2-Period RSI strategy (with filter)2-period RSI strategy backtest described in several books of the trader Larry Connors . This strategy uses a 2 periods RSI , one slow arithmetic moving average and one fast arithmetic moving average.
Entry signal:
- RSI 2 value below oversold level (Larry Connors usually sets oversold to be below 5, but other authors prefer to work below 10 due to the higher number of signals).
- Closing above the slow average (200 periods).
- Entry at closing of candle or opening of next candle.
Exit signal:
- Occurs when the candlestick closes above the fast average (the most common fast average is 5 periods, but some traders also suggest the 10 period average).
Entry Filter (modification made by me):
- Applied an RSI2 arithmetic moving average to smooth out oscillations.
- Entered only when RSI2 is below oversold level and RSI2 moving average is below 30.
* NOTE: In the stocks that I evaluate daily the averages of 4 and 6 periods work very well as a filter.
Comments:
This strategy works very well in Daily charts but can be applied in other chart times as well. As this is a strategy to catch market fluctuations, it presents different results with different stocks.
I have been applying this strategy to the stocks of the Brazilian market (BOVESPA) and have enjoyed the result. Every day I evaluate the stocks that are generating entry signals and choose which one to trade based on the stocks with the highest Profit Value.
The RSI 2 averaging filter probably will reduce profit of the backtests because reduces the number of signals, but the Profit Value will usually increase. For me this was a good thing because without the filter, this strategy usually shows more signals than I have capital to allocate.
Before entering a trade I look at which fast average the paper has the highest Profit Value and then I use this average as my output signal for that trade (this change has greatly improved the result of the outputs).
This strategy does not use Stop Loss because normally Stop Loss decreases effectiveness (profit). In any case, the option to apply a percentage Stop Loss if desired is added in the script. As the strategy does not use stop, extra caution with risk management is advisable. I advise not to allocate more than 20% of the trade capital in the same operation.
I'm still studying ways to improve this strategy, but so far this is the best setup I've found. Suggestions are always welcome and we can test to see if they improve the backtest result.
Good luck and good trades.
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Backtest das estratégia do IFR de 2 períodos descrita em varios livros do trader Larry Connors . Esta estratégia usa um IFR de 2 períodos, uma média movel aritmética lenta e uma média movel aritmética rápida.
Sinal de entrada:
- Valor do IFR 2 abaixo do nível de sobrevenda (Larry Connors usualmente define sobrevenda sendo abaixo de 5, mas outros autores preferem trabalhar abaixo de 10 devido ao maior número de sinais).
- Fechamento acima da média lenta (200 períodos).
- Realizado a compra no fechamento do candle ou na abertura do candle seguinte.
Sinal de saída:
- Ocorre quando o candle fecha acima da média rápida (a média rápida mais comum é a de 5 períodos, mas alguns traders sugerem também a média de 10 períodos).
Filtro para entrada (modificação feita por mim):
- Aplicado uma média móvel aritmética do IFR2 para suavisar as oscilações.
- Realizado a entrada apenas quando o IFR2 está abaixo do nível de sobrevenda e a média móvel do IFR2 está abaixo de 30.
*OBS: nos ativos que avalio diariamente as médias de 4 e 6 períodos funcionam muito bem como filtro.
Comentários:
Esta estratégia funciona muito bem no tempo gráfico Diário mas pode ser aplicada tambem em outros tempos gráficos. Como trata-se de uma estratégia para pegar oscilações do mercado, ela apresenta diferentes resultados com diferentes ativos.
Eu venho aplicando esta estratégia nos ativos do mercado brasileiro (BOVESPA) e tenho gostado do resultado. Diariamente eu avalio os papeis que estão gerando entrada e escolho qual irei realizar o trade baseado nos papeis que apresentam maior Profit Value.
O filtro da média do IFR 2 reduz o lucro nos backtests pois reduz também a quantidade de sinais, mas em compensação o Profit Value irá normalmente aumentar. Para mim isto foi algo positivo pois, sem o filtro, normalmente esta estratégia apresenta mais sinais do que possuo capital para alocar.
Antes de entrar em um trade eu olho em qual média rápida o papel apresenta maior Profit Value e então eu utilizo está média como meu sinal de saída para aquele trade (esta mudança tem melhorado bastante o resultado das saídas).
Está estratégia não utiliza Stop Loss pois normalmente o Stop Loss diminui a eficácia (lucro). De qualquer maneira, foi acrescentado no script a opção de aplicar um Stop Loss percentual caso seja desejado. Como a estratégia não utiliza stop é aconselhável um cuidado redobrado com o gerenciamento de risco. Eu aconselho não alocar mais de 20% do capital de trade em uma mesma operação.
Ainda estou estudando formas de melhorar esta estratégia, mas até o momento está é a melhor configuração que encontrei. Sugestões são sempre bem vindas e podemos testar para verificar se melhoram o resultado do backtest.
Boa sorte e bons trades.
חפש סקריפטים עבור "the script"
TOLGA ZORLUHello TradingView and world!
This is one of our latest concepts for an actual bot builder. This script comes with a bunch of features that we're hoping will alleviate a lot of the stress and confusion around using and building strategies here on TV. Especially if the end-goal is to automate the strategies using Autoview.
This is a combination of 2 strategies, and gives you full control of each component within the script.
The 2 strategies are:
2 Moving Averages == if close is greater than moving average and moving average 1 is greater than moving average 2
Bolling Bands == if close is less than lower or greater than upper
Features / Settings included :
- Ability to change settings from a commodity market (default) to an altcoin or forex market.
- Backtest time period selector component
- Heiken Ashi Candles on/off
- Moving Average Strategy on/off
- Bollinger Bands Strategy on/off
- Both Moving Average settings can be adjusted
- Bollinger Bands length and multiplier can be adjusted.
- Pyramiding Greater Than, Equal To, or Less Than
- Trailing Stop with the ability to set a price in which the Trailing Stop activate
- Take Profit on/off and editable
- Stop Loss on/off and editable
- Margin Call on/off dependent on Leverage which is editable
- If pyramiding is used, the strategy will calculate and display your average on the chart
- Profit and Loss visuals added to the chart
Moving Average Cross and/or Bbands botHello TradingView and world!
This is one of our latest concepts for an actual bot builder. This script comes with a bunch of features that we're hoping will alleviate a lot of the stress and confusion around using and building strategies here on TV. Especially if the end-goal is to automate the strategies using Autoview.
This is a combination of 2 strategies, and gives you full control of each component within the script.
The 2 strategies are:
2 Moving Averages == if close is greater than moving average and moving average 1 is greater than moving average 2
Bolling Bands == if close is less than lower or greater than upper
Features / Settings included :
- Ability to change settings from a commodity market (default) to an altcoin or forex market.
- Backtest time period selector component
- Heiken Ashi Candles on/off
- Moving Average Strategy on/off
- Bollinger Bands Strategy on/off
- Both Moving Average settings can be adjusted
- Bollinger Bands length and multiplier can be adjusted.
- Pyramiding Greater Than, Equal To, or Less Than
- Trailing Stop with the ability to set a price in which the Trailing Stop activate
- Take Profit on/off and editable
- Stop Loss on/off and editable
- Margin Call on/off dependent on Leverage which is editable
- If pyramiding is used, the strategy will calculate and display your average on the chart
- Profit and Loss visuals added to the chart
You can watch a video here on how all the settings can be used and work together.
www.youtube.com
You can learn more about Autoview here:
autoview.with.pink
Get your invite and join us in slack here:
slack.with.pink
Volume Weighted Bollinger Bands Strategy
Simple strategy,
Using Volume weighted Bollinger Bands
> Directions for Usage:
1. Use only in scripts where volume is specified by tradingview
2. Check on which timeframe the script has a profit factor greater than 1.4
3. Use that timeframe for profitability
4. In some high liquid securities there is a decent profit factor even at 5 min scale (optimise at your end!! all i want to say)
Enjoy!
Hope this helps!!
SMA Crossover demoHi I'm currently in the process of learning to write a script. Here's a very basic SMA 34/5 crossover script. Is somebody able to help me with adding the following functions to the script.
1. Add an alert and indicator to close a short or long trade whenever any candle touches the SMA 34 line?
2. When a SMA 34/5 Crossover has been executed (a Short Trade condition) add an alert/indicator (Titled “Add”) every time a Green bullish candle has closed.
3. When a SMA 34/5 Crossunder has been executed (a Long Trade condition) add an alert/indicator (Titled “Add) every time a Red bearish candle has closed.
4. To used on 15m/30m/1hr/2hr/4hr/1D/1W timeframe charts?
4-Hour Range Scalping [v6.3]User Guide: 4-Hour Range Scalping Strategy
Hello! Here is the guide for the Pine Script strategy. Please read it carefully to get the best results.
📈 This script automates the "4-Hour Range Scalping Strategy" from the video.
The main idea is that the first four hours of a major trading day (like New York) set up a "trap zone." The strategy waits for the price to break out of this zone and then fail, giving us a signal that the breakout was false and the price is likely to reverse.
Here’s the simple logic:
Define the Range: It precisely calculates the highest high and lowest low during the first four hours of the selected trading session (e.g., 00:00 to 04:00 New York Time).
Wait for a Breakout: It then monitors the 5-minute chart for a price breakout where a candle fully closes outside of this established range.
Identify the Reversal: The trade trigger occurs when the price fails to continue its breakout and a subsequent 5-minute candle closes back inside the range. This signals a potential reversal or "failed breakout."
Execute the Trade:
]A Short (Sell) trade is triggered after a failed breakout above the range high.
A Long (Buy) trade is triggered after a failed breakout below the range low.
Manage the Risk: The Stop Loss is automatically placed at the peak (for shorts) or trough (for longs) of the breakout move, and the Take Profit is set to a default 2:1 Risk/Reward Ratio.
How to Use the Script (Step-by-Step) ⚙️
Follow these instructions to get it running perfectly.
1. Set Your Chart Timeframe This is the most important step. The strategy is designed to run on a 5-minute (5m) chart. Open your TradingView chart and make sure the timeframe is set to "5m".
2. Add the Script to Your Chart Open the Pine Editor tab at the bottom of TradingView, paste the entire script, and click the "Add to chart" button.
3. Configure the Settings On your chart, find the strategy's name (e.g., "4-Hour Range Scalping ") and click the gear icon ⚙️ to open its settings.
Trading Session: Choose the session for the range. New York is the default and the one from the video.
Risk/Reward Ratio: The default is 2.0, meaning your potential profit is twice your potential loss. You can adjust this to test other targets.
Backtesting Period: To see how the strategy performed on all historical data, go to the "Strategy Tester" panel, click its own gear icon ⚙️, and uncheck the boxes for "Start Date" and "End Date."
4. Understand the Visuals on Your Chart
Blue Background Area: This is the 4-hour calculation window. The script is identifying the day's high and low during this time. No trades will ever happen here.
Red Line (Range High): The highest price of the 4-hour window. This is the upper boundary of the "trap zone."
Green Line (Range Low): The lowest price of the 4-hour window. This is the lower boundary.
Green Triangle (▲): Shows where a Long (Buy) trade was entered.
Red Triangle (▼): Shows where a Short (Sell) trade was entered.
A Very Important Note on Timezones 🕒
This is critical for you in the Philippines (PHT).
The script is based on the New York session, which is 12 hours behind you. Your TradingView chart will still show your local time, but the script works on NY time in the background.
The New York "day" begins at 12:00 PM (Noon) your time.
The script's blue calculation window will be from 12:00 PM to 4:00 PM your local time.
The red and green range lines will appear on your chart only after 4:00 PM your time.
So, if you look at your chart in the morning or early afternoon, you will not see today's range yet. This is normal! The script is just waiting for the New York session to start.
How to Set Up Trade Alerts 🔔
You can have TradingView send you a notification whenever the script enters a trade.
Click the "Alert" button (looks like a clock) in the right-hand toolbar of TradingView.
In the "Condition" dropdown, select the name of the script (e.g., "4-Hour Range Scalping...").
You will then see two options: "Long Signal" and "Short Signal".
Select one (e.g., "Long Signal") and configure how you want to be notified (e.g., "Notify on app").
Click "Create". Repeat the process to create an alert for the other signal.
⚠️ Important Disclosure
For Educational and Research Purposes Only.
This script and all accompanying information are provided for educational and research purposes only. The strategy demonstrated is a technical concept and should not be misconstrued as financial, investment, legal, or tax advice.
Trading financial markets involves substantial risk and is not suitable for every investor. There is a possibility that you could sustain a loss of some or all of your initial investment. Therefore, you should not invest money that you cannot afford to lose.
Past performance is not indicative of future results. The backtesting results shown by this script are historical and do not guarantee future performance. Market conditions are constantly changing.
By using this script, you acknowledge that you are solely responsible for any and all trading decisions you make. You should conduct your own thorough research and, if necessary, seek advice from an independent financial advisor before making any investment decisions. The creators of this script assume no liability for any of your trading results.
Altcoins DCA ScalperIntroduction
The Altcoins DCA Scalper is a Pine Strategy Script designed to automate Altcoins trading through 3Commas integration. It implements a Dollar-Cost Averaging (DCA) strategy that expands upon 3Commas' standard DCA capabilities, helping to manage risk while trading both long and short positions automatically.
This tool aims to assist both beginners exploring automated trading and experienced 3Commas users seeking dynamic DCA automation. The script is specifically designed for the 1-minute timeframe , where it has shown a good balance between performance and risk management. Complete setup typically takes less than 10 minutes, with a detailed guide making configuration straightforward for users of all experience levels.
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🔶 What is DCA?
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Dollar-cost averaging (DCA) refers to the practice of gradually increasing your position size at lower prices when trading long, or at higher prices when trading short, to achieve a better average entry price if the market moves against the initial entry . Instead of investing all capital at once, which could result in a significant drawdown if the price moves unfavorably, DCA spreads entries across different price levels to help manage potential drawdowns as they occur.
In this script, DCA is implemented through a system that:
🔹 Triggers safety orders only when/if needed (if take profit isn't reached quickly)
🔹 Dynamically adjusts order sizing based on market volatility
🔹 Automatically reduces take profit targets after each DCA order to increase the likelihood of a positive outcome
🔹 Can handle drawdowns depending on market volatility and settings
The images below illustrate two scenarios: one where an entry reaches the take profit directly, without activating DCA orders, and another where DCA is utilized, with the order closing positively after two DCA orders.
Case 1: Order closes in profit after entry
Case 2: Order closes in profit after 2 DCA orders (dynamically placed based on trend and volatility)
This DCA implementation aims to enhance standard 3Commas DCA by adding market-adaptive features while maintaining risk management principles.
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🔶 Could this strategy script benefit you?
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This script may be helpful if you are:
✅ Looking to automate your trading through 3Commas integration while maintaining full control of your assets
✅ Wanting to enhance 3Commas' standard DCA with market-adaptive features that consider:
Multi-timeframe trend analysis
Real-time volatility assessment
Dynamic safety order sizing and timing
✅ Seeking to minimize chart monitoring through full automation of:
Entry and exit decisions
Safety order management
Risk controls
✅ Interested in comprehensive performance tracking with:
Real-time position metrics
Detailed backtesting capabilities
Risk/reward analysis
Backtesting Metrics (script performance over the backtesting period - which is approx. 15 days on the 1min timeframe with the TradingView Pro Plan):
Current/Open Deal Metrics (the deal is currently under DCA, and waiting for further actions to close):
✅ Looking for trading automation that remains easy to set up and use
Note: While this script provides trading automation, successful trading requires proper education, risk management, and regular performance monitoring. No automated tool can guarantee trading success or profits.
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🔶 How it Works
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The Altcoins DCA Scalper provides trading automation through:
Market Analysis
* Multi-timeframe trend analysis (1m to 1d) for market direction and entry validation
* Volatility assessment (1h, 4h, 24h) benchmarked against TOTAL3 (excluding Top10 Altcoins and Stablecoins)
* Real-time adjustment of DCA parameters based on:
* Current volatility class (low/medium/high) vs. overall Altcoins market
* Market trend strength
* Price action dynamics
Trading Execution
* Position opening aligned with detected market trends
* "Beast Mode" base order sizing that increases position size during strong trends
* Dynamic take-profit targets that automatically reduce after each safety order to increase the likelihood of positive exits
* Dynamic DCA with safety orders that can:
* Adapt timing based on volatility
* Scale order sizes based on market conditions
* Handle 30-50% drawdowns depending on volatility class
* Execute up to 6 safety orders per position
Risk Management
* Emergency exits during extreme market events:
* "Black Swan" protection for long positions
* "God-Candle" protection for short positions
* Configurable stop-loss with volatility-based placement
* Trend-switch management with automated position reversal
* Position aging controls to prevent capital lock-up
* Leveraged trading protection with a pre-liquidation exit system
Integration & Automation
* Quick setup with two 3Commas bots (typically under 10 minutes)
* Fully automated signal generation and execution through 3Commas
* Detailed performance tracking including:
* Real-time position metrics
* DCA depth analysis
* Win rate and ROE calculations
* Pre-configured settings optimized for most pairs
* Multiple customization options for experienced users
Note: While this strategy employs automation and risk management, trading always carries the risk of loss. No system can guarantee profits, and market conditions significantly impact performance. Always do your own research and monitor your positions closely.
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How to Use
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Setting up the Altcoins DCA Scalper is quick and facilitated by the User Interface:
1️⃣ 3Commas/TradingView Setup
* Create two 3Commas accounts if using the FREE plan:
* One account for Long Bot
* One account for Short Bot
* This split allows full functionality while staying within 3Commas' free tier limits
* You do not need two separate accounts if you have a Paid 3Commas subscription
* While a free TradingView account works with the script, it limits you to one trading pair and a 4-day backtesting history. A paid TradingView subscription removes these limitations (such as the "Essential" plan).
2️⃣ Bot Configuration
* Create one Long and one Short DCA Bot in 3Commas
* Follow the setup guide available in the script itself for hassle-free configuration
* Copy Bot IDs and Email Token for script connection
* No complex settings needed - the script manages all DCA parameters by itself
3️⃣ Script Implementation
* Apply the script to your TradingView charts
* Use the built-in backtesting to analyze performance on different pairs
* Focus on USDT.P futures pairs with good volatility
4️⃣ Trading Activation
* Create TradingView alerts for each trading pair you want to activate
* Example: Set an alert for BINANCE: XRPUSDT.P following the in-script guide
* The script automatically manages all aspects:
* Entry and exit decisions
* DCA execution
* Risk management
* Position monitoring
Capital Requirements
* Important: Ensure sufficient capital to cover all activated pairs
* Consider volatility class when allocating capital to specific pairs
Once setup is complete, the script operates fully automatically while you maintain complete control of your funds through 3Commas and your exchange.
Note: While the setup is straightforward, always start with a small number of pairs and monitor performance before expanding. Trade responsibly and never risk more than you can afford to lose.
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Explaining the Settings
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The Altcoins DCA Scalper offers mulitple customization options during the setup process. All settings include detailed tooltips and default values.
Core Settings Sections:
1️⃣ 3Commas Connection
* Bot IDs and Email Token configuration
* Leverage settings (1x to 5x supported)
* Detailed 3Commas bot setup guide included
* Automatic bot control configuration
2️⃣ Trading Parameters
* Capital allocation per trade
* Timeframe verification
* Alert system setup
* Backtesting period control
* Performance tracking preferences
3️⃣ Advanced Features
🔹 Risk Management Suite
* Emergency exit controls (to strengthen protection against extraordinary market events)
* Customizable stop-loss system
* Trend-based exit management
* Position aging controls
* Liquidation protection features
* Advanced DCA controls
🔹 Performance Analytics
* Real-time position monitoring
* Comprehensive backtesting metrics
* DCA depth analysis
* Win rate calculations
* Capital efficiency tracking
🔹 Technical Optimizations
* Exchange minimum order adjustment
* Trading pair name override capability
* System stability controls
* Error handling mechanisms
🔹 Interface Customization
* Theme selection
* Chart overlay options
* Warning display preferences
* Performance metrics visibility
All settings come pre-configured but can be fully customized based on your trading preferences and risk tolerance. The script includes tooltips and setup guides for each option.
Note: While default settings may be tested, market conditions vary and all trading involves risk. Monitor performance and adjust settings according to your risk management requirements.
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Frequently Asked Questions
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Here are some common questions you may have, and our answers:
❓ Is this tool only for experts? I'm new to algo trading, can I use it?
No, the Altcoins DCA Scalper could be used by both beginners and experienced traders. The setup process is guided, and the algorithm handles all the calculations in the background.
❓ I'm not familiar with 3Commas. Is that a problem?
While the script is designed to work with 3Commas, a step-by-step guide is provided within the script to help you set up your 3Commas accounts and bots, if needed.
❓ Do I need to constantly monitor the script after it's set up?
No, after the initial setup and configuration, the script operates autonomously. It handles all aspects of trading including entries, exits, DCA management, and risk controls. However, we recommend:
* Checking performance metrics daily
* Reviewing position statistics weekly
* Adjusting pair selection monthly based on performance
* Monitoring overall market conditions that might require adjustments
❓ Can I use it with leverage?
Yes, the script is designed to work with leverage up to 5x on perpetual futures pairs (USDT.P). It includes specific features for leveraged trading:
* Dynamic safety order placement based on distance to liquidation
* Pre-liquidation exit system to minimize exchange fees
* Adjustable take-profit targets optimized for leveraged positions
* Emergency exit system for extreme market movements
* Optional risk controls specific to leverage:
* Automatic exit in the liquidation danger zone
* Position size scaling based on leverage level
* Safety order adjustments for different leverage settings
While leverage can amplify returns, it also increases risk. We recommend starting with lower leverage (2x), or no leverage at all, until familiar with the script's operation.
❓ Does this script guarantee profits?
No, no script or trading strategy can guarantee profits. The Altcoins DCA Scalper provides a framework for implementing an automated DCA strategy, but your success will depend on many different factors and conditions.
❓ Do I need to understand the complex algorithms used in the script?
No, it’s not necessary. The logic is handled by the script, and you do not need to understand every detail to use it effectively. However, a basic knowledge of DCA concepts will be beneficial.
❓ Can I use this script with spot or leveraged trades?
The script is optimized for USDT.P pairs (perpetual futures) with leverage up to 5x. This allows:
* Automatic long/short position management
* Increased capital utilization
* Full DCA functionality without holding the underlying assets
* Enhanced risk management features specific to futures
While spot trading is possible, it requires holding underlying assets for shorts and doesn't access the script's full capabilities.
❓What timeframe should I use?
This script is optimized for the 1-minute timeframe , which is the recommended setting for the best balance between performance, capital efficiency, and risk. While we recommend using the tool on the 1 minute TF, it would work on other timeframes too.
❓ What happens if my internet/computer goes down?
Since the script sends signals from Tradingview to 3Commas (which executes trades on your exchange), your positions and DCA management continue to function even if your TradingView chart is closed or your computer is off. The script only needs to be active to generate new signals.
❓ How are the DCA parameters determined?
The script dynamically adjusts DCA parameters based on:
* The pair's volatility class (compared to the overall altcoin market)
* Current market conditions and volatility
* Position direction (long/short)
* Leverage settings
* Number of safety orders already executed
This allows for adaptive/dynamic DCA compared to static or %-based parameters.
❓ What exchanges are supported?
The script works with any exchange supported by 3Commas for futures trading (approximately 15 different crypto Exchanges). However, it's optimized for Binance Futures (USDT.P pairs) due to its high liquidity and for consistency.
❓ What happens during extreme market conditions?
The script includes some (optional) protective measures that can be activated:
* Emergency exits during sharp and abnormal market moves
* Automatic adjustment of DCA parameters during high volatility
* Position closure on significant trend changes
* Special handling of aged positions
These features aim to protect capital during unusual market conditions.
❓How many pairs can I trade simultaneously?
This depends on your total capital. As a general indication, define the number of pairs to activate based on:
* Total available capital
* Desired position size per pair
* Risk tolerance
* Pairs' volatility class
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Final Thoughts
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We believe that your trading performance will greatly depend on your selection of appropriate trading pairs for this script (high volatility), and your commitment to regularly monitoring its performance and adjust the settings, rather than on the script alone.
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⚠️ Risk Disclaimer
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Remember that trading involves risk, and most day traders experience losses. This script is for educational and informational purposes only. Past performance does not guarantee future results. This is not financial advice, and you should always do your own research (DYOR). Trade responsibly with capital you can afford to lose.
The Altcoins DCA Scalper is an independent tool and is not endorsed, connected, or validated by TradingView.
3Commas is a third-party service, and TradingView is not responsible for the 3Commas integration or the performance of 3Commas bots. You are solely responsible for the security and management of your 3Commas account. Do not share your 3Commas access credentials (like login information, Bots-ID, Email Token) with anyone. The Author of the script has no access to such information, and nobody (but you) should.
QuantBuilder | FractalystWhat's the strategy's purpose and functionality?
QuantBuilder is designed for both traders and investors who want to utilize mathematical techniques to develop profitable strategies through backtesting on historical data.
The primary goal is to develop profitable quantitive strategies that not only outperform the underlying asset in terms of returns but also minimize drawdown.
For instance, consider Bitcoin (BTC), which has experienced significant volatility, averaging an estimated 200% annual return over the past decade, with maximum drawdowns exceeding -80%. By employing this strategy with diverse entry and exit techniques, users can potentially seek to enhance their Compound Annual Growth Rate (CAGR) while managing risk to maintain a lower maximum drawdown.
While this strategy employs quantitative techniques, including mathematical methods such as probabilities and positive expected values, it demonstrates exceptional efficacy across all markets. It particularly excels in futures, indices, stocks, cryptocurrencies, and commodities, leveraging their inherent trending behaviors for optimized performance.
In both trending and consolidating market conditions, QuantBuilder employs a combination of multi-timeframe probabilities, expected values, directional biases, moving averages and diverse entry models to identify and capitalize on bullish market movements.
How does the strategy perform for both investors and traders?
The strategy has two main modes, tailored for different market participants: Traders and Investors.
1. Trading:
- Designed for traders looking to capitalize on bullish markets.
- Utilizes a percentage risk per trade to manage risk and optimize returns.
- Suitable for both swing and intraday trading with a focus on probabilities and risk per trade approach.
2. Investing:
- Geared towards investors who aim to capitalize on bullish trending markets without using leverage while mitigating the asset's maximum drawdown.
- Utilizes pre-define percentage of the equity to buy, hold, and manage the asset.
- Focuses on long-term growth and capital appreciation by fully/partially investing in the asset during bullish conditions.
How does the strategy identify market structure? What are the underlying calculations?
The strategy utilizes an efficient logic with for loops to pinpoint the first swing candle featuring a pivot of 2, establishing the point at which the break of structure begins.
What entry criteria are used in this script? What are the underlying calculations?
The script utilizes two entry models: BreakOut and fractal.
Underlying Calculations:
Breakout: The script assigns the most recent swing high to a variable. When the price closes above this level and all other conditions are met, the script executes a breakout entry (conservative approach).
Fractal: The script identifies a swing low with a period of 2. Once this condition is met, the script executes the trade (aggressive approach).
How does the script calculate probabilities? What are the underlying calculations?
The script calculates probabilities by monitoring price interactions with liquidity levels. Here’s how the underlying calculations work:
Tracking Price Hits: The script counts the number of times the price taps into each liquidity side after the EQM level is activated. This data is stored in an array for further analysis.
Sample Size Consideration: The total number of price interactions serves as the sample size for calculating probabilities.
Probability Calculation: For each liquidity side, the script calculates the probability by taking the average of the recorded hits. This allows for a dynamic assessment of the likelihood that a particular side will be hit next, based on historical performance.
Dynamic Adjustment: As new price data comes in, the probabilities are recalculated, providing real-time aduptive insights into market behavior.
Note: The calculations are performed independently for each directional range. A range is considered bearish if the previous breakout was through a sellside liquidity. Conversely, a range is considered bullish if the most recent breakout was through a buyside liquidity.
How does the script calculate expected values? What are the underlying calculations?
The script calculates expected values by leveraging the probabilities of winning and losing trades, along with their respective returns. The process involves the following steps:
This quantitative methodology provides a robust framework for assessing the expected performance of trading strategies based on historical data and backtesting results.
How is the contextual bias calculated? What are the underlying calculations?
The contextual bias in the QuantBuilder script is calculated through a structured approach that assesses market structure based on swing highs and lows. Here’s how it works:
Identification of Swing Points: The script identifies significant swing points using a defined pivot logic, focusing on the first swing high and swing low. This helps establish critical levels for determining market structure.
Break of Structure (BOS) Assessment:
Bullish BOS: The script recognizes a bullish break of structure when a candle closes above the first swing high, followed by at least one swing low.
Bearish BOS: Conversely, a bearish break of structure is identified when a candle closes below the first swing low, followed by at least one swing high.
Bias Assignment: Based on the identified break of structure, the script assigns directional biases:
A bullish bias is assigned if a bullish BOS is confirmed.
A bearish bias is assigned if a bearish BOS is confirmed.
Quantitative Evaluation: Each identified bias is quantitatively evaluated, allowing the script to assign numerical values representing the strength of each bias. This quantification aids in assessing the reliability of market sentiment across multiple timeframes.
What's the purpose of using moving averages in this strategy? What are the underlying calculations?
Using moving averages is a widely-used technique to trade with the trend.
The main purpose of using moving averages in this strategy is to filter out bearish price action and to only take trades when the price is trading ABOVE specified moving averages.
The script uses different types of moving averages with user-adjustable timeframes and periods/lengths, allowing traders to try out different variations to maximize strategy performance and minimize drawdowns.
By applying these calculations, the strategy effectively identifies bullish trends and avoids market conditions that are not conducive to profitable trades.
The MA filter allows traders to choose whether they want a specific moving average above or below another one as their entry condition.
What type of stop-loss identification method are used in this strategy? What are the underlying calculations?
- Initial Stop-loss:
1. ATR Based:
The Average True Range (ATR) is a method used in technical analysis to measure volatility. It is not used to indicate the direction of price but to measure volatility, especially volatility caused by price gaps or limit moves.
Calculation:
- To calculate the ATR, the True Range (TR) first needs to be identified. The TR takes into account the most current period high/low range as well as the previous period close.
The True Range is the largest of the following:
- Current Period High minus Current Period Low
- Absolute Value of Current Period High minus Previous Period Close
- Absolute Value of Current Period Low minus Previous Period Close
- The ATR is then calculated as the moving average of the TR over a specified period. (The default period is 14)
2. ADR Based:
The Average Day Range (ADR) is an indicator that measures the volatility of an asset by showing the average movement of the price between the high and the low over the last several days.
Calculation:
- To calculate the ADR for a particular day:
- Calculate the average of the high prices over a specified number of days.
- Calculate the average of the low prices over the same number of days.
- Find the difference between these average values.
- The default period for calculating the ADR is 14 days. A shorter period may introduce more noise, while a longer period may be slower to react to new market movements.
3. PL Based:
This method places the stop-loss at the low of the previous candle.
If the current entry is based on the hunt entry strategy, the stop-loss will be placed at the low of the candle that wicks through the lower FRMA band.
Example:
If the previous candle's low is 100, then the stop-loss will be set at 100.
This method ensures the stop-loss is placed just below the most recent significant low, providing a logical and immediate level for risk management.
- Trailing Stop-Loss:
One of the key elements of this strategy is its ability to detect structural liquidity and structural invalidation levels across multiple timeframes to trail the stop-loss once the trade is in running profits.
By utilizing this approach, the strategy allows enough room for price to run.
By using these methods, the strategy dynamically adjusts the initial stop-loss based on market volatility, helping to protect against adverse price movements while allowing for enough room for trades to develop.
Each market behaves differently across various timeframes, and it is essential to test different parameters and optimizations to find out which trailing stop-loss method gives you the desired results and performance.
What type of break-even and take profit identification methods are used in this strategy? What are the underlying calculations?
For Break-Even:
Percentage (%) Based:
Moves the initial stop-loss to the entry price when the price reaches a certain percentage above the entry.
Calculation:
Break-even level = Entry Price * (1 + Percentage / 100)
Example:
If the entry price is $100 and the break-even percentage is 5%, the break-even level is $100 * 1.05 = $105.
Risk-to-Reward (RR) Based:
Moves the initial stop-loss to the entry price when the price reaches a certain RR ratio.
Calculation:
Break-even level = Entry Price + (Initial Risk * RR Ratio)
For TP1 (Take Profit 1):
- You can choose to set a take profit level at which your position gets fully closed or 50% if the TP2 boolean is enabled.
- Similar to break-even, you can select either a percentage (%) or risk-to-reward (RR) based take profit level, allowing you to set your TP1 level as a percentage amount above the entry price or based on RR.
For TP2 (Take Profit 2):
- You can choose to set a take profit level at which your position gets fully closed.
- As with break-even and TP1, you can select either a percentage (%) or risk-to-reward (RR) based take profit level, allowing you to set your TP2 level as a percentage amount above the entry price or based on RR.
What's the day filter Filter, what does it do?
The day filter allows users to customize the session time and choose the specific days they want to include in the strategy session. This helps traders tailor their strategies to particular trading sessions or days of the week when they believe the market conditions are more favorable for their trading style.
Customize Session Time:
Users can define the start and end times for the trading session.
This allows the strategy to only consider trades within the specified time window, focusing on periods of higher market activity or preferred trading hours.
Select Days:
Users can select which days of the week to include in the strategy.
This feature is useful for excluding days with historically lower volatility or unfavorable trading conditions (e.g., Mondays or Fridays).
Benefits:
Focus on Optimal Trading Periods:
By customizing session times and days, traders can focus on periods when the market is more likely to present profitable opportunities.
Avoid Unfavorable Conditions:
Excluding specific days or times can help avoid trading during periods of low liquidity or high unpredictability, such as major news events or holidays.
What tables are available in this script?
- Summary: Provides a general overview, displaying key performance parameters such as Net Profit, Profit Factor, Max Drawdown, Average Trade, Closed Trades and more.
Total Commission: Displays the cumulative commissions incurred from all trades executed within the selected backtesting window. This value is derived by summing the commission fees for each trade on your chart.
Average Commission: Represents the average commission per trade, calculated by dividing the Total Commission by the total number of closed trades. This metric is crucial for assessing the impact of trading costs on overall profitability.
Avg Trade: The sum of money gained or lost by the average trade generated by a strategy. Calculated by dividing the Net Profit by the overall number of closed trades. An important value since it must be large enough to cover the commission and slippage costs of trading the strategy and still bring a profit.
MaxDD: Displays the largest drawdown of losses, i.e., the maximum possible loss that the strategy could have incurred among all of the trades it has made. This value is calculated separately for every bar that the strategy spends with an open position.
Profit Factor: The amount of money a trading strategy made for every unit of money it lost (in the selected currency). This value is calculated by dividing gross profits by gross losses.
Avg RR: This is calculated by dividing the average winning trade by the average losing trade. This field is not a very meaningful value by itself because it does not take into account the ratio of the number of winning vs losing trades, and strategies can have different approaches to profitability. A strategy may trade at every possibility in order to capture many small profits, yet have an average losing trade greater than the average winning trade. The higher this value is, the better, but it should be considered together with the percentage of winning trades and the net profit.
Winrate: The percentage of winning trades generated by a strategy. Calculated by dividing the number of winning trades by the total number of closed trades generated by a strategy. Percent profitable is not a very reliable measure by itself. A strategy could have many small winning trades, making the percent profitable high with a small average winning trade, or a few big winning trades accounting for a low percent profitable and a big average winning trade. Most mean-reversion successful strategies have a percent profitability of 40-80% but are profitable due to risk management control.
BE Trades: Number of break-even trades, excluding commission/slippage.
Losing Trades: The total number of losing trades generated by the strategy.
Winning Trades: The total number of winning trades generated by the strategy.
Total Trades: Total number of taken traders visible your charts.
Net Profit: The overall profit or loss (in the selected currency) achieved by the trading strategy in the test period. The value is the sum of all values from the Profit column (on the List of Trades tab), taking into account the sign.
- Monthly: Displays performance data on a month-by-month basis, allowing users to analyze performance trends over each month and year.
- Weekly: Displays performance data on a week-by-week basis, helping users to understand weekly performance variations.
- UI Table: A user-friendly table that allows users to view and save the selected strategy parameters from user inputs. This table enables easy access to key settings and configurations, providing a straightforward solution for saving strategy parameters by simply taking a screenshot with Alt + S or ⌥ + S.
User-input styles and customizations:
To facilitate studying historical data, all conditions and filters can be applied to your charts. By plotting background colors on your charts, you'll be able to identify what worked and what didn't in certain market conditions.
Please note that all background colors in the style are disabled by default to enhance visualization.
How to Use This Quantitive Strategy Builder to Create a Profitable Edge and System?
Choose Your Strategy mode:
- Decide whether you are creating an investing strategy or a trading strategy.
Select a Market:
- Choose a one-sided market such as stocks, indices, or cryptocurrencies.
Historical Data:
- Ensure the historical data covers at least 10 years of price action for robust backtesting.
Timeframe Selection:
- Choose the timeframe you are comfortable trading with. It is strongly recommended to use a timeframe above 15 minutes to minimize the impact of commissions/slippage on your profits.
Set Commission and Slippage:
- Properly set the commission and slippage in the strategy properties according to your broker/prop firm specifications.
Parameter Optimization:
- Use trial and error to test different parameters until you find the performance results you are looking for in the summary table or, preferably, through deep backtesting using the strategy tester.
Trade Count:
- Ensure the number of trades is 200 or more; the higher, the better for statistical significance.
Positive Average Trade:
- Make sure the average trade is above zero.
(An important value since it must be large enough to cover the commission and slippage costs of trading the strategy and still bring a profit.)
Performance Metrics:
- Look for a high profit factor, and net profit with minimum drawdown.
- Ideally, aim for a drawdown under 20-30%, depending on your risk tolerance.
Refinement and Optimization:
- Try out different markets and timeframes.
- Continue working on refining your edge using the available filters and components to further optimize your strategy.
What makes this strategy original?
QuantBuilder stands out due to its unique combination of quantitative techniques and innovative algorithms that leverage historical data for real-time trading decisions. Unlike most algorithmic strategies that work based on predefined rules, this strategy adapts to real-time market probabilities and expected values, enhancing its reliability. Key features include:
Mathematical Framework: The strategy integrates advanced mathematical concepts, such as probabilities and expected values, to assess trade viability and optimize decision-making.
Multi-Timeframe Analysis: By utilizing multi-timeframe probabilities, QuantBuilder provides a comprehensive view of market conditions, enhancing the accuracy of entry and exit points.
Dynamic Market Structure Identification: The script employs a systematic approach to identify market structure changes, utilizing a blend of swing highs and lows to detect contextual/direction bias of the market.
Built-in Trailing Stop Loss: The strategy features a dynamic trailing stop loss based on multi-timeframe analysis of market structure. This allows traders to lock in profits while adapting to changing market conditions, ensuring that exits are executed at optimal levels without prematurely closing positions.
Robust Performance Metrics: With detailed performance tables and visualizations, users can easily evaluate strategy effectiveness and adjust parameters based on historical performance.
Adaptability: The strategy is designed to work across various markets and timeframes, making it versatile for different trading styles and objectives.
Suitability for Investors and Traders: QuantBuilder is ideal for both investors and traders looking to rely on mathematically proven data to create profitable strategies, ensuring that decisions are grounded in quantitative analysis.
These original elements combine to create a powerful tool that can help both traders and investors to build and refine profitable strategies based on algorithmic quantitative analysis.
Terms and Conditions | Disclaimer
Our charting tools are provided for informational and educational purposes only and should not be construed as financial, investment, or trading advice. They are not intended to forecast market movements or offer specific recommendations. Users should understand that past performance does not guarantee future results and should not base financial decisions solely on historical data.
Built-in components, features, and functionalities of our charting tools are the intellectual property of @Fractalyst Unauthorized use, reproduction, or distribution of these proprietary elements is prohibited.
By continuing to use our charting tools, the user acknowledges and accepts the Terms and Conditions outlined in this legal disclaimer and agrees to respect our intellectual property rights and comply with all applicable laws and regulations.
Fibonacci-Only StrategyFibonacci-Only Strategy
This script is a custom trading strategy designed for traders who leverage Fibonacci retracement levels to identify potential trade entries and exits. The strategy is versatile, allowing users to trade across multiple timeframes, with built-in options for dynamic stop loss, trailing stops, and take profit levels.
Key Features:
Custom Fibonacci Levels:
This strategy calculates three specific Fibonacci retracement levels: 19%, 82.56%, and the reverse 19% level. These levels are used to identify potential areas of support and resistance where price reversals or breaks might occur.
The Fibonacci levels are calculated based on the highest and lowest prices within a 100-bar period, making them dynamic and responsive to recent market conditions.
Dynamic Entry Conditions:
Touch Entry: The script enters long or short positions when the price touches specific Fibonacci levels and confirms the move with a bullish (for long) or bearish (for short) candle.
Break Entry (Optional): If the "Use Break Strategy" option is enabled, the script can also enter positions when the price breaks through Fibonacci levels, providing more aggressive entry opportunities.
Stop Loss Management:
The script offers flexible stop loss settings. Users can choose between a fixed percentage stop loss or an ATR-based stop loss, which adjusts based on market volatility.
The ATR (Average True Range) stop loss is multiplied by a user-defined factor, allowing for tailored risk management based on market conditions.
Trailing Stop Mechanism:
The script includes an optional trailing stop feature, which adjusts the stop loss level as the market moves in favor of the trade. This helps lock in profits while allowing the trade to run if the trend continues.
The trailing stop is calculated as a percentage of the difference between the entry price and the current market price.
Multiple Take Profit Levels:
The strategy calculates seven take profit levels, each at incremental percentages above (for long trades) or below (for short trades) the entry price. This allows for gradual profit-taking as the market moves in the trade's favor.
Each take profit level can be customized in terms of the percentage of the position to be closed, providing precise control over exit strategies.
Strategy Backtesting and Results:
Realistic Backtesting:
The script has been backtested with realistic account sizes, commission rates, and slippage settings to ensure that the results are applicable to actual trading scenarios.
The backtesting covers various timeframes and markets to ensure the strategy's robustness across different trading environments.
Default Settings:
The script is published with default settings that have been optimized for general use. These settings include a 15-minute timeframe, a 1.0% stop loss, a 2.0 ATR multiplier for stop loss, and a 1.5% trailing stop.
Users can adjust these settings to better fit their specific trading style or the market they are trading.
How It Works:
Long Entry Conditions:
The strategy enters a long position when the price touches the 19% Fibonacci level (from high to low) or the reverse 19% level (from low to high) and confirms the move with a bullish candle.
If the "Use Break Strategy" option is enabled, the script will also enter a long position when the price breaks below the 19% Fibonacci level and then moves back up, confirming the break with a bullish candle.
Short Entry Conditions:
The strategy enters a short position when the price touches the 82.56% Fibonacci level and confirms the move with a bearish candle.
If the "Use Break Strategy" option is enabled, the script will also enter a short position when the price breaks above the 82.56% Fibonacci level and then moves back down, confirming the break with a bearish candle.
Stop Loss and Take Profit Logic:
The stop loss for each trade is calculated based on the selected method (fixed percentage or ATR-based). The strategy then manages the trade by either trailing the stop or taking profit at predefined levels.
The take profit levels are set at increments of 0.5% above or below the entry price, depending on whether the position is long or short. The script gradually exits the trade as these levels are hit, securing profits while minimizing risk.
Usage:
For Fibonacci Traders:
This script is ideal for traders who rely on Fibonacci retracement levels to find potential trade entries and exits. The script automates the process, allowing traders to focus on market analysis and decision-making.
For Trend and Swing Traders:
The strategy's flexibility in handling both touch and break entries makes it suitable for trend-following and swing trading strategies. The multiple take profit levels allow traders to capture profits in trending markets while managing risk.
Important Notes:
Originality: This script uniquely combines Fibonacci retracement levels with dynamic stop loss management and multiple take profit levels. It is not just a combination of existing indicators but a thoughtful integration designed to enhance trading performance.
Disclaimer: Trading involves risk, and it is crucial to test this script in a demo account or through backtesting before applying it to live trading. Users should ensure that the settings align with their individual risk tolerance and trading strategy.
TENKAN SCALPER STRATEGYTENKAN SCALP is a fully automatic trading system.
It is a continuation of our previous ichimoku release. This time however we throw out the rule book and use ICHIMOKU in a very different way.
It applies non traditional money management tactics.
While most trading strategies rely on a stop loss and a take profit target to manage risk. This strategy uses either no stop loss at all or a time based stop loss.
You might ask yourself the question why would you keep a trade open if it goes against you? Here are a phew reasons why the script does what it does.
Forex Markets consolidate most of the time. If you wait long enough your Take Profit will get hit anyways most of the time
You don't have to risk everything per trade. I keep my orders small so to keep some powder to get into some more trades
All the extra trades you take while one trade is in drawdown limit the drawdown as they provide cashflow
On lower timeframes the markets are so chaotic that a stop loss is very likely to get hit by a wick
About backtest below
This backtest uses a spread of 2 pips for entries and a default position size of 100% of equity. This is only possible on exchanges where spread is low and you have 10:1 leverage or more. It does not represent results obtainable without leverage. Do take into account that there are a lot of forex exchanges that provide this leverage, however a 2 pip spread is not always guaranteed and only applies to major pairs.
This backtest does not use the TIME BASED STOPS functionality.
Always start with small position sizing and see how the strategy performs before adding risk.
Explanation of variables:
Chikou(lagging span): pink line, this is price plotted 26 bars ago. People ignore the power of this it is crucial to see how chikou behaves towards past price action as seen in the chart below where we got an entry at red arrow because chikou bounced from past fractal bottom.
Kijun-Sen(base line): Black line or color coded line. This is the equilibrium of last 26 candles. To me this is the most important line in the system as it attracts price.
Kijun = (Highest high of 26 periods + Lowest low of 26 periods) ÷ 2
Tenkan-Sen(conversion line): Blue line. This is the equilibrium of last 9 candles. In a strong uptrend price stays above this line.
Tenkan = (Highest high of 9 periods + Lowest low of 9 periods) ÷ 2
Senkou A (Leading span A)= Pink cloud line, this is the average of the 2 components projected 26 bars in the future.
Senkou A = (Tenkan + Kijun) ÷ 2
Senkou B (Leading span B) = Green cloud line, this is the 52 day equilibrium projected 26 bars in the future.
Senkou B = (Highest high of prior 52 periods + Lowest low of prior 52 periods) ÷ 2
projection: Script uses same function for variable calculation and substracts a number on each next bar as to make a projection of where the variable will be in future bars if price stayed the same. This works as ICHIMOKU calculations use the middle point of a past set of data. The shorter that amount of bars will be in line with the data that it will be restricted to in future if price stayed the same.
Detection of Market Environment
To enter trades the script uses a lot of ICHIMOKU concepts. Contrary to how most people trade ICHIMOKU this script takes an environment that ICHIMOKU identifies as trending upwards and shorts in that environment. The same will be applied to a downtrend where it will open LONGS.
List of CRITERIA for a trend:
Grapling Hook: this is a component based on the chikou span (closing price displaced 26 bars into the past). The script will use an ATR based range to define a possible future projection to the CHIKOU line. For a market to be bullish there should be no price action happening within this area. Market is free to move upwards. Vice versa for bearish .
Kumo Cloud: script will check if price is above the cloud for bullish trend and below cloud for bearish trend .
Chikou above Kijun: script will check if the chikou line is above the KIJUN line of 26 bars ago. This is further confirmation that price is trending high enough compared to it's past data. Vice versa for downtrend.
Kijun projection: script will check if past Kijun is lower than future projected Kijun. This to ensure we get an equilibrium in our favour in the future. Vice versa for downtrend
Tenkan projection: script will check if future Tenkan-sen will be higher than Kijun-sen for an uptrend. Vice versa for downtrend.
Cloud projection: script will check if in 9 bars the Senkou Span A will be higher than Senkou Span B for an uptrend. Vice versa for downtrend.
Example:
This script does not visualise the prediction lines like I show in the example. I show them here to clarify how the script works.
Usage
Backtests are not indicative of future results, although a trader may want to use a strategy script to have a deeper understanding of how their strategy responds to varying market conditions, or as a tool for identifying possible flaws for a strategy that may be indicative of good or bad performance in the future.
Strategy Settings:
Minimum Body Size (atr): this is the minimum ATR a signal bar needs to be for entry. This is useful because our TP is based on previous bar.
Lot size per trade: this setting does not impact backtest. It is used to for the signals to let tradingconnect.com know your position size.
Direction: do you want to trade longs or shorts. I personally use both a long bot and a short bot at the same time.
Positions Allowed: the amount of positions the script will keep open as a maximum. You do not want to open too many positions, this is for risk management.
Close all positions at drawdown: if total open positions loss gets to this % target it will close all positions.
MetaTrader Prefix: when the script sends a signal it will put this text right before the symbol name from syminfo.ticker
MetaTrader Suffix: when the script sends a signal it will put this text right after the symbol name from syminfo.ticker
Charts below are some examples on how the script handles orders on default settings:
without time based SL
with time based SL
how it handles pyramiding
www.tradingview.com
Tradingconnector.com:
For full automation of the forex market the script uses this connector to execute trade on MT4. The alerts the script sends using the alerts() function call are structured in a way tradingconnector will recognise and send directly to MT4. You can find documentation about this tool on their own website.
Personal recommendation is to start with a minimum lot size and track performance, if you are comfortable scale the size up. You can do that by increasing the lot size setting in the script and making a new alert. Make sure to delete the old one.
How to access
You can see the Author's Instructions below to visit our telegram to get more information on how to get access.
Alex trading stragedyOverview
This script, named "ALEX TRADING STRATEGY", is a technical trading strategy designed for new investing groups. It uses a combination of various technical indicators to identify potential buying and selling opportunities in the market. The script includes the Relative Strength Index (RSI), Simple Moving Averages (SMA), Exponential Moving Averages (EMA), and Higher High Lower Low (HHLL) strategies to create a complete trading solution.
The user can change the position from long to short in the Input Settings. The script uses bar colors to indicate the current trading position. The script also has exit strategies to help manage the open trades. The user can also set the period for the various indicators used in the strategy.
The script provides various technical indicators and entry/exit signals to make the trading decision easier for the user. It also includes pivot lines, resistance and support levels to help the user make a more informed decision.
This Pine script implements a multi-indicator trading strategy that combines several technical analysis techniques for making trading decisions. The script uses the Relative Strength Index (RSI) to determine overbought and oversold conditions in the market and plots the RSI values on the chart. The RSI values above 70 are considered overbought and plotted as red upward triangles, while the RSI values below 30 are considered oversold and plotted as green downward triangles.
The script also calculates Simple Moving Averages (SMAs) with the user-defined period and plots them along with the Exponential Moving Averages (EMAs) of 20, 50, and 100 periods. Based on the crossover of the close price and the moving averages, the script enters long or short trades. The script sets the trade exit conditions as the low or high crossing the lower or upper band, respectively.
In addition to the moving average crossover, the script uses the highest high and lowest low over a user-defined period to determine long and short entries. The script plots the long and short conditions on the chart as green upward and red downward triangles, respectively. The script allows the user to switch between long and short trades by changing the input settings.
Finally, the script changes the bar colors based on the trade direction, with green bars indicating a long trade, red bars indicating a short trade, and blue bars indicating no trade. Overall, this Pine script provides a comprehensive trading strategy that combines several technical analysis techniques to make informed trading decisions.
HOW TO USE
Input Settings: In the Input Settings section, you can change the long to short position. You can also change the period value (default is 10) used to calculate the Simple Moving Average (SMA) for the Keltner channel.
Indicators: The script uses RSI (Relative Strength Index) with 14 periods as well as multiple EMAs (Exponential Moving Averages) with periods 20, 50, and 100 to help in making trading decisions.
Entry Signals: The script uses two main entry signals: (1) Keltner Channel and (2) HHLL (High-Low). When the closing price crosses above the upper band of the Keltner channel, the script generates a long signal, and when the closing price crosses below the lower band of the Keltner channel, the script generates a short signal. The HHLL strategy generates a long signal when the current high crosses above the highest high of the last "nPeriod" bars, and generates a short signal when the current low crosses below the lowest low of the last "nPeriod" bars.
Exit Signals: The script uses two exit signals: (1) Stop Loss based on Keltner channel and (2) Profit Target based on Keltner channel. The script exits the long position when the closing price crosses below the lower band of the Keltner channel, and the script exits the short position when the closing price crosses above the upper band of the Keltner channel.
To use this script, you will need to have access to a trading platform that supports PineScript, such as TradingView, and attach the script to a chart. The script will then automatically generate entry and exit signals based on the rules described above. It's important to note that this script is just a tool and not a guarantee of profit. As with any trading strategy, it's important to thoroughly test and understand the script before using it for live trading.
BitcoinNinjas Ninja Signals Buy Sell Alert Trading Strategy v2.0Bitcoin Ninjas 'Ninja Signals' Buy/Sell Alerts & Backtesting TradingView Script v2.0
(for Cryptocurrencies, Forex, GunBot, ProfitTrailer, automatic trading software, and more)
'Ninja Signals' v2.0 (SCRIPT)
'Ninja Signals' v2.0 (STRATEGY)
'Ninja Signals' v1.0 (SCRIPT)
'Ninja Signals' v1.0 (STRATEGY)
-Allows users to easily set automated buy and sell alerts on TradingView for use with automatic and manual trading of cryptocurrencies, Forex securities, and more (alerts are compatible with automatic trading software such as GunBot, ProfitTrailer, and more).
-Synthesizes many powerful indicators [e.g. Relative Strength Index (RSI), stochastic RSI, Money Flow Index (MFI), Moving Average Convergence Divergence (MACD), etc.) into one super script to generate very precise buy and sell signals in almost any market condition.
-Buy arrows (blue) and sell arrows (red) can be changed or hidden for ease of viewing.
-No lag EMA trendline featuring trend-reversal color-coding (white uptrend, black downtrend).
-Adjustable ‘calibration’ setting allows users to customize the script to work for any currency or security available through TradingView, on any exchange, simply by adjusting a number.
-Complete with backtesting strategy version of script which allows users to test various buy and sell strategies based on the alerts the script generates (see info and screenshots below).
-Backtesting strategy incorporates a user-defined adjustable date range, so users can estimate the script’s performance over specific periods of time, such as the last day, week, or month.
-Backtesting strategy utilizes a minimum protective gain setting to help you never sell for a loss. Simply adjust your minimum profit (%) per trade, and the test results will update.
-Backtesting strategy allows for pyramid buying to test various average down / double up buying strategies. Simply adjust the number of pyramid buys and the quantity of each buy.
- Free 7-day trial available for TradingView users who join our free BitcoinNinjas community.
-Free 24/7 support via BitcoinNinjas Telegram GunBot support group with script purchase.
-Fully compatible with GunBot automatic trading software (TradingView plugin is required).
-Special discount available for traders who purchase GunBot automatic trading software and the GunBot TradingView plugin from BitcoinNinjas, allowing for fully automatic trading.
-Contact us via Email or Telegram for more information, to request additional / custom screenshots, or to start your free trial.
DISCLAIMER: By using this BitcoinNinjas document or ‘Ninja Signals’ planning script, you agree to the BitcoinNinjas 'Terms of Use', as presented on our website (www.BitcoinNinjas.org) and as stated here. No sharing, copying, reselling, modifying, or any other forms of use are authorized for our documents, script / strategy, and the information published with them. This informational document and planning script / strategy is strictly for individual use and educational purposes only. This is not financial or investment advice. Investments are always made at your own risk and are based on your personal judgement. BitcoinNinjas is not responsible for any losses you may incur. Please invest wisely.
Candle Breakout StrategyShort description (one-liner)
Candle Breakout Strategy — identifies a user-specified candle (UTC time), draws its high/low range, then enters on breakouts with configurable stop-loss, take-profit (via Risk:Reward) and optional alerts.
Full description (ready-to-paste)
Candle Breakout Strategy
Version 1.0 — Strategy script (Pine v5)
Overview
The Candle Breakout Strategy automatically captures a single "range candle" at a user-specified UTC time, draws its high/low as a visible box and dashed level lines, and waits for a breakout. When price closes above the range high it enters a Long; when price closes below the range low it enters a Short. Stop-loss is placed at the opposite range boundary and take-profit is calculated with a user-configurable Risk:Reward multiplier. Alerts for entries can be enabled.
This strategy is intended for breakout style trading where a clearly defined intraday range is established at a fixed time. It is simple, transparent and easy to adapt to multiple symbols and timeframes.
How it works (step-by-step)
On every bar the script checks the current UTC time.
When the first bar that matches the configured Target Hour:Target Minute (UTC) appears, the script records that candle’s high and low. This defines the breakout range.
A box and dashed lines are drawn on the chart to display the range and extended to the right while the range is active.
The script then waits for price to close outside the box:
Close > Range High → Long entry
Close < Range Low → Short entry
When an entry triggers:
Stop-loss = opposite range boundary (range low for longs, range high for shorts).
Take-profit = entry ± (risk × Risk:Reward). Risk is computed as the distance between entry price and stop-loss.
After entry the range becomes inactive (waitingForBreakout = false) until the next configured target time.
Inputs / Parameters
Target Hour (UTC) — the hour (0–23) in UTC when the range candle is detected.
Target Minute — minute (0–59) of the target candle.
Risk:Reward Ratio — multiplier for computing take profit from risk (0.5–10). Example: 2 means TP = entry + 2×risk.
Enable Alerts — turn on/off entry alerts (string message sent once per bar when an entry occurs).
Show Last Box Only (internal behavior) — when enabled the previous box is deleted at the next range creation so only the most recent range is visible (default behavior in the script).
Visuals & On-chart Info
A semi-transparent blue box shows the recorded range and extends to the right while active.
Dashed horizontal lines mark the range high and low.
On-chart shapes: green triangle below bar for Long signals, red triangle above bar for Short signals.
An information table (top-right) displays:
Target Time (UTC)
Active Range (Yes / No)
Range High
Range Low
Risk:Reward
Alerts
If Enable Alerts is on, the script sends an alert with the following formats when an entry occurs:
Long alert:
🟢 LONG SIGNAL
Entry Price:
Stop Loss:
Take Profit:
Short alert:
🔴 SHORT SIGNAL
Entry Price:
Stop Loss:
Take Profit:
Use TradingView's alert dialog to create alerts based on the script — select the script’s alert condition or use the alert() messages.
Recommended usage & tips
Timeframe: This strategy works on any timeframe but the definition of "candle at target time" depends on the chart timeframe. For intraday breakout styles, use 1m — 60m charts depending on the session you want to capture.
Target Time: Choose a time that is meaningful for the instrument (e.g., market open, economic release, session overlap). All times are handled in UTC.
Position Sizing: The script’s example uses strategy.percent_of_equity with 100% default — change default_qty_value or strategy settings to suit your risk management.
Filtering: Consider combining this breakout with trend filters (EMA, ADX, etc.) to reduce false breakouts.
Backtesting: Always backtest over a sufficiently large and recent sample. Pay attention to slippage and commission settings in TradingView’s strategy tester.
Known behavior & limitations
The script registers the breakout on close outside the recorded range. If you prefer intrabar breakout rules (e.g., high/low breach without close), you must adjust the condition accordingly.
The recorded range is taken from a single candle at the exact configured UTC time. If there are missing bars or the chart timeframe doesn't align, the intended candle may differ — choose the target time and chart timeframe consistently.
Only a single active position is allowed at a time (the script checks strategy.position_size == 0 before entries).
Example setups
EURUSD (Forex): Target Time 07:00 UTC — captures London open range.
Nifty / Index: Target Time 09:15 UTC — captures local session open range.
Crypto: Target Time 00:00 UTC — captures daily reset candle for breakout.
Risk disclaimer
This script is educational and provided as-is. Past performance is not indicative of future results. Use proper risk management, test on historical data, and consider slippage and commissions. Do not trade real capital without sufficient testing.
Change log
v1.0 — Initial release: range capture, box and level drawing, long/short entry by close breakout, SL at opposite boundary, TP via Risk:Reward, alerts, info table.
If you want, I can also:
Provide a short README version (2–3 lines) for the TradingView “Short description” field.
Add a couple of suggested alert templates for the TradingView alert dialog (if you want alerts that include variable placeholders).
Convert the disclaimer into multiple language versions.
OneHolo-TGAPSNRTGAPSNR: Multi time frame - Trend Gap Stop And Reverse strategy/Study PnL. This script outlines a systematic approach to generating buy and sell signals by combining Fair Value Gaps (FVGs), specific market structures, and three different trend direction methods (Swing, Gravity, and FVG Inverse direction). The strategy incorporates multiple entry modes, such as Hyper Mode, Swiper Mode, and a Custom mode, allowing users to tailor signal conditions, alongside extensive logic for trade management, higher time frame analysis, and various visual indicators for plotting trend, pivots, and profit and loss information.
I. Core Trend Direction Consensus (The Three-Pillar System)
The primary method for determining market bias is a three-pillar consensus model, requiring all directional methods to align before the overall Trend Direction is established (up or down). This ensures high conviction for trend signals.
• Pillar 1: Swing Direction: Determines market direction based on classic price action, specifically checking for continuous higher highs and higher lows for an upward bias, or lower lows and lower highs for a downward bias.
• Pillar 2: Gravity Direction (Peak and Valley): This uses specific market structure pivots. Direction is set based on whether the close price successfully crosses the established recent Peak High (indicating upward momentum) or crosses under the recent Valley Low (indicating downward pressure).
• Pillar 3: FVG Inverse Direction: This relies on Fair Value Gaps (FVGs), defined as a gap between the current bar's price and the price two bars prior. Direction shifts occur when the Close price crosses the midpoint of the last relevant FVG. For instance, crossing above the midpoint of the last FVG Down signals a potential inverse long trade.
II. Flexible Signal Generation Modes
The strategy offers several pre-configured and highly detailed entry modes, plus a powerful Custom Mode:
• Session Open Range Break (ORB) Mode: Uses the high/low of the session's first bar to generate initial signals, then defaults to the Three-Pillar Trend Direction after the ORB session concludes.
• Swiper Mode: Designed to identify continuations, combining a confirmed Trend Direction with a Stop and Reverse signal (SnR) while actively avoiding confirmed pivot breaks.
• Hyper/Aggressive Modes: These modes use broad combinations of signals, allowing for earlier entry based on momentum and structural breaks (like PeakCrossLong, SnRtrapLong, or FVG signals).
• Custom Query Mode (The Seven-Slot Logic): This non-redundant system allows the user to define complex, tailored entry conditions by selecting any combination of 14 core patterns across seven distinct slots.
◦ AND/OR Combination: For each of the seven slots, the user determines if the chosen pattern must be met (AND component) or if it can serve as an alternative trigger (OR component).
◦ The final signal requires that all configured AND conditions are true and then integrates the result of the OR conditions, allowing for highly specific "hook queries" (e.g., "Condition A AND Condition B, OR Condition C").
III. Advanced PnL and Mobile App Diagnostics
A key proprietary element is the implementation of a dual PnL system and customized visualization features:
• Dual PnL Display (Strategy PnL vs. Study PnL): Users can choose to view either the native platform's strategy performance data or the script's internal, proprietary Study PnL. The Study PnL calculates profits/losses based strictly on the close price and tracks performance using Pine Script® arrays, providing a transparent, diagnostic view of performance independent of broker/platform simulation biases.
• Lower Panel Visualization: Both PnL types are displayed on the lower panel using detailed bar plots (style=plot.style_columns), which color according to profitability, and include labels that show current open profit and total net profit.
• Detailed Trade Labels: The script generates detailed, customizable labels on both the chart (above/below bars) and the lower PnL panel, providing historical PnL, number of trades, and real-time profit information for each entry or exit.
IV. Higher Time Frame (HTF) Context and Lookahead Prevention
The strategy integrates multi-time frame analysis using strict methodology to prevent lookahead bias:
• HTF Bias Filtering: When enabled, the strategy uses the position calculated on a user-defined higher time frame (HTF) as a mandatory filter. A long signal on the current chart is only executed if the HTF is also in a long position, and vice-versa.
• Lookahead Prevention: To maintain integrity, all HTF data requests use a mandatory lookback index (often ) to ensure the script only accesses confirmed data from the prior completed bar on the higher timeframe.
• HTF Visual Mode: The user can opt to display key structural elements—such as the Gravity Pivots and the Trend Direction blocks—as calculated on the HTF, overlaying this higher-level context onto the current chart for visual analysis.
The TGAPSNR: Multi time frame - Trend Gap Stop And Reverse strategy/Study PnL script, despite its complexity, intentionally excludes realistic considerations such as fees, slippage, and explicit risk management settings (like fixed stop-loss or take-profit rules) from its primary logic.
Here is an explanation of why these elements are omitted in the strategy's current implementation and why they must be applied by the user for real-world application, drawing on the context of the sources:
1. Absence of Realistic Fees, Commissions, and Slippage
The primary function of the TGAPSNR script is to execute intricate signal generation and diagnostic PnL calculation based on its three-pillar trend system and Custom Mode logic.
However, the strategy's backtesting results, particularly those displayed by the internal Study PnL feature, are based purely on price difference (e.g., (close - lse) * syminfo.pointvalue * IUnits).
• Strategy Result Requirements: TradingView explicitly states that strategies published publicly should strive to use realistic commission AND slippage when calculating backtesting results to avoid misleading traders.
• User Responsibility: Since the script currently focuses on signal integrity and uses a fixed contract size (IUnits = 1) without configurable commission/slippage inputs shown in the source, the user must manually configure these fees within the Pine Script® Strategy Tester settings (Properties tab) to ensure the strategy results are reflective of actual trading costs.
2. Omission of Built-in Risk Management (Stop-Loss and Take-Profit)
The TGAPSNR strategy's core focuses on entry signals and trend confirmation. Exits are primarily governed by:
• Reversal signals (BuyStop or SellStop).
• End-of-Day (EOD) session closures (EODStop).
• HTF bias opposition.
What is Missing: The script does not include explicit, hard-coded risk management parameters for traditional stop-loss (SL) or take-profit (TP) levels (e.g., risk percentage or ATR-based exits).
• Viable Risk: TradingView guidelines stipulate that strategies should generally risk sustainable amounts of equity, usually not exceeding 5-10% on a single trade, and trade size must be appropriate.
• User Application: To ensure the strategy operates within realistic risk boundaries, users must apply their own risk management rules. This includes:
◦ Implementing realistic stops and profit targets, which can be added via Pine Script® code or manually managed during live trading.
◦ Sizing trades to only risk sustainable amounts of equity. The current default unit size (IUnits = 1) is unrealistic for risk assessment unless the symbol is micro-sized.
3. Execution Quality (Fills)
The strategy is set to fill_orders_on_standard_ohlc = true and operates on confirmed bar closes (barstate.isconfirmed).
• Fill Assumption: This suggests the strategy primarily uses close price or the HTF close price (EntryPrice = HTFClose) for execution.
• Real-World Limitation: In volatile markets, obtaining a fill price equal to the close of the bar is rare. The user must be aware that the simulated fill price shown in backtesting may differ significantly from actual execution prices due to market action and chosen order type, reinforcing the importance of applying slippage settings.
In summary, while the script provides highly detailed and unique signal generation and internal PnL diagnostics, users must exercise caution and apply their own realistic parameters for fees, slippage, and explicit risk controls to prevent misleading performance results and ensure viable trading
TASC 2025.05 Trading The Channel█ OVERVIEW
This script implements channel-based trading strategies based on the concepts explained by Perry J. Kaufman in the article "A Test Of Three Approaches: Trading The Channel" from the May 2025 edition of TASC's Traders' Tips . The script explores three distinct trading methods for equities and futures using information from a linear regression channel. Each rule set corresponds to different market behaviors, offering flexibility for trend-following, breakout, and mean-reversion trading styles.
█ CONCEPTS
Linear regression
Linear regression is a model that estimates the relationship between a dependent variable and one or more independent variables by fitting a straight line to the observed data. In the context of financial time series, traders often use linear regression to estimate trends in price movements over time.
The slope of the linear regression line indicates the strength and direction of the price trend. For example, a larger positive slope indicates a stronger upward trend, and a larger negative slope indicates the opposite. Traders can look for shifts in the direction of a linear regression slope to identify potential trend trading signals, and they can analyze the magnitude of the slope to support trading decisions.
One caveat to linear regression is that most financial time series data does not follow a straight line, meaning a regression line cannot perfectly describe the relationships between values. Prices typically fluctuate around a regression line to some degree. As such, analysts often project ranges above and below regression lines, creating channels to model the expected extent of the data's variability. This strategy constructs a channel based on the method used in Kaufman's article. It measures the maximum distances from points on the linear regression line to historical price values, then adds those distances and the current slope to the regression points.
Depending on the trading style, traders might look for prices to move outside an established channel for breakout signals, or they might look for price action to reach extremes within the channel for potential mean reversion opportunities.
█ STRATEGY CALCULATIONS
Primary trade rules
This strategy implements three distinct sets of rules for trend, breakout, and mean-reversion trades based on the methods Kaufman describes in his article:
Trade the trend (Rule 1) : Open new positions when the sign of the slope changes, indicating a potential trend reversal. Close short trades and enter a long trade when the slope changes from negative to positive, and do the opposite when the slope changes from positive to negative.
Trade channel breakouts (Rule 2) : Open new positions when prices cross outside the linear regression channel for the current sample. Close short trades and enter a long trade when the price moves above the channel, and do the opposite when the price moves below the channel.
Trade within the channel (Rule 3) : Open new positions based on price values within the channel's range. Close short trades and enter a long trade when the price is near the channel's low, within a specified percentage of the channel's range, and do the opposite when the price is near the channel's high. With this rule, users can also filter the trades based on the channel's slope. When the filter is active, long positions are allowed only when the slope is positive, and short positions are allowed only when it is negative.
Position sizing
Kaufman's strategy uses specific trade sizes for equities and futures markets:
For an equities symbol, the number of shares traded is $10,000 divided by the current price.
For a futures symbol, the number of contracts traded is based on a volatility-adjusted formula that divides $25,000 by the product of the 20-bar average true range and the instrument's point value.
By default, this script automatically uses these sizes for its trade simulation on equities and futures symbols and does not simulate trading on other symbols. However, users can control position sizes from the "Settings/Properties" tab and enable trade simulation on other symbol types by selecting the "Manual" option in the script's "Position sizing" input.
Stop-loss
This strategy includes the option to place an accompanying stop-loss order for each trade, which users can enable from the "SL %" input in the "Settings/Inputs" tab. When enabled, the strategy places a stop-loss order at a specified percentage distance from the closing price where the entry order occurs, allowing users to compare how the strategy performs with added loss protection.
█ USAGE
This strategy adapts its display logic for the three trading approaches based on the rule selected in the "Trade rule" input:
For all rules, the script plots the linear regression slope in a separate pane. The plot is color-coded to indicate whether the current slope is positive or negative.
When the selected rule is "Trade the trend", the script plots triangles in the separate pane to indicate when the slope's direction changes from positive to negative or vice versa. Additionally, it plots a color-coded SMA on the main chart pane, allowing visual comparison of the slope to directional changes in a moving average.
When the rule is "Trade channel breakouts" or "Trade within the channel", the script draws the current period's linear regression channel on the main chart pane, and it plots bands representing the history of the channel values from the specified start time onward.
When the rule is "Trade within the channel", the script plots overbought and oversold zones between the bands based on a user-specified percentage of the channel range to indicate the value ranges where new trades are allowed.
Users can customize the strategy's calculations with the following additional inputs in the "Settings/Inputs" tab:
Start date : Sets the date and time when the strategy begins simulating trades. The script marks the specified point on the chart with a gray vertical line. The plots for rules 2 and 3 display the bands and trading zones from this point onward.
Period : Specifies the number of bars in the linear regression channel calculation. The default is 40.
Linreg source : Specifies the source series from which to calculate the linear regression values. The default is "close".
Range source : Specifies whether the script uses the distances from the linear regression line to closing prices or high and low prices to determine the channel's upper and lower ranges for rules 2 and 3. The default is "close".
Zone % : The percentage of the channel's overall range to use for trading zones with rule 3. The default is 20, meaning the width of the upper and lower zones is 20% of the range.
SL% : If the checkbox is selected, the strategy adds a stop-loss to each trade at the specified percentage distance away from the closing price where the entry order occurs. The checkbox is deselected by default, and the default percentage value is 5.
Position sizing : Determines whether the strategy uses Kaufman's predefined trade sizes ("Auto") or allows user-defined sizes from the "Settings/Properties" tab ("Manual"). The default is "Auto".
Long trades only : If selected, the strategy does not allow short positions. It is deselected by default.
Trend filter : If selected, the strategy filters positions for rule 3 based on the linear regression slope, allowing long positions only when the slope is positive and short positions only when the slope is negative. It is deselected by default.
NOTE: Because of this strategy's trading rules, the simulated results for a specific symbol or channel configuration might have significantly fewer than 100 trades. For meaningful results, we recommend adjusting the start date and other parameters to achieve a reasonable number of closed trades for analysis.
Additionally, this strategy does not specify commission and slippage amounts by default, because these values can vary across market types. Therefore, we recommend setting realistic values for these properties in the "Cost simulation" section of the "Settings/Properties" tab.
Qullamaggie [Modified] | FractalystWhat's the purpose of this strategy?
The strategy aims to identify high-probability breakout setups in trending markets, inspired by Kristjan "Qullamaggie" Kullamägi’s approach.
It focuses on capturing explosive price moves after periods of consolidation, using technical criteria like moving averages, breakouts, trailing stop-loss and momentum confirmation.
Ideal for swing traders seeking to ride strong trends while managing risk.
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How does the strategy work?
The strategy follows a systematic process to capture high-momentum breakouts:
Pre-Breakout Criteria:
Prior Price Surge: Identifies stocks that have rallied 30-100%+ in recent month(s), signaling strong underlying momentum (per Qullamaggie’s volatility expansion principles).
Consolidation Phase: Looks for a tightening price range (e.g., flag, pennant, or tight base), indicating a potential "coiling" before continuation.
Trend Confirmation: Uses moving averages (e.g., 20/50/200 EMA) to ensure the stock is trading above key averages on the daily chart, confirming an uptrend.
Price Break: Enters when price clears the consolidation high with conviction.
Risk Management:
Initial Stop Loss: Placed below the consolidation low or a recent swing point to limit downside.
Break-Even Adjustment: Moves stop loss to breakeven once the trade reaches 1.5x risk-to-reward (RR), securing a "free trade" while letting winners run.
Trailing Stop (Unique Edge):
Market Structure Trailing: Instead of trailing via moving averages, the stop is dynamically adjusted using structural invalidation level. This adapts to price action, allowing the trade to stay open during volatile retracements while locking in gains as new structure forms.
Why This Matters: Most strategies use rigid trailing stops (e.g., below the 10EMA), which often exit prematurely in choppy markets. By trailing based on structure, this strategy avoids "noise" and captures larger trends, directly boosting overall returns.
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What markets or timeframes is this suited for?
This is a long-only strategy designed for trending markets, and it performs best in:
Markets: Stocks (especially high-growth, liquid equities), cryptocurrencies (major pairs with strong volatility), commodities (e.g., oil, gold), and futures (index/commodity futures).
Timeframes: Primarily daily charts for swing trades (1-30 day holds), though weekly charts can help confirm broader trends.
Key Advantage: The TradingView script allows instant backtesting with adjustable parameters
You can:
- Test historical performance across multiple markets to identify which assets align best with the strategy.
- Optimize settings (e.g., trailing stop sensitivity, moving averages etc.) to match a market’s volatility profile.
Build a diversified portfolio by filtering for markets that show consistent profitability in backtests.
For example, you might discover cryptos require tighter trailing stops due to volatility, while stocks thrive with wider structural stops. The script automates this analysis, letting you to trade confidently.
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What indicators or tools does the strategy use?
The strategy combines customizable technical tools with strict anti-lookahead safeguards:
Core Indicators:
Moving Averages: Adjustable periods (e.g., 20/50/200 EMA or SMA) and timeframes (daily/weekly) to confirm trend alignment. Users can test combinations (e.g., 10EMA vs. 20EMA) to optimize for specific markets.
Breakout Parameters:
Consolidation Length: Adjustable window to define the "tightness" of the pre-breakout pattern.
Entry Models: Flexible entry logics (Breakouts and fractals)
Anti-Lookahead Design:
All calculations (e.g., moving averages, consolidation ranges, volume averages) use only closed/confirmed data available at the time of the signal.
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How do I manage risk with this strategy?
The strategy prioritizes customizable risk controls to align with your trading style and account size:
User-Defined Risk Inputs:
Risk Per Trade: Set a % of Equity (e.g., 1-2%) to determine position size. The strategy auto-calculates shares/contracts to match your selected risk per trade.
Flexibility: Choose between fixed risk or equity-based scaling.
The script adjusts position sizing dynamically based on your selection.
Pyramiding Feature:
Customizable Entries: Adjust the number of pyramiding trades allowed (e.g., 1-3 additional positions) in the strategy settings. Each new entry is triggered only if the prior trade hits its 1.5x RR target and the trend remains intact.
Risk-Scaled Additions: New positions use profits from prior trades, compounding gains without increasing initial risk.
Risk-Free Trade Mechanic:
Once a trade reaches 1.5x RR, the stop loss is moved to breakeven, eliminating downside risk.
The strategy then opens a new position (if pyramiding is enabled) using a portion of the locked-in profit. This "snowballs" winners while keeping total capital exposure stable.
Impact on Net Profit & Drawdown:
Net Profit Boost: Pyramiding lets you ride multi-leg trends aggressively. For example, a 100% runner could generate 2-3x more profit vs. a single-entry approach.
Controlled Drawdowns: Since new positions are funded by profits (not initial capital), max drawdown stays anchored to your original risk per trade (e.g., 1-2% of account). Even if later entries fail, the breakeven stop on prior trades protects overall equity.
Why This Works: Most strategies either over-leverage (increasing drawdowns) or exit too early. By recycling profits into new positions only after securing risk-free capital, this approach mimics hedge fund "scaling in" tactics while staying retail-trader friendly.
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How does the strategy identify market structure for its trailing stoploss?
The strategy identifies market structure by utilizing an efficient logic with for loops to pinpoint the first swing candle that features a pivot of 2. This marks the beginning of the break of structure, where the market's previous trend or pattern is considered invalidated or changed.
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What are the underlying calculations?
The underlying calculations involve:
Identifying Swing Points: The strategy looks for swing highs (marked with blue Xs) and swing lows (marked with red Xs). A swing high is identified when a candle's high is higher than the highs of the candles before and after it. Conversely, a swing low is when a candle's low is lower than the lows of the candles before and after it.
Break of Structure (BOS):
Bullish BOS: This occurs when the price breaks above the swing high level of the previous structure, indicating a potential shift to a bullish trend.
Bearish BOS: This happens when the price breaks below the swing low level of the previous structure, signaling a potential shift to a bearish trend.
Structural Liquidity and Invalidation:
Structural Liquidity: After a break of structure, liquidity levels are updated to the first swing high in a bullish BOS or the first swing low in a bearish BOS.
Structural Invalidation: If the price moves back to the level of the first swing low before the bullish BOS or the first swing high before the bearish BOS, it invalidates the break of structure, suggesting a potential reversal or continuation of the previous trend.
This method provides users with a technical approach to filter market regimes, offering an advantage by minimizing the risk of overfitting to historical data, which is often a concern with traditional indicators like moving averages.
By focusing on identifying pivotal swing points and the subsequent breaks of structure, the strategy maintains a balance between sensitivity to market changes and robustness against historical data anomalies, ensuring a more adaptable and potentially more reliable market analysis tool.
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What entry criteria are used in this script?
The script uses two entry models for trading decisions: BreakOut and Fractal.
Underlying Calculations:
Breakout: The script records the most recent swing high by storing it in a variable. When the price closes above this recorded level, and all other predefined conditions are satisfied, the script triggers a breakout entry. This approach is considered conservative because it waits for the price to confirm a breakout above the previous high before entering a trade. As shown in the image, as soon as the price closes above the new candle (first tick), the long entry gets taken. The stop-loss is initially set and then moved to break-even once the price moves in favor of the trade.
Fractal: This method involves identifying a swing low with a period of 2, which means it looks for a low point where the price is lower than the two candles before and after it. Once this pattern is detected, the script executes the trade. This is an aggressive approach since it doesn't wait for further price confirmation. In the image, this is represented by the 'Fractal 2' label where the script identifies and acts on the swing low pattern.
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What type of stop-loss identification method are used in this strategy?
This strategy employs two types of stop-loss methods: Initial Stop-loss and Trailing Stop-Loss.
Underlying Calculations:
Initial Stop-loss:
ATR Based: The strategy uses the Average True Range (ATR) to set an initial stop-loss, which helps in accounting for market volatility without predicting price direction.
Calculation:
- First, the True Range (TR) is calculated for each period, which is the greatest of:
- Current Period High - Current Period Low
- Absolute Value of Current Period High - Previous Period Close
- Absolute Value of Current Period Low - Previous Period Close
- The ATR is then the moving average of these TR values over a specified period, typically 14 periods by default. This ATR value can be used to set the stop-loss at a distance from the entry price that reflects the current market volatility.
Swing Low Based:
For this method, the stop-loss is set based on the most recent swing low identified in the market structure analysis. This approach uses the lowest point of the recent price action as a reference for setting the stop-loss.
Trailing Stop-Loss:
The strategy uses structural liquidity and structural invalidation levels across multiple timeframes to adjust the stop-loss once the trade is profitable. This method involves:
Detecting Structural Liquidity: After a break of structure, the liquidity levels are updated to the first swing high in a bullish scenario or the first swing low in a bearish scenario. These levels serve as potential areas where the price might find support or resistance, allowing the stop-loss to trail the price movement.
Detecting Structural Invalidation: If the price returns to the level of the first swing low before a bullish break of structure or the first swing high before a bearish break of structure, it suggests the trend might be reversing or invalidating, prompting the adjustment of the stop-loss to lock in profits or minimize losses.
By using these methods, the strategy dynamically adjusts the initial stop-loss based on market volatility, helping to protect against adverse price movements while allowing for enough room for trades to develop. The ATR-based stop-loss adapts to the current market conditions by considering the volatility, ensuring that the stop-loss is not too tight during volatile periods, which could lead to premature exits, nor too loose during calm markets, which might result in larger losses. Similarly, the swing low based stop-loss provides a logical exit point if the market structure changes unfavorably.
Each market behaves differently across various timeframes, and it is essential to test different parameters and optimizations to find out which trailing stop-loss method gives you the desired results and performance. This involves backtesting the strategy with different settings for the ATR period, the distance from the swing low, and how the trailing stop-loss reacts to structural liquidity and invalidation levels.
Through this process, you can tailor the strategy to perform optimally in different market environments, ensuring that the stop-loss mechanism supports the trade's longevity while safeguarding against significant drawdowns.
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What type of break-even method is used in this strategy? What are the underlying calculations?
Moves the initial stop-loss to the entry price when the price reaches a certain RR ratio.
Calculation:
Break-even level = Entry Price + (Initial Risk * RR Ratio)
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What tables are available in this script?
- Summary: Provides a general overview, displaying key performance parameters such as Net Profit, Profit Factor, Max Drawdown, Average Trade, Closed Trades and more.
Total Commission: Displays the cumulative commissions incurred from all trades executed within the selected backtesting window. This value is derived by summing the commission fees for each trade on your chart.
Average Commission: Represents the average commission per trade, calculated by dividing the Total Commission by the total number of closed trades. This metric is crucial for assessing the impact of trading costs on overall profitability.
Avg Trade: The sum of money gained or lost by the average trade generated by a strategy. Calculated by dividing the Net Profit by the overall number of closed trades. An important value since it must be large enough to cover the commission and slippage costs of trading the strategy and still bring a profit.
MaxDD: Displays the largest drawdown of losses, i.e., the maximum possible loss that the strategy could have incurred among all of the trades it has made. This value is calculated separately for every bar that the strategy spends with an open position.
Profit Factor: The amount of money a trading strategy made for every unit of money it lost (in the selected currency). This value is calculated by dividing gross profits by gross losses.
Avg RR: This is calculated by dividing the average winning trade by the average losing trade. This field is not a very meaningful value by itself because it does not take into account the ratio of the number of winning vs losing trades, and strategies can have different approaches to profitability. A strategy may trade at every possibility in order to capture many small profits, yet have an average losing trade greater than the average winning trade. The higher this value is, the better, but it should be considered together with the percentage of winning trades and the net profit.
Winrate: The percentage of winning trades generated by a strategy. Calculated by dividing the number of winning trades by the total number of closed trades generated by a strategy. Percent profitable is not a very reliable measure by itself. A strategy could have many small winning trades, making the percent profitable high with a small average winning trade, or a few big winning trades accounting for a low percent profitable and a big average winning trade. Most mean-reversion successful strategies have a percent profitability of 40-80% but are profitable due to risk management control.
BE Trades: Number of break-even trades, excluding commission/slippage.
Losing Trades: The total number of losing trades generated by the strategy.
Winning Trades: The total number of winning trades generated by the strategy.
Total Trades: Total number of taken traders visible your charts.
Net Profit: The overall profit or loss (in the selected currency) achieved by the trading strategy in the test period. The value is the sum of all values from the Profit column (on the List of Trades tab), taking into account the sign.
- Monthly: Displays performance data on a month-by-month basis, allowing users to analyze performance trends over each month and year.
- Weekly: Displays performance data on a week-by-week basis, helping users to understand weekly performance variations.
- UI Table: A user-friendly table that allows users to view and save the selected strategy parameters from user inputs. This table enables easy access to key settings and configurations, providing a straightforward solution for saving strategy parameters by simply taking a screenshot with Alt + S or ⌥ + S.
User-input styles and customizations:
Please note that all background colors in the style are disabled by default to enhance visualization.
How to Use This Strategy to Create a Profitable Edge and Systems?
Choose Your Strategy mode:
- Decide whether you are creating an investing strategy or a trading strategy.
Select a Market:
- Choose a one-sided market such as stocks, indices, or cryptocurrencies.
Historical Data:
- Ensure the historical data covers at least 10 years of price action for robust backtesting.
Timeframe Selection:
- Choose the timeframe you are comfortable trading with. It is strongly recommended to use a timeframe above 15 minutes to minimize the impact of commissions/slippage on your profits.
Set Commission and Slippage:
- Properly set the commission and slippage in the strategy properties according to your broker/prop firm specifications.
Parameter Optimization:
- Use trial and error to test different parameters until you find the performance results you are looking for in the summary table or, preferably, through deep backtesting using the strategy tester.
Trade Count:
- Ensure the number of trades is 200 or more; the higher, the better for statistical significance.
Positive Average Trade:
- Make sure the average trade is above zero.
(An important value since it must be large enough to cover the commission and slippage costs of trading the strategy and still bring a profit.)
Performance Metrics:
- Look for a high profit factor, and net profit with minimum drawdown.
- Ideally, aim for a drawdown under 20-30%, depending on your risk tolerance.
Refinement and Optimization:
- Try out different markets and timeframes.
- Continue working on refining your edge using the available filters and components to further optimize your strategy.
What Makes This Strategy Unique?
This strategy combines flexibility, smart risk management, and momentum focus in a way that’s rare and practical:
1. Adapts to Any Market Rhythm
Works on daily, weekly, or intraday charts without code changes.
Uses two entry types: classic breakouts (like trending stocks) or fractal patterns (to avoid false starts).
2. Smarter Stop-Loss System
No rigid rules: Stops adjust based on price structure (e.g., new “higher lows”), not fixed percentages.
Avoids whipsaws: Tightens stops only when the trend strengthens, not in choppy markets.
3. Safe Profit-Boosting Pyramiding
Adds new positions only after prior trades are risk-free (stops moved above breakeven).
Scales up using locked-in profits, not new capital, to grow gains safely.
4. Built-In Momentum Check
Tracks 1/3/6-month price growth to spotlight stocks with strong, lasting momentum.
Terms and Conditions | Disclaimer
Our charting tools are provided for informational and educational purposes only and should not be construed as financial, investment, or trading advice. They are not intended to forecast market movements or offer specific recommendations. Users should understand that past performance does not guarantee future results and should not base financial decisions solely on historical data.
Built-in components, features, and functionalities of our charting tools are the intellectual property of @Fractalyst Unauthorized use, reproduction, or distribution of these proprietary elements is prohibited.
- By continuing to use our charting tools, the user acknowledges and accepts the Terms and Conditions outlined in this legal disclaimer and agrees to respect our intellectual property rights and comply with all applicable laws and regulations.
Dow Theory Trend StrategyDow Theory Trend Strategy (Pine Script)
Overview
This Pine Script implements a trading strategy based on the core principles of Dow Theory. It visually identifies trends (uptrend, downtrend) by analyzing pivot highs and lows and executes trades when the trend direction changes. This script is an improved version that features refined trend determination logic and strategy implementation.
Core Concept: Dow Theory
The script uses a fundamental Dow Theory concept for trend identification:
Uptrend: Characterized by a series of Higher Highs (HH) and Higher Lows (HL).
Downtrend: Characterized by a series of Lower Highs (LH) and Lower Lows (LL).
How it Works
Pivot Point Detection:
It uses the built-in ta.pivothigh() and ta.pivotlow() functions to identify significant swing points (potential highs and lows) in the price action.
The pivotLookback input determines the number of bars to the left and right required to confirm a pivot. Note that this introduces a natural lag (equal to pivotLookback bars) before a pivot is confirmed.
Improved Trend Determination:
The script stores the last two confirmed pivot highs and the last two confirmed pivot lows.
An Uptrend (trendDirection = 1) is confirmed only when the latest pivot high is higher than the previous one (HH) AND the latest pivot low is higher than the previous one (HL).
A Downtrend (trendDirection = -1) is confirmed only when the latest pivot high is lower than the previous one (LH) AND the latest pivot low is lower than the previous one (LL).
Key Improvement: If neither a clear uptrend nor a clear downtrend is confirmed based on the latest pivots, the script maintains the previous trend state (trendDirection := trendDirection ). This differs from simpler implementations that might switch to a neutral/range state (e.g., trendDirection = 0) more frequently. This approach aims for smoother trend following, acknowledging that trends often persist through periods without immediate new HH/HL or LH/LL confirmations.
Trend Change Detection:
The script monitors changes in the trendDirection variable.
changedToUp becomes true when the trend shifts to an Uptrend (from Downtrend or initial state).
changedToDown becomes true when the trend shifts to a Downtrend (from Uptrend or initial state).
Visualizations
Background Color: The chart background is colored to reflect the currently identified trend:
Blue: Uptrend (trendDirection == 1)
Red: Downtrend (trendDirection == -1)
Gray: Initial state or undetermined (trendDirection == 0)
Pivot Points (Optional): Small triangles (shape.triangledown/shape.triangleup) can be displayed above pivot highs and below pivot lows if showPivotPoints is enabled.
Trend Change Signals (Optional): Labels ("▲ UP" / "▼ DOWN") can be displayed when a trend change is confirmed (changedToUp / changedToDown) if showTrendChange is enabled. These visually mark the potential entry points for the strategy.
Strategy Logic
Entry Conditions:
Enters a long position (strategy.long) using strategy.entry("L", ...) when changedToUp becomes true.
Enters a short position (strategy.short) using strategy.entry("S", ...) when changedToDown becomes true.
Position Management: The script uses strategy.entry(), which automatically handles position reversal. If the strategy is long and a short signal occurs, strategy.entry() will close the long position and open a new short one (and vice-versa).
Inputs
pivotLookback: The number of bars on each side to confirm a pivot high/low. Higher values mean pivots are confirmed later but may be more significant.
showPivotPoints: Toggle visibility of pivot point markers.
showTrendChange: Toggle visibility of the trend change labels ("▲ UP" / "▼ DOWN").
Key Improvements from Original
Smoother Trend Logic: The trend state persists unless a confirmed reversal pattern (opposite HH/HL or LH/LL) occurs, reducing potential whipsaws in choppy markets compared to logic that frequently resets to neutral.
Strategy Implementation: Converted from a pure indicator to a strategy capable of executing backtests and potentially live trades based on the Dow Theory trend changes.
Disclaimer
Dow Theory signals are inherently lagging due to the nature of pivot confirmation.
The effectiveness of the strategy depends heavily on the market conditions and the chosen pivotLookback setting.
This script serves as a basic template. Always perform thorough backtesting and implement proper risk management (e.g., stop-loss, take-profit, position sizing) before considering any live trading.
Dollar Cost Averaging (DCA) | FractalystWhat's the purpose of this strategy?
The purpose of dollar cost averaging (DCA) is to grow investments over time using a disciplined, methodical approach used by many top institutions like MicroStrategy and other institutions.
Here's how it functions:
Dollar Cost Averaging (DCA): This technique involves investing a set amount of money regularly, regardless of market conditions. It helps to mitigate the risk of investing a large sum at a peak price by spreading out your investment, thus potentially lowering your average cost per share over time.
Regular Contributions: By adding money to your investments on a pre-determined frequency and dollar amount defined by the user, you take advantage of compounding. The script will remind you to contribute based on your chosen schedule, which can be weekly, bi-weekly, monthly, quarterly, or yearly. This systematic approach ensures that your returns can earn their own returns, much like interest on savings but potentially at a higher rate.
Technical Analysis: The strategy employs a market trend ratio to gauge market sentiment. It calculates the ratio of bullish vs bearish breakouts across various timeframes, assigning this ratio a percentage-based score to determine the directional bias. Once this score exceeds a user-selected percentage, the strategy looks to take buy entries, signaling a favorable time for investment based on current market trends.
Fundamental Analysis: This aspect looks at the health of the economy and companies within it to determine bullish market conditions. Specifically, we consider:
Specifically, it considers:
Interest Rate: High interest rates can affect borrowing costs, potentially slowing down economic growth or making stocks less attractive compared to fixed income.
Inflation Rate: Inflation erodes purchasing power, but moderate inflation can be a sign of a healthy economy. We look for investments that might benefit from or withstand inflation.
GDP Rate: GDP growth indicates the overall health of the economy; we aim to invest in sectors poised to grow with the economy.
Unemployment Rate: Lower unemployment typically signals consumer confidence and spending power, which can boost certain sectors.
By integrating these elements, the strategy aims to:
Reduce Investment Volatility: By spreading out your investments, you're less impacted by short-term market swings.
Enhance Growth Potential: Using both technical and fundamental filters helps in choosing investments that are more likely to appreciate over time.
Manage Risk: The strategy aims to balance the risk of market timing by investing consistently and choosing assets wisely based on both economic data and market conditions.
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What are Regular Contributions in this strategy?
Regular Contributions involve adding money to your investments on a pre-determined frequency and dollar amount defined by the user. The script will remind you to contribute based on your chosen schedule, which can be weekly, bi-weekly, monthly, quarterly, or yearly. This systematic approach ensures that your returns can earn their own returns, much like interest on savings but potentially at a higher rate.
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How do regular contributions enhance compounding and reduce timing risk?
Enhances Compounding: Regular contributions leverage the power of compounding, where returns on investments can generate their own returns, potentially leading to exponential growth over time.
Reduces Timing Risk: By investing regularly, the strategy minimizes the risk associated with trying to time the market, spreading out the investment cost over time and potentially reducing the impact of volatility.
Automated Reminders: The script reminds users to make contributions based on their chosen schedule, ensuring consistency and discipline in investment practices, which is crucial for long-term success.
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How does the strategy integrate technical and fundamental analysis for investors?
A: The strategy combines technical and fundamental analysis in the following manner:
Technical Analysis: It uses a market trend ratio to determine the directional bias by calculating the ratio of bullish vs bearish breakouts. Once this ratio exceeds a user-selected percentage threshold, the strategy signals to take buy entries, optimizing the timing within the given timeframe(s).
Fundamental Analysis: This aspect assesses the broader economic environment to identify sectors or assets that are likely to benefit from current economic conditions. By understanding these fundamentals, the strategy ensures investments are made in assets with strong growth potential.
This integration allows the strategy to select investments that are both technically favorable for entry and fundamentally sound, providing a comprehensive approach to investment decisions in the crypto, stock, and commodities markets.
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How does the strategy identify market structure? What are the underlying calculations?
Q: How does the strategy identify market structure?
A: The strategy identifies market structure by utilizing an efficient logic with for loops to pinpoint the first swing candle that features a pivot of 2. This marks the beginning of the break of structure, where the market's previous trend or pattern is considered invalidated or changed.
What are the underlying calculations for identifying market structure?
A: The underlying calculations involve:
Identifying Swing Points: The strategy looks for swing highs (marked with blue Xs) and swing lows (marked with red Xs). A swing high is identified when a candle's high is higher than the highs of the candles before and after it. Conversely, a swing low is when a candle's low is lower than the lows of the candles before and after it.
Break of Structure (BOS):
Bullish BOS: This occurs when the price breaks above the swing high level of the previous structure, indicating a potential shift to a bullish trend.
Bearish BOS: This happens when the price breaks below the swing low level of the previous structure, signaling a potential shift to a bearish trend.
Structural Liquidity and Invalidation:
Structural Liquidity: After a break of structure, liquidity levels are updated to the first swing high in a bullish BOS or the first swing low in a bearish BOS.
Structural Invalidation: If the price moves back to the level of the first swing low before the bullish BOS or the first swing high before the bearish BOS, it invalidates the break of structure, suggesting a potential reversal or continuation of the previous trend.
This method provides users with a technical approach to filter market regimes, offering an advantage by minimizing the risk of overfitting to historical data, which is often a concern with traditional indicators like moving averages.
By focusing on identifying pivotal swing points and the subsequent breaks of structure, the strategy maintains a balance between sensitivity to market changes and robustness against historical data anomalies, ensuring a more adaptable and potentially more reliable market analysis tool.
What entry criteria are used in this script?
The script uses two entry models for trading decisions: BreakOut and Fractal.
Underlying Calculations:
Breakout: The script records the most recent swing high by storing it in a variable. When the price closes above this recorded level, and all other predefined conditions are satisfied, the script triggers a breakout entry. This approach is considered conservative because it waits for the price to confirm a breakout above the previous high before entering a trade. As shown in the image, as soon as the price closes above the new candle (first tick), the long entry gets taken. The stop-loss is initially set and then moved to break-even once the price moves in favor of the trade.
Fractal: This method involves identifying a swing low with a period of 2, which means it looks for a low point where the price is lower than the two candles before and after it. Once this pattern is detected, the script executes the trade. This is an aggressive approach since it doesn't wait for further price confirmation. In the image, this is represented by the 'Fractal 2' label where the script identifies and acts on the swing low pattern.
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How does the script calculate trend score? What are the underlying calculations?
Market Trend Ratio: The script calculates the ratio of bullish to bearish breakouts. This involves:
Counting Bullish Breakouts: A bullish breakout is counted when the price breaks above a recent swing high (as identified in the strategy's market structure analysis).
Counting Bearish Breakouts: A bearish breakout is counted when the price breaks below a recent swing low.
Percentage-Based Score: This ratio is then converted into a percentage-based score:
For example, if there are 10 bullish breakouts and 5 bearish breakouts in a given timeframe, the ratio would be 10:5 or 2:1. This could be translated into a score where 66.67% (10/(10+5) * 100) represents the bullish trend strength.
The score might be calculated as (Number of Bullish Breakouts / Total Breakouts) * 100.
User-Defined Threshold: The strategy uses this score to determine when to take buy entries. If the trend score exceeds a user-defined percentage threshold, it indicates a strong enough bullish trend to justify a buy entry. For instance, if the user sets the threshold at 60%, the script would look for a buy entry when the trend score is above this level.
Timeframe Consideration: The calculations are performed across the timeframes specified by the user, ensuring the trend score reflects the market's behavior over different periods, which could be daily, weekly, or any other relevant timeframe.
This method provides a quantitative measure of market trend strength, helping to make informed decisions based on the balance between bullish and bearish market movements.
What type of stop-loss identification method are used in this strategy?
This strategy employs two types of stop-loss methods: Initial Stop-loss and Trailing Stop-Loss.
Underlying Calculations:
Initial Stop-loss:
ATR Based: The strategy uses the Average True Range (ATR) to set an initial stop-loss, which helps in accounting for market volatility without predicting price direction.
Calculation:
- First, the True Range (TR) is calculated for each period, which is the greatest of:
- Current Period High - Current Period Low
- Absolute Value of Current Period High - Previous Period Close
- Absolute Value of Current Period Low - Previous Period Close
- The ATR is then the moving average of these TR values over a specified period, typically 14 periods by default. This ATR value can be used to set the stop-loss at a distance from the entry price that reflects the current market volatility.
Swing Low Based:
For this method, the stop-loss is set based on the most recent swing low identified in the market structure analysis. This approach uses the lowest point of the recent price action as a reference for setting the stop-loss.
Trailing Stop-Loss:
The strategy uses structural liquidity and structural invalidation levels across multiple timeframes to adjust the stop-loss once the trade is profitable. This method involves:
Detecting Structural Liquidity: After a break of structure, the liquidity levels are updated to the first swing high in a bullish scenario or the first swing low in a bearish scenario. These levels serve as potential areas where the price might find support or resistance, allowing the stop-loss to trail the price movement.
Detecting Structural Invalidation: If the price returns to the level of the first swing low before a bullish break of structure or the first swing high before a bearish break of structure, it suggests the trend might be reversing or invalidating, prompting the adjustment of the stop-loss to lock in profits or minimize losses.
By using these methods, the strategy dynamically adjusts the initial stop-loss based on market volatility, helping to protect against adverse price movements while allowing for enough room for trades to develop. The ATR-based stop-loss adapts to the current market conditions by considering the volatility, ensuring that the stop-loss is not too tight during volatile periods, which could lead to premature exits, nor too loose during calm markets, which might result in larger losses. Similarly, the swing low based stop-loss provides a logical exit point if the market structure changes unfavorably.
Each market behaves differently across various timeframes, and it is essential to test different parameters and optimizations to find out which trailing stop-loss method gives you the desired results and performance. This involves backtesting the strategy with different settings for the ATR period, the distance from the swing low, and how the trailing stop-loss reacts to structural liquidity and invalidation levels.
Through this process, you can tailor the strategy to perform optimally in different market environments, ensuring that the stop-loss mechanism supports the trade's longevity while safeguarding against significant drawdowns.
What type of break-even and take profit identification methods are used in this strategy? What are the underlying calculations?
For Break-Even:
Percentage (%) Based:
Moves the initial stop-loss to the entry price when the price reaches a certain percentage above the entry.
Calculation:
Break-even level = Entry Price * (1 + Percentage / 100)
Example:
If the entry price is $100 and the break-even percentage is 5%, the break-even level is $100 * 1.05 = $105.
Risk-to-Reward (RR) Based:
Moves the initial stop-loss to the entry price when the price reaches a certain RR ratio.
Calculation:
Break-even level = Entry Price + (Initial Risk * RR Ratio)
For TP
- You can choose to set a take profit level at which your position gets fully closed.
- Similar to break-even, you can select either a percentage (%) or risk-to-reward (RR) based take profit level, allowing you to set your TP1 level as a percentage amount above the entry price or based on RR.
What's the day filter Filter, what does it do?
The day filter allows users to customize the session time and choose the specific days they want to include in the strategy session. This helps traders tailor their strategies to particular trading sessions or days of the week when they believe the market conditions are more favorable for their trading style.
Customize Session Time:
Users can define the start and end times for the trading session.
This allows the strategy to only consider trades within the specified time window, focusing on periods of higher market activity or preferred trading hours.
Select Days:
Users can select which days of the week to include in the strategy.
This feature is useful for excluding days with historically lower volatility or unfavorable trading conditions (e.g., Mondays or Fridays).
Benefits:
Focus on Optimal Trading Periods:
By customizing session times and days, traders can focus on periods when the market is more likely to present profitable opportunities.
Avoid Unfavorable Conditions:
Excluding specific days or times can help avoid trading during periods of low liquidity or high unpredictability, such as major news events or holidays.
What tables are available in this script?
- Summary: Provides a general overview, displaying key performance parameters such as Net Profit, Profit Factor, Max Drawdown, Average Trade, Closed Trades and more.
Total Commission: Displays the cumulative commissions incurred from all trades executed within the selected backtesting window. This value is derived by summing the commission fees for each trade on your chart.
Average Commission: Represents the average commission per trade, calculated by dividing the Total Commission by the total number of closed trades. This metric is crucial for assessing the impact of trading costs on overall profitability.
Avg Trade: The sum of money gained or lost by the average trade generated by a strategy. Calculated by dividing the Net Profit by the overall number of closed trades. An important value since it must be large enough to cover the commission and slippage costs of trading the strategy and still bring a profit.
MaxDD: Displays the largest drawdown of losses, i.e., the maximum possible loss that the strategy could have incurred among all of the trades it has made. This value is calculated separately for every bar that the strategy spends with an open position.
Profit Factor: The amount of money a trading strategy made for every unit of money it lost (in the selected currency). This value is calculated by dividing gross profits by gross losses.
Avg RR: This is calculated by dividing the average winning trade by the average losing trade. This field is not a very meaningful value by itself because it does not take into account the ratio of the number of winning vs losing trades, and strategies can have different approaches to profitability. A strategy may trade at every possibility in order to capture many small profits, yet have an average losing trade greater than the average winning trade. The higher this value is, the better, but it should be considered together with the percentage of winning trades and the net profit.
Winrate: The percentage of winning trades generated by a strategy. Calculated by dividing the number of winning trades by the total number of closed trades generated by a strategy. Percent profitable is not a very reliable measure by itself. A strategy could have many small winning trades, making the percent profitable high with a small average winning trade, or a few big winning trades accounting for a low percent profitable and a big average winning trade. Most mean-reversion successful strategies have a percent profitability of 40-80% but are profitable due to risk management control.
BE Trades: Number of break-even trades, excluding commission/slippage.
Losing Trades: The total number of losing trades generated by the strategy.
Winning Trades: The total number of winning trades generated by the strategy.
Total Trades: Total number of taken traders visible your charts.
Net Profit: The overall profit or loss (in the selected currency) achieved by the trading strategy in the test period. The value is the sum of all values from the Profit column (on the List of Trades tab), taking into account the sign.
- Monthly: Displays performance data on a month-by-month basis, allowing users to analyze performance trends over each month and year.
- Weekly: Displays performance data on a week-by-week basis, helping users to understand weekly performance variations.
- UI Table: A user-friendly table that allows users to view and save the selected strategy parameters from user inputs. This table enables easy access to key settings and configurations, providing a straightforward solution for saving strategy parameters by simply taking a screenshot with Alt + S or ⌥ + S.
User-input styles and customizations:
Please note that all background colors in the style are disabled by default to enhance visualization.
How to Use This Strategy to Create a Profitable Edge and Systems?
Choose Your Strategy mode:
- Decide whether you are creating an investing strategy or a trading strategy.
Select a Market:
- Choose a one-sided market such as stocks, indices, or cryptocurrencies.
Historical Data:
- Ensure the historical data covers at least 10 years of price action for robust backtesting.
Timeframe Selection:
- Choose the timeframe you are comfortable trading with. It is strongly recommended to use a timeframe above 15 minutes to minimize the impact of commissions/slippage on your profits.
Set Commission and Slippage:
- Properly set the commission and slippage in the strategy properties according to your broker/prop firm specifications.
Parameter Optimization:
- Use trial and error to test different parameters until you find the performance results you are looking for in the summary table or, preferably, through deep backtesting using the strategy tester.
Trade Count:
- Ensure the number of trades is 200 or more; the higher, the better for statistical significance.
Positive Average Trade:
- Make sure the average trade is above zero.
(An important value since it must be large enough to cover the commission and slippage costs of trading the strategy and still bring a profit.)
Performance Metrics:
- Look for a high profit factor, and net profit with minimum drawdown.
- Ideally, aim for a drawdown under 20-30%, depending on your risk tolerance.
Refinement and Optimization:
- Try out different markets and timeframes.
- Continue working on refining your edge using the available filters and components to further optimize your strategy.
What makes this strategy original?
Incorporation of Fundamental Analysis:
This strategy integrates fundamental analysis by considering key economic indicators such as interest rates, inflation, GDP growth, and unemployment rates. These fundamentals help in assessing the broader economic health, which in turn influences sector performance and market trends. By understanding these economic conditions, the strategy can identify sectors or assets that are likely to thrive, ensuring investments are made in environments conducive to growth. This approach allows for a more informed investment decision, aligning technical entries with fundamentally strong market conditions, thus potentially enhancing the strategy's effectiveness over time.
Technical Analysis Without Classical Methods:
The strategy's technical analysis diverges from traditional methods like moving averages by focusing on market structure through a trend score system.
Instead of using lagging indicators, it employs a real-time analysis of market trends by calculating the ratio of bullish to bearish breakouts. This provides several benefits:
Immediate Market Sentiment: The trend score system reacts more dynamically to current market conditions, offering insights into the market's immediate sentiment rather than historical trends, which can often lag behind real-time changes.
Reduced Overfitting: By not relying on moving averages or similar classical indicators, the strategy avoids the common pitfall of overfitting to historical data, which can lead to poor performance in new market conditions. The trend score provides a fresh perspective on market direction, potentially leading to more robust trading signals.
Clear Entry Signals: With the trend score, entry decisions are based on a clear percentage threshold, making the strategy's decision-making process straightforward and less subjective than interpreting moving average crossovers or similar signals.
Regular Contributions and Reminders:
The strategy encourages regular investments through a system of predefined frequency and amount, which could be weekly, bi-weekly, monthly, quarterly, or yearly. This systematic approach:
Enhances Compounding: Regular contributions leverage the power of compounding, where returns on investments can generate their own returns, potentially leading to exponential growth over time.
Reduces Timing Risk: By investing regularly, the strategy minimizes the risk associated with trying to time the market, spreading out the investment cost over time and potentially reducing the impact of volatility.
Automated Reminders: The script reminds users to make contributions based on their chosen schedule, ensuring consistency and discipline in investment practices, which is crucial for long-term success.
Long-Term Wealth Building:
Focused on long-term wealth accumulation, this strategy:
Promotes Patience and Discipline: By emphasizing regular contributions and a disciplined approach to both entry and risk management, it aligns with the principles of long-term investing, discouraging impulsive decisions based on short-term market fluctuations.
Diversification Across Asset Classes: Operating across crypto, stocks, and commodities, the strategy provides diversification, which is a key component of long-term wealth building, reducing risk through varied exposure.
Growth Over Time: The strategy's design to work with the market's natural growth cycles, supported by fundamental analysis, aims for sustainable growth rather than quick profits, aligning with the goals of investors looking to build wealth over decades.
This comprehensive approach, combining fundamental insights, innovative technical analysis, disciplined investment habits, and a focus on long-term growth, offers a unique and potentially effective pathway for investors seeking to build wealth steadily over time.
Terms and Conditions | Disclaimer
Our charting tools are provided for informational and educational purposes only and should not be construed as financial, investment, or trading advice. They are not intended to forecast market movements or offer specific recommendations. Users should understand that past performance does not guarantee future results and should not base financial decisions solely on historical data.
Built-in components, features, and functionalities of our charting tools are the intellectual property of @Fractalyst Unauthorized use, reproduction, or distribution of these proprietary elements is prohibited.
- By continuing to use our charting tools, the user acknowledges and accepts the Terms and Conditions outlined in this legal disclaimer and agrees to respect our intellectual property rights and comply with all applicable laws and regulations.
Strategy without indicators v11. General Script Strategy
The objective of this strategy is to open buy or sell orders every new hour based on:
Whether the previous candle closed high (buy) or low (sell).
The presence of tops and bottoms to avoid opening orders at times of possible reversals.
The strategy also allows the user to set a date range (start date and end date) to calculate profit, loss, percentage of gain and percentage of loss only in that period.
2. Initial Settings and Parameters
Start Date and End Date: The start_date and end_date variables define the date range to account for profits and losses. These dates can be adjusted by the user to view results in specific periods.
3. Conditions for Order Entry
At each time change, the script checks the conditions for buying or selling, using the following variables and logic:
Detection of Bullish or Bearish Candle:
bullish_candle: True if the previous candle closed high.
bearish_candle: True if the previous candle closed lower.
Analysis of Tops and Bottoms:
To avoid opening orders close to tops and bottoms, the script uses the function find_top_and_bottom(period), which analyzes the last 500 candles and identifies the highest value (top) and the lowest value (bottom).
The variables current_top and current_bottom store these values.
next_top and next_bottom indicate whether the current candle is close to a top (prevents buying) or a bottom (prevents selling).
4. Opening Orders (Buy and Sell)
At each time change, the script checks the conditions to open buy or sell orders:
Condition for Sell:
The sell order is opened if the previous candle was bullish (bullish_candle) and is not close to a top (not next_top).
If there is an open buy order, it is closed before the new sell order.
Buy Condition:
The buy order is opened if the previous candle was bearish (bearish_candle) and is not near a bottom (not_near_bottom).
If there is an open sell order, it is closed before the new buy order.
5. Calculating Profit and Loss
The profit and loss calculation is only done within the configured date range (start_date and end_date):
Profit and Loss:
total_profit and total_loss accumulate the profit and loss values of all operations during the defined period.
percentage_gain and percentage_loss calculate the percentage of gain and loss in relation to the initial capital.
6. Displaying Results on the Chart
The script displays on the chart, next to the candles, the information on Total Profit, Total Loss, % Gain and % Loss:
Strategy Summary
Setting the Date Range: Allows you to set the period for calculating profit and loss.
Previous Candlestick Analysis: Decide whether to buy or sell based on the previous candlestick.
Preventing Entries at Tops and Bottoms: Avoids buying at tops and selling at bottoms to reduce false signals.
Result Calculation: Accumulates profits, losses and percentages within the configured date range.
Results Display on Chart: Displays the configured statistics directly on the chart, next to the candlesticks.
1. Estratégia Geral do Script
O objetivo dessa estratégia é abrir ordens de compra ou venda a cada nova hora com base em:
Se a vela anterior fechou em alta (compra) ou em baixa (venda).
A presença de topos e fundos para evitar abrir ordens em momentos de possíveis reversões.
A estratégia também permite que o usuário configure um intervalo de datas (data inicial e data final) para calcular o lucro, perda, percentual de ganho e percentual de perda apenas nesse período.
2. Configurações e Parâmetros Iniciais
Data Inicial e Data Final: As variáveis data_inicial e data_final definem o intervalo de datas para contabilizar os lucros e perdas. Essas datas podem ser ajustadas pelo usuário para visualizar resultados em períodos específicos.
3. Condições para Entrada de Ordens
A cada mudança de hora, o script verifica as condições de compra ou venda, usando as seguintes variáveis e lógicas:
Detecção de Vela de Alta ou Baixa:
vela_de_alta: Verdadeiro se a vela anterior fechou em alta.
vela_de_baixa: Verdadeiro se a vela anterior fechou em baixa.
Análise de Topos e Fundos:
Para evitar abrir ordens próximas de topos e fundos, o script utiliza a função find_top_and_bottom(periodo), que analisa as últimas 500 velas e identifica o valor mais alto (topo) e o valor mais baixo (fundo).
As variáveis topo_atual e fundo_atual armazenam esses valores.
topo_proximo e fundo_proximo indicam se a vela atual está perto de um topo (evita compra) ou de um fundo (evita venda).
4. Abertura de Ordens (Compra e Venda)
A cada mudança de hora, o script verifica as condições para abrir ordens de compra ou venda:
Condição para Venda:
A ordem de venda é aberta se a vela anterior foi de alta (vela_de_alta) e não está perto de um topo (not topo_proximo).
Se houver uma ordem de compra aberta, ela é fechada antes da nova ordem de venda.
Condição para Compra:
A ordem de compra é aberta se a vela anterior foi de baixa (vela_de_baixa) e não está perto de um fundo (not fundo_proximo).
Se houver uma ordem de venda aberta, ela é fechada antes da nova ordem de compra.
5. Cálculo de Lucros e Perdas
O cálculo de lucro e perda só é feito dentro do intervalo de datas configurado (data_inicial e data_final):
Lucro e Perda:
lucro_total e perca_total acumulam os valores de lucro e perda de todas as operações durante o período definido.
percentual_ganho e percentual_perca calculam o percentual de ganho e perda em relação ao capital inicial.
6. Exibição dos Resultados no Gráfico
O script exibe no gráfico, próximo das velas, as informações de Lucro Total, Perda Total, % de Ganho e % de Perda:
Resumo da Estratégia
Configuração de Intervalo de Datas: Permite configurar o período para cálculo do lucro e da perda.
Análise de Vela Anterior: Decide se a ordem é de compra ou venda com base na vela anterior.
Prevenção de Entradas em Topos e Fundos: Evita compras em topos e vendas em fundos para reduzir sinais falsos.
Cálculo de Resultados: Acumula lucros, perdas e percentuais dentro do período de datas configurado.
Exibição dos Resultados no Gráfico: Exibe as estatísticas configuradas diretamente no gráfico, próximo das velas.
NNFX RSI EMA FVMA MACD ALGOThis Pine Script introduces a cutting-edge trading strategy that seamlessly integrates multiple technical indicators—namely, the Flexible Variable Moving Average ( FVMA ), Relative Strength Index ( RSI ), Moving Average Convergence Divergence ( MACD ), and Exponential Moving Average ( EMA )—to deliver a sophisticated trading experience. This script stands out due to its comprehensive approach, robust risk management, and the inclusion of crucial data tables for various timeframes, making it an invaluable tool for traders seeking to enhance their market performance.
Originality of the Strategy:
The originality of this script lies in its unique combination of multiple powerful indicators, enabling traders to benefit from diverse perspectives on market dynamics. This mashup enhances decision-making processes, providing multiple layers of confirmation for trade entries and exits. The strategy is designed to offer an innovative solution for traders looking to improve their performance through well-defined rules and a solid framework.
Flexible Variable Moving Average (FVMA):
The FVMA adapts dynamically to market conditions, offering a more responsive trend line than traditional moving averages. This flexibility allows for quick identification of trends and reversals, crucial for fast-paced trading environments.
Exponential Moving Average (EMA):
By giving greater weight to recent price data, the EMA enhances sensitivity to price changes, allowing for more accurate entries and exits when used alongside the FVMA. This combination maximizes the effectiveness of the strategy in identifying optimal trading opportunities.
Relative Strength Index (RSI):
The RSI helps identify overbought or oversold conditions, integrating seamlessly with other indicators to enhance the strategy's ability to pinpoint potential reversal points. This aspect of the strategy ensures that traders can make informed decisions based on market momentum.
Moving Average Convergence Divergence (MACD):
The MACD serves as an essential confirmation tool, providing insights into trend strength and momentum. This enhances the accuracy of entry and exit signals, allowing traders to make more informed decisions based on robust technical analysis.
Multi-Take Profit (TP) and Stop Loss (SL) Levels:
The strategy supports multiple TPs, allowing traders to lock in profits at various levels while effectively managing risk through a robust SL system. This flexibility caters to diverse trading styles and risk profiles, ensuring that the strategy can adapt to individual trader needs.
Default Properties:
Take Profit Levels: TP1 is set to 2.0, and TP2 is set to 2.9, which is designed to enhance profit potential while maintaining a solid risk-reward ratio.
Stop Loss: A SL is set at 2% of the 5% account balance, which helps to preserve capital and manage risk effectively, adhering to the guideline of not risking more than 5-10% of the account balance per trade.
Labeling System for Exits: Automatic labeling of TP and SL exits on the chart provides clear visualization of trading outcomes. This feature supports informed decision-making and performance tracking, aligning with the guideline of providing transparent results.
Custom Alerts System:
The inclusion of customizable alerts for trade entries, exits, and SL/TP hits keeps traders informed in real-time, enabling prompt actions without constant market monitoring. This is crucial for effective trade management and helps traders respond quickly to market changes.
API Boxes for Automated Trading:
The strategy features API boxes, allowing traders to set up automated trading based on indicator signals. This functionality enables seamless integration with trading platforms, enhancing efficiency and streamlining the trading process, which is particularly valuable for traders looking to optimize their execution.
Data Tables for Enhanced Analysis:
The script includes data tables displaying critical insights across various timeframes: 2-hour, daily, weekly, and monthly. These tables provide a comprehensive overview of market conditions, allowing traders to analyze trends and make informed decisions based on a broad spectrum of data. By leveraging this information, traders can identify high-probability setups and align their strategies with prevailing market trends, significantly increasing their chances of success.
Default Properties:
Initial Capital: £1,000, ensuring a realistic starting point for traders.
Risk per Trade: 5% of the account balance, promoting sustainable trading practices.
Commission: 0.1%, reflecting realistic transaction costs that traders may encounter.
Slippage: 1%, accounting for potential market volatility during trade execution.
Take Profit Levels:
TP1: 2.0
TP2: 2.9
Stop Loss (SL): 2% of the 5% account balance, which is well within acceptable risk parameters.
Compliance with TradingView Guidelines:
This script fully complies with TradingView's guidelines, specifically:
Strategy Results:
The strategy is designed to publish backtesting results that do not mislead traders. The realistic parameters outlined in the default properties ensure that traders have a clear understanding of potential outcomes.
The dataset used for backtesting has sufficient trades to produce a reliable sample size, aligning with the guideline of ideally having more than 100 trades.
Any deviations from recommended practices are justified in the script description, ensuring transparency and adherence to best practices.
The script explains the default properties in detail, providing a thorough understanding of how these settings influence performance.
Why This Script is Worth Paying For:
This Pine Script offers an unparalleled trading experience through its unique combination of technical indicators, comprehensive trade management features, and detailed data tables for multiple timeframes. Here are compelling reasons to invest in this strategy:
Holistic Approach: The integration of multiple indicators ensures a well-rounded perspective on market conditions, increasing the likelihood of successful trades.
Advanced Risk Management: The flexibility of multiple TPs and SLs empowers traders to tailor their risk profiles according to individual strategies, enhancing overall profitability.
Automated Trading Capability: The inclusion of API boxes for automated trading streamlines execution, allowing traders to capitalize on opportunities without the need for manual intervention.
Comprehensive Data Analysis: The detailed data tables provide invaluable insights across different timeframes, enabling traders to make informed decisions based on robust market analysis.
In summary, this innovative Pine Script represents a powerful tool designed to empower traders at all levels. Its originality, synergistic functionality, and comprehensive features create a dynamic and effective trading environment, justifying its value and positioning it as a must-have for anyone serious about achieving consistent trading success.
DMR By ANTExplanation of the DMR by ANT Script
a. What is This Script and How Is It Useful?
This Pine Script, named "DMR by ANT, " is designed for use on TradingView, focusing on dynamically assessing market conditions. It calculates key levels, specifically the high and low of the previous two days, to establish trading zones that assist traders in making informed decisions.
The script highlights:
Previous Day's High and Low : It captures the high and low prices from the previous two days to help set up trading ranges.
First 15 Minutes Candles High and low is marked with Orange Lines .
Trade Zones : It identifies whether the current price is in a 'tradeable' zone or 'non-tradeable' zone. The zones are determined based on the relationship between the current price, today's open price, and the calculated high and low levels.
Targets and Stop Losses : The script dynamically provides target and stop-loss levels based on user-defined input points, which can help manage risk effectively.
This script is beneficial for traders looking to enter (or avoid) trades based on defined price action criteria and can effectively streamline the analysis process in fast-moving markets.
Customize Input Parameters:(settings)
Adjust the ATR, based on ATR target and stop-loss is calculated and displayed. The default values 7(rest see the help), Dynamics changes based on ATR values changes in real time.
b. How to Effectively Use This Script
The DMR script can be utilized across various trading instruments, including:
Indexes: Suitable for gauging market sentiment and overall trends; can assist in short-term trading strategies.
Options: Helps determine the likely movement of the underlying assets, providing insight into probable volatility and directional bias.
ETFs (Exchange-Traded Funds): Useful for trading diversified portfolios; traders can define entry and exit points relevant to the basket of stocks.
Stocks: Ideal for individual stock trading, as traders can analyze stock movements concerning broader market trends.
When utilizing this script, traders should:
Identify key trading levels before entering trades based on the calculated high and low ranges.
Use the dynamic targets and stop-loss levels to protect capital and maximize potential gains.
Continuously monitor the script's signals and adapt to ongoing market changes.
c. Best Time Frames for Different Instruments
The optimal time frames for using the DMR script can vary based on the trading instrument.
Here’s a summary in tabular format for clearer guidance:
Instrument Best Time Frames
Index 5-minute, 15-minute, 1-hour
Options 1-minute, 5-minute, 15-minute
ETF 5-minute, 15-minute, 1-hour
Stocks 5-minute, 15-minute, 1-hour, Daily
Indexes: Shorter time frames (5 to 15 minutes) can capture quick market movements, while 1-hour frames can provide a broader market overview.
Options Trading: Given the time sensitivity of options, using very short time frames (1-5 minutes) can be effective to seize rapid price movements before expiry.
ETFs: Similar to indices, shorter frames help in effectively tracking movements of the underlying assets.
Stocks: A mix of short (5-15 minutes) for day trading and daily charts for swing trading can provide balanced insights.
Conclusion
Utilizing the DMR by ANT script can greatly enhance a trader's ability to analyze market conditions, identify opportunities, and manage risk effectively. By adapting the script through the different listed recommendations, traders can maximize their trading strategy’s effectiveness across various instruments.
Do comment below for further improvement.
Varanormal Mac N Cheez Strategy v1Mac N Cheez Strategy (Set a $200 Take profit Manually)
It's super cheesy. Strategy does the following:
Here's a detailed explanation of what the entire script does, including its key components, functionality, and purpose.
1. Strategy Setup and Input Parameters:
Strategy Name: The script is named "NQ Futures $200/day Strategy" and is set as an overlay, meaning all elements (like moving averages and signals) are plotted on the price chart.
Input Parameters:
fastLength: This sets the length of the fast moving average. The user can adjust this value, and it defaults to 9.
slowLength: This sets the length of the slow moving average. The user can adjust this value, and it defaults to 21.
dailyTarget: The daily profit target, which defaults to $200. If set to 0, this disables the daily profit target.
stopLossAmount: The fixed stop-loss amount per trade, defaulting to $100. This value is used to calculate how much you're willing to lose on a single trade.
trailOffset: This value sets the distance for a trailing stop. It helps protect profits by automatically adjusting the stop-loss as the price moves in your favor.
2. Calculating the Moving Averages:
fastMA: The fast moving average is calculated using the ta.sma() function on the close price with a period length of fastLength. The ta.sma() function calculates the simple moving average.
slowMA: The slow moving average is also calculated using ta.sma() but with the slowLength period.
These moving averages are used to determine trend direction and identify entry points.
3. Buy and Sell Signal Conditions:
longCondition: This is the buy condition. It occurs when the fast moving average crosses above the slow moving average. The script uses ta.crossover() to detect this crossover event.
shortCondition: This is the sell condition. It occurs when the fast moving average crosses below the slow moving average. The script uses ta.crossunder() to detect this crossunder event.
4. Executing Buy and Sell Orders:
Buy Orders: When the longCondition is true (i.e., fast MA crosses above slow MA), the script enters a long position using strategy.entry("Buy", strategy.long).
Sell Orders: When the shortCondition is true (i.e., fast MA crosses below slow MA), the script enters a short position using strategy.entry("Sell", strategy.short).
5. Setting Stop Loss and Trailing Stop:
Stop-Loss for Long Positions: The stop-loss is calculated as the entry price minus the stopLossAmount. If the price falls below this level, the trade is exited automatically.
Stop-Loss for Short Positions: The stop-loss is calculated as the entry price plus the stopLossAmount. If the price rises above this level, the short trade is exited.
Trailing Stop: The trail_offset dynamically adjusts the stop-loss as the price moves in favor of the trade, locking in profits while still allowing room for market fluctuations.
6. Conditional Daily Profit Target:
The script includes a daily profit target that automatically closes all trades once the total profit for the day reaches or exceeds the dailyTarget.
Conditional Logic:
If the dailyTarget is greater than 0, the strategy checks whether the strategy.netprofit (total profit for the day) has reached or exceeded the target.
If the strategy.netprofit >= dailyTarget, the script calls strategy.close_all(), closing all open trades for the day and stopping further trading.
If dailyTarget is set to 0, this logic is skipped, and the script continues trading without a daily profit target.
7. Plotting Moving Averages:
plot(fastMA): This plots the fast moving average as a blue line on the price chart.
plot(slowMA): This plots the slow moving average as a red line on the price chart. These help visualize the crossover points and the trend direction on the chart.
8. Plotting Buy and Sell Signals:
plotshape(): The script uses plotshape() to add visual markers when buy or sell conditions are met:
"Long Signal": When a buy condition (longCondition) is met, a green marker is plotted below the price bar with the label "Long".
"Short Signal": When a sell condition (shortCondition) is met, a red marker is plotted above the price bar with the label "Short".
These markers help traders quickly see when buy or sell signals occurred on the chart.
In addition, triangle markers are plotted:
Green Triangle: Indicates where a buy entry occurred.
Red Triangle: Indicates where a sell entry occurred.
Summary of What the Script Does:
Inputs: The script allows the user to adjust moving average lengths, daily profit targets, stop-loss amounts, and trailing stop offsets.
Signals: It generates buy and sell signals based on the crossovers of the fast and slow moving averages.
Order Execution: It executes long positions on buy signals and short positions on sell signals.
Stop-Loss and Trailing Stop: It sets dynamic stop-losses and uses a trailing stop to protect profits.
Daily Profit Target: The strategy stops trading for the day once the net profit reaches the daily target (unless the target is disabled by setting it to 0).
Visual Markers: It plots moving averages and buy/sell signals directly on the main price chart to aid in visual analysis.
This script is designed to trade based on moving average crossovers, with robust risk management features like stop-loss and trailing stops, along with an optional daily profit target to limit daily trading activity. Let me know if you need further clarification or want to adjust any specific part of the script!
Bollinger Bands Enhanced StrategyOverview
The common practice of using Bollinger bands is to use it for building mean reversion or squeeze momentum strategies. In the current script Bollinger Bands Enhanced Strategy we are trying to combine the strengths of both strategies types. It utilizes Bollinger Bands indicator to buy the local dip and activates trailing profit system after reaching the user given number of Average True Ranges (ATR). Also it uses 200 period EMA to filter trades only in the direction of a trend. Strategy can execute only long trades.
Unique Features
Trailing Profit System: Strategy uses user given number of ATR to activate trailing take profit. If price has already reached the trailing profit activation level, scrip will close long trade if price closes below Bollinger Bands middle line.
Configurable Trading Periods: Users can tailor the strategy to specific market windows, adapting to different market conditions.
Major Trend Filter: Strategy utilizes 100 period EMA to take trades only in the direction of a trend.
Flexible Risk Management: Users can choose number of ATR as a stop loss (by default = 1.75) for trades. This is flexible approach because ATR is recalculated on every candle, therefore stop-loss readjusted to the current volatility.
Methodology
First of all, script checks if currently price is above the 200-period exponential moving average EMA. EMA is used to establish the current trend. Script will take long trades on if this filtering system showing us the uptrend. Then the strategy executes the long trade if candle’s low below the lower Bollinger band. To calculate the middle Bollinger line, we use the standard 20-period simple moving average (SMA), lower band is calculated by the substruction from middle line the standard deviation multiplied by user given value (by default = 2).
When long trade executed, script places stop-loss at the price level below the entry price by user defined number of ATR (by default = 1.75). This stop-loss level recalculates at every candle while trade is open according to the current candle ATR value. Also strategy set the trailing profit activation level at the price above the position average price by user given number of ATR (by default = 2.25). It is also recalculated every candle according to ATR value. When price hit this level script plotted the triangle with the label “Strong Uptrend” and start trail the price at the middle Bollinger line. It also started to be plotted as a green line.
When price close below this trailing level script closes the long trade and search for the next trade opportunity.
Risk Management
The strategy employs a combined and flexible approach to risk management:
It allows positions to ride the trend as long as the price continues to move favorably, aiming to capture significant price movements. It features a user-defined ATR stop loss parameter to mitigate risks based on individual risk tolerance. By default, this stop-loss is set to a 1.75*ATR drop from the entry point, but it can be adjusted according to the trader's preferences.
There is no fixed take profit, but strategy allows user to define user the ATR trailing profit activation parameter. By default, this stop-loss is set to a 2.25*ATR growth from the entry point, but it can be adjusted according to the trader's preferences.
Justification of Methodology
This strategy leverages Bollinger bangs indicator to open long trades in the local dips. If price reached the lower band there is a high probability of bounce. Here is an issue: during the strong downtrend price can constantly goes down without any significant correction. That’s why we decided to use 200-period EMA as a trend filter to increase the probability of opening long trades during major uptrend only.
Usually, Bollinger Bands indicator is using for mean reversion or breakout strategies. Both of them have the disadvantages. The mean reversion buys the dip, but closes on the return to some mean value. Therefore, it usually misses the major trend moves. The breakout strategies usually have the issue with too high buy price because to have the breakout confirmation price shall break some price level. Therefore, in such strategies traders need to set the large stop-loss, which decreases potential reward to risk ratio.
In this strategy we are trying to combine the best features of both types of strategies. Script utilizes ate ATR to setup the stop-loss and trailing profit activation levels. ATR takes into account the current volatility. Therefore, when we setup stop-loss with the user-given number of ATR we increase the probability to decrease the number of false stop outs. The trailing profit concept is trying to add the beat feature from breakout strategies and increase probability to stay in trade while uptrend is developing. When price hit the trailing profit activation level, script started to trail the price with middle line if Bollinger bands indicator. Only when candle closes below the middle line script closes the long trade.
Backtest Results
Operating window: Date range of backtests is 2020.10.01 - 2024.07.01. It is chosen to let the strategy to close all opened positions.
Commission and Slippage: Includes a standard Binance commission of 0.1% and accounts for possible slippage over 5 ticks.
Initial capital: 10000 USDT
Percent of capital used in every trade: 30%
Maximum Single Position Loss: -9.78%
Maximum Single Profit: +25.62%
Net Profit: +6778.11 USDT (+67.78%)
Total Trades: 111 (48.65% win rate)
Profit Factor: 2.065
Maximum Accumulated Loss: 853.56 USDT (-6.60%)
Average Profit per Trade: 61.06 USDT (+1.62%)
Average Trade Duration: 76 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.
How to Use
Add the script to favorites for easy access.
Apply to the desired timeframe and chart (optimal performance observed on 4h BTC/USDT).
Configure settings using the dropdown choice list in the built-in menu.
Set up alerts to automate strategy positions through web hook with the text: {{strategy.order.alert_message}}
Disclaimer:
Educational and informational tool reflecting Skyrex commitment to informed trading. Past performance does not guarantee future results. Test strategies in a simulated environment before live implementation
