ThinkTech AI SignalsThink Tech AI Strategy
The Think Tech AI Strategy provides a structured approach to trading by integrating liquidity-based entries, ATR volatility thresholds, and dynamic risk management. This strategy generates buy and sell signals while automatically calculating take profit and stop loss levels, boasting a 64% win rate based on historical data.
Usage
The strategy can be used to identify key breakout and retest opportunities. Liquidity-based zones act as potential accumulation and distribution areas and may serve as future support or resistance levels. Buy and sell zones are identified using liquidity zones and ATR-based filters. Risk management is built-in, automatically calculating take profit and stop loss levels using ATR multipliers. Volume and trend filtering options help confirm directional bias using a 50 EMA and RSI filter. The strategy also allows for session-based trading, limiting trades to key market hours for higher probability setups.
Settings
The risk/reward ratio can be adjusted to define the desired stop loss and take profit calculations. The ATR length and threshold determine ATR-based breakout conditions for dynamic entries. Liquidity period settings allow for customized analysis of price structure for support and resistance zones. Additional trend and RSI filters can be enabled to refine trade signals based on moving averages and momentum conditions. A session filter is included to restrict trade signals to specific market hours.
Style
The strategy includes options to display liquidity lines, showing key support and resistance areas. The first 15-minute candle breakout zones can also be visualized to highlight critical market structure points. A win/loss statistics table is included to track trade performance directly on the chart.
This strategy is intended for descriptive analysis and should be used alongside other confluence factors. Optimize your trading process with Think Tech AI today!
ค้นหาในสคริปต์สำหรับ "trend"
Liquidity Sweep Filter Strategy [AlgoAlpha X PineIndicators]This strategy is based on the Liquidity Sweep Filter developed by AlgoAlpha. Full credit for the concept and original indicator goes to AlgoAlpha.
The Liquidity Sweep Filter Strategy is a non-repainting trading system designed to identify liquidity sweeps, trend shifts, and high-impact price levels. It incorporates volume-based liquidation analysis, trend confirmation, and dynamic support/resistance detection to optimize trade entries and exits.
This strategy helps traders:
Detect liquidity sweeps where major market participants trigger stop losses and liquidations.
Identify trend shifts using a volatility-based moving average system.
Analyze volume distribution with a built-in volume profile visualization.
Filter noise by differentiating between major and minor liquidity sweeps.
How the Liquidity Sweep Filter Strategy Works
1. Trend Detection Using Volatility-Based Filtering
The strategy applies a volatility-adjusted moving average system to determine trend direction:
A central trend line is calculated using an EMA smoothed over a user-defined length.
Upper and lower deviation bands are created based on the average price deviation over multiple periods.
If price closes above the upper band, the strategy signals an uptrend.
If price closes below the lower band, the strategy signals a downtrend.
This approach ensures that trend shifts are confirmed only when price significantly moves beyond normal market fluctuations.
2. Liquidity Sweep Detection
Liquidity sweeps occur when price temporarily breaks key levels, triggering stop-loss liquidations or margin call events. The strategy tracks swing highs and lows, marking potential liquidity grabs:
Bearish Liquidity Sweeps – Price breaks a recent high, then reverses downward.
Bullish Liquidity Sweeps – Price breaks a recent low, then reverses upward.
Volume Integration – The strategy analyzes trading volume at each sweep to differentiate between major and minor sweeps.
Key levels where liquidity sweeps occur are plotted as color-coded horizontal lines:
Red lines indicate bearish liquidity sweeps.
Green lines indicate bullish liquidity sweeps.
Labels are displayed at each sweep, showing the volume of liquidated positions at that level.
3. Volume Profile Analysis
The strategy includes an optional volume profile visualization, displaying how trading volume is distributed across different price levels.
Features of the volume profile:
Point of Control (POC) – The price level with the highest traded volume is marked as a key area of interest.
Bounding Box – The profile is enclosed within a transparent box, helping traders visualize the price range of high trading activity.
Customizable Resolution & Scale – Traders can adjust the granularity of the profile to match their preferred time frame.
The volume profile helps identify zones of strong support and resistance, making it easier to anticipate price reactions at key levels.
Trade Entry & Exit Conditions
The strategy allows traders to configure trade direction:
Long Only – Only takes long trades.
Short Only – Only takes short trades.
Long & Short – Trades in both directions.
Entry Conditions
Long Entry:
A bullish trend shift is confirmed.
A bullish liquidity sweep occurs (price sweeps below a key level and reverses).
The trade direction setting allows long trades.
Short Entry:
A bearish trend shift is confirmed.
A bearish liquidity sweep occurs (price sweeps above a key level and reverses).
The trade direction setting allows short trades.
Exit Conditions
Closing a Long Position:
A bearish trend shift occurs.
The position is liquidated at a predefined liquidity sweep level.
Closing a Short Position:
A bullish trend shift occurs.
The position is liquidated at a predefined liquidity sweep level.
Customization Options
The strategy offers multiple adjustable settings:
Trade Mode: Choose between Long Only, Short Only, or Long & Short.
Trend Calculation Length & Multiplier: Adjust how trend signals are calculated.
Liquidity Sweep Sensitivity: Customize how aggressively the strategy identifies sweeps.
Volume Profile Display: Enable or disable the volume profile visualization.
Bounding Box & Scaling: Control the size and position of the volume profile.
Color Customization: Adjust colors for bullish and bearish signals.
Considerations & Limitations
Liquidity sweeps do not always result in reversals. Some price sweeps may continue in the same direction.
Works best in volatile markets. In low-volatility environments, liquidity sweeps may be less reliable.
Trend confirmation adds a slight delay. The strategy ensures valid signals, but this may result in slightly later entries.
Large volume imbalances may distort the volume profile. Adjusting the scale settings can help improve visualization.
Conclusion
The Liquidity Sweep Filter Strategy is a volume-integrated trading system that combines liquidity sweeps, trend analysis, and volume profile data to optimize trade execution.
By identifying key price levels where liquidations occur, this strategy provides valuable insight into market behavior, helping traders make better-informed trading decisions.
Key use cases for this strategy:
Liquidity-Based Trading – Capturing moves triggered by stop hunts and liquidations.
Volume Analysis – Using volume profile data to confirm high-activity price zones.
Trend Following – Entering trades based on confirmed trend shifts.
Support & Resistance Trading – Using liquidity sweep levels as dynamic price zones.
This strategy is fully customizable, allowing traders to adapt it to different market conditions, timeframes, and risk preferences.
Full credit for the original concept and indicator goes to AlgoAlpha.
Destroyer LifeDestroyer Life Strategy - High-Frequency Long & Short Trading
Overview:
The Destroyer Life strategy is an advanced cryptocurrency trading algorithm designed for high-frequency execution on the 15-second timeframe. It combines CRT (Candle Range Trend) and Turtle Soup trading logic with multi-timeframe analysis to optimize entries and exits for both long and short trades. This strategy is specifically optimized for high-volatility crypto pairs, such as SOL/USD on MEXC, ensuring precise execution with minimal drawdown.
Key Features:
15-Second Timeframe Execution: Optimized for ultra-short-term trading.
Long & Short Strategy: Simultaneously identifies profitable buy and sell opportunities.
CRT & Turtle Soup Logic: Leverages price action patterns for enhanced trade accuracy.
Higher Timeframe Analysis (HTF): Incorporates liquidity zones, fair value gaps (FVG), and breaker blocks for context-aware trading.
Dynamic Position Sizing: Uses an adjustable leverage multiplier for risk-controlled trade sizing.
Commission Optimization: Ensures profitability even with trading fees.
Strict Risk Management: Implements exit conditions based on liquidity structure and trend reversals.
Strategy Performance (Backtested on SOL/USD - MEXC):
Overall Profitability: ~80% win rate in backtesting.
Net Profit: $3,151.12 (6.30% ROI).
Gross Profit: $3,795.68 (7.59%).
Gross Loss: $644.56 (1.29%).
Long Trades Profit: $1,459.05 (2.92%).
Short Trades Profit: $1,692.07 (3.38%).
Commission Paid: $924.82.
Minimum Trade Holding Period: 1-minute cooldown between trades.
Trading Logic:
Entry Conditions:
Long Trades: Triggered when the price enters a liquidity void and aligns with higher timeframe bullish bias.
Short Trades: Triggered when price approaches a resistance level with bearish higher timeframe confluence.
CRT & Turtle Soup Patterns: Identifies reversals by analyzing breakout and fake-out structures.
Exit Conditions:
Long Positions Close: Upon price exceeding a 3.88% profit threshold or reversing below an HTF structure.
Short Positions Close: Upon reaching a similar 3.88% threshold or showing strong bullish signals.
Dynamic Position Sizing:
Uses a leverage-based calculation that adapts trade size based on volatility.
Liquidity Awareness:
Tracks Mitigation Blocks (MB), Fair Value Gaps (FVG), Buy/Sell-Side Liquidity (BSL/SSL) to determine optimal execution.
Best Use Cases:
Scalpers & High-Frequency Traders: Those looking for rapid trade execution with short holding periods.
Crypto Traders Focused on Low Timeframes: Optimized for 15-second price action.
Traders Utilizing Liquidity Concepts: Built to exploit liquidity traps and inefficiencies.
Risks & Considerations:
High-Frequency Execution Requires Low Latency: Ensure your broker or exchange supports fast order execution.
Backtested Results May Vary: Real-time performance depends on market conditions.
Commission & Fees Impact Profits: Consider exchanges with low fees to maximize strategy efficiency.
Final Thoughts:
The Destroyer Life Strategy is designed for serious traders looking to take advantage of high-volatility markets with a structured, liquidity-based approach. By combining price action, liquidity concepts, and adaptive risk management, it provides a solid framework for executing high-probability trades on crypto markets.
🚀 Ready to take your trading to the next level? Try Destroyer Life today and dominate the markets!
Strategy SuperTrend SDI WebhookThis Pine Script™ strategy is designed for automated trading in TradingView. It combines the SuperTrend indicator and Smoothed Directional Indicator (SDI) to generate buy and sell signals, with additional risk management features like stop loss, take profit, and trailing stop. The script also includes settings for leverage trading, equity-based position sizing, and webhook integration.
Key Features
1. Date-based Trade Execution
The strategy is active only between the start and end dates set by the user.
times ensures that trades occur only within this predefined time range.
2. Position Sizing and Leverage
Uses leverage trading to adjust position size dynamically based on initial equity.
The user can set leverage (leverage) and percentage of equity (usdprcnt).
The position size is calculated dynamically (initial_capital) based on account performance.
3. Take Profit, Stop Loss, and Trailing Stop
Take Profit (tp): Defines the target profit percentage.
Stop Loss (sl): Defines the maximum allowable loss per trade.
Trailing Stop (tr): Adjusts dynamically based on trade performance to lock in profits.
4. SuperTrend Indicator
SuperTrend (ta.supertrend) is used to determine the market trend.
If the price is above the SuperTrend line, it indicates an uptrend (bullish).
If the price is below the SuperTrend line, it signals a downtrend (bearish).
Plots visual indicators (green/red lines and circles) to show trend changes.
5. Smoothed Directional Indicator (SDI)
SDI helps to identify trend strength and momentum.
It calculates +DI (bullish strength) and -DI (bearish strength).
If +DI is higher than -DI, the market is considered bullish.
If -DI is higher than +DI, the market is considered bearish.
The background color changes based on the SDI signal.
6. Buy & Sell Conditions
Long Entry (Buy) Conditions:
SDI confirms an uptrend (+DI > -DI).
SuperTrend confirms an uptrend (price crosses above the SuperTrend line).
Short Entry (Sell) Conditions:
SDI confirms a downtrend (+DI < -DI).
SuperTrend confirms a downtrend (price crosses below the SuperTrend line).
Optionally, trades can be filtered using crossovers (occrs option).
7. Trade Execution and Exits
Market entries:
Long (strategy.entry("Long")) when conditions match.
Short (strategy.entry("Short")) when bearish conditions are met.
Trade exits:
Uses predefined take profit, stop loss, and trailing stop levels.
Positions are closed if the strategy is out of the valid time range.
Usage
Automated Trading Strategy:
Can be integrated with webhooks for automated execution on supported trading platforms.
Trend-Following Strategy:
Uses SuperTrend & SDI to identify trend direction and strength.
Risk-Managed Leverage Trading:
Supports position sizing, stop losses, and trailing stops.
Backtesting & Optimization:
Can be used for historical performance analysis before deploying live.
Conclusion
This strategy is suitable for traders who want to automate their trading using SuperTrend and SDI indicators. It incorporates risk management tools like stop loss, take profit, and trailing stop, making it adaptable for leverage trading. Traders can customize settings, conduct backtests, and integrate it with webhooks for real-time trade execution. 🚀
Important Note:
This script is provided for educational and template purposes and does not constitute financial advice. Traders and investors should conduct their research and analysis before making any trading decisions.
IronBot v4IronBot v4 – Trading Strategy Overview
1. Quick Context
IronBot v4 is a trading strategy designed for users who want a simple yet effective approach to reading the markets. It uses a combination of Fibonacci retracement levels, custom logic triggers, and innovative modules (EMA validation, Iron Impulse Shield and Iron Auto Volume Detector) to identify potential entry and exit points, strengthening the strategy’s detection of sudden market volatility or shifts in trading volume.
2. Theoretical Details
Fibonacci Analysis
The script identifies recent market highs and lows, then calculates key Fibonacci levels (high- and low-based). These levels can help confirm potential reversals or trends.
EMA Option
When enabled, the exponential moving average (EMA) offers additional validation for trade entries. If the current price remains above a certain EMA threshold, long positions may be favored; conversely, if it stays below the EMA, short positions may be initiated.
IIS (Iron Impulse Shield)
IIS helps to filter out risky trades by measuring recent price shocks or surges. If an extreme movement is detected, the strategy may temporarily disable longs or shorts to avoid false signals.
IAVD (Iron Auto Volume Detector)
This functionality automatically detects the average market volume over a defined period (regardless of the market, since it relies on real data). When entering a position, it ensures that overall volume is high enough to confirm a genuinely active, robust market. By providing an additional filter, it can strengthen the decision-making process whenever the market’s participation level is in question.
Panel
IronBot v4 displays a real-time backtest panel that summarizes the selected configuration (including the current pair, analysis window, enabled filters), as well as showing net profit, applicable exchange fees, country taxes, and the final net balance. This gives traders an immediate overview of strategy performance and risk metrics.
What Pinescript Adds Visually
The script plots:
Fibonacci levels (highlighting potential reversal zones)
Trend lines indicating bullish (green) or bearish (red) lean
Optional EMA line
Optional Fibonacci forecast lines for anticipating future moves
Automatic labeling of entry, take-profit, and stop-loss levels, indicating the profit percentage of each trade.
3. Explanation of Inputs
The strategy exposes multiple inputs that can be toggled or configured by the user:
Analysis Window : Dictates how many bars to consider for high/low calculations and the fib retracement thresholds.
TRADES
Display TP/SL: For displaying Take profits and Stop loss.
Display Forecast: When enabled, this feature calculates and projects possible future Fibonacci retracements using historical data, helping traders anticipate potential upcoming trade setups.
Leverage: Only used for the Panel and not for trades. Lets you amplify your position size; higher leverage increases potential gains but also heightens risk. TradingView strategy is using properties for doing this.
Exchange Maker Fees & Exchange Taker Fees: Only used for the Panel and not for trades. Define the percentage cost applied by your exchange for maker and taker trades, respectively. These fees are accounted for in final profit calculations of the Panel.
Country Tax: Only used for the Panel and not for trades. Specifies a tax percentage to be deducted from net profits.
STOP LOSS and TAKE PROFITS
Stop-Loss & Take-Profit Parameters: Controls the percentage distances at which the strategy will exit positions. Additionally, you can configure up to four distinct take-profit levels (TP1 through TP4). Each level should be higher target than the previous one, and you can assign a specific percentage of the total position to close at each TP, ensuring the sum equals 100%. A break-even feature is also available when multiple TPs are used.
EMA
EMA (Exponential Moving Average) Option: When enabled, the strategy opens long trades only if the current price is above the specified EMA length, and opens short trades only if it is below that threshold.
PANELS
Show Panel: For displaying the backtest integrated panel.
IRON IMPULSE SHIELD (IIS)
IIS (Iron Impulse Shield) Option: When enabled, IIS continuously monitors recent price volatility depending on the analysis window set. If the market experiences an extreme surge or drop beyond a specified threshold, IIS temporarily blocks new long or short positions.
IRON AUTO VOLUME DETECTOR (IAVD)
IAVD (Iron Auto Volume Detector) Option: When enabled, it continuously measures the average market volume over a special period, irrespective of the specific trading pair. This ensures that IronBot v4 focuses on markets with robust participation, reducing the likelihood of entering trades during low-liquidity conditions.
By changing these values, IronBot v4 reacts differently to market structure and risk management requirements. Stop-loss and take-profit levels will adjust accordingly, while advanced filters (like EMA or IIS) influence when trades can open.
4. TradingView Strategy Properties
IronBot v4 uses the built-in TradingView “strategy” functionality. In particular:
Order Placement: The code calls strategy.entry() and strategy.close() for direct orders, ensuring signals are sent immediately (no limit orders are used). This helps connect with exchange signal bots for automated execution.
Initial Capital: The code uses initial capital defined in properties for calculating Net balance in the integrated panel.
On bar close: This strategy fill orders on bar close.
Pyramiding: This strategy can take only 1 successive trade in the same direction
Be careful to configure your leverage input depending on your strategy properties.
5. Visualization
5. Purpose & Disclaimer
This script is for educational purposes only and does not constitute financial advice. Past performance does not guarantee future results. Always confirm your own risk tolerance and consult a financial professional before placing live trades. Trading leveraged products can involve substantial risk of loss.
Dow Theory Swing Trading-DexterThis Pine Script strategy that implements a basic price action-based trading system inspired by Dow Theory, focusing on swing highs and swing lows. This strategy will generate buy and sell signals based on the formation of higher highs (HH) and higher lows (HL) for an uptrend, and lower highs (LH) and lower lows (LL) for a downtrend.
Swing Highs and Swing Lows:
The script identifies swing highs and swing lows using the ta.highest and ta.lowest functions over a specified lookback period.
A swing high is identified when the high of the current bar is the highest high over the lookback period.
A swing low is identified when the low of the current bar is the lowest low over the lookback period.
Trend Detection:
An uptrend is detected when the current low is higher than the last identified swing low.
A downtrend is detected when the current high is lower than the last identified swing high.
Buy and Sell Signals:
A buy signal is generated when the price closes above the last swing high during an uptrend.
A sell signal is generated when the price closes below the last swing low during a downtrend.
Plotting:
Swing highs and swing lows are plotted on the chart using plotshape.
Buy and sell signals are also plotted on the chart for visual reference.
How to Use:
Copy and paste the script into the Pine Script editor in TradingView.
Adjust the lookback period as needed to suit your trading style and timeframe.
Apply the script to your chart and it will generate buy and sell signals based on the price action.
NOTE: Please uncheck the all the unwanted symbol from chart for clear view .
4Vietnamese 3x SupertrendThis strategy attempts to capture long positions in the Vietnamese stock market using a combination of three Supertrend indicators and additional filters. It utilizes pyramiding to enter up to three long positions with a 33.33% allocation each.
Key Elements:
Supertrend Indicators: Three Supertrend indicators are used with different lengths and multipliers to identify potential trend changes.
Entry Conditions:
The strategy looks for a downtrend on the slowest Supertrend (Supertrend3) followed by uptrends on the medium (Supertrend2) and fast (Supertrend1) Supertrends.
Alternatively, if Supertrend3 is still downtrending, but Supertrend1 is downtrending and a significant previous high (highestGreen) exists, an entry signal is generated.
An optional filter allows using the highest of the last two red candles for highestGreen calculation.
Entry Stop Loss:
An optional stop loss can be set based on the entry price of previous long positions, preventing further losses if the price falls below entry prices.
Exit Conditions:
Three exit options are available:
- All Downtrend Exit: Close all positions if all Supertrends turn uptrend and a bearish candlestick pattern (close price lower than open price) is formed.
- Average Price in Loss Exit: Close all positions if the average entry price of open positions is higher than the current closing price (indicating a loss).
- All Positions in Loss Exit: Close all positions if any of the following conditions are met:
A single open position exists, and its entry price is higher than the current close price.
Two open positions exist, and their entry prices are both higher than the current close price.
Three open positions exist, and their entry prices are all higher than the current close price.
Pyramiding: The strategy allows entering up to three long positions with a fixed allocation of 33.33% each.
Customization Options:
The strategy provides various input parameters to customize its behavior:
Supertrend lengths and multipliers for each indicator.
Option to use the highest of the last two red candles for highestGreen calculation.
Enabling/disabling Entry Stop Loss and different exit conditions.
Further Enhancements:
Explore additional entry and exit filters to refine trade signals.
Consider incorporating risk management techniques like position sizing and trailing stops.
Backtest the strategy with historical data to evaluate its effectiveness and identify potential areas for improvement.
[3Commas] DCA Bot TesterDCA Bot Tester
🔷What it does: A tool designed to simulate the behavior of a Dollar Cost Averaging (DCA) strategy based on input signals from a source indicator. Additionally, it enables you to send activation signals to 3Commas Bots via TradingView webhooks.
🔷Who is it for: This tool is ideal for those who want a visual representation and strategy report of how a DCA Bot would perform under specific conditions. By adjusting the parameters, you can assess whether the strategy aligns with your risk/reward expectations before implementation, helping you save time and protect your capital.
🔷How does it work: The tool leverages a pyramiding function to simulate price averaging, mimicking how a DCA Bot operates. It calculates volume-based averaging and, upon reaching the target, closes the positions. Conversely, if the target isn't reached, a Stop Loss is triggered, potentially resulting in significant losses if improperly configured.
🔷Why It’s Unique
Easy visualization of DCA Bot entry and exit points according to user preferences.
DCA Bot Summary table same as the one shown in the new 3Commas interface.
Use plots from other indicators as Entry Trigger Source, with a small modification of the code.
Option to Review message format before sending Signals to 3Commas. Compatibility with Multi-Pair, and futures contract pairs.
Option to filter signals by session and day according to the user’s timezone.
👉 Before continuing with the explanation of the tool, please take a few minutes to read this information, paying special attention to the risks of using DCA strategies.
DCA Bot: What is it, how does it work, and what are its advantages and risks?
A DCA Bot is an automated tool designed to simplify and optimize your trading operations, particularly in cryptocurrencies. Based on the concept of Dollar Cost Averaging (DCA) , this bot implements scaled strategies that allow you to distribute your investments intelligently. The key lies in dividing your capital into multiple orders, known as base orders and safety orders, which are executed at different price levels depending on market conditions.
These bots are highly customizable, meaning you can adapt them to your goals and trading style, whether you're operating Long (expecting a price increase) or Short (expecting a price decrease). Their primary purpose is to reduce the impact of entries that move against the estimated direction and ensure you achieve a more favorable average price.
🔸 Key Features of DCA Bots
Customizable configuration: DCA bots allow you to adjust the size of your initial investment, the number of safety orders, and the price levels at which these orders execute. These orders can be equal or incremental, depending on your risk tolerance.
Scaled safety orders: If the asset's price moves against your position, the bot executes safety orders at strategic levels to average your entry price and increase your chances of closing in profit.
Automatic Take Profit: When the predefined profit level is reached, the bot closes the position, ensuring net gains by averaging all entries made using the DCA strategy.
Stop Loss option: To protect your capital, you can set a stop loss level that limits losses if the market moves drastically against your position.
Flexibility: Bots can integrate with 3Commas technical indicators or external signals from TradingView, allowing you to trade in any trend, whether bullish or bearish.
Support for multiple assets: You can trade cryptocurrency pairs and exchanges compatible with 3Commas, offering a wide range of possibilities to diversify your strategies.
✅ Advantages of DCA Bots
Time-saving automation: DCA bots eliminate the need for constant market monitoring, executing your trades automatically and efficiently based on predefined settings.
Favorable averages in volatile markets: By averaging your entries, the bot can offer more competitive prices even under adverse market conditions. This increases your chances of recovering a position and closing it profitably.
Advanced capital management: With customizable settings, you can adjust the size of base and safety orders to optimize capital usage and reduce risk.
Additional protection: The ability to set a stop loss ensures your losses are limited, safeguarding your capital in extreme scenarios.
⚠️ Risks of Using a DCA Bot
Requires significant capital: Safety orders can accumulate quickly if the price moves against your position. This issue is compounded if increasing amounts are used for safety orders, which can immobilize large portions of capital in adverse markets.
Markets lacking clear direction: During consolidation periods or erratic movements, the bot may generate unrealized losses and make position recovery difficult.
Opportunity cost: Investing in an asset that doesn't show favorable behavior can prevent you from seizing opportunities in other markets.
Emotional pressure: Large investments in advanced stages of the DCA strategy can cause stress, especially if an asset takes too long to reach your take profit level.
Dependence on market recovery: DCA assumes that the price will eventually move in your favor, which does not always happen, especially in assets without solid fundamentals.
📖 Key Considerations for Effectively Using a DCA Bot
Use small amounts for your base and safety orders: Setting small initial orders not only limits capital usage but also allows you to manage multiple bots simultaneously, maximizing portfolio diversification.
Capital management: Define a clear budget and never risk more than you are willing to lose. This is essential for maintaining sustainable operations.
Select assets with strong fundamentals: Apply DCA to assets you understand and that have solid fundamentals and a proven historical growth record. Additionally, analyze each cryptocurrency's fundamentals: What problem does it solve? Does it have a clear use case? Is it viable in the long term? These questions will help you make more informed decisions.
Diversification: Do not concentrate all your capital on a single asset or strategy. Spread your risk across multiple bots or assets.
Monitor regularly: While bots are automated and eliminate the need to monitor the market constantly, it is essential to monitor the bots themselves to ensure they are performing as expected. This includes reviewing their performance and making adjustments if market conditions change. Remember, the goal is to automate trades, but active bot management is crucial to avoid surprises.
A DCA Bot is a powerful tool for traders looking to automate their strategies and reduce the impact of market fluctuations. However, like any tool, its success depends on how it is configured and used. By applying solid capital management principles, carefully selecting assets, and using small amounts in your orders, you can maximize its potential and minimize risks.
🔷FEATURES & HOW TO USE
🔸Strategy: Here you must select the type of signal you are going to analyze and send signals to the DCA Bot, either Long for buy signals or Short for sell signals. This must match the Bot created in 3Commas.
🔸Add a Source Indicator for Entry Triggers
Tradingview allows us to use indicator plots as a source in other indicators, we will use this functionality so that the buy or sell signals of an indicator are processed by the DCA Bot Tester.
In this EXAMPLE we will use a simple strategy that uses a Donchian Channel (DC) and an Exponential Moving Average (EMA).
Trigger to buy or long signal will be when: the price closes above the previous upper level and the average of the upper and lower level (basis) is greater than the EMA.
Trigger sell or short signal will be when: the price closes below the previous lower level and the average of the upper and lower level (basis) is less than the EMA.
trigger_buy = ta.crossover (close,upper ) and basis > ema and barstate.isconfirmed
trigger_sell = ta.crossunder(close,lower ) and basis < ema and barstate.isconfirmed
Then we create the plots that will be used as input source in the DCA Bot Tester indicator.
When a buy condition is given the plot "🟢 Trigger Buy" will have a value of 1 otherwise it will remain at 0.
When a sell condition is given the plot "🔴 Trigger Sell" will have a value of -1 otherwise it will remain at 0.
plot(trigger_buy ? 1 : 0 , '🟢 Trigger Buy' , color = na, display = display.data_window)
plot(trigger_sell? -1 : 0 , '🔴 Trigger Sell', color = na, display = display.data_window)
Here you have the complete code so you can use it and do tests. Basically you just have to define the buy or sell conditions of your preferred indicator or strategy and then create the plots with the same format that will be used in DCA Bot Tester.
//@version=6
indicator(title="Simple Strategy Example", overlay= false)
// Indicator and Signal Triggers
length = input.int(10, title = "DC Length" , display = display.none)
length_ema = input.int(50, title = "EMA Length", display = display.none)
lower = ta.lowest (length)
upper = ta.highest(length)
ema = ta.ema (close, length_ema)
basis = math.avg (upper, lower)
plot(basis, "Basis", color = color.orange, display = display.all-display.status_line)
plot(upper, "Upper", color = color.blue , display = display.all-display.status_line)
plot(lower, "Lower", color = color.blue , display = display.all-display.status_line)
plot(ema , "EMA" , color = color.red , display = display.all-display.status_line)
candlecol = open < close ? color.teal : color.red
plotcandle(open, high, low, close, title='Candles', color = candlecol, wickcolor = candlecol, bordercolor = candlecol, display = display.pane)
trigger_buy = ta.crossover (close,upper ) and basis > ema and barstate.isconfirmed
trigger_sell = ta.crossunder(close,lower ) and basis < ema and barstate.isconfirmed
plotshape(trigger_buy ?close:na, title="Label Buy" , style=shape.labelup , location= location.belowbar, color=color.green, text="B", textcolor=color.white, display=display.pane)
plotshape(trigger_sell?close:na, title="Label Sell", style=shape.labeldown, location= location.abovebar, color=color.red , text="S", textcolor=color.white, display=display.pane)
// ――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――
// 👇 Plots to be used in the DCA Bot Indicator as source triggers.
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plot(trigger_buy ? 1 : 0 , '🟢 Trigger Buy' , color = na, display = display.data_window)
plot(trigger_sell? -1 : 0 , '🔴 Trigger Sell', color = na, display = display.data_window)
To use the example code
Open the Pine Editor, paste the code and then click Add to chart.
Then in the Plot Entry Trigger Source option, we will select 🟢 Trigger Buy, as the plot that will give us the buy signals when it is worth 1, otherwise for the sell signals you must change the value to -1 in the Plot Entry Trigger Value and remember to change the strategy mode to Short.
🔸DCA Settings: Here you need to configure the DCA values of the strategy, you can see the meaning of each value in the Settings Section. Once you are satisfied with the tests configure the 3Commas DCA Bot with the same values so that the Summary Table matches the 3Commas Table. Pay close attention to the Total Volume that the Bot will use, according to the amount of Safety Orders you are going to execute, and that all the values in the table adapt to your risk tolerance.
🔸DCA Bot Deal Start: Once you create the Bot in 3Commas with the same settings it will give you a Deal Start Message, you must copy and paste it in this section, verify that it is the same in the summary table, this is used to be sent through tradingview alerts to the Bot and it can process the signals.
🔸DCA Bot Multi-Pair: A Multi-Pair Bot allows you to manage several pairs with a single bot, but you must specify which pair it will run on. 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 3Commas format) the symbol for each pair before you create the alert so that the bot understands which pair to work on.
In the following image we would be configuring the indicator to send a signal to activate the bot in the BTCUSDT pair using the given format it would be USDT_BTC, but if we wanted to send a signal in another pair we must change the pair in the chart and also in the configuration, an example with ETHUSDT would be USDT_ETH. After this we could create the alert, and the Mult-Pair Bot would detect it correctly.
🔸Strategy Tester Filters: This is useful if you want to test the strategy's result on a certain time window, the indicator will only enter this range. If disabled it will use all historical data available on the chart. If you are going to use the tool to send signals, make sure to disable the Use Custom Test Period. If you want the entries to only run at a certain time and day, in that case make sure that the timezone matches the one you are using in the chart.
🔸Properties: Adjust your initial capital and exchange commission appropriately to achieve realistic results.
🔸Create alerts to trigger the DCA Bot
Check that the message is the same as the one indicated by the DCA Bot.
In the case of Multi-Pair, enable the option to add the symbol with the correct format.
When creating an alert, select Any alert() function call.
Enter the any name of the alert.
Open the Notifications tab and enable Webhook URL
Paste Webhook URL provided by 3Commas looking in the section How to use TradingView custom signals.
Done, alerts will be sent with the correct format automatically to 3Commas.
🔷 INDICATOR SETTINGS
🔸3Commas DCA Bot Settings
Strategy: Select the direction of the strategy to test Long or Short, this must be the same as the Bot created in 3Commas, so that the signals are processed properly.
DCA Bot Deal Start: Copy and paste the message for the deal start signal of the DCA Bot you created in 3Commas. This is the message that will be sent with the alert to the Bot, you must verify that it is the same as the 3Commas bot so that it can process properly so that it executes and starts the trade.
DCA Bot Multi-Pair: A Multi-Pair Bot allows you to manage several pairs with a single bot, but you must specify which pair it will run on.
DCA Bot Summary Table: Here you can activate the display of table as well as change the size, position, text color and background color.
🔸Source Indicator Settings
Plot Entry Trigger Source: Select a Plot for Entries of the Source Indicator. This refers to the Long or Short entry signal that the indicator will use as BO (Base Order).
Plot Entry Trigger Value: Value of the Source Indicator to Deal Start Condition Trigger. The default value is 1, this means that when a signal is given for example Long in the source indicator, we will use 1 or for Short -1 if there is no signal it will be 0 so it will not execute any entry, please review the example code and adjust the indicator you are going to use in the same way.
🔸DCA Settings
Base Order: The Base Order is the first order the bot will create when starting a new deal.
Safety Order: Enter the amount of funds your safety orders will use to average the cost of the asset being traded.Safety orders are also known as Dollar Cost Averaging and help when prices move in the opposite direction to your bot's take profit target.
Safety Orders Deviation %: Enter the percentage difference in price to create the first Safety Order. All Safety Orders are calculated from the price the initial Base Order was filled on the exchange account.
Safety Orders Max Count: This is the total number of Safety Orders the bot is allowed to use per deal that is opened. All Safety Orders created by the bot are placed as Limit Orders on the exchange's order book.
Safety Orders Volume Scale: The Safety Order Volume Scale is used to multiply the amount of funds used by the last Safety Order that was created. Using a larger amount of funds for Safety Orders allows your bot to be more aggressive at Dollar Cost Averaging the price of the asset being traded.
Safety Orders Step Scale: The Safety Order Step Scale is used to multiply the Price Deviation percentage used by the last Safety Order placed on the exchange account. Using a larger value here will reduce the amount of Safety Orders your bot will require to cover a larger move in price in the opposite direction to the active deal's take profit target.
Take Profit %: The Take Profit section offers tools for flexible management of target parameters: automatic profit upon reaching one or more target levels in percentage.
Stop Loss % | Use SL: To enable Stop Loss, please check the "Use SL" box. This is the percentage that price needs to move in the opposite direction to close the deal at a loss. This must be greater than the sum of the deviations from the safety orders.
🔸Strategy Tester Filters
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.
Session Filter | Days | Background: Here you can choose a time zone in which signals will be sent or your strategy will be tested, as well as the days and a background of it. It is important that you use the same timezone as your chart so that it matches.
👨🏻💻💭 If this tool helps you, don’t forget to give it a boost! Feel free to share in the comments how you're using it or if you have any questions.
_________________________________________________________________
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.
Ichimoku Crosses_RSI_AITIchimoku Crosser_RSI_AIT
Overview
The "Ichimoku Cloud Crosses_AIT" strategy is a technical trading strategy that combines the Ichimoku Cloud components with the Relative Strength Index (RSI) to generate trade signals. This strategy leverages the crossovers of the Tenkan-sen and Kijun-sen lines of the Ichimoku Cloud, along with RSI levels, to identify potential entry and exit points for long and short trades. This guide explains the strategy components, conditions, and how to use it effectively in your trading.
1. Strategy Parameters
User Inputs
Tenkan-sen Period (tenkanLength): Default value is 21. This is the period used to calculate the Tenkan-sen line (conversion line) of the Ichimoku Cloud.
Kijun-sen Period (kijunLength): Default value is 120. This is the period used to calculate the Kijun-sen line (base line) of the Ichimoku Cloud.
Senkou Span B Period (senkouBLength): Default value is 52. This is the period used to calculate the Senkou Span B line (leading span B) of the Ichimoku Cloud.
RSI Period (rsiLength): Default value is 14. This period is used to calculate the Relative Strength Index (RSI).
RSI Long Entry Level (rsiLongLevel): Default value is 60. This level indicates the minimum RSI value for a long entry signal.
RSI Short Entry Level (rsiShortLevel): Default value is 40. This level indicates the maximum RSI value for a short entry signal.
2. Strategy Components
Ichimoku Cloud
Tenkan-sen: A short-term trend indicator calculated as the simple moving average (SMA) of the highest high and the lowest low over the Tenkan-sen period.
Kijun-sen: A medium-term trend indicator calculated as the SMA of the highest high and the lowest low over the Kijun-sen period.
Senkou Span A: Calculated as the average of the Tenkan-sen and Kijun-sen, plotted 26 periods ahead.
Senkou Span B: Calculated as the SMA of the highest high and lowest low over the Senkou Span B period, plotted 26 periods ahead.
Chikou Span: The closing price plotted 26 periods behind.
Relative Strength Index (RSI)
RSI: A momentum oscillator that measures the speed and change of price movements. It ranges from 0 to 100 and is used to identify overbought or oversold conditions.
3. Entry and Exit Conditions
Entry Conditions
Long Entry:
The Tenkan-sen crosses above the Kijun-sen (bullish crossover).
The RSI value is greater than or equal to the rsiLongLevel.
Short Entry:
The Tenkan-sen crosses below the Kijun-sen (bearish crossover).
The RSI value is less than or equal to the rsiShortLevel.
Exit Conditions
Exit Long Position: The Tenkan-sen crosses below the Kijun-sen.
Exit Short Position: The Tenkan-sen crosses above the Kijun-sen.
4. Visual Representation
Tenkan-sen Line: Plotted on the chart. The color changes based on its relation to the Kijun-sen (green if above, red if below) and is displayed with a line width of 2.
Kijun-sen Line: Plotted as a white line with a line width of 1.
Entry Arrows:
Long Entry: Displayed as a yellow triangle below the bar.
Short Entry: Displayed as a fuchsia triangle above the bar.
5. How to Use
Apply the Strategy: Apply the "Ichimoku Cloud Crosses_AIT" strategy to your chart in TradingView.
Configure Parameters: Adjust the strategy parameters (Tenkan-sen, Kijun-sen, Senkou Span B, and RSI settings) according to your trading preferences.
Interpret the Signals:
Long Entry: A yellow triangle appears below the bar when a long entry signal is generated.
Short Entry: A fuchsia triangle appears above the bar when a short entry signal is generated.
Monitor Open Positions: The strategy automatically exits positions based on the defined conditions.
Backtesting and Live Trading: Use the strategy for backtesting and live trading. Adjust risk management settings in the strategy properties as needed.
Conclusion
The "Ichimoku Cloud Crosses_AIT" strategy uses Ichimoku Cloud crossovers and RSI to generate trading signals. This strategy aims to capture market trends and potential reversals, providing a structured way to enter and exit trades. Make sure to backtest and optimize the strategy parameters to suit your trading style and market conditions before using it in a live trading environment.
Price-Volume Dynamic - Strategy [presentTrading]█ Introduction and How it is Different
The "Price-Volume Dynamic - Strategy" leverages a unique blend of price action, volume analysis, and statistical z-scores to establish trading positions. This approach differentiates itself by integrating the concept of the Point of Control (POC) from volume profile analysis with price-based z-score indicators to create a dynamic trading strategy. It tailors entry and exit thresholds based on current market volatility, providing a responsive and adaptive trading method. This strategy stands out by considering both historical volatility and price trends to adjust trading decisions in real-time, enhancing its effectiveness in various market conditions.
BTCUSD 4h LS Performance
█ Strategy: How It Works – Detailed Explanation
🔶 Calculating Point of Control (POC)
The Point of Control (POC) represents the price level with the highest traded volume over a specified lookback period. It's calculated by dividing the price range into a number of rows, each representing a price level. The volume at each price level is tallied and the level with the maximum volume is designated as the POC.
🔶 Dynamic Thresholds Adjustments
The entry and exit thresholds are dynamically adjusted based on normalized volatility, which is derived from the current, minimum, and maximum ATR over a specified period. This normalization ensures that the thresholds adapt to changes in market conditions, making the strategy sensitive to shifts in market volatility.
BTCUSD local performance
█ Trade Direction
The strategy can be configured to trade in three different directions: Long, Short, or Both. This flexibility allows traders to align their trading strategy with their market outlook or risk preferences. By adjusting the `POC_tradeDirection` input, traders can selectively participate in market movements that match their trading style and objectives.
█ Usage
To deploy this strategy, traders should apply it within a trading software that supports scripting and backtesting, such as TradingView's Pine Script environment. Users can input their parameters based on their analysis of the market conditions and their risk tolerance. It is essential for traders to backtest the strategy using historical data to evaluate its performance and make necessary adjustments before applying it in live trading scenarios.
█ Default Settings
- Lookback Length: Sets the period over which the highest and lowest prices, and the volume per price level, are calculated. A higher lookback length smoothens the volatility but may delay response to recent market movements.
- Number of Rows: Determines the granularity of price levels within the price range. More rows provide a more detailed volume profile but require more computational resources.
- Entry Z-Score Threshold Base: Influences the sensitivity of the strategy to enter trades. Higher values make the strategy more conservative, requiring stronger deviation from the mean to trigger a trade.
- Exit Z-Score Threshold Base: Sets the threshold for exiting trades, with lower values allowing trades to close on smaller price retractions, thereby potentially preserving profits or reducing losses.
- Trading Direction: Allows selection between Long, Short, or Both, enabling traders to tailor the strategy to their market view or risk preferences.
Ichimoku Clouds Strategy Long and ShortOverview:
The Ichimoku Clouds Strategy leverages the Ichimoku Kinko Hyo technique to offer traders a range of innovative features, enhancing market analysis and trading efficiency. This strategy is distinct in its combination of standard methodology and advanced customization, making it suitable for both novice and experienced traders.
Unique Features:
Enhanced Interpretation: The strategy introduces weak, neutral, and strong bullish/bearish signals, enabling detailed interpretation of the Ichimoku cloud and direct chart plotting.
Configurable Trading Periods: Users can tailor the strategy to specific market windows, adapting to different market conditions.
Dual Trading Modes: Long and Short modes are available, allowing alignment with market trends.
Flexible Risk Management: Offers three styles in each mode, combining fixed risk management with dynamic indicator states for versatile trade management.
Indicator Line Plotting: Enables plotting of Ichimoku indicator lines on the chart for visual decision-making support.
Methodology:
The strategy utilizes the standard Ichimoku Kinko Hyo model, interpreting indicator values with settings adjustable through a user-friendly menu. This approach is enhanced by TradingView's built-in strategy tester for customization and market selection.
Risk Management:
Our approach to risk management is dynamic and indicator-centric. With data from the last year, we focus on dynamic indicator states interpretations to mitigate manual setting causing human factor biases. Users still have the option to set a fixed stop loss and/or take profit per position using the corresponding parameters in settings, aligning with their risk tolerance.
Backtest Results:
Operating window: Date range of backtests is 2023.01.01 - 2024.01.04. 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.
Maximum Single Position Loss: -6.29%
Maximum Single Profit: 22.32%
Net Profit: +10 901.95 USDT (+109.02%)
Total Trades: 119 (51.26% profitability)
Profit Factor: 1.775
Maximum Accumulated Loss: 4 185.37 USDT (-22.87%)
Average Profit per Trade: 91.67 USDT (+0.7%)
Average Trade Duration: 56 hours
These results are obtained with realistic parameters representing trading conditions observed at major exchanges such as Binance and with realistic trading portfolio usage parameters. Backtest is calculated using deep backtest option in TradingView built-in strategy tester
How to Use:
Add the script to favorites for easy access.
Apply to the desired chart and timeframe (optimal performance observed on the 1H chart, ForEx or cryptocurrency top-10 coins with quote asset 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
London BreakOut ClassicHey there, this is my first time publishing a strategy. The strategy is based on the London Breakout Idea, an incredibly popular concept with abundant information available online.
Let me summarize the London Breakout Strategy in a nutshell: It involves identifying key price levels based on the Tokyo Session before the London Session starts. Typically, these key levels are the high and low of the previous Tokyo session. If a breakout occurs during the London session, you simply follow the trend.
The purpose of this code
After conducting my research, I came across numerous posts, videos, and articles discussing the London Breakout Strategy. I aimed to automatically test it myself to verify whether the claims made by these so-called trading gurus are accurate or not. Consequently, I wrote this script to gain an understanding of how this strategy would perform if I were to follow its basic settings blindly.
Explanation of drawings on the chart:
Red or Green Box: A box is drawn on our chart displaying the exact range of the Tokyo trading session. This box is colored red if the trend during the session was downward and green if it was upward. The box is always drawn between the high and the low between 0:00 AM and 7:00 AM UTC. You can change the settings via the Inputs "Session time Tokyo" & "Session time zone".
Green Background: The green background represents the London trading session. My code allows us to make entries only during this time. If we haven't entered a trade, any pending orders are canceled. I've also programmed a timeout at 11 pm to ensure every trade is closed before the new Tokyo session begins.
Red Line: The red line is automatically placed in the middle of our previous Tokyo range. This line acts as our stop loss. If we cross this line after entering a trade but before reaching our take profit, we'll be stopped out.
When do we enter a trade?
We wait for a candle body to close outside of the previous Tokyo range to enter a trade with the opening of the next candle. We only enter one trade per day.
Where do we put our Take Profit?
The code calculates the exact distance between our entry point and the stop loss. We are trading a risk-reward ratio of 1:1 by default, meaning our take profit is always the same number of pips away from our entry as the stop loss. The Stop Loss is always defined by the red line on the chart. You can change the risk-reward ratio via the inputs setting "CRV", to see how the result changes.
What is the purpose of this script?
I wanted to backtest the London breakout strategy to see how it actually works. Therefore, I wrote this code so that everybody can test it for themselves. You can change the settings and see how the result changes. Typically, you should test this strategy on forex markets and on either 1Min, 5 Min, or 15 Min timeframe.
What are the results?
Over the last 3-6 months (over 100 trades), trading the strategy with my default settings hasn't proven to be very successful. Consequently, I do not recommend trading this strategy blindly. The purpose of this code is to provide you with a foundation for the London Breakout Strategy, allowing you to modify and enhance it according to your preferences. If you're contemplating whether to give it a try, you can assess the results from the past months by using this code as a starting point.
Sniper [Decentrader]Bespoke Decentrader Mean Reversion / Colume based support/resistance Strategy builder.
Colour-coded mean line using price and volume
Volatility Bands (chose % or Std Dev)
Major support and resistance plotted lines
Suggested dynamic hard-stop placement
Built for all markets
A realistic strategy for multi-asset portfolio management
Complementary components to assist other indicators/strategies
Filtering for Long / Short only conditions is possible under settings.
Can be automated by including 3rd party code into the settings to be used as alerts.
Use the Mitigate lines to show previous areas of support or resistance, which have been broken.
4 main strategy options:
1. You can choose whether to enter based on the upper or lower Meanline. If the price is below the Meanline, the lower Meanline will be used for entry, while if the price is above the Meanline, the upper Meanline will be used. \n\nIf you want to use this condition to exit the position, you also need to select the "Exit at the Meanline" option as well.
2. If the selected strategy is "3. Buy/Sell Volatility Bands," you can specify which Band should trigger the position to open. The price must touch or cross the edge of the chosen Band. Additionally, if the "Exit at the Volatility Bands" option is selected, the same Band will be used for the exit criteria.
3. Buy/Sell Meanline retest": A position will be opened when the price retests the Meanline. The price must touch or wick through the Meanline without closing below/above it. (If this strategy is combined with "Exit at the Meanline" option, then in case price goes against our position, the strategy will exit if the price closes under/above the meanline
Buy/Sell Meanline breakout (UP/DOWN)": A long or short position will be opened when the price breaks above or below the Meanline
4. Buy/Sell Support/Resistance lines": A position will be opened when the price touches the support or resistance lines. This option can also be combined with the "Exit at the Meanline" option.
This tool can be used to help enter a trending asset or find entries for an asset retracing.
Please take care to test strategies before automation, which is also possible.
Previous Day High Low Strategy only for LongWelcome to the "Previous Day High Low Strategy only for Long"!.
This strategy aims to identify potential long trading opportunities based on the previous day's high and low prices, along with certain market strength conditions.
Key Features:
Entry Conditions: The strategy triggers a long position when the current day's closing price crosses above the previous day's high or low.
Market Strength Filter: The strategy incorporates a market strength filter using the Average Directional Index (ADX). It only takes long positions when the ADX value is above a specific threshold and when there is a predominance of upward movement.
Trade Timing: The strategy operates within a specified trade window, starting at 09:30 and ending at 15:10. Positions are closed at 15:15 if still active.
Risk Management: The strategy employs dynamic stop-loss and profit-taking levels based on a user-defined Max Profit value. It has three profit targets (T1, T2, T3) and a stop-loss level to manage risk effectively.
Rules:
Ensure that the strategy idea is clearly understandable. Provide an easy-to-read title and a thoughtful description explaining the reasoning behind the strategy.
All content should be ad-free. Avoid any form of promotion, advertising, or solicitation.
No fundraising requests or money solicitation is allowed on TradingView.
Publish in the same language as the TradingView subdomain you're on, except for script titles, which must be in English.
Don't plagiarize. Create and share only unique content, and always give credit when using someone else's work.
Be respectful, kind, and constructive when engaging with others.
Zero tolerance for contentious political discourse, defamatory, threatening, or discriminatory remarks.
Avoid sharing harmful, misleading, or inappropriate content.
Respect the moderators' work and address complaints privately.
Use only your original account and avoid creating duplicate or fake accounts.
Do not attempt to manipulate the reputation system or engage in like-for-like schemes.
Explanation of how the strategy works
1. Previous Day's High and Low (HH, LL):
In this strategy, we start by obtaining the high and low prices of the previous day (not the current day) using the request.security function. This function allows us to access historical data for a specific time frame. The high and low prices are stored in the variables HH and LL, respectively.
2. Entry Conditions:
The strategy uses two conditions to trigger a long position:
Condition 1 (Long Condition 1): If the closing price of the current day crosses above the previous day's high (HH), it generates a long signal. This is achieved using the ta.crossover function, which detects when a crossover occurs.
Condition 2 (Long Condition 2): Similarly, if the closing price of the current day crosses above the previous day's low (LL), it also generates a long signal.
Combined Condition: To take long positions, the strategy combines both long conditions using the logical OR operator (or). This means that if either of the two conditions is met, a long position will be initiated.
3. Market Strength Filter:
The strategy also includes a filter based on the Average Directional Index (ADX) to gauge the market's strength before taking long positions. The ADX measures the strength of a trend in the market. The higher the ADX value, the stronger the trend.
Calculation of ADX: The ADX is calculated using the adx function, which takes two parameters: LWdilength (DMI Length) and LWadxlength (ADX period).
Strength Condition (strength_up): The strategy requires that the ADX value should be above a threshold (11 in this case) and that there is a predominance of upward movement (up > down) before initiating a long position. The LWADX value is multiplied by 2.5 and compared to the highest value of LWADX from the last 4 periods using ta.highest(LWADX , 4). If these conditions are met, the variable strength_up is set to true.
Combined Condition: The strength_up condition is then combined with the long conditions using the logical AND operator (and). This means that the strategy will only take a long position if both the long conditions and the market strength condition are met.
4. Trade Timing:
The strategy sets a specific trade window between 09:30 and 15:10. It will only execute trades within this time frame (TradeTime).
5. Risk Management:
The strategy implements dynamic stop-loss (SL) and profit-taking levels (T1, T2, T3) based on a user-defined Max Profit value. The stop-loss is set as a percentage of the Max Profit value. As the position moves in favor of the trader, the profit targets are adjusted accordingly.
6. Position Management:
The strategy uses the strategy.entry function to enter long positions based on the combined entry conditions. Once a position is open, the script uses strategy.exit to define the exit condition when either the profit target or stop-loss level is hit. The strategy.close function is used to close any open position at the end of the trade window (15:15).
7. Plotting:
The strategy uses the plot function to visualize the previous day's high and low prices, as well as the stop-loss (SL) and profit-taking (T1, T2, T3) levels on the chart.
Overall, the "Previous Day High Low Strategy only for Long" aims to identify potential long trading opportunities based on the previous day's price action and market strength conditions. However, as with any trading strategy, it's essential to thoroughly test it and consider risk management before applying it to real-world trading scenarios.
Disclaimer:
The information presented by this strategy is for educational purposes only and should not be considered as investment advice. The strategy is not designed for qualified investors. Always conduct your own research and consult with a financial advisor before making any trading decisions.
Remember, the success of any trading strategy depends on various factors, including market conditions, risk management, and individual trading skills. Past performance is not indicative of future results.
SuperTrend Enhanced Pivot Reversal - Strategy [PresentTrading]
- Introduction and How it is Different
The SuperTrend Enhanced Pivot Reversal is a unique approach to trading that combines the best of two worlds: the precision of pivot reversal points and the trend-following power of the SuperTrend indicator. This strategy is designed to provide traders with clear entry and exit points, while also filtering out potentially false signals using the SuperTrend indicator.
BTCUSDT 6hr
ETHBTC 6hr
Unlike traditional pivot reversal strategies, this approach uses the SuperTrend indicator as a filter. This means that it only takes trades that align with the overall trend, as determined by the SuperTrend indicator. This can help to reduce the number of false signals and improve the overall profitability of the strategy.
The Pivot Reversal Strategy with SuperTrend Filter is particularly well-suited to the cryptocurrency market for the reason of High Volatility. This means that prices can change rapidly in a very short time, making it possible to make a profit quickly. The strategy's use of pivot points allows traders to take advantage of these rapid price changes by identifying potential reversal points
- Strategy: How it Works
The strategy works by identifying pivot reversal points, which are points in the price chart where the price is likely to reverse. These points are identified using a combination of the ta.pivothigh and ta.pivotlow functions, which find the highest and lowest points in the price chart over a certain period.
Once a pivot reversal point is identified, the strategy checks the direction of the SuperTrend indicator. If the SuperTrend is positive (indicating an uptrend), the strategy will only take long trades. If the SuperTrend is negative (indicating a downtrend), the strategy will only take short trades.
The strategy also includes a stop loss level, which is set as a percentage of the entry price. This helps to limit potential losses if the price moves in the opposite direction to the trade.
- Trade Direction
The trade direction can be set to "Long", "Short", or "Both". This allows the trader to choose whether they want to take only long trades (buying low and selling high), only short trades (selling high and buying low), or both. This can be useful depending on the trader's view of the market and their risk tolerance.
- Usage
To use the Pivot Reversal Strategy with SuperTrend Filter, simply input the desired parameters into the script and apply it to the price chart of the asset you wish to trade. The strategy will then identify potential trade entry and exit points, which will be displayed on the price chart.
- Default Settings
The default settings for the strategy are as follows:
ATR Length: 5
Factor: 2.618
Trade Direction: Both
Stop Loss Level: 20%
Commission: 0.1%
Slippage: 1
Currency: USD
Each trade: 10% of account equity
Initial capital: $10,000
These settings can be adjusted to suit the trader's preferences and risk tolerance. Always remember to test any changes to the settings using historical data before applying them to live trades.
Swing Algo V1.4◆ Introduction
The latest version of the Swing Algo features a complementary system consisting of two internal swing trading logics: an enhanced Swing Algo V1.3 and a secondary control engine to stabilize the overall strategy behaviour in times of increased market chop. Both algorithms feature different averaging lines as well as oscillators, leading to a higher strategy diversification for swing trading as well as a reduced maximum drawdown in comparison to each stand-alone strategy.
While the Swing Algo V1.x series so far featured a single trend-following swing algorithm for each release, where one just switches between Long and Short trades based on one general logic, here two strategies, which act independently of each other, are applied. Due to this, we introduce a third position a trader can be in: the Hedge. The overall logic is as follows:
When both sub-logics are Long, the overall strategy is Long.
When both sub-logics are Short, the overall strategy is Short.
When one sub-logic is Long and the other is Short, the overall strategy is in a Hedge position. It doesn't matter which component is Short and which is Long.
As PineScript doesn't currently offer a real steady hedging-function for two competing swing trading sub-logics (in the sense of a continuously applied Hedge state after hedging conditions are met at least once for an entry), a workaround via position closes was created for this release. For each new internal sub-signal, the overall strategy changes its state (Long/Short/Hedge) visibly on the chart, and the trader can adjust their position accordingly.
For detailed differences to previous Swing Algo V1.x releases, see further below.
◆ Purpose of this Script
This indicator will give Long, Short and Hedge signals on the chart that can be used for e.g. swing trading. Each of the aforementioned sub-logics uses a combination of several (custom) functions and rules to find good entry points for trend trading. After many iterations and tests I came up with this particular setup, which is highly optimized for the ETH/USD trading pair on the daily (D) timeframe.
Attention was also paid to stability, as all parameters are set onto plateaus, so that smaller changes in the characteristic price action should not affect the efficiancy too much, done as an attempt to reduce overfitting as much as possible. Additionally this dual algorithm system is specifically designed to have a safety net: should for the unlikely scenario one swing trading algorithm not trigger at a certain mid-term reversal point, the probability is high that the other will trigger, resulting in an overall hedged position (so that no money is lost in the meantime) until the first algorithm can rejoin at the next mid-term trend change.
For other assets and/or timeframes it is in principle possible to change algorithmic parameters within the indicator settings to tune the swing algorithms, though it is strongly recommended to use the standard asset and timeframe mentioned above.
◆ Viability
For the here presented backtest data, we omitted the biggest portion of the cryptocurrency bullrun in 2017 (starting only at 1st July 2017) so that the results become more realistic for long-term swing traders (investing at least 2-4 years into trading) if such large runs do not happen again. As cryptocurrencies like Ethereum are still to this date capable of doing comparatively smaller runs of about 2-3x in a few weeks/months during accumulation phases (as witnessed e.g. in 2020 and more recently in 2023) and bigger runs during bullmarkets (as witnessed in 2021), the quality of the shown results is still realistic for long-term trend trading efforts over several years, Note that very conservative trading parameters as mentioned below in "Forwardtesting and Backtesting" are used here.
Generally do not expect results in a matter of days or weeks, and of course as with any trading strategy past performances are not indicative of future results.
◆ Forwardtesting and Backtesting
The individual components have been back- and partially forwardtested: The first sub-logic is an advancement of Swing Algo V1.3, with which we have extensive experience running back to October 2020 for its release, while the secondary control strategy, which was privately published for DeanTrader members as a stand-alone script on TradingView in June 2022 and was running in the background since then, is showing good & expected behaviour so far.
While this does not mean that fowardtesting was performed specifically for the combined Swing Algo V1.4 system we have now (which cannot be done realistically considering the timeframes used, i.e. months and especially years), we can at least look at some considerable experience with the individual components. Then again, as I have implemented an exact hedging-function so that both sub-algorithms run independently from each other, it is not likely to see any unexpected behaviour resulting purely from the combination into one script.
For strategy backtesting you can choose the backtest time interval to test the performance of this algorithm for different time windows and different trading pairs. Here various backtesting parameters (e.g. trading fees) can be customized. Default settings for the shown backtest are a starting balance of $1000, a slippage of 20 ticks (= $0.20) and a trading fee of 0.05 % (which is the worst taker fee on the Kraken Pro futures exchange) to have realistic settings. However as we do not conduct many trades with this strategy, fees should not impact our performance too much. As long-term swing traders, we at DeanTrader generally devote one initial portion of our portfolio to swing trading and from then on always use 100% of this portion for the next trade to get the compounding starting. This is in difference to other trading styles which use various, often very small, percentage values for their short- or mid-term trades. Please note that for the here presented backtest only 10% of compounded equity is used for each successive trade to show an estimation for a lower risk & lower reward approach . Keep this in mind when evaluating the backtest data. You can set appropriate values for each backtest parameter in the "Properties" setting menu of the strategy, including the order size percentage of equity value for your trades. Also note that due to the small number of trades the statistical significance is low. It is not possible to gather an abundance of long-term trend signals in the order of hundreds or thousands trades, as much more time would have to pass for this in the case of rather new assets like Ethereum.
Additionally to the TradingView Strategy Tester you can also plot your equity directly on the chart to get a sense for the performance. For this you can also scale the equity graph to e.g. match the starting point of your equity with some price point on the chart to get a direct comparison to 'Buy & Hold' strategies over time.
This indicator (and all other content I provide) is no financial advice. If you use this indicator you agree to my Terms and Conditions which can be found on my website linked on my TradingView profile or in my signature.
◆ Visual Representation on the Chart
Shown below is a screenshot of how the chart looks like when the strategy is applied. Here we can see two different averaging lines, where each line belongs to one of the two sub-logics respectively. Note that this is not a MA-crossover strategy, and the crossing of the lines is not accounted for in the code at all and therefore has no effect on the strategy's signal output. Also note that the price scale is set on logarithmic.
The space between the lines is filled with a faint background color as a rough visual indicator. Magenta-colored fills indicate zones where only Short or Hedge signals can appear, while green-colored fills indicate zones where only Long or Hedge signals can appear. Gray-colored fills mark zones where only Hedge signals can appear, which also means that Hedge signals can appear in any zone. So treat those background fills more as a visual aid to roughly know what can happen next, but pay most attention to the actual signals (with arrows) that appear on the chart.
◆ Differences to Other Versions
Consists now of two competing sub-algorithms instead of just one algorithm. The new system outputs Long, Short and Hedge signals instead of just Long and Short signals.
The first sub-logic is the spiritual successor of the original Swing Algo V1.3 release, with a modified oscillator part.
The second sub-logic serves as a control algorithm (while still having equal rights in terms of strategy impact), newly introduced to the Swing Algo series, but already forwardtested for roughly a year at time of release.
Lowers risk significantly by diversifying swing trading strategies, so that for the rare scenario of a missed trend on one sub-algorithm, losses are prevented as the overall strategy is hedged during that time.
Lowers risk further as the maximum drawdown of the combined strategy is reduced by roughly 1/3 in comparison to each stand-alone strategy while almost retaining the same net profit over a 6-year backtest compared to the first, leading sub-logic.
No guesswork anymore when to use which short leverage (1x corresponding to a Hedge, or 2x corresponding to a Short with an asset-value-change-to-gain-proportionality of -1) as it is clearly defined within the trading system via the displayed signals. In earlier Swing Algo versions, the short leverage for any particular Short signal had to be chosen by hand dependent on market sentiment, which required further market analysis, or was fixed at 2x, leading to less flexibility.
◆ Access
For access please contact me via DM on TradingView or via other channels (linked on my TradingView profile and in my signature).
Baseline Cross Qualifier Volatility Strategy with HMA Trend BiasFor trading ES on 30min Chart
Trading Rules
Post Baseline Cross Qualifier (PBCQ): If price crosses the baseline but the trade is invalid due to additional qualifiers, then the strategy doesn't enter a trade on that candle. This setting allows you override this disqualification in the following manner: If price crosses XX bars ago and is now qualified by other qualifiers, then the strategy enters a trade.
Volatility: If price crosses the baseline, we check to see how far it has moved in terms of multiples of volatility denoted in price (ATR x multiple). If price has moved by at least "Qualifier multiplier" and less than "Range Multiplier", then the strategy enters a trade. This range is shown on the chart with yellow area that tracks price above/blow the baseline. Also, see the dots at the top of the chart. If the dots are green, then price passes the volatility test for a long. If the dots are red, then price passes the volatility test for a short.
Take Profit/Stoploss Quantity Removed
1 Take Profit: 100% of the trade is closed when the profit target or stoploss is reached.
2 Take Profits: Quantity is split 50/50 between Take Profit 1 and Take Profit 2
3 Take Profits: Quantify is split 50/25/25.
Stratgey Inputs
Baseline Length
37
Post Baseline Cross Qualifier Enabled
On
Post Baseline Cross Qualifier Bars Ago
9
ATR Length
9
Volatility Multiplier
0
Volatility Range Multiplier
10
Volatility Qualifier Multiplier
2
Take Profit Type
1 Take Profit
HMA Length
11
TUE ADX/MACD Confluence Algorithm V1This algorithm is designed to look at the ADX/MACD confluence for opening conditions, apply various filters including volume and volatility, then determine stop outs, break evens, and take profits.
The ADX and MACD confluence can be a powerful predictor in stock movements. Both of these indicators find trend but do it in different ways. When they're combined they have a high success rate of finding openings. That's done by finding the bar in which both show the same direction - that bar is the beginning of the confluence. I have a free indicator called the TUE ADX/MACD Confluence that you can use to see this in action.
This script will help you find those confluences in an easy to understand manner. It will open a trade on a detected confluence, using the rest of the variables available in the algorithm as filters. You can filter based on cumulative volume delta, volatility, and trend. It includes settings for either trend following or contrarian trades, and the ability to go long, short, or both.
It includes Buy and Sell signals for detected confluences, and will show colored candles to help you determine when to exit a trade if you don't want to follow the included take profit areas. When the candles turn to white that means the detected confluence is no longer in play. The Buy and Sell signals will display on the first occurrence of each confluence.
The take profit areas are based on proprietary math that help find peaks and valleys. You can adjust the size of the take profits as a percentage of the position, change to static take profits (i.e. take profit in 16 ticks), or use both. You can also disable them and use the natural closing conditions (reversal of MACD/ADX confluence).
Our algo works in any market and will allow user to adjust input settings to be used on any ticker they'd like. It is built as a strategy so you can back test on any ticker to find the exact right settings to dial it in and then switch to live trading mode to see signals. Can be used for day trades or swing trades.
Automated Trading
This algo has been tested and certified to work for automated trading.
Works on Forex
It's confirmed to work on forex so you can trade that market.
Gets you into long successful trades, and gets out of poor ones quickly
It keeps you in the long trades taking small profits along the way, but cuts losers quickly in comparison. This style leads to a high profit factor, as you can see over 3.0 in the included ES 3 Min chart.
It looks at many variables so you don't have to
- Uses ADX/MACD confluence for opening/closing conditions.
- It uses volume, if the user wants, to help filter entries. The volume calculation is based off of my proprietary cumulative volume delta indicator and helps find if the volume is moving long or short.
- It uses proprietary take profit math to help find peaks and valleys to peel off profits. It is based on the changes in momentum of the underlying.
- It allows for stop outs and break evens based on volatility so they'll always adjust with the movement of the underlying ticker (see the blue lines above and below the opening in the chart).
- It allows for offset break evens to keep a portion of the profit.
Strategy for the Algo
Included so you can understand how to trade with it.
ONE: After loading this strategy onto a ticker turn off volume if it's a ticker with no volume , set the dates at the bottom to when the stock is active (you want to start backtesting when a stock started trading like it trades currently).
TWO: From there adjust the ADX/MACD to find the highest win rate and profit factor.
THREE: Then adjust the volume length to find the highest win rate and profit factor. It's important while doing these that you pay attention to a smooth upward equity curve.
FOUR: After this has been done now adjust the long and short risk multipliers. This determines your stop out.
FIVE: Then adjust breakeven multipliers - this is the level at which it changes to a breakeven stop out instead of the previous one. You can also set an offset to keep a small part of the profit.
SIX: Finally adjust the take profit sizes.
SEVEN: Once this is all done go back through the list and adjust up and down by one or two clicks and see if a better curve can be obtained. Very frequently long and short trades have different settings.
EIGHT: When you are finished save the settings in a custom indicator template and put it with it's own chart.
Additional
The settings shown on screen are not the default settings, but are settings chosen for this ticker and timeframe based on the process above. Nearly every ticker and timeframe will require adjustment from default, that's why the algorithm is built to be highly flexible. It can fit any ticker and timeframe, as well as market environment.
Also included in the chart above is a $1.25 commission per contract, and a tick of slippage (which on average is about right for automated trading on ES).
Strategy Myth-Busting #13 - MultiEMA+BXTrender - [SP/MYN]#13 on the Myth-Busting bench, we are automating the "I Found The Highest Win Rate 15 Minute Scalping Trading Strategy Ever" strategy from "TradeIQ" who claims to have backtested this manually and achieved 410% profit over 100 trades within 6 months on Natural Gas with 79 Wins / 21 Losses with an astounding 3.96% Max Drawdown.
It was quite challenging emulating the same subjective EMA pullback logic along with the dependent sequencing of events necessary to enter a trade and we might improve on this to make it better in the future. Super kudos to @spdoinkal who helped with this strategy. If you have ideas on how this could be improved on, would love to hear about them.
As is, we were unable to substantiate similar results to what was manually backtested by TradeIQ, we do however see potential here. Given some optimizations and improvements to the the entry logic accommodating for a wider more variable margin after pullbacks reestablish above/below the fast EMA we think the performance of this strategy could certainly be improved upon. So not sure if we have totally myth busted this completely at this point in time.
This strategy uses a combination of 2 open-source public indicators:
3 EMA's (Trading View Internal)
B-Xtrender by Puppytherapy
Three separate (21), (89) and (200) EMA's are used as a means to confirm and keep entry out of ranged markets. When the 3 EMA's are all clumped up together with no distance it's indicative of a flat or ranged market. This is then used in conjunction with B-XTrender as a means to detect the trend direction. B-XTrender which is a trend following indicator originally published in the IFTA Journal by Bharat Jhunjhunwala. It uses both a short and long term lengths along with a compound EMA used as a means to smooth and sample trend direction.
Trading Rules
15 min candles but other lower time-frames
Stop Loss on previous swing high/low
No Take Profit, Exit on new red/green circles from BX-Trender
Long
EMA Green (21) on top, White (89)in middle and red (200) on bottom and there is distance between EMA's need to be spaced, otherwise in a ranged market
Price action must pull back into 89 EMA (White line) either close or touching it.
Once pullback occurs wait for BX Trender to issue a new green circle and BX Trend line must be green and above 0
Price action must also pull up back above the (Green Line) EMA 21
Short
EMA Red (200) on top, White (89) in middle and Green (21) on bottom and there is distance between EMA's need to be spaced, otherwise in a ranged market
Price action must pull back into 89 EMA (White line) either close or touching it.
Once pullback occurs wait for BX Trender to issue a new red circle and BX Trend line must be red and below 0
Price action must also pull up back below the (green Line) EMA 21
If you know of or have a strategy you want to see myth-busted or just have an idea for one, please feel free to message me.
TTP OSC SuperTrendThis strategy instead of following the trend of the price it follows the trend of an oscillator.
You can follow the trend of RSI or CCI.
We use SuperTrend applied to either oscillator for entering a long.
Position can close from
- using a stop loss percentage parameter
- or when entering downtrend
- or when using TP% when the target is achieved
Ideas:
- Use the SuperTrend multiplier to match the oscillator behaviour, CCI moves less, so I use 1.5 multiplier. With RSI I use 3
- I find this strategy works great to do swing trades during bull markets. When backtesting BTCUSDT it outperforms buy and hold before the beginning of the bear market.
- Try RSI 7 instead of RSI 14 for faster response
Alerts
It supports separated payloads for each alert type:
1- Deal open
2- TP% reached
3- SL%
4- Downtrend deal close
Cipher_B (Finandy support)In this version of the script you can force to cancel your position after some amount of time indepedently on price action. For example, your bot open a short position with SL=1% and TP=2.4% but price did not reach any of this level over the course of to say 8 hours. In this case, position will be closed regardless of the price.
Other interesting features are volume and slope filters. Slope is essentially a derivative of price action. If you don't like to buy your instrument under high volatility, for example, if a trend goes down too fast then you can filter long position which could be opened according to the strategy. Same thing for volume filter. If the volume is too high/too low, you might want to escape such setup in your trading strategy.
Moreover, you can tune price shift for opening position. To say, if you believe that the signal for opening position comes too early everytime, you can force the strategy to buy at 1% lower price than the current price when the signal comes. Similar logic for short: open position price will be always higher than the price of the signal. If the price did not reach such level then position will be automatically cancel with a new signal arrival. Check the backtesting results to understand better the logic.
Trend #4 - ATR+EMA channelOverview:
This strategy use ATR to take-profit, Red-EMA to stop-loss, Blue-EMA channel to judgment breakout.
This strategy use commission setting is 0.05%, slippage setting is 2 ticks, you can set the appropriate value size in the properties page.
What it does:
This strategy detects when a trend is emerging and buy or sell.
How it does it:
When the price breaks through the blue EMA channel, the trend is judged to be strong in the short term, strategy generates a buy or sell order.
After buying or selling,, if the price moves in the expected direction, uses ATR to determine the appropriate spread to take profit, otherwise use red EMA for stop loss.
How to use it:
Start Date and Stop Date - This parameter adjusts the time range used by the strategy.
Stoploss - This parameter adjusts the stop loss amount after each order is placed.
Blue EMA length - This parameter adjusts the length of the channel.
Blue EMA multy - This parameter adjusts the width of the top and bottom of the channel.
ATR Period - This parameter adjusts the number of candles used by the ATR.
ATR mult - This parameter adjusts the upper and lower widths of the ATR. Lowering this parameter can improve the win rate, but not necessarily the profitability.
Red EMA length - This parameter adjusts the number of candles used by the red EMA .
Long - This switch is used to turn Long position on or off.
Short - This switch is used to turn short position on or off.
Strategy Myth-Busting #8 - TrendSurfers+TrendOsc - [MYN]This is part of a new series we are calling "Strategy Myth-Busting" where we take open public manual trading strategies and automate them. The goal is to not only validate the authenticity of the claims but to provide an automated version for traders who wish to trade autonomously.
Our 8th one is an automated version of the " 653% Gain Magical 1 Minute Scalping Strategy Tested 100 Times | Become Consistently Huge Profit " strategy from " Fxaccurate US " who claims to have achieved 653% profit scalping GOLD on the 5 minute timeframe. As you can see from the backtest results below, I was unable to substantiate anything close to that that claim on any timeframe or symbol. Myth 10000% busted.
If you know of or have a strategy you want to see myth-busted or just have an idea for one, please feel free to message me.
This strategy uses a combination of 2 open-source public indicators:
Trend Surfers - Premium Breakout + Alerts by TrendSurfersSignals
Mawreez' Trend Oscillator Indicator by Mawreez
Trading Rules:
1 min - 15 min candles
Stop loss middle between high and low Risk 1:2
Long Condition
Trend Surfers Trailing stop line goes below (Crosses) lowest low
Bullish Candle (red)
Mawreeze Trend Oscilator Indicator is green
Short Condition
Trend Surfers Trailing stop line goes above (Crosses) highest high
Bearish Candle (red)
Mawreeze Trend Oscilator Indicator is red
