ZEMA Crossover Strategy with Volume & ATR FiltersThis strategy is based on the crossover of two ZEMAs (Zero-Lag Exponential Moving Averages) with additional filters for volume and ATR to confirm signals. It automatically opens long ("Long") and short ("Short") positions and sets stop-loss and take-profit levels based on ATR.
Long Position ("Long"): Opens when ZEMA1 crosses above ZEMA2, volume exceeds the threshold (if filter is enabled), and ATR is above its SMA (if filter is enabled).
Short Position ("Short"): Opens when ZEMA1 crosses below ZEMA2, with the same filter conditions.
Stop-Loss and Take-Profit: Automatically set based on the current ATR value. For example, with a multiplier of 2.0, the stop-loss is 2×ATR from the entry price.
ZEMA lines are plotted on the chart: green (ZEMA1) and red (ZEMA2). The area between them is filled with color (green for bullish, red for bearish).
Medie mobili
BigBarChaser 1 MIN TrailingBigBarCahser 1MIN Trailing (ES & YM)
The BigBarChaser 1MIN is an adaptive breakout and trend-following strategy designed for the E-mini S&P 500 (ES) and Dow Jones (YM) on a 1-minute chart. Unlike rigid breakout systems, this strategy allows trades to develop and run as long as the trend remains intact, maximizing profit potential while accepting a higher number of losing trades.
How It Works
✅ Momentum-Based Entries: Uses a more flexible set of conditions to identify breakout and trend continuation opportunities.
✅ Trend Following: Instead of setting a fixed take-profit level, trades are managed dynamically, staying open as long as the trend remains strong.
✅ Trailing Stop-Loss on SMA12: Risk is managed through a 12-period simple moving average (SMA12) trailing stop, ensuring trades stay open during strong trends and exit when momentum weakens.
✅ Higher Risk, Higher Reward: Accepts a greater number of small losses but relies on long-running profitable trades to cover and exceed them.
✅ Multi-Market Application: Optimized for both ES (S&P 500 E-mini) and YM (Dow Jones E-mini), making it versatile across major indices.
✅ Position Sizing: Backtesting results are based on trading 1 ES contract, demonstrating realistic performance over longer periods.
Performance
✅ The strategy has shown strong profitability over extended backtesting periods, even with more frequent losing trades.
✅ Trend-capturing ability allows for major winners that significantly outweigh smaller losses.
✅ Designed for traders who prefer to let winners run rather than take fixed profit targets.
How to Use It
✅ The script automatically executes trades based on trend confirmation—no manual input is required.
✅ No fixed take-profit levels—trades are exited when the SMA12 trailing stop is hit.
✅ Best suited for traders comfortable with higher risk and trade frequency in exchange for higher reward potential.
Disclaimer
"This strategy is a trading tool designed for traders seeking structured breakout and trend-following setups. While it follows a defined approach, trading involves risk, and there are no guarantees of profitability. Past performance does not guarantee future results. Users are responsible for their own trading decisions and should conduct thorough research before using this strategy in live markets. This is not financial advice."
BigBarChaser v2 ES 2minBigBarChaser v2 ES 2min
The BigBarChaser v2 is a straightforward, conservative breakout trading strategy designed for the E-mini S&P 500 (ES) on a 2-minute chart. It focuses on capturing momentum-based breakouts following a period of consolidation, using strict trade criteria to filter out low-probability setups.
How It Works
✅ Breakout Confirmation: Trades are only taken when a bar closes with significant strength relative to its range, confirming a strong directional move.
✅ Sideways Market Filter: The strategy ensures that breakouts occur after a period of reduced volatility, avoiding false signals in choppy conditions.
✅ Trend Alignment: A combination of moving averages helps confirm overall market direction, filtering out counter-trend trades.
✅ Fixed Risk Management: The stop-loss is set at 67% of the entry point, while take-profit levels are dynamically calculated based on market volatility.
✅ Market Hours Optimization: Trades are executed only within specific trading hours to maintain efficiency and avoid illiquid periods.
✅ Position Sizing: Backtested results are based on trading 1 ES contract, ensuring realistic performance that is achievable for any trader.
Performance
✅ The strategy has shown consistently positive results in backtesting, demonstrating strong potential in real-market conditions.
✅ Risk is managed through fixed stop-loss levels and a volatility-adjusted take-profit mechanism.
✅ The method is designed to be accessible to traders of all levels, without requiring excessive capital or complex trade management.
How to Use It
✅ The script automatically executes trades based on predefined conditions—no user input is required.
✅ Signals are plotted on the chart for visual reference.
✅ All risk management settings, including stop-loss and take-profit, are fixed to ensure a structured approach.
Disclaimer
"This strategy is a trading tool designed for traders seeking structured breakout setups. While it follows a defined approach, trading involves risk, and there are no guarantees of profitability. Past performance does not guarantee future results. Users are responsible for their own trading decisions and should conduct thorough research before using this strategy in live markets. This is not financial advice."
Gold(1-10), Oil(1-3,45)fRS**Deskripsi Metode Script:**
Script ini adalah strategi trading yang dirancang untuk digunakan di platform TradingView dengan menggunakan bahasa Pine Script (versi 5). Fokus dari strategi ini adalah untuk mengidentifikasi titik masuk dan keluar berdasarkan indikator teknikal, termasuk Bollinger Bands (BB), Exponential Moving Average (EMA), Average True Range (ATR), dan fitur stop loss (SL) serta take profit (TP).
Berikut adalah penjelasan dari setiap bagian dan fungsi dalam script ini:
### 1. **Parameter Input:**
- **BB Length:** Panjang periode untuk Bollinger Bands (default: 20).
- **BB Multiplier:** Multiplier untuk deviasi standar Bollinger Bands (default: 1.9).
- **EMA Length:** Panjang periode untuk Exponential Moving Average (default: 68).
- **Use EMA Filter:** Pilihan untuk menggunakan filter EMA untuk menentukan tren pasar.
- **Use ATR for SL/TP:** Pilihan untuk menggunakan ATR dalam perhitungan level Stop Loss (SL) dan Take Profit (TP).
- **ATR Multiplier for SL:** Multiplier ATR yang digunakan untuk menghitung jarak SL (default: 2.75).
- **Stop Loss %:** Persentase dari harga saat ini yang digunakan untuk menghitung nilai Stop Loss (default: 2.75%).
- **Risk-Reward Ratio:** Rasio risiko-imbalan untuk menentukan TP (default: 1.75).
- **Use TSL:** Pilihan untuk menggunakan Trailing Stop Loss.
- **Trailing Stop ATR Multiplier:** Multiplier ATR yang digunakan untuk menentukan Trailing Stop Loss.
### 2. **Indikator Bollinger Bands (BB):**
- **Basis:** Menggunakan Simple Moving Average (SMA) dengan periode yang ditentukan oleh input `BB Length` sebagai basis Bollinger Bands.
- **Deviasi:** Deviasi standar dari harga penutupan selama periode `BB Length`, yang kemudian dikalikan dengan `BB Multiplier` untuk menentukan jarak atas dan bawah Bollinger Bands.
- **UpperBB dan LowerBB:** Menghitung level atas dan bawah dari Bollinger Bands berdasarkan basis dan deviasi.
### 3. **Filter Tren (EMA):**
- **EMA:** Exponential Moving Average dihitung berdasarkan periode `EMA Length`.
- **Trend Bullish:** Jika harga penutupan berada di atas EMA, tren dianggap bullish (naik).
- **Trend Bearish:** Jika harga penutupan berada di bawah EMA, tren dianggap bearish (turun).
### 4. **Kondisi Masuk (Entry Signal):**
- **Long Condition:** Didefinisikan sebagai crossover harga penutupan dengan Lower Bollinger Band (BB) dan tren pasar mendukung sinyal bullish, berdasarkan EMA.
- **Short Condition:** Didefinisikan sebagai crossunder harga penutupan dengan Upper Bollinger Band (BB) dan tren pasar mendukung sinyal bearish, berdasarkan EMA.
- **Alert:** Dikirimkan saat kondisi Long atau Short terpenuhi.
### 5. **Stop Loss dan Take Profit (SL/TP):**
- **ATR:** Menghitung ATR dengan periode 14 untuk mengukur volatilitas pasar.
- **SL (Stop Loss):** Dihitung berdasarkan ATR dikalikan dengan multiplier `ATR Multiplier`, atau berdasarkan persentase harga saat ini menggunakan `Stop Loss %`.
- **TP (Take Profit):** Dihitung berdasarkan rasio Risk-Reward yang ditentukan (`RiskRewardRatio`), yaitu 1.75 kali jarak Stop Loss.
- **Level SL dan TP:** Untuk posisi long, SL berada di bawah harga saat ini, dan TP berada di atas harga saat ini. Untuk posisi short, SL berada di atas harga saat ini, dan TP berada di bawah harga saat ini.
### 6. **Trailing Stop Loss (TSL):**
- **Trailing Stop:** Jika `UseTSL` diaktifkan, Trailing Stop dihitung berdasarkan ATR yang dikalikan dengan `Trailing Stop ATR Multiplier`. Trailing Stop ini bergerak seiring dengan pergerakan harga untuk melindungi keuntungan yang sudah terakumulasi.
### 7. **Alert untuk TP dan SL:**
- **Alert Condition:** Kondisi untuk memberikan alert ketika harga menembus level Take Profit (TP) atau Stop Loss (SL).
### 8. **Teks dan Label Konfirmasi di Chart:**
- **Label BUY/SELL:** Ketika kondisi long atau short terpenuhi, label akan muncul di chart yang menampilkan harga saat entry, level Stop Loss, dan level Take Profit.
- **Label SL dan TP:** Menampilkan level Stop Loss dan Take Profit yang terkait dengan posisi tersebut.
### **Kesimpulan:**
Strategi ini memanfaatkan indikator teknikal seperti Bollinger Bands untuk menentukan titik masuk dan keluar berdasarkan volatilitas pasar, serta EMA untuk menilai arah tren. Sistem ini menggunakan ATR untuk menetapkan level Stop Loss dan Take Profit yang adaptif terhadap volatilitas pasar dan menawarkan opsi Trailing Stop Loss untuk mengamankan keuntungan. Alert akan dikirimkan saat kondisi entry atau exit terjadi, membantu trader dalam pengambilan keputusan secara otomatis.
Oil FRS 30/60### Deskripsi Metode "Oil FRS 30/60"
**Metode "Oil FRS 30/60"** adalah sebuah strategi trading yang memanfaatkan **Stochastic Oscillator** pada dua timeframe yang berbeda (misalnya 30 menit dan 60 menit) untuk menghasilkan sinyal beli dan jual pada pasar minyak. Strategi ini dirancang untuk mengidentifikasi kondisi overbought (jenuh beli) atau oversold (jenuh jual) dengan memanfaatkan indikator teknikal untuk memberikan sinyal yang lebih akurat berdasarkan konfirmasi dari dua timeframe yang berbeda. Berikut adalah penjelasan lebih mendalam mengenai komponen dan cara kerja strategi ini:
### 1. **Indikator Stochastic Oscillator**
- **Stochastic Oscillator** adalah indikator momentum yang digunakan untuk menunjukkan kondisi overbought (jenuh beli) atau oversold (jenuh jual) pada harga suatu aset. Indikator ini terdiri dari dua komponen utama:
- **%K**: Menunjukkan posisi harga relatif terhadap rentang harga selama periode tertentu.
- **%D**: Merupakan rata-rata dari %K dan digunakan untuk menghaluskan sinyal.
- Dalam strategi ini, **Stochastic Oscillator** dihitung dengan periode **K Length** dan **D Length**, kemudian disaring menggunakan **Smooth K** untuk mendapatkan sinyal yang lebih halus.
### 2. **Penggunaan Dua Timeframe**
- **Timeframe Utama**: Menggunakan Stochastic Oscillator pada timeframe yang lebih rendah (misalnya, 30 menit) untuk mendapatkan sinyal trading yang lebih sensitif dan cepat.
- **Timeframe Lebih Tinggi (Higher Timeframe)**: Untuk mengonfirmasi sinyal dari timeframe utama, digunakan **Stochastic Oscillator** pada timeframe yang lebih tinggi (misalnya, 60 menit). Konfirmasi dari timeframe yang lebih tinggi membantu mengurangi kemungkinan sinyal palsu dan memastikan bahwa posisi yang diambil sesuai dengan tren yang lebih besar.
### 3. **Kondisi Sinyal Beli dan Jual**
- **Sinyal Beli (Buy Condition)**:
- **Crossover** antara %K dan %D (ketika %K melintasi %D dari bawah ke atas) pada timeframe utama.
- Nilai **%K** di bawah 20 (menunjukkan kondisi oversold).
- Pada timeframe lebih tinggi, **%K** juga harus berada di bawah 20 dan **%K** harus lebih tinggi dari **%D**, yang menunjukkan kemungkinan pembalikan arah tren.
- **Sinyal Jual (Sell Condition)**:
- **Crossunder** antara %K dan %D (ketika %K melintasi %D dari atas ke bawah) pada timeframe utama.
- Nilai **%K** di atas 80 (menunjukkan kondisi overbought).
- Pada timeframe lebih tinggi, **%K** harus berada di atas 80 dan **%K** harus lebih rendah dari **%D**, yang menunjukkan potensi pembalikan tren ke bawah.
### 4. **Manajemen Risiko: Take Profit dan Stop Loss**
- **Take Profit (TP)** dan **Stop Loss (SL)** ditentukan berdasarkan persentase dari harga saat ini.
- **Take Profit**: Level keuntungan ditentukan dengan mengalikan harga saat ini dengan faktor pengali TP (misalnya, 2.4% lebih tinggi dari harga saat ini untuk posisi beli).
- **Stop Loss**: Level kerugian ditentukan dengan mengalikan harga saat ini dengan faktor pengali SL (misalnya, 1.7% lebih rendah dari harga saat ini untuk posisi beli).
- Dengan demikian, manajemen risiko yang baik diterapkan untuk melindungi modal dan mengoptimalkan keuntungan.
### 5. **Visualisasi dan Labeling**
- **Sinyal Beli dan Jual** ditandai pada chart dengan label yang menunjukkan **BUY** atau **SELL**.
- **Level TP dan SL** digambarkan dengan garis putus-putus yang menunjukkan posisi keuntungan dan kerugian yang diinginkan.
- **Bar Color** juga diubah menjadi hijau untuk sinyal beli dan merah untuk sinyal jual untuk memudahkan visualisasi.
### 6. **Keunggulan Metode Ini**
- **Konfirmasi dari Dua Timeframe**: Penggunaan dua timeframe membantu memastikan bahwa sinyal yang dihasilkan lebih valid, mengurangi kemungkinan sinyal palsu dan meningkatkan keakuratan dalam pengambilan keputusan.
- **Strategi Momentum**: Dengan menggunakan indikator Stochastic, strategi ini mengandalkan identifikasi kondisi jenuh beli atau jenuh jual, yang sering kali menunjukkan potensi pembalikan arah harga.
- **Manajemen Risiko yang Jelas**: Dengan adanya level TP dan SL yang dinamis, trader dapat dengan mudah mengontrol risiko dan mengatur target keuntungan.
### 7. **Cocok Untuk Apa?**
- **Minyak (Oil)**: Metode ini dirancang khusus untuk pasar minyak, karena harga minyak cenderung mengalami fluktuasi yang cepat dan seringkali terpengaruh oleh berita ekonomi dan politik. Oleh karena itu, penggunaan dua timeframe untuk konfirmasi sinyal menjadi sangat penting.
- **Trader Jangka Pendek hingga Menengah**: Strategi ini cocok untuk trader yang lebih suka melakukan trading dalam jangka pendek hingga menengah (scalping atau swing trading), dengan memanfaatkan pergerakan harga yang cepat dalam timeframe rendah dan tinggi.
### Kesimpulan
Strategi **Oil FRS 30/60** mengombinasikan indikator teknikal Stochastic Oscillator pada dua timeframe berbeda untuk memberikan sinyal beli dan jual yang lebih akurat. Dengan konfirmasi dari timeframe lebih tinggi dan pengaturan manajemen risiko yang baik melalui Take Profit dan Stop Loss, strategi ini dirancang untuk meminimalkan risiko dan memaksimalkan potensi keuntungan dalam trading minyak.
Adaptive Pivot FlowСтратегия Adaptive Pivot Flow использует комбинацию уровней pivot и скользящих средних для определения тренда и поиска точек входа. Торговые сигналы формируются на основе пересечений ценой ключевых уровней и положения относительно МА
Custom MACrossOverLorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.
TEMA OBOS Strategy PakunTEMA OBOS Strategy
Overview
This strategy combines a trend-following approach using the Triple Exponential Moving Average (TEMA) with Overbought/Oversold (OBOS) indicator filtering.
By utilizing TEMA crossovers to determine trend direction and OBOS as a filter, it aims to improve entry precision.
This strategy can be applied to markets such as Forex, Stocks, and Crypto, and is particularly designed for mid-term timeframes (5-minute to 1-hour charts).
Strategy Objectives
Identify trend direction using TEMA
Use OBOS to filter out overbought/oversold conditions
Implement ATR-based dynamic risk management
Key Features
1. Trend Analysis Using TEMA
Uses crossover of short-term EMA (ema3) and long-term EMA (ema4) to determine entries.
ema4 acts as the primary trend filter.
2. Overbought/Oversold (OBOS) Filtering
Long Entry Condition: up > down (bullish trend confirmed)
Short Entry Condition: up < down (bearish trend confirmed)
Reduces unnecessary trades by filtering extreme market conditions.
3. ATR-Based Take Profit (TP) & Stop Loss (SL)
Adjustable ATR multiplier for TP/SL
Default settings:
TP = ATR × 5
SL = ATR × 2
Fully customizable risk parameters.
4. Customizable Parameters
TEMA Length (for trend calculation)
OBOS Length (for overbought/oversold detection)
Take Profit Multiplier
Stop Loss Multiplier
EMA Display (Enable/Disable TEMA lines)
Bar Color Change (Enable/Disable candle coloring)
Trading Rules
Long Entry (Buy Entry)
ema3 crosses above ema4 (Golden Cross)
OBOS indicator confirms up > down (bullish trend)
Execute a buy position
Short Entry (Sell Entry)
ema3 crosses below ema4 (Death Cross)
OBOS indicator confirms up < down (bearish trend)
Execute a sell position
Take Profit (TP)
Entry Price + (ATR × TP Multiplier) (Default: 5)
Stop Loss (SL)
Entry Price - (ATR × SL Multiplier) (Default: 2)
TP/SL settings are fully customizable to fine-tune risk management.
Risk Management Parameters
This strategy emphasizes proper position sizing and risk control to balance risk and return.
Trading Parameters & Considerations
Initial Account Balance: $7,000 (adjustable)
Base Currency: USD
Order Size: 10,000 USD
Pyramiding: 1
Trading Fees: $0.94 per trade
Long Position Margin: 50%
Short Position Margin: 50%
Total Trades (M5 Timeframe): 128
Deep Test Results (2024/11/01 - 2025/02/24)BTCUSD-5M
Total P&L：+1638.20USD
Max equity drawdown：694.78USD
Total trades：128
Profitable trades:44.53
Profit factor:1.45
These settings aim to protect capital while maintaining a balanced risk-reward approach.
Visual Support
TEMA Lines (Three EMAs)
Trend direction is indicated by color changes (Blue/Orange)
ema3 (short-term) and ema4 (long-term) crossover signals potential entries
OBOS Histogram
Green → Strong buying pressure
Red → Strong selling pressure
Blue → Possible trend reversal
Entry & Exit Markers
Blue Arrow → Long Entry Signal
Red Arrow → Short Entry Signal
Take Profit / Stop Loss levels displayed
Strategy Improvements & Uniqueness
This strategy is based on indicators developed by "l_lonthoff" and "jdmonto0", but has been significantly optimized for better entry accuracy, visual clarity, and risk management.
Enhanced Trend Identification with TEMA
Detects early trend reversals using ema3 & ema4 crossover
Reduces market noise for a smoother trend-following approach
Improved OBOS Filtering
Prevents excessive trading
Reduces unnecessary risk exposure
Dynamic Risk Management with ATR-Based TP/SL
Not a fixed value → TP/SL adjusts to market volatility
Fully customizable ATR multiplier settings
(Default: TP = ATR × 5, SL = ATR × 2)
Summary
The TEMA + OBOS Strategy is a simple yet powerful trading method that integrates trend analysis and oscillators.
TEMA for trend identification
OBOS for noise reduction & overbought/oversold filtering
ATR-based TP/SL settings for dynamic risk management
Before using this strategy, ensure thorough backtesting and demo trading to fine-tune parameters according to your trading style.
EMA 5 Alert Candle ShortThe 5 EMA (Exponential Moving Average) Strategy is a simple yet effective trading strategy that helps traders identify short-term trends and potential entry and exit points. This strategy is widely used in intraday and swing trading, particularly in forex, stocks, and crypto markets.
Components of the 5 EMA Strategy
5 EMA: A fast-moving average that reacts quickly to price movements.
15-minute or 1-hour timeframe (commonly used, but adaptable to other timeframes).
Candlestick Patterns: To confirm entry signals.
How the 5 EMA Strategy Works
Buy (Long) Setup:
Price Above the 5 EMA: The price should be trading above the 5 EMA.
Pullback to the 5 EMA: A minor retracement or consolidation near the 5 EMA.
Bullish Candlestick Confirmation: A bullish candle (e.g., engulfing or pin bar) forms near the 5 EMA.
Entry: Enter a long trade at the close of the bullish candle.
Stop Loss: Place below the recent swing low or 5-10 pips below the 5 EMA.
Take Profit: Aim for a risk-reward ratio of at least 1:2 or trail the stop using a higher EMA (e.g., 10 or 20 EMA).
Sell (Short) Setup:
Price Below the 5 EMA: The price should be trading below the 5 EMA.
Pullback to the 5 EMA: A small retracement towards the 5 EMA.
Bearish Candlestick Confirmation: A bearish candle (e.g., engulfing or pin bar) near the 5 EMA.
Entry: Enter a short trade at the close of the bearish candle.
Stop Loss: Place above the recent swing high or 5-10 pips above the 5 EMA.
Take Profit: Aim for a 1:2 risk-reward ratio or use a trailing stop.
Additional Filters for Better Accuracy
Higher Timeframe Confirmation: Check the trend on a higher timeframe (e.g., 1-hour or 4-hour).
Volume Confirmation: Enter trades when volume is increasing.
Avoid Sideways Market: Use the strategy only when the market is trending.
Advantages of the 5 EMA Strategy
✔️ Simple and easy to use.
✔️ Works well in trending markets.
✔️ Helps traders capture short-term momentum.
Disadvantages
❌ Less effective in choppy or sideways markets.
❌ Requires discipline in following stop-loss rules.
Slark Signal XtremeStrategy Description: Slark Signal Xtreme
The Slark Signal Xtreme is an innovative trading strategy designed to identify and capitalize on market opportunities by leveraging pivots, trend breakouts, and dynamic risk management. This strategy combines day-of-week and time filters with a ticks-based Stop Loss (SL) and Take Profit (TP) system, delivering customized signals and real-time alerts. Ideal for traders seeking a structured and highly customizable approach, Slark Signal Xtreme also incorporates advanced visual tools for efficient trade management.
Key Features:
Pivot- and Breakout-Based Signals: Utilizes pivot detection (highs/lows) combined with an ATR-based slope calculation to pinpoint trend changes and potential entry or exit points.
Dynamic Stop-Loss (SL) and Take-Profit (TP) Levels: Automatically calculates SL and TP based on the entry price and user-defined tick settings, adapting to volatility and optimizing risk management.
Time and Day Filters: Allows you to select specific days of the week and trading sessions during which signals are generated, avoiding low-liquidity periods or unwanted high volatility.
Customizable Risk Management: Lets you define the number of ticks for SL and TP, trading hours, initial capital, pyramiding, and commissions, tailoring the strategy to various risk profiles and assets.
Enhanced Visualization:
- SL and TP Boxes: Displays rectangular boxes on the chart indicating SL and TP levels, streamlining trade management.
- Candle Color Changes: Candles can be colored according to price position relative to pivot lines (bullish, bearish, or neutral).
- Session Highlight: Shades the chart background during the selected trading hours, providing immediate context on when the strategy is active.
Automated Alerts: Generates customizable alerts in TradingView whenever a buy or sell signal is triggered, detailing the timing, instrument, and SL/TP levels.
How the Strategy Works:
Technical Indicator Calculations:
- Pivot High/Low and Slope: Identifies price pivot points and calculates slope (based on ATR) to measure trend strength.
- Time and Day Filters: Signals only trigger within the specified days and hours, helping avoid undesirable market conditions.
Generating Buy and Sell Signals:
- Buy Signal (Long): Activated when price breaks above a downward pivot-based trendline or meets the condition for higher pivots.
- Sell Signal (Short): Activated when price breaks below an upward pivot-based trendline or meets the condition for lower pivots.
- Operation Conditions: Signals are only generated on selected days and during chosen trading hours, avoiding periods of low liquidity or excessive volatility.
Dynamic SL and TP Calculation:
- Stop-Loss (SL) and Take-Profit (TP): Determined by the entry price ± a user-defined number of ticks.
- SL and TP Visualization: Boxes are drawn on the chart from the entry price to SL/TP levels, enabling clear visual reference for trade management.
Order Execution and Alerts:
- Order Execution: When a signal is generated, Slark Signal Xtreme automatically opens a long or short position in TradingView’s backtesting environment.
- Alerts: Customizable alerts can be set up to provide real-time notifications (via TradingView or third-party integrations), offering essential details like instrument, time, SL/TP, etc.
Trade Management and Monitoring:
- Automatic Closure: Each trade is automatically closed upon reaching its SL or TP, ensuring disciplined risk control.
- Trade Summary: TradingView’s built-in reporting tools list all trades with cumulative results, simplifying performance evaluation.
Additional Visualization:
- Candle Coloring by Trend: Candles can be colored bullish, bearish, or neutral based on the pivot-driven trend detection.
- Operational Range Highlighting: The chart background is shaded during the permitted trading hours, clarifying when the strategy is active and enhancing visibility.
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Strategy Properties (Important)
This backtest was conducted in TradingView under the following configuration:
Initial Capital: 1000 USD
Order Size: 10,000 contracts (adjust according to the traded asset)
Commission: 0.05 USD per order
Slippage: 1 tick
Pyramiding: 1 order
Price Verification for Limit Orders: 0 ticks
Recalculate on Every Tick & On Bar Close: Enabled
Bar Magnifier for Backtesting Precision: Enabled
These properties provide a realistic view of the strategy’s performance. However, default parameters may vary depending on each user or market:
Order Size: Should be calculated according to the asset traded and your desired risk level.
Commission and Slippage: Costs can vary by market and instrument; there is no universal default that guarantees realistic results.
All users are strongly recommended to adjust these properties within the script settings to match their own trading accounts and platforms, ensuring the most accurate backtest results.
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Backtesting Results:
- Net Profit: +28.70
- Total Trades: 397
- Winning Trades: 138
- Win Rate: 34.76%
- Profit Factor: 1.07
- Sharpe Ratio: 1.25
- Sortino Ratio: 1.45
- Average Bars per Trade: 24
- Average Profit per Trade: 1.45
These numbers provide an overview of the strategy’s historical performance, demonstrating its potential for profitability given appropriate risk management.
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Interpretation of Results:
- The strategy can be profitable despite a relatively modest win rate, thanks to a suitable risk-reward ratio.
- A profit factor of 1.07 indicates that total profits slightly exceed total losses.
- It is essential to monitor drawdown and ensure it aligns with your personal risk tolerance.
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Risk Warning:
Trading leveraged financial instruments carries a high level of risk and may not be suitable for all investors. Before trading, carefully consider your investment objectives, experience level, and risk tolerance. Past performance does not guarantee future results. Always perform additional testing and adjust the strategy to your specific needs.
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What Makes This Strategy Original?
Focus on Pivots and Time/Day Filters: Rather than purely relying on momentum indicators, Slark Signal Xtreme uses pivot-based signals and scheduling filters to capture higher-liquidity, directional market moves.
Dynamic Risk Management: Ticks-based SL/TP and customizable trading sessions enable precise adaptation to various markets and trading styles.
Advanced Visualization Tools: SL/TP boxes, candle coloring, and session highlights streamline market interpretation and facilitate real-time decision-making.
Seamless Alert Integration: Although native TradingView alerts are provided, it can be integrated with third-party messaging services (Telegram, Discord, etc.) for enhanced automation.
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Additional Considerations
Continuous Testing and Optimization: Regularly backtest and fine-tune parameters (SL, TP, time filters, etc.) to accommodate changing market conditions.
Complementary Analysis: Combine this strategy with other technical or fundamental tools to confirm signals.
Rigorous Risk Management: Ensure SL/TP levels and position sizes conform to your overall risk management plan.
Updates and Support: Future updates and improvements may be released based on community feedback. For questions or suggestions, feel free to reach out.
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Example Configuration
Assume you want to run Slark Signal Xtreme with these settings:
Trading Days: Monday to Friday
Trading Hours: 8:00 to 11:00 (exchange or broker time)
Stop Loss (SL) in Ticks: 100
Take Profit (TP) in Ticks: 300
SL/TP Box Extension: 20 bars
Initial Capital: 1000 USD
Risk per Trade: 1% of capital
Commissions & Slippage: 0.05 USD commission, 1 tick slippage
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Conclusion
The Slark Signal Xtreme strategy delivers a robust and adaptable solution by merging pivots, time/day filters, flexible risk parameters, and advanced visualization. Its distinctive and customizable design makes it a powerful resource for traders aiming to diversify their methods and exploit trend breakouts under specific conditions. Fully compatible with TradingView, Slark Signal Xtreme can enhance your trading toolkit and foster a more systematic approach to your operations.
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Final Disclaimer:
Financial markets are inherently volatile and pose significant risks. This strategy should be employed as part of a comprehensive trading plan and does not guarantee positive outcomes. Always consult a qualified financial advisor before making investment decisions. The use of Slark Signal Xtreme is solely at the user’s discretion, who must evaluate personal risk tolerance and financial objectives.
IBS (Internal Bar Strength) Trading Strategy for SPY and NDQImplementation by AlgoTradeKit
Overview
The IBS Trading Strategy is a daily bars long-only trading system, based on the concept of Internal Bar Strength (IBS). The strategy aims to identify potential reversals by monitoring how the previous bar’s close positions itself within its high-low range. It is suitable for stock and US indices. The default parameters are optimized for SPY/SPX and NDQ/QQQ
Strategy Concept
The Internal Bar Strength (IBS) is calculated using the formula:
IBS = (Previous Close - Previous Low) / (Previous High - Previous Low)
This value always lies between 0 and 1. An IBS value below 0.2 is typically interpreted as an oversold condition, while a value above 0.9 suggests an overbought state.
Trading Rules
- Long Entry :
- Condition 1 : IBS is below the user-defined entry threshold (default is 0.2).
- Condition 2 : The current price is above an N-period Exponential Moving Average (EMA) (default period is 252).
- Note : You can disable the EMA condition by setting the EMA period to 0.
- Long Exit
- The position is closed when IBS rises above the user-defined exit threshold (default is 0.9).
Customization Options
- IBS Entry Threshold : Adjust to set the sensitivity for entering a long trade based on oversold conditions.
- IBS Exit Threshold : Customize to define the exit point when the market becomes overbought.
- EMA Period : Set the lookback period for the EMA to align with your trend bias; disable this condition by setting the period to 0.
Risk Management & Trading Considerations
- Designed for daily charts, the strategy captures higher timeframe trends and minimizes noise.
- The entry and exit conditions are straightforward, aiming to avoid over-trading while letting clear signals dictate trade management.
- Always use proper risk management techniques and test the strategy thoroughly on historical data and in a simulated environment before applying it in live markets.
Disclaimer
This strategy is for educational and informational purposes only and does not constitute financial advice. Trading involves risk, and past performance is not indicative of future results. Always conduct your own research and consider your risk tolerance before making any trades.
Neon Momentum Waves StrategyIntroduction
The Neon Momentum Waves Strategy is a momentum-based indicator designed to help traders visualize potential shifts in market direction. It builds upon a MACD-style calculation while incorporating an enhanced visual representation of momentum waves. This approach may assist traders in identifying areas of increasing or decreasing momentum, potentially aligning with market trends or reversals.
How It Works
This strategy is based on a modified MACD (Moving Average Convergence Divergence) method, calculating the difference between two Exponential Moving Averages (EMAs). The momentum wave represents this difference, while an additional smoothing line (signal line) helps highlight potential momentum shifts.
Key Components:
Momentum Calculation:
Uses a fast EMA (12-period) and a slow EMA (26-period) to measure short-term and long-term momentum.
A signal line (20-period EMA of the MACD difference) smooths fluctuations.
The histogram (momentum wave) represents the divergence between the MACD value and the signal line.
Interpreting Momentum Changes:
Momentum Increasing: When the histogram rises above the zero line, it may indicate strengthening upward movement.
Momentum Decreasing: When the histogram moves below the zero line, it may signal a weakening trend or downward momentum.
Potential Exhaustion Points: Users can define custom threshold levels (default: ±10) to highlight when momentum is significantly strong or weak.
Visual Enhancements:
The neon glow effect is created by layering multiple plots with decreasing opacity, enhancing the clarity of momentum shifts.
Aqua-colored waves highlight upward momentum, while purple waves represent downward momentum.
Horizontal reference lines mark the zero line and user-defined thresholds to improve interpretability.
How It Differs from Traditional Indicators
Improved Visualization: Unlike standard MACD histograms, this approach provides clearer visual cues using a neon-style wave format.
Customizable Thresholds: Rather than relying solely on MACD crossovers, users can adjust sensitivity settings to better suit their trading style.
Momentum-Based Approach: The strategy is focused on visualizing shifts in momentum strength, rather than predicting price movements.
Potential Use Cases
Momentum Trend Awareness: Helps traders identify periods where momentum appears to be strengthening or fading.
Market Structure Analysis: May complement other indicators to assess whether price action aligns with momentum changes.
Flexible Timeframe Application: Can be used across different timeframes, depending on the trader’s strategy.
Important Considerations
This strategy is purely momentum-based and does not incorporate volume, fundamental factors, or price action confirmation.
Momentum shifts do not guarantee price direction changes—they should be considered alongside broader market context.
The strategy may perform differently in trending vs. ranging markets, so adjustments in sensitivity may be needed.
Risk management is essential—traders should apply proper stop-losses and position sizing techniques in line with their risk tolerance.
Conclusion
The Neon Momentum Waves Strategy provides a visually enhanced method of tracking momentum, allowing traders to observe potential changes in market strength. While not a predictive tool, it serves as a complementary indicator that may help traders in momentum-based decision-making. As with any technical tool, it should be used as part of a broader strategy that considers multiple factors in market analysis.
ChronoSync | QuantEdgeB Introducing ChronoSync by QuantEdgeB
🛠️ Overview
ChronoSync is a multi-layered universal strategy designed for adaptability across various assets, timeframes, and market conditions. By integrating five high-quality indicators, it generates a dynamic, aggregated signal that enhances decision-making and optimizes performance in trending and mean-reverting environments.
📊 Key Strengths
✔️ Multi-indicator fusion for enhanced accuracy
✔️ Built-in adaptive filtering techniques
✔️ Works across varied market regimes
✔️ Provides quantifiable, rule-based signals
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✨ Key Features
🔹 Universal Signal Aggregation
Combines five complementary indicators to form a balanced, adaptive signal, ensuring robust performance across different market conditions.
🔹 Advanced Filtering Techniques
Utilizes Gaussian smoothing, average true range and standard deviation filtering, indicator normalization, and other non-lagging filters to refine trend detection and minimize noise.
🔹 Dynamic Market Adaptation
Employs percentile-based filtering and normalization techniques, allowing it to adjust dynamically to volatility shifts.
🔹 Modular & Customizable
Each indicator can be toggled independently, allowing traders to fine-tune the strategy based on their specific market outlook.
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📊 How It Works & Signal Generation
⚙ Multi-Layer Signal Aggregation: ChronoSync calculates individual trend signals from five indicators, combining their outputs into a Final Strategy Score to determine trade signals.
✅ Long Entry: Triggered when the aggregated final score surpasses the long threshold
❌ Short Entry (Cash Mode): Triggered when the final signal falls below the short threshold
🎨 Color Visualization: Changes dynamically to reflect market conditions
🔹 Volatility Adaptable: Traders can adjust the long and short signal thresholds to fine-tune sensitivity to volatility—wider thresholds reduce false signals in choppy markets, while narrower thresholds increase responsiveness in high-momentum trends.
🖥️ Dashboard & Signal Display:
• Displays individual indicator values and final aggregation score
• Signals (Long / Cash) appear directly on the chart when the label display is turned on
• Customizable visual settings to match user preferences
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👥 Who is this for?
✔ Swing & Medium-Term Traders → Ideal for multi-day to multi-week trades.
✔Long-Term Investors & Trend Followers – Designed for traders and investors with a months-to-years horizon who seek to capture market trends on a cycle basis.
✔ Quantitative Traders → Structured, rules-based approach for systematic execution
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📊 Expanded Explanation : How the Five Indicators Work Together in ChronoSync
The ChronoSync strategy is built upon five carefully selected indicators, each fulfilling a crucial role in trend detection, volatility adaptation, and signal refinement. The synergy between these components ensures that signals are both robust and adaptable to different market conditions.
🔗 The Five-Indicator Synergy
Each indicator plays a specific role in the trend-following system, working together to enhance the strength, reliability, and adaptability of trade signals:
1️⃣ VIDYA ATR Gaussian Filter → Noise-Reduced Trend Detection
✔ What it Does:
The VIDYA ATR Gaussian Filter combines a volatility-adjusted moving average (VIDYA) with Gaussian smoothing to enhance trend clarity while minimizing market noise.
✔ Why It's Important:
• VIDYA dynamically adjusts to price fluctuations, ensuring smoother trend signals.
• Gaussian filtering eliminates erratic price movements that could otherwise trigger false entries/exits.
• By applying ATR filtering, the indicator remains adaptive to different volatility environments.
✔ How It Works With Others:
• Works in tandem with Kijun ATR & Dual SD Kijun to confirm long-term price trends while filtering out market noise.
• Enhances signal stability by reducing whipsaws in choppy conditions.
2️⃣ Kijun ATR & Dual SD Kijun → Trend Confirmation & Volatility Filtering
✔ What it Does:
The Kijun ATR and Dual SD Kijun components combine trend structure with volatility adjustments to capture sustained price moves.
✔ Why It's Important:
• The Kijun ATR dynamically adjusts to price swings, allowing the system to filter out market noise and identify valid breakout conditions.
• The Dual SD Kijun introduces an extra layer of confirmation by incorporating a standard deviation-based volatility filter to assess trend strength.
✔ How It Works With Others:
• Confirms trends initiated by VIDYA ATR Gaussian Filter, ensuring signals are based on structural price movements rather than short-term fluctuations.
• Complements PRC-ALMA Adaptive Bands in detecting price deviations and trend shifts.
3️⃣ VIDYA Loop Function → Iterative Trend Reinforcement
✔ What it Does:
The VIDYA Loop Function applies a recursive method to track sustained trends, using a loop-based iterative calculation.
✔ Why It's Important:
• Identifies persistent trends by aggregating historical VIDYA changes over a defined loop window.
• Helps eliminate short-lived price movements by smoothing trend signals over time.
✔ How It Works With Others:
• Enhances Bollinger Bands % SD by providing an additional trend strength confirmation.
• Strengthens Kijun ATR signals by filtering out weak or temporary price movements.
4️⃣ PRC-ALMA Adaptive Bands → Mean Reversion & Trend Filtering
✔ What it Does:
The PRC-ALMA Adaptive Bands combine a percentile-based ranking system with an adaptive smoothing function (ALMA) to define overbought/oversold zones within trend movements.
✔ Why It's Important:
• Adaptive percentile-based ranking ensures the indicator adjusts to market shifts dynamically.
• ALMA filtering ensures non-lagging trend detection, reducing delays in trade signals.
• Acts as a contrarian filter for trend exhaustion signals.
✔ How It Works With Others:
• Complements VIDYA ATR & Kijun ATR by refining trend-following entries.
• Provides mean-reverting insights to balance aggressive trend-following signals.
5️⃣ Bollinger Bands % SD → Volatility Expansion & Trend Strength Evaluation
✔ What it Does:
The Bollinger Bands % SD indicator measures price positioning relative to standard deviation bounds, helping assess volatility-driven trend strength.
✔ Why It's Important:
• Measures price movements relative to historical volatility thresholds.
• Helps determine when price action is statistically stretched (i.e., strong trend moves vs. mean-reverting pullbacks).
• Allows dynamic market adaptation, ensuring that signals remain relevant across different volatility phases.
✔ How It Works With Others:
• Enhances PRC-ALMA by confirming whether a price move is an actual breakout or a short-term deviation.
• Validates VIDYA ATR & Kijun ATR signals by ensuring the trend has sufficient strength to continue.
The ChronoSync strategy ensures a balanced fusion of trend-following and volatility adaptation. Each component adds a distinct layer of analysis, reducing false signals and improving robustness:
✅ Trend Identification → VIDYA ATR, Kijun ATR, & Dual SD Kijun
✅ Noise Reduction & Trend Confirmation → VIDYA Loop Function & Gaussian Smoothing
✅ Volatility Adaptation & Overbought/Oversold Conditions → PRC-ALMA Adaptive Bands & Bollinger Bands % SD
This multi-layered approach ensures that no single indicator dominates the strategy, allowing it to adapt dynamically to various market conditions.
📌 Conclusion
ChronoSync is a universal trend aggregation strategy, built on adaptive multi-indicator filtering and robust risk management. Designed for dynamic market conditions, it offers a rule-based, quantifiable approach to trend identification. Whether used as a standalone trading system or an auxiliary confirmation tool, it provides a scientific, data-driven edge for traders navigating volatile markets.
🔹 Disclaimer: Past performance is not indicative of future results. No trading strategy can guarantee success in financial markets.
🔹 Strategic Advice: Always backtest, optimize, and align parameters with your trading objectives and risk tolerance before live trading.
Btc and Eth 5 min winnerWhat the Strategy Does
Finding the Trend (Like Watching the Bus Move): The strategy uses special tools called Hull Moving Averages (HMAs) to figure out if Bitcoin (BTC) Ethereum (ETH) prices are generally going up or down. It looks at short-term (5 minutes) and long-term (10 minutes) price movements to make sure the “bus” (the market) is moving strongly in one direction—up for buying, down for selling.
Spotting Good Times to Jump On (Buy or Sell Signals): It looks for two types of opportunities:
Pullbacks: When the price dips a little while still moving up (like the bus slowing down but not stopping), it’s a chance to buy.
Breakouts: When the price suddenly jumps higher after being stuck (like the bus speeding up), it’s another chance to buy. It does the opposite for selling when prices are dropping.
It also checks if there’s enough “passenger activity” (volume) and momentum (speed of price change) to make sure it’s a good move.
Avoiding Traffic Jams (Filters): The strategy uses tools like RSI (to check if the market’s too fast or too slow), volume (to see if enough people are trading), and ATR (to measure how wild the price swings are). It skips trades if things look too chaotic or if the trend isn’t strong enough.
Setting Safety Stops and Profit Targets: Once you’re on the “bus,” it sets rules to protect you:
Stop-Loss: If the price moves against you by a small amount (0.5% of the typical price swing), you jump off to avoid losing too much—think of it as getting off before the bus crashes.
Take-Profit: If the price moves in your favor by a small amount (1.0% of the typical swing), you cash out—imagine getting off at your stop with a profit.
Trailing Stop: If the price keeps moving your way, it adjusts your exit point to lock in more profit, like moving your stop closer as the bus keeps going.
Using Leverage (10x Boost): This strategy uses 10x leverage on Binance futures, meaning for every $1 you have, you trade like you have $10. This can make profits (or losses) 10 times bigger, so it’s risky but can be rewarding if you’re careful.
Why 5 Minutes and Bitcoin and Ethereum?
5-Minute Chart: This is like checking the bus every 5 minutes to make quick, small trades—perfect for fast, short profits.
Bitcoin Ethereum (BTC/USD)(ETH/USD): It’s the most popular and liquid crypto, so there’s lots of activity, making it easier to jump on and off without getting stuck.
Why It Aims for 90% Wins (But Be Realistic)
The goal is to win 9 out of 10 trades by being super picky about when to trade—only jumping on when the trend, momentum, and volume are all perfect. But in real trading, markets can be unpredictable, so 90% is very hard to achieve. Still, this strategy tries to be as accurate as possible by avoiding bad moves and focusing on strong trends.
Risks for a New Trader
Leverage: Trading with 10x leverage means small price moves can lead to big losses if you’re not careful. Start with a demo account (pretend money) on TradingView or Binance to practice.
Learning Curve: This strategy uses technical terms (like HMAs, RSI) and tools you’ll need to learn over time. Don’t rush—just practice and ask questions!
How to Use It
Go to TradingView, load this strategy on a 5-minute BTC/USD futures chart on Binance.
Watch the green triangles (buy signals) and red triangles (sell signals) on the chart—they tell you when to trade.
Use the stops and targets to manage your trades—don’t guess, let the strategy guide you.
Start small, learn from each trade, and don’t risk money you can’t afford to lose.
This is like learning to ride a bike—start slow, practice, and you’ll get better. If you have more questions or want simpler tips, feel free to ask! Trading can be fun and rewarding, but it takes patience and practice.
[3Commas] HA & MAHA & MA
🔷What it does: This tool is designed to test a trend-following strategy using Heikin Ashi candles and moving averages. It enters trades after pullbacks, aiming to let profits run once the risk-to-reward ratio reaches 1:1 while securing the position.
🔷Who is it for: It is ideal for traders looking to compare final results using fixed versus dynamic take profits by adjusting parameters and trade direction—a concept applicable to most trading strategies.
🔷How does it work: We use moving averages to define the market trend, then wait for opposite Heikin Ashi candles to form against it. Once these candles reverse in favor of the trend, we enter the trade, using the last swing created by the pullback as the stop loss. By applying the breakeven ratio, we protect the trade and let it run, using the slower moving average as a trailing stop.
A buy signal is generated when:
The previous candle is bearish (ha_bear ), indicating a pullback.
The fast moving average (ma1) is above the slow moving average (ma2), confirming an uptrend.
The current candle is bullish (ha_bull), showing trend continuation.
The Heikin Ashi close is above the fast moving average (ma1), reinforcing the bullish bias.
The real price close is above the open (close > open), ensuring bullish momentum in actual price data.
The signal is confirmed on the closed candle (barstate.isconfirmed) to avoid premature signals.
dir is undefined (na(dir)), preventing repeated signals in the same direction.
A sell signal is generated when:
The previous candle is bullish (ha_bull ), indicating a temporary upward move before a potential reversal.
The fast moving average (ma1) is below the slow moving average (ma2), confirming a downtrend.
The current candle is bearish (ha_bear), showing trend continuation to the downside.
The Heikin Ashi close is below the fast moving average (ma1), reinforcing bearish pressure.
The real price close is below the open (close < open), confirming bearish momentum in actual price data.
The signal is confirmed after the candle closes (barstate.isconfirmed), avoiding premature entries.
dir is undefined (na(dir)), preventing consecutive signals in the same direction.
In simple terms, this setup looks for trend continuation after a pullback, confirming entries with both Heikin Ashi and real price action, supported by moving average alignment to avoid false signals.
If the price reaches a 1:1 risk-to-reward ratio, the stop will be moved to the entry point. However, if the slow moving average surpasses this level, it will become the new exit point, acting as a trailing stop
🔷Why It’s Unique
Easily visualizes the benefits of using risk-to-reward ratios when trading instead of fixed percentages.
Provides a simple and straightforward approach to trading, embracing the "keep it simple" concept.
Offers clear visualization of DCA Bot entry and exit points based on user preferences.
Includes an option to review the message format before sending signals to bots, with compatibility for multi-pair and futures contract pairs.
🔷 Considerations Before Using the Indicator
⚠️Very important: The indicator must be used on charts with real price data, such as Japanese candlesticks, line charts, etc. Do not use it on Heikin Ashi charts, as this may lead to unrealistic results.
🔸Since this is a trend-following strategy, use it on timeframes above 4 hours, where market noise is reduced and trends are clearer. Also, carefully review the statistics before using it, focusing on pairs that tend to have long periods of well-defined trends.
🔸Disadvantages:
False Signals in Ranges: Consolidating markets can generate unreliable signals.
Lagging Indicator: Being based on moving averages, it may react late to sudden price movements.
🔸Advantages:
Trend Focused: Simplifies the identification of trending markets.
Noise Reduction: Uses Heikin Ashi candles to identify trend continuation after pullbacks.
Broad Applicability: Suitable for forex, crypto, stocks, and commodities.
🔸The strategy provides a systematic way to analyze markets but does not guarantee successful outcomes. Use it as an additional tool rather than relying solely on an automated system.
Trading results depend on various factors, including market conditions, trader discipline, and risk management. Past performance does not ensure future success, so always approach the market cautiously.
🔸Risk Management: Define stop-loss levels, position sizes, and profit targets before entering any trade. Be prepared for potential losses and ensure your approach aligns with your overall trading plan.
🔷 STRATEGY PROPERTIES
Symbol: BINANCE:BTCUSDT (Spot).
Timeframe: 4h.
Test Period: All historical data available.
Initial Capital: 10000 USDT.
Order Size per Trade: 1% of Capital, you can use a higher value e.g. 5%, be cautious that the Max Drawdown does not exceed 10%, as it would indicate a very risky trading approach.
Commission: Binance commission 0.1%, adjust according to the exchange being used, lower numbers will generate unrealistic results. By using low values e.g. 5%, it allows us to adapt over time and check the functioning of the strategy.
Slippage: 5 ticks, for pairs with low liquidity or very large orders, this number should be increased as the order may not be filled at the desired level.
Margin for Long and Short Positions: 100%.
Indicator Settings: Default Configuration.
MA1 Length: 9.
MA2 Length: 18.
MA Calculations: EMA.
Take Profit Ratio: Disable. Ratio 1:4.
Breakeven Ratio: Enable, Ratio 1:1.
Strategy: Long & Short.
🔷 STRATEGY RESULTS
⚠️Remember, past results do not guarantee future performance.
Net Profit: +324.88 USDT (+3.25%).
Max Drawdown: -81.18 USDT (-0.78%).
Total Closed Trades: 672.
Percent Profitable: 35.57%.
Profit Factor: 1.347.
Average Trade: +0.48 USDT (+0.48%).
Average # Bars in Trades: 13.
🔷 HOW TO USE
🔸 Adjust Settings:
The default values—MA1 (9) and MA2 (18) with EMA calculation—generally work well. However, you can increase these values, such as 20 and 40, to better identify stronger trends.
🔸 Choose a Symbol that Typically Trends:
Select an asset that tends to form clear trends. Keep in mind that the Strategy Tester results may show poor performance for certain assets, making them less suitable for sending signals to bots.
🔸 Experiment with Ratios:
Test different take profit and breakeven ratios to compare various scenarios—especially to observe how the strategy performs when only the trade is protected.
🔸This is an example of how protecting the trade works: once the price moves in favor of the position with a 1:1 risk-to-reward ratio, the stop loss is moved to the entry price. If the Slow MA surpasses this level, it will act as a trailing stop, aiming to follow the trend and maximize potential gains.
🔸In contrast, in this example, for the same trade, if we set a take profit at a 1:3 risk-to-reward ratio—which is generally considered a good risk-reward relationship—we can see how a significant portion of the upward move is left on the table.
🔸Results Review:
It is important to check the Max Drawdown. This value should ideally not exceed 10% of your capital. Consider adjusting the trade size to ensure this threshold is not surpassed.
Remember to include the correct values for commission and slippage according to the symbol and exchange where you are conducting the tests. Otherwise, the results will not be realistic.
If you are satisfied with the results, you may consider automating your trades. However, it is strongly recommended to use a small amount of capital or a demo account to test proper execution before committing real funds.
🔸Create alerts to trigger the DCA Bot:
Verify Messages: Ensure the message matches the one specified by the DCA Bot.
Multi-Pair Configuration: For multi-pair setups, enable the option to add the symbol in the correct format.
Signal Settings: Enable whether you want to receive long or short signals (Entry | TP | SL), copy and paste the the messages for the DCA Bots configured.
Alert Setup:
When creating an alert, set the condition to the indicator and choose "alert() function call only.
Enter any desired Alert Name.
Open the Notifications tab, enable Webhook URL, and paste the Webhook URL.
For more details, refer to the section: "How to use TradingView Custom Signals".
Finalize Alerts: Click Create, you're done! Alerts will now be sent automatically in the correct format.
🔷 INDICATOR SETTINGS
MA 1: Fast MA Length
MA 2: Slow MA Length
MA Calc: MA's Calculations (SMA,EMA, RMA,WMA)
TP Ratio: This is the take profit ratio relative to the stop loss, where the trade will be closed in profit.
BE Ratio: This is the breakeven ratio relative to the stop loss, where the stop loss will be updated to breakeven or if the MA2 is greater than this level.
Strategy: Order Type direction in which trades are executed.
Use Custom Test Period: When enabled signals only works in the selected time window. If disabled it will use all historical data available on the chart.
Test Start and End: Once the Custom Test Period is enabled, here you select the start and end date that you want to analyze.
Check Messages: Enable the table to review the messages to be sent to the bot.
Entry | TP | SL: Enable this options to send Buy Entry, Take Profit (TP), and Stop Loss (SL) signals.
Deal Entry and Deal Exit : Copy and paste the message for the deal start signal and close order at Market Price of the DCA Bot. This is the message that will be sent with the alert to the Bot, you must verify that it is the same as the bot so that it can process properly so that it executes and starts the trade.
DCA Bot Multi-Pair: You must activate it if you want to use the signals in a DCA Bot Multi-pair in the text box you must enter (using the correct format) the symbol in which you are creating the alert, you can check the format of each symbol when you create the bot.
👨🏻💻💭 We hope this tool helps enhance your trading. Your feedback is invaluable, so feel free to share any suggestions for improvements or new features you'd like to see implemented.
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The information and publications within the 3Commas TradingView account are not meant to be and do not constitute financial, investment, trading, or other types of advice or recommendations supplied or endorsed by 3Commas and any of the parties acting on behalf of 3Commas, including its employees, contractors, ambassadors, etc.
Sunil WMA 5Sunil WMA 5 – Precision Trend Following Strategy
Overview
The Sunil WMA 5 is a trend-following trading strategy designed to identify optimal entry and exit points based on price action and momentum confirmation. The strategy is fully non-repainting and works effectively across various markets, including stocks, forex, commodities, indices, and cryptocurrencies.
This strategy employs a Weighted Moving Average (WMA) filter to enhance trend identification. It is particularly useful for scalping, day trading, and swing trading in volatile markets.
Key Features
🔹 Adaptive Trading Window – Allows users to define a specific time range for trade execution, preventing unnecessary entries outside active hours.
🔹 Flexible Trade Direction – Users can configure the strategy to trade Long Only, Short Only, or Long/Short mode.
🔹 Automated Alerts for Trade Execution – Webhook-compatible alerts allow seamless integration with brokers and automated trading platforms.
🔹 Strict Entry & Exit Rules – Ensures a disciplined approach to trading with clear logic for opening and closing positions.
🔹 Optimized for Various Timeframes – Can be used on lower timeframes (e.g., 1s, 5s, 15s) for high-frequency trading or on higher timeframes for swing trading.
Default Input Parameters & Settings
1. Trading Session (Time Window)
📌 Parameter: Trading Window
Default Value: "0000-0000" (Trades 24/7 unless a specific window is set)
Description: Allows traders to define a specific time range for trade execution. If a trade is open when the window closes, the position is automatically exited.
2. Trade Direction
📌 Parameter: Strategy Direction
Default Value: "Long/Short"
Options: "Long Only", "Short Only", "Long/Short"
Description: Determines whether the strategy will take only long trades, only short trades, or both.
3. Automated Trading Alerts (Webhook-Compatible)
📌 Parameters:
Long_Entry_Jason – (Default: "") Webhook JSON for long entries.
Long_Exit_Jason – (Default: "") Webhook JSON for long exits.
Short_Entry_Jason – (Default: "") Webhook JSON for short entries.
Short_Exit_Jason – (Default: "") Webhook JSON for short exits.
💡 Purpose: These parameters allow the strategy to send automated alerts, which can be connected to external trading platforms for trade execution.
4. Moving Average Settings
📌 Indicator Used: Weighted Moving Average (WMA)
Period: 5 (Fixed)
Description: The strategy calculates a short-term 5-period WMA as a trend filter. Trade signals are generated based on price interaction with this WMA.
How the Strategy Works
📌 1. Trade Entry Logic
The strategy identifies potential buy or sell opportunities when price action meets certain trend-confirmation criteria.
Long trades are triggered when price crosses above the 5-period WMA.
Short trades are triggered when price crosses below the 5-period WMA.
Only one position (long or short) is held at a time, ensuring clear and structured trade management.
📌 2. Trade Exit Logic
A position is closed when an opposite trade condition occurs.
If a long position is open and a short signal is triggered, the long trade is closed.
If a short position is open and a long signal is triggered, the short trade is closed.
If the trading session ends while a trade is open, the position is closed automatically.
📌 3. Automated Trading & Alerts
Users can integrate this strategy with TradingView Alerts to receive notifications or execute trades automatically.
The webhook-compatible alerts allow seamless execution with third-party trading platforms.
Best Use Cases
✅ Scalping & High-Frequency Trading – Works well on lower timeframes such as 1s, 5s, and 15s.
✅ Day Trading & Swing Trading – Can also be applied to longer timeframes for structured trend-following setups.
✅ Crypto, Forex, Stocks, and Indices – Best suited for assets with strong volatility and liquidity.
Boilerplate Configurable Strategy [Yosiet]This is a Boilerplate Code!
Hello! First of all, let me introduce myself a little bit. I don't come from the world of finance, but from the world of information and communication technologies (ICT) where we specialize in data processing with the aim of automating it and eliminating all human factors and actors in the processes. You could say that I am an algotrader.
That said, in my journey through trading in recent years I have understood that this world is often shown to be incomplete. All those who want to learn about trading only end up learning a small part of what it really entails, they only seek to learn how to read candlesticks. Therefore, I want to share with the entire community a fraction of what I have really understood it to be.
As a computer scientist, the most important thing is the data, it is the raw material of our work and without data you simply cannot do anything. Entropy is simple: Data in -> Data is transformed -> Data out.
The quality of the outgoing data will directly depend on the incoming data, there is no greater mystery or magic in the process. In trading it is no different, because at the end of the day it is nothing more than data. As we often say, if garbage comes in, garbage comes out.
Most people focus on the results only, on the outgoing data, because in the end we all want the same thing, to make easy money. Very few pay attention to the input data, much less to the process.
Now, I am not here to delude you, because there is no bigger lie than easy money, but I am here to give you a boilerplate code that will help you create strategies where you only have to concentrate on the quality of the incoming data.
To the Point
The code is a strategy boilerplate that applies the technique that you decide to customize for the criteria for opening a position. It already has the other factors involved in trading programmed and automated.
1. The Entry
This section of the boilerplate is the one that each individual must customize according to their needs and knowledge. The code is offered with two simple, well-known strategies to exemplify how the code can be reused for your own benefits.
For the purposes of this post on tradingview, I am going to use the simplest of the known strategies in trading for entries: SMA Crossing
// SMA Cross Settings
maFast = ta.sma(close, length)
maSlow = ta.sma(open, length)
The Strategy Properties for all cases published here:
For Stock TSLA H1 From 01/01/2025 To 02/15/2025
For Crypto XMR-USDT 30m From 01/01/2025 To 02/15/2025
For Forex EUR-USD 5m From 01/01/2025 To 02/15/2025
But the goal of this post is not to sell you a dream, else to show you that the same Entry decision works very well for some and does not for others and with this boilerplate code you only have to think of entries, not exits.
2. Schedules, Days, Sessions
As you know, there are an infinite number of markets that are susceptible to the sessions of each country and the news that they announce during those sessions, so the code already offers parameters so that you can condition the days and hours of operation, filter the best time parameters for a specific market and time frame.
3. Data Filtering
The data offered in trading are numerical series presented in vectors on a time axis where an endless number of mathematical equations can be applied to process them, with matrix calculation and non-linear regressions being the best, in my humble opinion.
4. Read Fundamental Macroeconomic Events, News
The boilerplate has integration with the tradingview SDK to detect when news will occur and offers parameters so that you can enable an exclusion time margin to not operate anything during that time window.
5. Direction and Sense
In my experience I have found the peculiarity that the same algorithm works very well for a market in a time frame, but for the same market in another time frame it is only a waste of time and money. So now you can easily decide if you only want to open LONG, SHORT or both side positions and know how effective your strategy really is.
6. Reading the money, THE PURPOSE OF EVERYTHING
The most important section in trading and the reason why many clients usually hire me as a financial programmer, is reading and controlling the money, because in the end everyone wants to win and no one wants to lose. Now they can easily parameterize how the money should flow and this is the genius of this boilerplate, because it is what will really decide if an algorithm (Indicator: A bunch of math equations) for entries will really leave you good money over time.
7. Managing the Risk, The Ego Destroyer
Many trades, little money. Most traders focus on making money and none of them know about statistics and the few who do know something about it, only focus on the winrate. Well, with this code you can unlock what really matters, the true success criteria to be able to live off of trading: Profit Factor, Sortino Ratio, Sharpe Ratio and most importantly, will you really make money?
8. Managing Emotions
Finally, the main reason why many lose money is because they are very bad at managing their emotions, because with this they will no longer need to do so because the boilerplate has already programmed criteria to chase the price in a position, cut losses and maximize profits.
In short, this is a boilerplate code that already has the data processing and data output ready, you only have to worry about the data input.
“And so the trader learned: the greatest edge was not in predicting the storm, but in building a boat that could not sink.”
DISCLAIMER
This post is intended for programmers and quantitative traders who already have a certain level of knowledge and experience. It is not intended to be financial advice or to sell you any money-making script, if you use it, you do so at your own risk.
CBC Strategy with Trend Confirmation & Separate Stop LossCBC Flip Strategy with Trend Confirmation and ATR-Based Targets
This strategy is based on the CBC Flip concept taught by MapleStax and inspired by the original CBC Flip indicator by AsiaRoo. It focuses on identifying potential reversals or trend continuation points using a combination of candlestick patterns (CBC Flips), trend filters, and a time-based entry window. This approach helps traders avoid false signals and increase trade accuracy.
What is a CBC Flip?
The CBC Flip is a candlestick-based pattern that identifies moments when the market is likely to change direction or strengthen its trend. It checks for a shift in price behavior between consecutive candles, signaling a bullish (upward) or bearish (downward) move.
However, not all flips are created equal! This strategy differentiates between Strong Flips and All Flips, allowing traders to choose between a more conservative or aggressive approach.
Strong Flips vs. All Flips
Strong Flips
A Strong Flip is a high-probability setup that occurs only after liquidity is swept from the previous candle’s high or low.
What is a liquidity sweep? This happens when the price briefly moves beyond the high or low of the previous candle, triggering stop-losses and trapping traders in the wrong direction. These sweeps often create fuel for the next move, making them powerful reversal signals.
Examples:
Long Setup: The price dips below the previous candle’s low (sweeping liquidity) and then closes higher, signaling a potential bullish move.
Short Setup: The price moves above the previous candle’s high and then closes lower, signaling a potential bearish move.
Why Use Strong Flips?
They provide fewer signals, but the accuracy is generally higher.
Ideal for trending markets where liquidity sweeps often mark key turning points.
All Flips
All Flips are less selective, offering both Strong Flips and additional signals without requiring a liquidity sweep.
This approach gives traders more frequent opportunities but comes with a higher risk of false signals, especially in sideways markets.
Examples:
Long Setup: A CBC flip occurs without sweeping the previous low, but the trend direction is confirmed (slow EMA is still above VWAP).
Short Setup: A CBC flip occurs without sweeping the previous high, but the trend is still bearish (slow EMA below VWAP).
Why Use All Flips?
Provides more frequent entries for active or aggressive traders.
Works well in trending markets but requires caution during consolidation periods.
How This Strategy Works
The strategy combines CBC Flips with multiple filters to ensure better trade quality:
Trend Confirmation: The slow EMA (20-period) must be positioned relative to the VWAP to confirm the overall trend direction.
Long Trades: Slow EMA must be above VWAP (upward trend).
Short Trades: Slow EMA must be below VWAP (downward trend).
Time-Based Filter: Traders can specify trading hours to limit entries to a particular time window, helping avoid low-volume or high-volatility periods.
Profit Target and Stop-Loss:
Profit Target: Defined as a multiple of the 14-period ATR (Average True Range). For example, if the ATR is 10 points and the profit target multiplier is set to 1.5, the strategy aims for a 15-point profit.
Stop-Loss: Uses a dynamic, candle-based stop-loss:
Long Trades: The trade closes if the market closes below the low of two candles ago.
Short Trades: The trade closes if the market closes above the high of two candles ago.
This approach adapts to recent price behavior and protects against unexpected reversals.
Customizable Settings
Strong Flips vs. All Flips: Choose between a more selective or aggressive entry style.
Profit Target Multiplier: Adjust the ATR multiplier to control the distance for profit targets.
Entry Time Range: Define specific trading hours for the strategy.
Indicators and Visuals
Fast EMA (10-Period) – Black Line
Slow EMA (20-Period) – Red Line
VWAP (Volume-Weighted Average Price) – Orange Line
Visual Labels:
▵ (Triangle Up) – Marks long entries (buy signals).
▿ (Triangle Down) – Marks short entries (sell signals).
Credits
CBC Flip Concept: Inspired by MapleStax, who teaches this concept.
Original Indicator: Developed by AsiaRoo, this strategy builds on the CBC Flip framework with additional features for improved trade management.
Risks and Disclaimer
This strategy is for educational purposes only and does not constitute financial advice.
Trading involves significant risk and may result in the loss of capital. Past performance does not guarantee future results. Use this strategy in a simulated environment before applying it to live trading.
Smart MA Crossover BacktesterSmart MA Crossover Backtester - Strategy Overview
Strategy Name: Smart MA Crossover Backtester
Published on: TradingView
Applicable Markets: Works well on crypto (tested profitably on ETH)
Strategy Concept
The Smart MA Crossover Backtester is an improved Moving Average (MA) crossover strategy that incorporates a trend filter and an ATR-based stop loss & take profit mechanism for better risk management. It aims to capture trends efficiently while reducing false signals by only trading in the direction of the long-term trend.
Core Components & Logic
Moving Averages (MA) for Entry Signals
Fast Moving Average (9-period SMA)
Slow Moving Average (21-period SMA)
A trade signal is generated when the fast MA crosses the slow MA.
Trend Filter (200-period SMA)
Only enters long positions if price is above the 200-period SMA (bullish trend).
Only enters short positions if price is below the 200-period SMA (bearish trend).
This helps in avoiding counter-trend trades, reducing whipsaws.
ATR-Based Stop Loss & Take Profit
Uses the Average True Range (ATR) with a multiplier of 2 to calculate stop loss.
Risk-Reward Ratio = 1:2 (Take profit is set at 2x ATR).
This ensures dynamic stop loss and take profit levels based on market volatility.
Trading Rules
✅ Long Entry (Buy Signal):
Fast MA (9) crosses above Slow MA (21)
Price is above the 200 MA (bullish trend filter active)
Stop Loss: Below entry price by 2× ATR
Take Profit: Above entry price by 4× ATR
✅ Short Entry (Sell Signal):
Fast MA (9) crosses below Slow MA (21)
Price is below the 200 MA (bearish trend filter active)
Stop Loss: Above entry price by 2× ATR
Take Profit: Below entry price by 4× ATR
Why This Strategy Works Well for Crypto (ETH)?
🔹 Crypto markets are highly volatile – ATR-based stop loss adapts dynamically to market conditions.
🔹 Long-term trend filter (200 MA) ensures trading in the dominant direction, reducing false signals.
🔹 Risk-reward ratio of 1:2 allows for profitable trades even with a lower win rate.
This strategy has been tested on Ethereum (ETH) and has shown profitable performance, making it a strong choice for crypto traders looking for trend-following setups with solid risk management. 🚀
Universal Strategy | QuantEdgeBIntroducing the Universal Strategy by QuantEdgeB
The Universal Strategy | QuantEdgeB is a dynamic, multi-indicator strategy designed to operate across various asset classes with precision and adaptability. This cutting-edge system utilizes four sophisticated methodologies, each integrating advanced trend-following, volatility filtering, and normalization techniques to provide robust signals. Its modular architecture and customizable features ensure suitability for diverse market conditions, empowering traders with data-driven decision-making tools. Its adaptability to different price behaviors and volatility levels makes it a robust and versatile tool, equipping traders with data-driven confidence in their market decisions.
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1. Core Methodologies and Features
1️⃣ DEMA ATR
Strength : Fast responsiveness to trend shifts.
The double exponential moving average is inherently aggressive, designed to reduce lag and quickly identify early signs of trend reversals or breakout opportunities. ATR bands add a volatility-sensitive layer, dynamically adjusting the breakout thresholds to match current market conditions, ensuring it remains responsive while filtering out noise
How It Fits :
This indicator is the first responder, providing early signals of potential trend shifts. While its aggressiveness can result in quick entries, it may occasionally overreact in noisy markets. This is where the smoother indicators step in to confirm signals.
2️⃣ Gaussian - VIDYA ATR (Variable Index Dynamic Average)
Strength : Smooth, adaptive trend identification.
Unlike DEMA, VIDYA adapts to market volatility through its standard deviation-based formula, making it smoother and less reactive to short-term fluctuations. ATR filtering ensures the indicator remains effective in volatile markets by dynamically adjusting its sensitivity.
How It Fits :
The smoother complement to DEMA ATR, VIDYA ATR filters out false signals from minor price movements. It provides confirmation for the trends identified by DEMA ATR, ensuring entries are based on robust, sustained price movements.
3️⃣ VIDYA Loop Trend Scoring
Strength : Historical trend scoring for consistent momentum detection.
This module evaluates the relative strength of trends by comparing the current VIDYA value to its historical values over a defined range. The loop mechanism provides a trend confidence score, quantifying the momentum behind price movements.
How It Fits :
VIDYA For-Loop adds a quantitative measure of trend strength, ensuring that trades are backed by sustained momentum. It balances the early signals from DEMA ATR and the smoothness of VIDYA ATR by providing a statistical check on the underlying trend.
4️⃣ Median SD with Normalization
Strength : Precision in breakout detection and market normalization.
The Median price serves as a robust baseline for detecting breakouts and reversals.
SD bands expand dynamically during periods of high volatility, making the indicator particularly effective for spotting strong trends or breakout opportunities. Normalization ensures the indicator adapts seamlessly across different assets and timeframes, providing consistent performance.
How It Fits :
The Median SD module provides final confirmation by focusing on price breakouts and market normalization. While the other indicators focus on momentum and trend strength, Median SD emphasizes precision, ensuring entries align with significant price movements rather than random fluctuations.
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2. How The Single Components Work Together
1️⃣ Balance of Speed and Smoothness :
The strategy blends quick responsiveness (DEMA ATR) with smooth and adaptive confirmation (VIDYA ATR & For-Loop), ensuring timely reactions without overreacting to market fluctuations. Median SD with Normalization refines breakout detection and stabilizes performance across assets using statistical anchors like price median and standard deviation.
Adaptability to Market Dynamics:
2️⃣ Adaptability to Market Dynamics :
The indicators complement each other seamlessly in trending markets, with the DEMA ATR and Median SD with Normalization quickly identifying shifts and confirming sustained momentum. In volatile or choppy markets, normalization and SD bands work together to filter out noise and reduce false signals, ensuring precise entries and exits. Meanwhile, the For-Loop scoring and Gaussian-Filtered VIDYA ATR focus on providing smoother, more reliable trend detection, offering consistent performance regardless of market conditions.
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3. Scoring and Signal Confirmation
The Universal Strategy consolidates signals from all four methodologies, calculating a Trend Probability Index (TPI). The four core indicators operate independently but contribute to a unified TPI, enabling highly adaptive behavior across asset classes.
- Each methodology generates a trend score: 1 for bullish trends, -1 for bearish trends.
- The TPI averages the scores, creating a unified signal.
- Long Position: Triggered when the TPI exceeds the long threshold (default: 0).
- Short Position: Triggered when the TPI falls below the short threshold (default: 0).
The strategy’s customizable settings allow traders to tailor its behavior to different market conditions—whether smoother trends in low-volatility assets or quick reaction to high-volatility breakouts. The long and short thresholds can be fine-tuned to match a trader’s risk tolerance and preferences.
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4. Use Cases:
The Universal Strategy | QuantEdgeB is designed to excel across a wide range of trading scenarios, thanks to its modular architecture and adaptability. Whether you're navigating trending, volatile, or range-bound markets, this strategy offers robust tools to enhance your decision-making. Below are the key use cases for its application:
1️⃣ Trend Trading
The strategy’s Gaussian-Filtered DEMA ATR and VIDYA ATR modules are perfect for identifying and riding sustained trends.
Ideal For: Traders looking to capture long-term momentum or position trades.
2️⃣ Breakout and Volatility-Based Strategies
With its Median SD with Normalization, the strategy excels in detecting volatility breakouts and significant price movements.
Ideal For: Traders aiming to capitalize on sudden market movements, especially in assets like cryptocurrencies and commodities.
3️⃣ Momentum and Strength Assessment
By generating a trend confidence score, the VIDYA For-Loop quantifies momentum strength—helping traders distinguish temporary spikes from sustainable trends.
Ideal For: Swing traders and those focusing on momentum-driven setups.
4️⃣ Adaptability Across Multiple Assets
The strategy’s robust framework ensures it performs consistently across different assets and timeframes.
Ideal For: Traders managing diverse portfolios or shifting between asset classes.
5️⃣ Backtesting and Optimization
Built-in backtesting and equity visualization tools make this strategy ideal for testing and refining parameters in real-world conditions.
• How It Helps: The strategy equity curve and metrics table offer a clear picture of performance, helping traders identify optimal settings for their chosen market and timeframe.
• Ideal For: Traders focused on rigorous testing and long-term optimization.
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5. Signal Composition Table:
This table presents a real-time breakdown of each indicator’s trend score (+1 bullish, -1 bearish) alongside the final aggregated signal. By visualizing the contribution of each methodology, traders gain greater transparency, confidence, and clarity in identifying long or short opportunities.
6. Customized Settings:
1️⃣ General Inputs
• Strategy Long Threshold (Lu): 0
• Strategy Short Threshold (Su): 0
2️⃣ Gaussian Filter
• Gaussian Length (len_FG): 4
• Gaussian Source (src_FG): close
• Gaussian Sigma (sigma_FG): 2.0
3️⃣ DEMA ATR
• DEMA Length (len_D): 30
• DEMA Source (src_D): close
• ATR Length (atr_D): 14
• ATR Multiplier (mult_D): 1.0
4️⃣ VIDYA ATR
• VIDYA Length (len_V1): 9
• SD Length (len_VHist1): 30
• ATR Length (atr_V): 14
• ATR Multiplier (mult_V): 1.7
5️⃣ VIDYA For-Loop
• VIDYA Length (len_V2): 2
• SD Length (len_VHist2): 5
• VIDYA Source (src_V2): close
• Start Loop (strat_loop): 1
• End Loop (end_loop): 60
• Long Threshold (long_t): 40
• Short Threshold (short_t): 8
6️⃣ Median SD
• Median Length (len_m): 24
• Normalized Median Length (len_msd): 50
• SD Length (SD_len): 32
• Long SD Weight (w1): 0.98
• Short SD Weight (w2): 1.02
• Long Normalized Smooth (smooth_long): 1
• Short Normalized Smooth (smooth_short): 1
Conclusion
The Universal Strategy | QuantEdgeB is a meticulously crafted, multi-dimensional trading system designed to thrive across diverse market conditions and asset classes. By combining Gaussian-Filtered DEMA ATR, VIDYA ATR, VIDYA For-Loop, and Median SD with Normalization, this strategy provides a seamless balance between speed, smoothness, and adaptability. Each component complements the others, ensuring traders benefit from early responsiveness, trend confirmation, momentum scoring, and breakout precision.
Its modular structure ensures versatility across trending, volatile, and consolidating markets. Whether applied to equities, forex, commodities, or crypto, it delivers data-driven precision while minimizing reliance on randomness, reinforcing confidence in decision-making.
With built-in backtesting tools, traders can rigorously evaluate performance under real-world conditions, while customization options allow fine-tuning for specific market dynamics and individual trading styles.
Why It Stands Out
The Universal Strategy | QuantEdgeB isn’t just a trading algorithm—it’s a comprehensive framework that empowers traders to make confident, informed decisions in the face of ever-changing market conditions. Its emphasis on precision, reliability, and transparency makes it a powerful tool for both professional and retail traders seeking consistent performance and enhanced risk management.
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🔹 Disclaimer: Past performance is not indicative of future results. No trading strategy can guarantee success in financial markets.
🔹 Strategic Advice: Always backtest, optimize, and align parameters with your trading objectives and risk tolerance before live trading.
BTC Future Gamma-Weighted Momentum Model (BGMM)The BTC Future Gamma-Weighted Momentum Model (BGMM) is a quantitative trading strategy that utilizes the Gamma-weighted average price (GWAP) in conjunction with a momentum-based approach to predict price movements in the Bitcoin futures market. The model combines the concept of weighted price movements with trend identification, where the Gamma factor amplifies the weight assigned to recent prices. It leverages the idea that historical price trends and weighting mechanisms can be utilized to forecast future price behavior.
Theoretical Background:
1. Momentum in Financial Markets:
Momentum is a well-established concept in financial market theory, referring to the tendency of assets to continue moving in the same direction after initiating a trend. Any observed market return over a given time period is likely to continue in the same direction, a phenomenon known as the “momentum effect.” Deviations from a mean or trend provide potential trading opportunities, particularly in highly volatile assets like Bitcoin.
Numerous empirical studies have demonstrated that momentum strategies, based on price movements, especially those correlating long-term and short-term trends, can yield significant returns (Jegadeesh & Titman, 1993). Given Bitcoin’s volatile nature, it is an ideal candidate for momentum-based strategies.
2. Gamma-Weighted Price Strategies:
Gamma weighting is an advanced method of applying weights to price data, where past price movements are weighted by a Gamma factor. This weighting allows for the reinforcement or reduction of the influence of historical prices based on an exponential function. The Gamma factor (ranging from 0.5 to 1.5) controls how much emphasis is placed on recent data: a value closer to 1 applies an even weighting across periods, while a value closer to 0 diminishes the influence of past prices.
Gamma-based models are used in financial analysis and modeling to enhance a model’s adaptability to changing market dynamics. This weighting mechanism is particularly advantageous in volatile markets such as Bitcoin futures, as it facilitates quick adaptation to changing market conditions (Black-Scholes, 1973).
Strategy Mechanism:
The BTC Future Gamma-Weighted Momentum Model (BGMM) utilizes an adaptive weighting strategy, where the Bitcoin futures prices are weighted according to the Gamma factor to calculate the Gamma-Weighted Average Price (GWAP). The GWAP is derived as a weighted average of prices over a specific number of periods, with more weight assigned to recent periods. The calculated GWAP serves as a reference value, and trading decisions are based on whether the current market price is above or below this level.
1. Long Position Conditions:
A long position is initiated when the Bitcoin price is above the GWAP and a positive price movement is observed over the last three periods. This indicates that an upward trend is in place, and the market is likely to continue in the direction of the momentum.
2. Short Position Conditions:
A short position is initiated when the Bitcoin price is below the GWAP and a negative price movement is observed over the last three periods. This suggests that a downtrend is occurring, and a continuation of the negative price movement is expected.
Backtesting and Application to Bitcoin Futures:
The model has been tested exclusively on the Bitcoin futures market due to Bitcoin’s high volatility and strong trend behavior. These characteristics make the market particularly suitable for momentum strategies, as strong upward or downward movements are often followed by persistent trends that can be captured by a momentum-based approach.
Backtests of the BGMM on the Bitcoin futures market indicate that the model achieves above-average returns during periods of strong momentum, especially when the Gamma factor is optimized to suit the specific dynamics of the Bitcoin market. The high volatility of Bitcoin, combined with adaptive weighting, allows the model to respond quickly to price changes and maximize trading opportunities.
Scientific Citations and Sources:
• Jegadeesh, N., & Titman, S. (1993). Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency. The Journal of Finance, 48(1), 65–91.
• Black, F., & Scholes, M. (1973). The Pricing of Options and Corporate Liabilities. Journal of Political Economy, 81(3), 637–654.
• Fama, E. F., & French, K. R. (1992). The Cross-Section of Expected Stock Returns. The Journal of Finance, 47(2), 427–465.
The RetrieverThis Pine Script strategy, named "The Retriever" aims to capitalize on price dips based on the size of the candlestick body. It uses a moving average of the body size to identify potential long entry points. Here's a breakdown:
Body Size Calculation: It calculates the absolute difference between the close and open prices (body) to determine the candlestick body size.
Entry Signals:
long: A long entry signal is generated when the close price is significantly higher than the moving average of the body size (ta.sma(body, 100)) multiplied by a factor (mult). Thanks to this principle we are entering just bigger dips but just in case it is sudden movement, typically dip during bulish trend.
longExtra: A second, more aggressive long entry signal is generated when the close price is even further above the moving average (multiplied by mult * 2). This signal is very rare and it is helping to decrease entry point in case huge market dips which can occor just few times per year.
Quantity Calculation: The order quantity (qty) is dynamically calculated based on the current equity and the price range between minRange and maxRange. It aims to adjust the quantity inversely to the price range, possibly increasing the quantity when the price range is smaller. It is actually very smart in several ways:
it is making bigger trades when market price is low (closer to manually defined minRange) and vice versa making smaller trades when market is close to maxRange
trade size is calculated based on current equity so it allows to use compound interest effect
as there is no SL in this strategy trade size is calculated to be max around 50-60% drawdown based on backtested results so it can survive 80-90% market drawdowns (entry point is after huge dip)
Exit Conditions: All open positions are closed when either of these conditions is met:
The last candle is green (close is lower than open). There is also minProfit param defined which is set to 0 so it means that our position has to be in profit. So we are never closing in loss. We have to differentiate here between order and position. Order can be in loss but overal position has to be always in profit.
