.5; exit SHORT when fundingRate < +0.5.
Profit-Taking & Stop-Loss: default TP = 5%, SL = 3% of entry price.
Trailing Stop: optional 2% trailing (togglable).
2. Default Settings & Backtest Parameters
Account Size: $10,000
Position Sizing: 10% of equity per trade
Commission: 0.10% per side
Slippage: 0.05% per trade
Instrument & Timeframe: BTCUSDT perpetual, 1H bars, Jan 1 2022 – Dec 31 2023
Volume Increase: 5%
Session Filter: 4-hour bars only
Max Signals/Day: 5
Weekend Trading: Enabled
3. Backtest Results (Jan 2022–Dec 2023)
Total Trades: 142
Win Rate: 55.6%
Average R/R: 1 : 1.4
Max Drawdown: 14.8%
Net Return: +22.3%
These results assume realistic commission (0.1%) and slippage (0.05%). Past performance is not indicative of future results.
4. Default Properties Explained
Property Default Description
rateSourceChoice External Select funding‐rate data source
fundingRateLongThreshold –2.0 Funding ≤ –2% → LONG condition
fundingRateShortThreshold +2.0 Funding ≥ +2% → SHORT condition
volumeIncreasePercent 5.0 Min % volume increase vs prior bar
enableFourHourFilter true Only trigger on new 4H sessions
maxSignalsPerDay 5 Daily cap on entries
exitLongThreshold –0.5 Funding > –0.5% → exit LONG
exitShortThreshold +0.5 Funding < +0.5% → exit SHORT
takeProfitPercent 5.0 Fixed profit target in %
stopLossPercent 3.0 Fixed stop‐loss in %
useTrailingStop false Toggle trailing stop
trailingStopPercent 2.0 Trailing stop distance in %
allowWeekendTrading true Allow entries on Sat/Sun
5. How to Use
Add to Chart → search “Funding Rate Backtest.”
Configure Inputs → choose your funding‐rate feed, adjust thresholds, volume and session filters.
Position Sizing → defaults to 10% equity; adjust if desired.
Monitor Table & Signals → on‐chart shapes mark entries/exits; status table shows open P&L and signals count.
Risk Management → always verify commission/slippage settings; limit risk to sustainable levels (≤ 10% equity per trade).
6. Warnings & Disclaimer
This strategy is for educational purposes only. Real funding rates may differ—replace simulation or custom inputs with actual data. Always apply your own analysis and risk management. Past backtest performance does not guarantee future results.
