Squeeze Momentum Indicator Strategy [LazyBear + PineIndicators]The Squeeze Momentum Indicator Strategy (SQZMOM_LB Strategy) is an automated trading strategy based on the Squeeze Momentum Indicator developed by LazyBear, which itself is a modification of John Carter's "TTM Squeeze" concept from his book Mastering the Trade (Chapter 11). This strategy is designed to identify low-volatility phases in the market, which often precede explosive price movements, and to enter trades in the direction of the prevailing momentum.
Concept & Indicator Breakdown
The strategy employs a combination of Bollinger Bands (BB) and Keltner Channels (KC) to detect market squeezes:
Squeeze Condition:
When Bollinger Bands are inside the Keltner Channels (Black Crosses), volatility is low, signaling a potential upcoming price breakout.
When Bollinger Bands move outside Keltner Channels (Gray Crosses), the squeeze is released, indicating an expansion in volatility.
Momentum Calculation:
A linear regression-based momentum value is used instead of traditional momentum indicators.
The momentum histogram is color-coded to show strength and direction:
Lime/Green: Increasing bullish momentum
Red/Maroon: Increasing bearish momentum
Signal Colors:
Black: Market is in a squeeze (low volatility).
Gray: Squeeze is released, and volatility is expanding.
Blue: No squeeze condition is present.
Strategy Logic
The script uses historical volatility conditions and momentum trends to generate buy/sell signals and manage positions.
1. Entry Conditions
Long Position (Buy)
The squeeze just released (Gray Cross after Black Cross).
The momentum value is increasing and positive.
The momentum is at a local low compared to the past 100 bars.
The price is above the 100-period EMA.
The closing price is higher than the previous close.
Short Position (Sell)
The squeeze just released (Gray Cross after Black Cross).
The momentum value is decreasing and negative.
The momentum is at a local high compared to the past 100 bars.
The price is below the 100-period EMA.
The closing price is lower than the previous close.
2. Exit Conditions
Long Exit:
The momentum value starts decreasing (momentum lower than previous bar).
Short Exit:
The momentum value starts increasing (momentum higher than previous bar).
Position Sizing
Position size is dynamically adjusted based on 8% of strategy equity, divided by the current closing price, ensuring risk-adjusted trade sizes.
How to Use This Strategy
Apply on Suitable Markets:
Best for stocks, indices, and forex pairs with momentum-driven price action.
Works on multiple timeframes but is most effective on higher timeframes (1H, 4H, Daily).
Confirm Entries with Additional Indicators:
The author recommends ADX or WaveTrend to refine entries and avoid false signals.
Risk Management:
Since the strategy dynamically sizes positions, it's advised to use stop-losses or risk-based exits to avoid excessive drawdowns.
Final Thoughts
The Squeeze Momentum Indicator Strategy provides a systematic approach to trading volatility expansions, leveraging the classic TTM Squeeze principles with a unique linear regression-based momentum calculation. Originally inspired by John Carter’s method, LazyBear's version and this strategy offer a refined, adaptable tool for traders looking to capitalize on market momentum shifts.
Göstergeler ve stratejiler
Long-Only For SPXThe "GOATED Long-Only" TradingView strategy, written in Pine Script v5, is designed for long-term momentum trading with a $50 initial capital. It identifies high-momentum stocks by calculating a composite momentum score across 3-month (63 days), 6-month (126 days), 9-month (189 days), and 12-month (252 days) periods, using the formula (current_price / past_price) - 1. The strategy filters stocks with annualized volatility below 0.5 (calculated as the standard deviation of daily returns, annualized by multiplying by the square root of 252 trading days) and requires momentum to exceed a customizable threshold (default 0.0). It enters long positions when momentum becomes positive and exits when it turns negative, using stop-loss (1%) and take-profit (50%) levels to manage risk. The strategy visualizes momentum and volatility on the chart, plotting entry/exit signals as green triangles (long entry) and red triangles (long exit) for backtesting and analysis.
Grim SlashOverview:
The Touch Previous Candle Strategy is a simple yet effective trading approach designed for the 1-hour chart. It focuses on price action by placing trades when the current candle interacts with key levels from the previous candle. The strategy is fully automated and includes risk management with take profit and stop loss levels.
Entry Conditions:
Buy Signal: A buy order is triggered when the low of the current candle touches or drops below the previous candle's closing price.
Sell Signal: A position is closed when the high of the current candle reaches or exceeds the previous candle's highest price.
Risk Management:
Take Profit: The trade is exited automatically when the price increases by 15% from the entry point.
Stop Loss: A stop loss is set at 5% below the entry price to minimize risk.
Best Use Cases:
Works well in volatile markets where price frequently tests previous levels.
Suitable for traders who prefer price-action-based strategies over indicators.
Can be optimized for different assets or timeframes based on market behavior.
EMA Scoring Strategy## **📊 EMA Scoring Strategy for Trend Analysis**
This strategy is designed to **identify bullish trends** based on multiple **Exponential Moving Averages (EMAs)**. It assigns a **score** based on how the price and EMAs interact, and highlights strong bullish conditions when the score reaches **4 or above**.
---
## **🔹 Strategy Logic**
### 1️⃣ **Calculating EMAs**
- **EMA 21** → Short-term trend
- **EMA 50** → Mid-term trend
- **EMA 100** → Long-term trend
---
### 2️⃣ **Scoring System**
For each trading day, the strategy assigns **+1 or -1 points** based on the following conditions:
| Condition | Score |
|-----------|-------|
| If **Price > EMA 21** | +1 |
| If **Price > EMA 50** | +1 |
| If **Price > EMA 100** | +1 |
| If **EMA 21 > EMA 50** | +1 |
| If **EMA 50 > EMA 100** | +1 |
| If **EMA 21 > EMA 100** | +1 |
| If **Price < EMA 21** | -1 |
| If **Price < EMA 50** | -1 |
| If **Price < EMA 100** | -1 |
| If **EMA 21 < EMA 50** | -1 |
| If **EMA 50 < EMA 100** | -1 |
| If **EMA 21 < EMA 100** | -1 |
---
### 3️⃣ **Bullish Confirmation** (Score ≥ 4)
- The **score is calculated every day**.
- When the **score reaches 4 or above**, it confirms a strong **bullish trend**.
- A **green background** is applied to highlight such days.
- A **histogram** is plotted **only when the score is 4 or higher** to keep the chart clean.
- A **buy signal** is generated when the score **crosses above 4**.
---
## **🔹 Visualization & Alerts**
### ✅ **What You See on the Chart**
1. **EMA Lines (21, 50, 100)** 📈
2. **Green Background for Strong Bullish Days (Score ≥ 4)** ✅
3. **Histogram Showing Score (Only for 4 and above)** 📊
4. **Buy Signal When Score Crosses Above 4** 💰
### 🔔 **Alerts**
- **An alert is triggered** when the score crosses **above 4**, notifying the user about a bullish trend.
---
## **📌 How to Use This Strategy**
1. **Identify Strong Bullish Trends:** When the score is **4 or above**, it suggests that price momentum is strong.
2. **Enter Trades on Buy Signals:** When the score **crosses above 4**, it could be a good time to buy.
3. **Stay in the Trade While Score is 4+:** The green background confirms a **strong uptrend**.
4. **Exit When Score Drops Below 4:** This suggests weakening momentum.
---
## **🔹 Advantages of This Strategy**
✅ **Simple & Objective** - Uses clear rules for trend confirmation
✅ **Filters Out Noise** - Only highlights strong bullish conditions
✅ **Works on Any Market** - Can be applied to stocks, indices, crypto, etc.
✅ **Customizable** - You can tweak EMAs or score conditions as needed
---
## **🚀 Next Steps**
Would you like me to add **stop-loss conditions**, **sell signals**, or any **extra confirmations like RSI or volume**? 😃
ADX for BTC [PineIndicators]The ADX Strategy for BTC is a trend-following system that uses the Average Directional Index (ADX) to determine market strength and momentum shifts. Designed for Bitcoin trading, this strategy applies a customizable ADX threshold to confirm trend signals and optionally filters entries using a Simple Moving Average (SMA). The system features automated entry and exit conditions, dynamic trade visualization, and built-in trade tracking for historical performance analysis.
⚙️ Core Strategy Components
1️⃣ Average Directional Index (ADX) Calculation
The ADX indicator measures trend strength without indicating direction. It is derived from the Positive Directional Movement (+DI) and Negative Directional Movement (-DI):
+DI (Positive Directional Index): Measures upward price movement.
-DI (Negative Directional Index): Measures downward price movement.
ADX Value: Higher values indicate stronger trends, regardless of direction.
This strategy uses a default ADX length of 14 to smooth out short-term fluctuations while detecting sustainable trends.
2️⃣ SMA Filter (Optional Trend Confirmation)
The strategy includes a 200-period SMA filter to validate trend direction before entering trades. If enabled:
✅ Long Entry is only allowed when price is above a long-term SMA multiplier (5x the standard SMA length).
✅ If disabled, the strategy only considers the ADX crossover threshold for trade entries.
This filter helps reduce entries in sideways or weak-trend conditions, improving signal reliability.
📌 Trade Logic & Conditions
🔹 Long Entry Conditions
A buy signal is triggered when:
✅ ADX crosses above the threshold (default = 14), indicating a strengthening trend.
✅ (If SMA filter is enabled) Price is above the long-term SMA multiplier.
🔻 Exit Conditions
A position is closed when:
✅ ADX crosses below the stop threshold (default = 45), signaling trend weakening.
By adjusting the entry and exit ADX levels, traders can fine-tune sensitivity to trend changes.
📏 Trade Visualization & Tracking
Trade Markers
"Buy" label (▲) appears when a long position is opened.
"Close" label (▼) appears when a position is exited.
Trade History Boxes
Green if a trade is profitable.
Red if a trade closes at a loss.
Trend Tracking Lines
Horizontal lines mark entry and exit prices.
A filled trade box visually represents trade duration and profitability.
These elements provide clear visual insights into trade execution and performance.
⚡ How to Use This Strategy
1️⃣ Apply the script to a BTC chart in TradingView.
2️⃣ Adjust ADX entry/exit levels based on trend sensitivity.
3️⃣ Enable or disable the SMA filter for trend confirmation.
4️⃣ Backtest performance to analyze historical trade execution.
5️⃣ Monitor trade markers and history boxes for real-time trend insights.
This strategy is designed for trend traders looking to capture high-momentum market conditions while filtering out weak trends.
MACD Volume Strategy for XAUUSD (15m) [PineIndicators]The MACD Volume Strategy is a momentum-based trading system designed for XAUUSD on the 15-minute timeframe. It integrates two key market indicators: the Moving Average Convergence Divergence (MACD) and a volume-based oscillator to identify strong trend shifts and confirm trade opportunities. This strategy uses dynamic position sizing, incorporates leverage customization, and applies structured entry and exit conditions to improve risk management.
⚙️ Core Strategy Components
1️⃣ Volume-Based Momentum Calculation
The strategy includes a custom volume oscillator to filter trade signals based on market activity. The oscillator is derived from the difference between short-term and long-term volume trends using Exponential Moving Averages (EMAs)
Short EMA (default = 5) represents recent volume activity.
Long EMA (default = 8) captures broader volume trends.
Positive values indicate rising volume, supporting momentum-based trades.
Negative values suggest weak market activity, reducing signal reliability.
By requiring positive oscillator values, the strategy ensures momentum confirmation before entering trades.
2️⃣ MACD Trend Confirmation
The strategy uses the MACD indicator as a trend filter. The MACD is calculated as:
Fast EMA (16-period) detects short-term price trends.
Slow EMA (26-period) smooths out price fluctuations to define the overall trend.
Signal Line (9-period EMA) helps identify crossovers, signaling potential trend shifts.
Histogram (MACD – Signal) visualizes trend strength.
The system generates trade signals based on MACD crossovers around the zero line, confirming bullish or bearish trend shifts.
📌 Trade Logic & Conditions
🔹 Long Entry Conditions
A buy signal is triggered when all the following conditions are met:
✅ MACD crosses above 0, signaling bullish momentum.
✅ Volume oscillator is positive, confirming increased trading activity.
✅ Current volume is at least 50% of the previous candle’s volume, ensuring market participation.
🔻 Short Entry Conditions
A sell signal is generated when:
✅ MACD crosses below 0, indicating bearish momentum.
✅ Volume oscillator is positive, ensuring market activity is sufficient.
✅ Current volume is less than 50% of the previous candle’s volume, showing decreasing participation.
This multi-factor approach filters out weak or false signals, ensuring that trades align with both momentum and volume dynamics.
📏 Position Sizing & Leverage
Dynamic Position Calculation:
Qty = strategy.equity × leverage / close price
Leverage: Customizable (default = 1x), allowing traders to adjust risk exposure.
Adaptive Sizing: The strategy scales position sizes based on account equity and market price.
Slippage & Commission: Built-in slippage (2 points) and commission (0.01%) settings provide realistic backtesting results.
This ensures efficient capital allocation, preventing overexposure in volatile conditions.
🎯 Trade Management & Exits
Take Profit & Stop Loss Mechanism
Each position includes predefined profit and loss targets:
Take Profit: +10% of risk amount.
Stop Loss: Fixed at 10,100 points.
The risk-reward ratio remains balanced, aiming for controlled drawdowns while maximizing trade potential.
Visual Trade Tracking
To improve trade analysis, the strategy includes:
📌 Trade Markers:
"Buy" label when a long position opens.
"Close" label when a position exits.
📌 Trade History Boxes:
Green for profitable trades.
Red for losing trades.
📌 Horizontal Trade Lines:
Shows entry and exit prices.
Helps identify trend movements over multiple trades.
This structured visualization allows traders to analyze past performance directly on the chart.
⚡ How to Use This Strategy
1️⃣ Apply the script to a XAUUSD (Gold) 15m chart in TradingView.
2️⃣ Adjust leverage settings as needed.
3️⃣ Enable backtesting to assess past performance.
4️⃣ Monitor volume and MACD conditions to understand trade triggers.
5️⃣ Use the visual trade markers to review historical performance.
The MACD Volume Strategy is designed for short-term trading, aiming to capture momentum-driven opportunities while filtering out weak signals using volume confirmation.
Balance of Power for US30 4H [PineIndicators]The Balance of Power (BoP) Strategy is a momentum-based trading system for the US30 index on a 4-hour timeframe. It measures the strength of buyers versus sellers in each candle using the Balance of Power (BoP) indicator and executes trades based on predefined threshold crossovers. The strategy includes dynamic position sizing, adjustable leverage, and visual trade tracking.
⚙️ Core Strategy Mechanics
Positive values indicate buying strength.
Negative values indicate selling strength.
Values close to 1 suggest strong bullish momentum.
Values close to -1 indicate strong bearish pressure.
The strategy uses fixed threshold crossovers to determine trade entries and exits.
📌 Trade Logic
Entry Conditions
Long Entry: When BoP crosses above 0.8, signaling strong buying pressure.
Exit Conditions
Position Close: When BoP crosses below -0.8, indicating a shift to selling pressure.
This threshold-based system filters out low-confidence signals and focuses on high-momentum shifts.
📏 Position Sizing & Leverage
Leverage: Adjustable by the user (default = 5x).
Risk Management: Position size adapts dynamically based on equity fluctuations.
📊 Trade Visualization & History Tracking
Trade Markers:
"Buy" labels appear when a long position is opened.
"Close" labels appear when a position is exited.
Trade History Boxes:
Green for profitable trades.
Red for losing trades.
These elements provide clear visual tracking of past trade execution.
⚡ Usage & Customization
1️⃣ Apply the script to a US30 4H chart in TradingView.
2️⃣ Adjust leverage settings as needed.
3️⃣ Review trade signals and historical performance with visual markers.
4️⃣ Enable backtesting to evaluate past performance.
This strategy is designed for momentum-based trading and is best suited for volatile market conditions.
Supertrend pro+ (Adaptive ATR) Supertrend Pro+ (Adaptive ATR) - Param Approach
By SKP
Overview
This advanced Supertrend Pro+ strategy improves on the classic Supertrend indicator by integrating an Adaptive ATR, ensuring dynamic volatility adjustments for more accurate trend detection. This strategy filters out false signals using ADX trend strength validation and volume confirmation, making it a powerful tool for trend-following traders.
Key Features
✔ Adaptive ATR Calculation - Dynamically adjusts to market volatility for more reliable Supertrend signals.
✔ ADX Trend Filter - Ensures trades occur only in strong trending markets, avoiding false breakouts.
✔ Volume Confirmation - Prevents trading in low-liquidity conditions by verifying volume strength.
✔ Multi-Timeframe Analysis - Displays Supertrend trends from different timeframes for enhanced trade confidence.
✔ Trailing Stop & Take Profit Options - Allows flexible risk management with stop-loss and profit-targeting mechanisms.
✔ Custom Alerts for Trade Signals - Alerts trigger on confirmed Supertrend buy/sell signals and potential trend shifts.
✔ Max Drawdown Protection - Automatically closes trades if equity drops beyond a set percentage, preventing excessive losses.
How It Works
Adaptive ATR Calculation
Instead of using a fixed ATR, this strategy calculates an adaptive ATR based on a longer-term ATR baseline.
If volatility increases, the ATR expands dynamically, ensuring stop-losses and Supertrend calculations adjust accordingly.
Supertrend Confirmation
Uses an enhanced Supertrend algorithm with adaptive ATR to determine trend direction.
If price crosses above the trendline, it signals a bullish reversal (Buy Signal).
If price crosses below the trendline, it signals a bearish reversal (Sell Signal).
ADX Trend Strength Filter
Trades are only taken when ADX is above the threshold, ensuring entry in strong trending markets.
Volume Confirmation
Uses a relative volume filter to ensure sufficient liquidity before entering trades.
Helps avoid false breakouts in low-volume conditions.
Risk Management
Trailing Stop Loss - Automatically moves the stop as price moves in favor of the trade.
Manual Stop Loss & Take Profit - Allows precise percentage-based exit points.
Max Drawdown Protection - Closes all trades if equity falls below a set threshold, reducing risk.
Multi-Timeframe Supertrend Table
Displays Supertrend signals across different timeframes (1 min, 5 min, 15 min, 1 hour, Daily)
Helps traders align their entries with higher timeframe trends for better accuracy.
Custom Alerts
Alerts notify when a new buy/sell signal appears.
Extra early warning alerts indicate potential trade setups before confirmation.
How to Use
📌 For trend-following traders:
Focus on entries in the direction of the higher timeframes.
Only enter when ADX is trending and volume confirms liquidity.
📌 For scalpers:
Use shorter timeframes (1m, 5m, 15m) for quick trades.
Adjust the ATR multiplier and Adaptive ATR sensitivity for tighter stops.
📌 For swing traders:
Use longer timeframes (1H, Daily) for more stable trends.
Enable trailing stop loss to lock in profits as the trend progresses.
Inputs & Customization
ATR Period & Adaptive ATR Sensitivity
Supertrend Multiplier
ADX Filter & Threshold
Volume Confirmation Settings
Stop Loss & Take Profit Options
Multi-Timeframe Supertrend Display
Custom Alerts
Bot for Spot Market - Custom GridThis script is designed to create a trading bot for the spot market, specifically for buying and selling bitcoins profitably. Recommended for timeframes above two hours. Here are the main functions and features of the script:
Strategy Setup: The bot is set up with a custom grid strategy, defining parameters like pyramiding (allowed number of simultaneous trades), margin requirements, commission, and initial capital.
Order Requirements: It calculates the order price and amount based on the minimum requirements set by the exchange and rounds them appropriately.
Entry Conditions: The bot makes new entries if the closing price falls a certain percentage below the last entry price. It continues to make entries until the closing price rises a certain percentage above the average entry price.
Targets and Plots:
It calculates and plots the target profit level.
It plots the average entry price and the last entry price.
It plots the next entry price based on the defined conditions.
It plots the maximum number of orders allowed based on equity and the number of open orders.
Timerange: The bot can start trading from a specific date and time defined by the user.
Entries: It places orders if the timerange conditions are met. It also places new orders if the closing price is below the last entry price by a defined percentage.
Profit Calculation: The script calculates open profit or loss for the open positions.
Exit Conditions: It closes all positions if the open profit is positive and the closing price is above the target profit level.
Performance Table: The bot maintains and displays statistics like the number of open and closed trades, net profit, and equity in a table format.
The script is customizable, allowing users to adjust parameters like initial capital, commission, order values, and profit targets to fit their specific trading needs and exchange requirements.
NSE Index Strategy with Entry/Exit MarkersExplanation of the Code
Trend Filter (200 SMA):
The line trendSMA = ta.sma(close, smaPeriod) calculates the 200‑period simple moving average. By trading only when the current price is above this SMA (inUptrend = close > trendSMA), we aim to trade in the direction of the dominant trend.
RSI Entry Signal:
The RSI is calculated with rsiValue = ta.rsi(close, rsiPeriod). The script checks for an RSI crossover above the oversold threshold using ta.crossover(rsiValue, rsiOversold). This helps capture a potential reversal from a minor pullback in an uptrend.
ATR-Based Exits:
ATR is computed by atrValue = ta.atr(atrPeriod) and is used to set the stop loss and take profit levels:
Stop Loss: stopLossPrice = close - atrMultiplier * atrValue
Take Profit: takeProfitPrice = close + atrMultiplier * atrValue
This dynamic approach allows the exit levels to adjust according to the current market volatility.
Risk and Money Management:
The strategy uses a fixed percentage of equity (10% by default) for each trade. The built‑in commission parameter helps simulate real-world trading costs.
Supertrend Strategy with Money Ocean TradeStrategy Overview
The Supertrend Strategy with Trend Change Confirmation leverages the Supertrend indicator to identify potential buy and sell signals based on changes in trend direction and subsequent price action. The strategy is designed to work with any financial instrument (symbol) and aims to provide clear entry and exit signals.
Key Components
Supertrend Indicator: The core of this strategy is the Supertrend indicator, calculated using a length of 3 and a factor of 1. The Supertrend line is plotted on the chart to visually represent trend direction.
Direction 1: Indicates an uptrend (bullish).
Direction -1: Indicates a downtrend (bearish).
Trend Change Detection: The strategy monitors changes in the trend direction. When a trend change is detected, it checks if the next candle confirms the trend change by breaking above or below the Supertrend line.
Entry Conditions:
Long Entry (Buy): When the Supertrend direction changes to 1 (uptrend) and the next candle closes above the Supertrend line.
Short Entry (Sell): When the Supertrend direction changes to -1 (downtrend) and the next candle closes below the Supertrend line.
Exit Conditions: The strategy closes the position based on the opposite signal.
Long Exit: When the Supertrend direction changes to -1 (downtrend) and the next candle closes below the Supertrend line.
Short Exit: When the Supertrend direction changes to 1 (uptrend) and the next candle closes above the Supertrend line.
Visual Signals: The strategy plots buy and sell signals on the chart using plotshape:
BUY: A green label below the bar when a long entry is triggered.
SELL: A red label above the bar when a short entry is triggered.
Alerts: Alerts are set up to notify when a buy or sell signal is triggered.
Script Summary
This strategy helps traders identify potential trading opportunities based on trend changes and confirms the trend by checking the next candle's price action. The visual signals and dashboard enhance the user's ability to monitor and manage trades effectively.
Feel free to test and adjust the parameters to suit your trading preferences! If you need further customizations or explanations, let me know.
GM+For a Short Trade:
When a bullish candle (close > open) is larger than the previous candle and the MACD histogram for the past three bars is consecutively lower (suggesting weakening upward momentum), the script enters a short position.
For a Long Trade:
When a bearish candle (close < open) is larger (in body size) than the previous candle and the MACD histogram for the past three bars is consecutively higher (suggesting the downward move is losing strength), the script enters a long position.
Position Management:
There are no stop loss or take profit levels. The position is closed only when an opposite signal appears.
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.
AO/AC Trading Zones Strategy [Skyrexio] Overview
AO/AC Trading Zones Strategy leverages the combination of Awesome Oscillator (AO), Acceleration/Deceleration Indicator (AC), Williams Fractals, Williams Alligator and Exponential Moving Average (EMA) to obtain the high probability long setups. Moreover, strategy uses multi trades system, adding funds to long position if it considered that current trend has likely became stronger. Combination of AO and AC is used for creating so-called trading zones to create the signals, while Alligator and Fractal are used in conjunction as an approximation of short-term trend to filter them. At the same time EMA (default EMA's period = 100) is used as high probability long-term trend filter to open long trades only if it considers current price action as an uptrend. More information in "Methodology" and "Justification of Methodology" paragraphs. The strategy opens only long trades.
Unique Features
No fixed stop-loss and take profit: Instead of fixed stop-loss level strategy utilizes technical condition obtained by Fractals and Alligator to identify when current uptrend is likely to be over. In some special cases strategy uses AO and AC combination to trail profit (more information in "Methodology" and "Justification of Methodology" paragraphs)
Configurable Trading Periods: Users can tailor the strategy to specific market windows, adapting to different market conditions.
Multilayer trades opening system: strategy uses only 10% of capital in every trade and open up to 5 trades at the same time if script consider current trend as strong one.
Short and long term trend trade filters: strategy uses EMA as high probability long-term trend filter and Alligator and Fractal combination as a short-term one.
Methodology
The strategy opens long trade when the following price met the conditions:
1. Price closed above EMA (by default, period = 100). Crossover is not obligatory.
2. Combination of Alligator and Williams Fractals shall consider current trend as an upward (all details in "Justification of Methodology" paragraph)
3. Both AC and AO shall print two consecutive increasing values. At the price candle close which corresponds to this condition algorithm opens the first long trade with 10% of capital.
4. If combination of Alligator and Williams Fractals shall consider current trend has been changed from up to downtrend, all long trades will be closed, no matter how many trades has been opened.
5. If AO and AC both continue printing the rising values strategy opens the long trade on each candle close with 10% of capital while number of opened trades reaches 5.
6. If AO and AC both has printed 5 rising values in a row algorithm close all trades if candle's low below the low of the 5-th candle with rising AO and AC values in a row.
Script also has additional visuals. If second long trade has been opened simultaneously the Alligator's teeth line is plotted with the green color. Also for every trade in a row from 2 to 5 the label "Buy More" is also plotted just below the teeth line. With every next simultaneously opened trade the green color of the space between teeth and price became less transparent.
Strategy settings
In the inputs window user can setup strategy setting:
EMA Length (by default = 100, period of EMA, used for long-term trend filtering EMA calculation).
User can choose the optimal parameters during backtesting on certain price chart.
Justification of Methodology
Let's explore the key concepts of this strategy and understand how they work together. We'll begin with the simplest: the EMA.
The Exponential Moving Average (EMA) is a type of moving average that assigns greater weight to recent price data, making it more responsive to current market changes compared to the Simple Moving Average (SMA). This tool is widely used in technical analysis to identify trends and generate buy or sell signals. The EMA is calculated as follows:
1.Calculate the Smoothing Multiplier:
Multiplier = 2 / (n + 1), Where n is the number of periods.
2. EMA Calculation
EMA = (Current Price) × Multiplier + (Previous EMA) × (1 − Multiplier)
In this strategy, the EMA acts as a long-term trend filter. For instance, long trades are considered only when the price closes above the EMA (default: 100-period). This increases the likelihood of entering trades aligned with the prevailing trend.
Next, let’s discuss the short-term trend filter, which combines the Williams Alligator and Williams Fractals. Williams Alligator
Developed by Bill Williams, the Alligator is a technical indicator that identifies trends and potential market reversals. It consists of three smoothed moving averages:
Jaw (Blue Line): The slowest of the three, based on a 13-period smoothed moving average shifted 8 bars ahead.
Teeth (Red Line): The medium-speed line, derived from an 8-period smoothed moving average shifted 5 bars forward.
Lips (Green Line): The fastest line, calculated using a 5-period smoothed moving average shifted 3 bars forward.
When the lines diverge and align in order, the "Alligator" is "awake," signaling a strong trend. When the lines overlap or intertwine, the "Alligator" is "asleep," indicating a range-bound or sideways market. This indicator helps traders determine when to enter or avoid trades.
Fractals, another tool by Bill Williams, help identify potential reversal points on a price chart. A fractal forms over at least five consecutive bars, with the middle bar showing either:
Up Fractal: Occurs when the middle bar has a higher high than the two preceding and two following bars, suggesting a potential downward reversal.
Down Fractal: Happens when the middle bar shows a lower low than the surrounding two bars, hinting at a possible upward reversal.
Traders often use fractals alongside other indicators to confirm trends or reversals, enhancing decision-making accuracy.
How do these tools work together in this strategy? Let’s consider an example of an uptrend.
When the price breaks above an up fractal, it signals a potential bullish trend. This occurs because the up fractal represents a shift in market behavior, where a temporary high was formed due to selling pressure. If the price revisits this level and breaks through, it suggests the market sentiment has turned bullish.
The breakout must occur above the Alligator’s teeth line to confirm the trend. A breakout below the teeth is considered invalid, and the downtrend might still persist. Conversely, in a downtrend, the same logic applies with down fractals.
In this strategy if the most recent up fractal breakout occurs above the Alligator's teeth and follows the last down fractal breakout below the teeth, the algorithm identifies an uptrend. Long trades can be opened during this phase if a signal aligns. If the price breaks a down fractal below the teeth line during an uptrend, the strategy assumes the uptrend has ended and closes all open long trades.
By combining the EMA as a long-term trend filter with the Alligator and fractals as short-term filters, this approach increases the likelihood of opening profitable trades while staying aligned with market dynamics.
Now let's talk about the trading zones concept and its signals. To understand this we need to briefly introduce what is AO and AC. The Awesome Oscillator (AO), developed by Bill Williams, is a momentum indicator designed to measure market momentum by contrasting recent price movements with a longer-term historical perspective. It helps traders detect potential trend reversals and assess the strength of ongoing trends.
The formula for AO is as follows:
AO = SMA5(Median Price) − SMA34(Median Price)
where:
Median Price = (High + Low) / 2
SMA5 = 5-period Simple Moving Average of the Median Price
SMA 34 = 34-period Simple Moving Average of the Median Price
The Acceleration/Deceleration (AC) Indicator, introduced by Bill Williams, measures the rate of change in market momentum. It highlights shifts in the driving force of price movements and helps traders spot early signs of trend changes. The AC Indicator is particularly useful for identifying whether the current momentum is accelerating or decelerating, which can indicate potential reversals or continuations. For AC calculation we shall use the AO calculated above is the following formula:
AC = AO − SMA5(AO) , where SMA5(AO)is the 5-period Simple Moving Average of the Awesome Oscillator
When the AC is above the zero line and rising, it suggests accelerating upward momentum.
When the AC is below the zero line and falling, it indicates accelerating downward momentum.
When the AC is below zero line and rising it suggests the decelerating the downtrend momentum. When AC is above the zero line and falling, it suggests the decelerating the uptrend momentum.
Now let's discuss the trading zones concept and how it can create the signal. Zones are created by the combination of AO and AC. We can divide three zone types:
Greed zone: when the AO and AC both are rising
Red zone: when the AO and AC both are decreasing
Gray zone: when one of AO or AC is rising, the other is falling
Gray zone is considered as uncertainty. AC and AO are moving in the opposite direction. Strategy skip such price action to decrease the chance to stuck in the losing trade during potential sideways. Red zone is also not interesting for the algorithm because both indicators consider the trend as bearish, but strategy opens only long trades. It is waiting for the green zone to increase the chance to open trade in the direction of the potential uptrend. When we have 2 candles in a row in the green zone script executes a long trade with 10% of capital.
Two green zone candles in a row is considered by algorithm as a bullish trend, but now so strong, that's the reason why trade is going to be closed when the combination of Alligator and Fractals will consider the the trend change from bullish to bearish. If id did not happens, algorithm starts to count the green zone candles in a row. When we have 5 in a row script change the trade closing condition. Such situation is considered is a high probability strong bull market and all trades will be closed if candle's low will be lower than fifth green zone candle's low. This is used to increase probability to secure the profit. If long trades are initiated, the strategy continues utilizing subsequent signals until the total number of trades reaches a maximum of 5. Each trade uses 10% of capital.
Why we use trading zones signals? If currently strategy algorithm considers the high probability of the short-term uptrend with the Alligator and Fractals combination pointed out above and the long-term trend is also suggested by the EMA filter as bullish. Rising AC and AO values in the direction of the most likely main trend signaling that we have the high probability of the fastest bullish phase on the market. The main idea is to take part in such rapid moves and add trades if this move continues its acceleration according to indicators.
Backtest Results
Operating window: Date range of backtests is 2023.01.01 - 2024.12.31. It is chosen to let the strategy to close all opened positions.
Commission and Slippage: Includes a standard Binance commission of 0.1% and accounts for possible slippage over 5 ticks.
Initial capital: 10000 USDT
Percent of capital used in every trade: 10%
Maximum Single Position Loss: -9.49%
Maximum Single Profit: +24.33%
Net Profit: +4374.70 USDT (+43.75%)
Total Trades: 278 (39.57% win rate)
Profit Factor: 2.203
Maximum Accumulated Loss: 668.16 USDT (-5.43%)
Average Profit per Trade: 15.74 USDT (+1.37%)
Average Trade Duration: 60 hours
How to Use
Add the script to favorites for easy access.
Apply to the desired timeframe and chart (optimal performance observed on 4h BTC/USDT).
Configure settings using the dropdown choice list in the built-in menu.
Set up alerts to automate strategy positions through web hook with the text: {{strategy.order.alert_message}}
Disclaimer:
Educational and informational tool reflecting Skyrex commitment to informed trading. Past performance does not guarantee future results. Test strategies in a simulated environment before live implementation
These results are obtained with realistic parameters representing trading conditions observed at major exchanges such as Binance and with realistic trading portfolio usage parameters.
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.
[SHORT ONLY] 10 Bar Low Pullback█ STRATEGY DESCRIPTION
The "10 Bar Low Pullback" strategy is a contrarian short trading system designed to capture pullbacks after a new 10‐bar low is made. it identifies a potential short opportunity when the current bar’s low breaks below the lowest low of the previous 10 bars, provided that the bar exhibits strong internal momentum as measured by its IBS value. An optional trend filter further refines entries by requiring that the close is below a 200-period EMA.
█ WHAT IS INTERNAL BAR STRENGTH (IBS)?
Internal Bar Strength (IBS) measures where the closing price falls within the high-low range of a bar. It is calculated as:
ibs = (close - low) / (high - low)
- Low IBS (≤ 0.2): Indicates the close is near the bar's low, suggesting oversold conditions.
- High IBS (≥ 0.8): Indicates the close is near the bar's high, suggesting overbought conditions.
█ SIGNAL GENERATION
1. SHORT ENTRY
A Short Signal is triggered when:
The current bar’s low is below the lowest low of the past X bars (default: 10).
The bar’s IBS is greater than the specified threshold (default: 0.85).
The signal occurs within the defined trading window (between Start Time and End Time).
If the EMA Filter is enabled, the close must be below the 200-period EMA.
2. EXIT CONDITION
An exit Signal is generated when the current close falls below the previous bar’s low (close < low ), indicating a potential bearish reversal and prompting the strategy to close its short position.
█ ADDITIONAL SETTINGS
Lookback Period: Defines the number of bars (default is 10) over which the lowest low is calculated.
IBS Threshold: Sets the minimum required IBS value (default is 0.85) to qualify as a pullback.
Trading Window: Trades are only executed between the user-defined Start Time and End Time.
EMA Filter (Optional): When enabled, short entries are only considered if the current close is below the 200-period EMA, with the EMA period being adjustable (default is 200).
█ PERFORMANCE OVERVIEW
Designed for shorting opportunities, this strategy aims to capture pullbacks following an aggressive 10-bar low break.
It leverages a combination of a lookback low and IBS measurement to identify overextended bullish moves that may revert.
The optional EMA filter helps confirm a bearish market environment by ensuring the price remains under the trend line.
Suitable for use on various assets, including stocks and ETFs, on daily or similar timeframes.
Backtesting and parameter optimization are recommended to tailor the strategy to specific market conditions.
[SHORT ONLY] ATR Sell the Rip Mean Reversion Strategy█ STRATEGY DESCRIPTION
The "ATR Sell the Rip Mean Reversion Strategy" is a contrarian system that targets overextended price moves on stocks and ETFs. It calculates an ATR‐based trigger level to identify shorting opportunities. When the current close exceeds this smoothed ATR trigger, and if the close is below a 200-period EMA (if enabled), the strategy initiates a short entry, aiming to profit from an anticipated corrective pullback.
█ HOW IS THE ATR SIGNAL BAND CALCULATED?
This strategy computes an ATR-based signal trigger as follows:
Calculate the ATR
The strategy computes the Average True Range (ATR) using a configurable period provided by the user:
atrValue = ta.atr(atrPeriod)
Determine the Threshold
Multiply the ATR by a predefined multiplier and add it to the current close:
atrThreshold = close + atrValue * atrMultInput
Smooth the Threshold
Apply a Simple Moving Average over a specified period to smooth out the threshold, reducing noise:
signalTrigger = ta.sma(atrThreshold, smoothPeriodInput)
█ SIGNAL GENERATION
1. SHORT ENTRY
A Short Signal is triggered when:
The current close is above the smoothed ATR signal trigger.
The trade occurs within the specified trading window (between Start Time and End Time).
If the EMA filter is enabled, the close must also be below the 200-period EMA.
2. EXIT CONDITION
An exit Signal is generated when the current close falls below the previous bar’s low (close < low ), indicating a potential bearish reversal and prompting the strategy to close its short position.
█ ADDITIONAL SETTINGS
ATR Period: The period used to calculate the ATR, allowing for adaptability to different volatility conditions (default is 20).
ATR Multiplier: The multiplier applied to the ATR to determine the raw threshold (default is 1.0).
Smoothing Period: The period over which the raw ATR threshold is smoothed using an SMA (default is 10).
Start Time and End Time: Defines the time window during which trades are allowed.
EMA Filter (Optional): When enabled, short entries are only executed if the current close is below the 200-period EMA, confirming a bearish trend.
█ PERFORMANCE OVERVIEW
This strategy is designed for use on the Daily timeframe, targeting stocks and ETFs by capitalizing on overextended price moves.
It utilizes a dynamic, ATR-based trigger to identify when prices have potentially peaked, setting the stage for a mean reversion short entry.
The optional EMA filter helps align trades with broader market trends, potentially reducing false signals.
Backtesting is recommended to fine-tune the ATR multiplier, smoothing period, and EMA settings to match the volatility and behavior of specific markets.
TSI Long/Short for BTC 2HThe TSI Long/Short for BTC 2H strategy is an advanced trend-following system designed specifically for trading Bitcoin (BTC) on a 2-hour timeframe. It leverages the True Strength Index (TSI) to identify momentum shifts and executes both long and short trades in response to dynamic market conditions.
Unlike traditional moving average-based strategies, this script uses a double-smoothed momentum calculation, enhancing signal accuracy and reducing noise. It incorporates automated position sizing, customizable leverage, and real-time performance tracking, ensuring a structured and adaptable trading approach.
🔹 What Makes This Strategy Unique?
Unlike simple crossover strategies or generic trend-following approaches, this system utilizes a customized True Strength Index (TSI) methodology that dynamically adjusts to market conditions.
🔸 True Strength Index (TSI) Filtering – The script refines the TSI by applying double exponential smoothing, filtering out weak signals and capturing high-confidence momentum shifts.
🔸 Adaptive Entry & Exit Logic – Instead of fixed thresholds, it compares the TSI value against a dynamically determined high/low range from the past 100 bars to confirm trade signals.
🔸 Leverage & Risk Optimization – Position sizing is dynamically adjusted based on account equity and leverage settings, ensuring controlled risk exposure.
🔸 Performance Monitoring System – A built-in performance tracking table allows traders to evaluate monthly and yearly results directly on the chart.
📊 Core Strategy Components
1️⃣ Momentum-Based Trade Execution
The strategy generates long and short trade signals based on the following conditions:
✅ Long Entry Condition – A buy signal is triggered when the TSI crosses above its 100-bar highest value (previously set), confirming bullish momentum.
✅ Short Entry Condition – A sell signal is generated when the TSI crosses below its 100-bar lowest value (previously set), indicating bearish pressure.
Each trade execution is fully automated, reducing emotional decision-making and improving trading discipline.
2️⃣ Position Sizing & Leverage Control
Risk management is a key focus of this strategy:
🔹 Dynamic Position Sizing – The script calculates position size based on:
Account Equity – Ensuring trade sizes adjust dynamically with capital fluctuations.
Leverage Multiplier – Allows traders to customize risk exposure via an adjustable leverage setting.
🔹 No Fixed Stop-Loss – The strategy relies on reversals to exit trades, meaning each position is closed when the opposite signal appears.
This design ensures maximum capital efficiency while adapting to market conditions in real time.
3️⃣ Performance Visualization & Tracking
Understanding historical performance is crucial for refining strategies. The script includes:
📌 Real-Time Trade Markers – Buy and sell signals are visually displayed on the chart for easy reference.
📌 Performance Metrics Table – Tracks monthly and yearly returns in percentage form, helping traders assess profitability over time.
📌 Trade History Visualization – Completed trades are displayed with color-coded boxes (green for long trades, red for short trades), visually representing profit/loss dynamics.
📢 Why Use This Strategy?
✔ Advanced Momentum Detection – Uses a double-smoothed TSI for more accurate trend signals.
✔ Fully Automated Trading – Removes emotional bias and enforces discipline.
✔ Customizable Risk Management – Adjust leverage and position sizing to suit your risk profile.
✔ Comprehensive Performance Tracking – Integrated reporting system provides clear insights into past trades.
This strategy is ideal for Bitcoin traders looking for a structured, high-probability system that adapts to both bullish and bearish trends on the 2-hour timeframe.
📌 How to Use: Simply add the script to your 2H BTC chart, configure your leverage settings, and let the system handle trade execution and tracking! 🚀
[SHORT ONLY] Consecutive Bars Above MA Strategy█ STRATEGY DESCRIPTION
The "Consecutive Bars Above MA Strategy" is a contrarian trading system aimed at exploiting overextended bullish moves in stocks and ETFs. It monitors the number of consecutive bars that close above a chosen short-term moving average (which can be either a Simple Moving Average or an Exponential Moving Average). Once the count reaches a preset threshold and the current bar’s close exceeds the previous bar’s high within a designated trading window, a short entry is initiated. An optional EMA filter further refines entries by requiring that the current close is below the 200-period EMA, helping to ensure that trades are taken in a bearish environment.
█ HOW ARE THE CONSECUTIVE BULLISH COUNTS CALCULATED?
The strategy utilizes a counter variable, `bullCount`, to track consecutive bullish bars based on their relation to the short-term moving average. Here’s how the count is determined:
Initialize the Counter
The counter is initialized at the start:
var int bullCount = na
Bullish Bar Detection
For each bar, if the close is above the selected moving average (either SMA or EMA, based on user input), the counter is incremented:
bullCount := close > signalMa ? (na(bullCount) ? 1 : bullCount + 1) : 0
Reset on Non-Bullish Condition
If the close does not exceed the moving average, the counter resets to zero, indicating a break in the consecutive bullish streak.
█ SIGNAL GENERATION
1. SHORT ENTRY
A short signal is generated when:
The number of consecutive bullish bars (i.e., bars closing above the short-term MA) meets or exceeds the defined threshold (default: 3).
The current bar’s close is higher than the previous bar’s high.
The signal occurs within the specified trading window (between Start Time and End Time).
Additionally, if the EMA filter is enabled, the entry is only executed when the current close is below the 200-period EMA.
2. EXIT CONDITION
An exit signal is triggered when the current close falls below the previous bar’s low, prompting the strategy to close the short position.
█ ADDITIONAL SETTINGS
Threshold: The number of consecutive bullish bars required to trigger a short entry (default is 3).
Trading Window: The Start Time and End Time inputs define when the strategy is active.
Moving Average Settings: Choose between SMA and EMA, and set the MA length (default is 5), which is used to assess each bar’s bullish condition.
EMA Filter (Optional): When enabled, this filter requires that the current close is below the 200-period EMA, supporting entries in a downtrend.
█ PERFORMANCE OVERVIEW
This strategy is designed for stocks and ETFs and can be applied across various timeframes.
It seeks to capture mean reversion by shorting after a series of bullish bars suggests an overextended move.
The approach employs a contrarian short entry by waiting for a breakout (close > previous high) following consecutive bullish bars.
The adjustable moving average settings and optional EMA filter allow for further optimization based on market conditions.
Comprehensive backtesting is recommended to fine-tune the threshold, moving average parameters, and filter settings for optimal performance.
[SHORT ONLY] Consecutive Close>High[1] Mean Reversion Strategy█ STRATEGY DESCRIPTION
The "Consecutive Close > High " Mean Reversion Strategy is a contrarian daily trading system for stocks and ETFs. It identifies potential shorting opportunities by counting consecutive days where the closing price exceeds the previous day's high. When this consecutive day count reaches a predetermined threshold, and if the close is below a 200-period EMA (if enabled), a short entry is triggered, anticipating a corrective pullback.
█ HOW ARE THE CONSECUTIVE BULLISH COUNTS CALCULATED?
The strategy uses a counter variable called `bullCount` to track how many consecutive bars meet a bullish condition. Here’s a breakdown of the process:
Initialize the Counter
var int bullCount = 0
Bullish Bar Detection
Every time the close exceeds the previous bar's high, increment the counter:
if close > high
bullCount += 1
Reset on Bearish Bar
When there is a clear bearish reversal, the counter is reset to zero:
if close < low
bullCount := 0
█ SIGNAL GENERATION
1. SHORT ENTRY
A Short Signal is triggered when:
The count of consecutive bullish closes (where close > high ) reaches or exceeds the defined threshold (default: 3).
The signal occurs within the specified trading window (between Start Time and End Time).
2. EXIT CONDITION
An exit Signal is generated when the current close falls below the previous bar’s low (close < low ), prompting the strategy to exit the position.
█ ADDITIONAL SETTINGS
Threshold: The number of consecutive bullish closes required to trigger a short entry (default is 3).
Start Time and End Time: The time window during which the strategy is allowed to execute trades.
EMA Filter (Optional): When enabled, short entries are only triggered if the current close is below the 200-period EMA.
█ PERFORMANCE OVERVIEW
This strategy is designed for Stocks and ETFs on the Daily timeframe and targets overextended bullish moves.
It aims to capture mean reversion by entering short after a series of consecutive bullish closes.
Further optimization is possible with additional filters (e.g., EMA, volume, or volatility).
Backtesting should be used to fine-tune the threshold and filter settings for specific market conditions.
[SHORT ONLY] Internal Bar Strength (IBS) Mean Reversion Strategy█ STRATEGY DESCRIPTION
The "Internal Bar Strength (IBS) Strategy" is a mean-reversion strategy designed to identify trading opportunities based on the closing price's position within the daily price range. It enters a short position when the IBS indicates overbought conditions and exits when the IBS reaches oversold levels. This strategy is Short-Only and was designed to be used on the Daily timeframe for Stocks and ETFs.
█ WHAT IS INTERNAL BAR STRENGTH (IBS)?
Internal Bar Strength (IBS) measures where the closing price falls within the high-low range of a bar. It is calculated as:
IBS = (Close - Low) / (High - Low)
- Low IBS (≤ 0.2) : Indicates the close is near the bar's low, suggesting oversold conditions.
- High IBS (≥ 0.8) : Indicates the close is near the bar's high, suggesting overbought conditions.
█ SIGNAL GENERATION
1. SHORT ENTRY
A Short Signal is triggered when:
The IBS value rises to or above the Upper Threshold (default: 0.9).
The Closing price is greater than the previous bars High (close>high ).
The signal occurs within the specified time window (between `Start Time` and `End Time`).
2. EXIT CONDITION
An exit Signal is generated when the IBS value drops to or below the Lower Threshold (default: 0.3). This prompts the strategy to exit the position.
█ ADDITIONAL SETTINGS
Upper Threshold: The IBS level at which the strategy enters trades. Default is 0.9.
Lower Threshold: The IBS level at which the strategy exits short positions. Default is 0.3.
Start Time and End Time: The time window during which the strategy is allowed to execute trades.
█ PERFORMANCE OVERVIEW
This strategy is designed for Stocks and ETFs markets and performs best when prices frequently revert to the mean.
The strategy can be optimized further using additional conditions such as using volume or volatility filters.
It is sensitive to extreme IBS values, which help identify potential reversals.
Backtesting results should be analyzed to optimize the Upper/Lower Thresholds for specific instruments and market conditions.
