Williams %R Cross Strategy with 200 MA Filter
1. The script is a trading strategy based on the Williams %R indicator and a 200-period moving average (MA) filter.
2. The user can input the length of the Williams %R indicator (`wrLength`), the threshold for %R crossing (`crossPips`), the take profit level in pips (`takeProfitPips`), and the stop loss level in pips (`stopLossPips`).
3. The script calculates the Williams %R using the `ta.highest` and `ta.lowest` functions to find the highest high and lowest low over the specified length (`wrLength`).
4. It also calculates a 200-period simple moving average (`ma200`) using the `ta.sma` function.
5. The entry conditions are defined as follows:
- For a long entry, it checks if the Williams %R crosses above the -50 line by a threshold of `crossPips` and if the close price is above the 200-period MA.
- For a short entry, it checks if the Williams %R crosses below the -50 line by a threshold of `crossPips` and if the close price is below the 200-period MA.
6. The exit conditions are defined as follows:
- For a long position, it checks if the close price reaches the take profit level (defined as the average entry price plus `takeProfitPips` in pips) or the stop loss level (defined as the average entry price minus `stopLossPips` in pips).
- For a short position, it checks if the close price reaches the take profit level (defined as the average entry price minus `takeProfitPips` in pips) or the stop loss level (defined as the average entry price plus `stopLossPips` in pips).
7. The script uses the `strategy.entry` function to place long and short orders when the respective entry conditions are met.
8. It uses the `strategy.close` function to close the long and short positions when the respective exit conditions are met.
The script allows you to customize the parameters such as the length of Williams %R, the crossing threshold, take profit and stop loss levels, and the moving average period to suit your trading preferences.
Indikatoren und Strategien
The Z-score The Z-score, also known as the standard score, is a statistical measurement that describes a value's relationship to the mean of a group of values. It's measured in terms of standard deviations from the mean. If a Z-score is 0, it indicates that the data point's score is identical to the mean score. Z-scores may be positive or negative, with a positive value indicating the score is above the mean and a negative score indicating it is below the mean.
The concept of Z-score was introduced by statistician Carl Friedrich Gauss as part of his "method of the least squares," which was an important step in the development of the normal distribution and Z-score tables. It's a key concept in statistics and is used in various statistical tests.
In financial analysis, Z-scores are used to determine whether a data point is usual or unusual. You can think of it as a measure of how many standard deviations an element is from the mean. For instance, a Z-score of 1.0 would denote a value that is one standard deviation from the mean. Z-scores are also used to predict probabilities, with Z-scores having a distribution that is expected to be normal.
In trading, a Z-score is used to determine how often a trading system may produce a string of winners or losers. It can help a trader to understand whether the losses or profits they see are something that the system would most likely produce, or if it's a once in a blue moon situation. This helps traders make decisions about when to start or stop a system.
I just wanted to play a bit with the Z-score I guess.
Feel free to share your findings if you discover additional applications for this strategy or identify timeframes where it appears to perform more optimally.
How it works:
This strategy is based on a statistical concept called Z-score, which measures the number of standard deviations a data point is from the mean. In other words, it helps determine how unusual or usual a data point is.
In the context of this strategy, Z-score is applied to a 10-period EMA (Exponential Moving Average) of Heikin-Ashi candlestick close prices. The Z-score is calculated over a look-back period of 25 bars.
The EMA of the Z-score is then calculated over a 20-bar period, and the upper and lower thresholds (bounds for buy and sell signals) are defined using the 90th and 10th percentiles of this EMA score.
Long positions are taken when the Z-score crosses above the lower threshold or crosses above the mid-line (50th percentile). An additional long entry is made when the Z-score crosses above the highest value the EMA has been in the past 100 periods.
Short positions are initiated when the EMA crosses below the upper threshold, lower threshold or the highest value the EMA has been in the past 100 periods.
Positions are closed when opposing entry conditions are met, for example, a long position is closed when the short entry condition is true, and vice versa.
Set your desired start date for the strategy. This can be modified in the timestamp("YYYY MM DD") function at the top of the script.
D-BoT Alpha 'Short' SMA and RSI StrategyDostlar selamlar,
İşte son derece basit ama etkili ve hızlı, HTF de çok iyi sonuçlar veren bir strateji daha, hepinize bol kazançlar dilerim ...
Nedir, Nasıl Çalışır:
Strateji, iki ana girdiye dayanır: SMA ve RSI. SMA hesaplama aralığı 200 olarak, RSI ise 14 olarak ayarlanmıştır. Bu değerler, kullanıcı tercihlerine veya geriye dönük test sonuçlarına göre ayarlanabilir.
Strateji, iki koşul karşılandığında bir short sinyali oluşturur: RSI değeri, belirlenen bir giriş seviyesini (burada 51 olarak belirlenmiş) aşar ve kapanış fiyatı SMA değerinin altındadır.
Strateji, kısa pozisyonu üç durumda kapatır: Kapanış fiyatı, takip eden durdurma seviyesinden (pozisyon açıldığından beri en düşük kapanış olarak belirlenmiştir) büyükse, RSI değeri belirlenen bir durdurma seviyesini (bu durumda 54) aşarsa veya RSI değeri belirli bir kar al seviyesinin (bu durumda 32) altına düşerse.
Güçlü Yönleri:
İki farklı gösterge (SMA ve RSI) kullanımı, yalnızca birini kullanmaktan daha sağlam bir sinyal sağlayabilir.
Strateji, karları korumaya ve fiyat dalgalanmalarında kayıpları sınırlamaya yardımcı olabilecek bir iz süren durdurma seviyesi içerir.
Script oldukça anlaşılır ve değiştirmesi nispeten kolaydır.
Zayıf Yönleri:
Strateji, hacim, oynaklık veya daha geniş piyasa eğilimleri gibi diğer potansiyel önemli faktörleri göz önünde bulundurmaz.
RSI seviyeleri ve SMA süresi için belirli parametreler sabittir ve tüm piyasa koşulları veya zaman aralıkları için optimal olmayabilir.
Strateji oldukça basittir. Trade maliyetini (kayma veya komisyonlar gibi) hesaba katmaz, bu da trade performansını önemli ölçüde etkileyebilir.
Bu Stratejiyle Nasıl İşlem Yapılır:
Strateji, short işlemler için tasarlanmıştır. RSI, 51'in üzerine çıktığında ve kapanış fiyatı 200 periyotluk SMA'nın altında olduğunda işleme girer. RSI, 54'ün üzerine çıktığında veya 32'nin altına düştüğünde veya fiyat, pozisyon açıldığından beri en düşük kapanış fiyatının üzerine çıktığında işlemi kapatır.
Lütfen Dikkat, bu strateji veya herhangi bir strateji izole bir şekilde kullanılmamalıdır. Tüm bu çalışmalar eğitsel amaçlıdır. Yatırım tavsiyesi içermez.
This script defines a trading strategy based on Simple Moving Average (SMA) and the Relative Strength Index (RSI) indicators. Here's an overview of how it works, along with its strengths and weaknesses, and how to trade using this strategy:
How it works:
The strategy involves two key inputs: SMA and RSI. The SMA length is set to 200, and the RSI length is set to 14. These values can be adjusted based on user preferences or back-testing results.
The strategy generates a short signal when two conditions are met: The RSI value crosses over a defined entry level (set at 51 here), and the closing price is below the SMA value.
When a short signal is generated, the strategy opens a short position.
The strategy closes the short position under three conditions: If the close price is greater than the trailing stop (which is set as the lowest close since the position opened), if the RSI value exceeds a defined stop level (54 in this case), or if the RSI value drops below a certain take-profit level (32 in this case).
Strengths:
The use of two different indicators (SMA and RSI) can provide a more robust signal than using just one.
The strategy includes a trailing stop, which can help to protect profits and limit losses as the price fluctuates.
The script is straightforward and relatively easy to understand and modify.
Weaknesses:
The strategy doesn't consider other potentially important factors, such as volume, volatility, or broader market trends.
The specific parameters for the RSI levels and SMA length are hard-coded, and may not be optimal for all market conditions or timeframes.
The strategy is very simplistic. It doesn't take into account the cost of trading (like slippage or commissions), which can significantly impact trading performance.
How to trade with this strategy:
The strategy is designed for short trades. It enters a trade when the RSI crosses above 51 and the closing price is below the 200-period SMA. It will exit the trade when the RSI goes above 54 or falls below 32, or when the price rises above the lowest closing price since the position was opened.
Please note, this strategy or any strategy should not be used in isolation. It's important to consider other aspects of trading such as risk management, capital allocation, and combining different strategies to diversify. Back-testing the strategy on historical data and demo trading before going live is also a recommended practice.
D-Bot Alpha RSI Breakout StrategyHello dear Traders,
Here is a simple yet effective strategy to use, for best profit higher time frame, such as daily.
Structure of the code
The code defines inputs for SMA (simple moving average) length, RSI (relative strength index) length, RSI entry level, RSI stop loss level, and RSI take profit level. The default values of these variables can be customized as per the user's preferences.
The script calculates SMA and RSI based on the input parameters and the closing price of the asset.
Trading logic
This strategy allows the placement of a long position when:
The RSI crosses above the RSI entry level and
The close price is above the SMA value.
After entering a long position, it applies a trailing stop mechanism. The stop price is updated to the close price if the close price is lower than the last close price.
The script closes the long position when:
RSI falls below the stop loss level.
RSI reaches or exceeds the take profit level.
If the trailing stop is activated (once RSI reaches or exceeds the take profit level), the closing price falls below the trailing stop level.
Strengths
The strategy includes mechanisms for entering a position, taking profit, and stopping losses, which are fundamental aspects of a trading strategy.
It applies a trailing stop mechanism that allows to capture further gains if the price keeps increasing while protecting from losses if the price starts to decrease.
Weaknesses
This strategy only contemplates long positions. Depending on the market situation, the strategy may miss opportunities for short selling when the market is on a downward trend.
The choice of the fixed RSI entry, stop loss, and take profit levels may not be ideal for all market conditions or assets. It might benefit from a more adaptive mechanism that adjusts these levels according to market volatility or trend.
The strategy doesn't factor in trading costs (such as spread or commission), which could have a significant impact on the net profit, especially if the user is trading with a high frequency or in a low liquidity market.
How to trade with this strategy
Given these parameters and the strategy outlined by the code, the trader would enter a long position when the RSI crosses above the RSI entry level (default 34) and the closing price is above the SMA value (SMA calculated with default period of 200). The trader would exit the position when either the RSI falls below the RSI stop loss level (default 30), or RSI rises above the RSI take profit level (default 50), or when the trailing stop is hit.
Remember "The strategies I have prepared are entirely for educational purposes and should not be considered as investment advice. Support your trades using other tools. Wishing everyone profitable trades..."
Mechanical Trading StrategyThe "Mechanical Trading Strategy" is a simple and systematic approach to trading that aims to capture short-term price movements in the financial markets. This strategy focuses on executing trades based on specific conditions and predetermined profit targets and stop loss levels.
Key Features:
Profit Target: The strategy allows you to set a profit target as a percentage of the entry price. This target represents the desired level of profit for each trade.
Stop Loss: The strategy incorporates a stop loss level as a percentage of the entry price. This level represents the maximum acceptable loss for each trade, helping to manage risk.
Entry Condition: The strategy triggers trades at a specific time. In this case, the condition for entering a trade is based on the hour of the candle being 16 (4:00 PM). This time-based entry condition provides a systematic approach to executing trades.
Position Sizing: The strategy determines the position size based on a fixed percentage of the available equity. This approach ensures consistent risk management and allows for potential portfolio diversification.
Execution:
When the entry condition is met, signified by the hour being 16, the strategy initiates a long position using the strategy.entry function. It sets the exit conditions using the strategy.exit function, with a limit order for the take profit level and a stop order for the stop loss level.
Take Profit and Stop Loss:
The take profit level is calculated by adding a percentage of the entry price to the entry price itself. This represents the profit target for the trade. Conversely, the stop loss level is calculated by subtracting a percentage of the entry price from the entry price. This level represents the maximum acceptable loss for the trade.
By using this mechanical trading strategy, traders can establish a disciplined and systematic approach to their trading decisions. The predefined profit target and stop loss levels provide clear exit rules, helping to manage risk and potentially maximize returns. However, it is important to note that no trading strategy is guaranteed to be profitable, and careful analysis and monitoring of market conditions are always recommended.
RSI-CCI Fusion StrategyRSI-CCI Fusion Strategy: Harnessing the Power of RSI and CCI
The "RSI-CCI Fusion Strategy" is a powerful trading approach that combines the strengths of the Relative Strength Index (RSI) and the Commodity Channel Index (CCI) to provide enhanced trading insights. This strategy is based on the popular "RSI & CCI Fusion + Alerts" indicator, which utilizes the RSI and CCI indicators from TradingView .
1. Overview of RSI and CCI:
The Relative Strength Index (RSI) is a widely used momentum oscillator that measures the speed and change of price movements. It helps traders identify overbought and oversold conditions in the market. On the other hand, the Commodity Channel Index (CCI) is a versatile indicator that identifies cyclical trends and provides insights into overbought and oversold levels.
2. The RSI-CCI Fusion Strategy:
The RSI-CCI Fusion Strategy harnesses the combined power of the RSI and CCI indicators to generate robust trading signals. By blending the RSI and CCI, this strategy captures both momentum and cyclical trend dynamics, offering a more comprehensive view of the market.
3. Utilizing the RSI-CCI Fusion Indicator + Alerts:
The "RSI & CCI Fusion + Alerts" indicator serves as the backbone of the RSI-CCI Fusion Strategy. It integrates the RSI and CCI indicators from TradingView, providing traders with a clear and actionable trading signal.
4. How it Works:
- The indicator calculates the RSI and CCI values, standardizes them using z-score, and combines them with a weighted fusion approach.
- The resulting RSI-CCI Fusion indicator is plotted on the chart, accompanied by dynamic upper and lower bands, which help identify potential overbought and oversold conditions.
- Traders can customize alerts based on their preferred thresholds and timeframes, enabling them to receive timely notifications for potential buy and sell signals.
5. Implementing the RSI-CCI Fusion Strategy:
Traders following the RSI-CCI Fusion Strategy can utilize the buy and sell signals generated by the RSI-CCI Fusion indicator. When the indicator crosses below the upper band, it may signal a potential selling opportunity. Conversely, when it crosses above the lower band, it may indicate a potential buying opportunity. Traders can also consider additional factors and technical analysis tools to validate the signals before making trading decisions.
Conclusion: The RSI-CCI Fusion Strategy provides traders with a robust approach to analyze the market and make well-informed trading decisions. By incorporating the RSI and CCI indicators through the "RSI & CCI Fusion + Alerts" indicator, traders can take advantage of the combined strengths of these indicators. However, it is important to remember that no strategy guarantees success, and traders should always practice risk management and conduct thorough analysis before executing trades using this strategy.
Disclaimer: Trading involves risks, and it is important to conduct your own research and consult with a financial advisor before making any investment decisions.
Note: The RSI-CCI Fusion Strategy serves as a general guide, and individual traders may have different preferences and trading styles.
Ultimate Balance StrategyThe Ultimate Balance Oscillator Strategy harnesses the power of the Ultimate Balance Oscillator to deliver a comprehensive and disciplined approach to trading. By combining the insights of the Rate of Change (ROC), Relative Strength Index (RSI), Commodity Channel Index (CCI), Williams Percent Range, and Average Directional Index (ADX) from TradingView, this strategy offers traders a systematic way to navigate the markets with precision.
The core principle of this strategy lies in its ability to identify optimal entry and exit points based on the movement of the Ultimate Balance Oscillator. When the oscillator line crosses below the 0.75 level, a buy signal is generated, indicating a potential opportunity for a bullish trend reversal. Conversely, when the oscillator line crosses above the 0.25 level, it triggers an exit signal, suggesting a possible end to a bullish trend.
Key Features:
1. Objective Market Analysis: The Ultimate Balance Oscillator Strategy provides a disciplined and objective approach to market analysis. By relying on the quantified insights of multiple indicators, it helps traders cut through market noise and focus on key signals, improving decision-making and reducing emotional biases.
2. Enhanced Timing and Precision: This strategy's entry and exit signals are based on the specific thresholds of the Ultimate Balance Oscillator. By waiting for confirmation through the crossing of these levels, traders can potentially enter trades at opportune moments and exit with greater precision, maximizing profit potential and minimizing risk exposure.
3. Customizability and Adaptability: The strategy offers flexibility, allowing traders to customize the parameters to fit their preferred trading style and timeframes. Whether you're a short-term trader or a long-term investor, the Ultimate Balance Oscillator Strategy can be adjusted to suit your specific needs, making it adaptable to various market conditions.
4. Real-time Alerts: Stay informed and never miss a potential trade opportunity with the strategy's built-in alert system. Set personalized alerts for buy and exit signals to receive timely notifications, ensuring you're always aware of the latest developments in the market.
5. Backtesting and Optimization: Before applying the strategy to live trading, it's recommended to conduct thorough backtesting and optimization. By testing the strategy's performance over historical data and fine-tuning the parameters, you can gain insights into its strengths and weaknesses, enabling you to make informed adjustments and increase its effectiveness.
Trading involves risk. Use the Ultimate Balance Oscillator Strategy at your own discretion. Past performance is not indicative of future results.
DZ Strategy ICTThe script presented is a trading strategy called "Breaker Block Strategy with Price Channel". This strategy uses multiple time frames (1 minute, 5 minutes, 15 minutes, 1 hour, and 4 hours) to detect support and resistance areas on the chart.
The strategy uses parameters such as length, deviations, multiplier, Fibonacci level, move lag and volume threshold for each time frame. These parameters are adjustable by the user.
The script then calculates support and resistance levels using the simple moving average (SMA) and standard deviation (STDEV) of closing prices for each time frame.
It also detects "Breaker Blocks" based on price movement from support and resistance levels, as well as trade volume. A Breaker Block occurs when there is a significant breakout of a support or resistance level with high volume.
Buy and sell signals are generated based on the presence of a Breaker Block and price movement from support and resistance levels. When a buy signal is generated, a buy order is placed, and when a sell signal is generated, a sell order is placed.
The script also plots price channels for each time frame, representing resistance and support levels.
Profit limit levels are set for each time range, indicating that the price levels assigned to positions should be closed with a profit. Stop-loss levels are also set to limit losses in the event of canceled price movements.
In summary, this trading strategy uses a combination of Breaker Block detection, support and resistance levels, price channels and profit limit levels to generate buy and sell signals and manage positions on different time ranges.
Williams %R Strategy
The Williams %R Strategy is a trading approach that is based on the Williams Percent Range indicator, available on the TradingView platform.
This strategy aims to identify potential overbought and oversold conditions in the market, providing clear buy and sell signals for entry and exit.
The strategy utilizes the Williams %R indicator, which measures the momentum of the market by comparing the current close price with the highest high and lowest low over a specified period. When the Williams %R crosses above the oversold level, a buy signal is generated, indicating a potential upward price movement. Conversely, when the indicator crosses below the overbought level, a sell signal is generated, suggesting a possible downward price movement.
Position management is straightforward with this strategy. Upon receiving a buy signal, a long position is initiated, and the position is closed when a sell signal is generated. This strategy allows traders to capture potential price reversals and take advantage of short-term market movements.
To manage risk, it is recommended to adjust the position size based on the available capital. In this strategy, the position size is set to 10% of the initial capital, ensuring proper risk allocation and capital preservation.
It is important to note that the Williams %R Strategy should be used in conjunction with other technical analysis tools and risk management techniques. Backtesting and paper trading can help evaluate the strategy's performance and fine-tune the parameters before deploying it with real funds.
Remember, trading involves risks, and past performance is not indicative of future results. It is always advised to do thorough research, seek professional advice, and carefully consider your financial goals and risk tolerance before making any investment decisions.
9:22 5 MIN 15 MIN BANKNIFTY9:22 5 MIN 15 MIN BANKNIFTY Strategy with Additional Filters
The 9:22 5 MIN 15 MIN BANKNIFTY Strategy with Additional Filters is a trend-following strategy designed for trading the BANKNIFTY instrument on a 5-minute chart. It aims to capture potential price movements by generating buy and sell signals based on moving average crossovers, breakout confirmations, and additional filters.
Key Features:
Fast MA Length: 9
Slow MA Length: 22
ATR Length: 14
ATR Filter: 0.5
Trailing Stop Percentage: 1.5%
Pullback Threshold: 0.5
Minimum Candle Body Percentage: 0.5
Use Breakout Confirmation: Enabled
Additional Filters:
Volume Threshold: Set a minimum volume requirement for trades.
Trend Filter: Optionally enable a trend filter based on a higher timeframe moving average.
Momentum Filter: Optionally enable a momentum filter using the RSI indicator.
Support/Resistance Filter: Optionally enable a filter based on predefined support and resistance levels.
Buy and Sell Signals:
Buy Signal: A buy signal is generated when the fast moving average crosses above the slow moving average, with additional confirmation from breakout and volume criteria, along with optional trend, momentum, and support/resistance filters.
Sell Signal: A sell signal is generated when the fast moving average crosses below the slow moving average, with similar confirmation and filtering criteria as the buy signal.
Exit Strategy:
The strategy employs a trailing stop-loss mechanism based on a percentage of the average entry price. The stop-loss is dynamically adjusted to protect profits while allowing for potential upside.
Please note that this strategy should be thoroughly backtested and evaluated in different market conditions before applying it to live trading. It is also recommended to adjust the parameters and filters according to individual preferences and risk tolerance.
Feel free to customise and adapt the description as needed to suit your preferences and the specific details of your strategy.
HK Percentile Interpolation One
This script is designed to execute a trading strategy based on Heikin Ashi candlesticks, moving averages, and percentile levels.
Please note that you should keep your original chart in normal candlestick mode and not switch it to Heikin Ashi mode. The script itself calculates Heikin Ashi values from regular candlesticks. If your chart is already in Heikin Ashi mode, the script would be calculating Heikin Ashi values based on Heikin Ashi values, which would produce incorrect results.
The strategy begins trading from a start date that you can specify by modifying the `startDate` parameter. The format of the date is "YYYY MM DD". So, for example, to start the strategy from January 1, 2022, you would set `startDate = timestamp("2022 01 01")`.
The script uses Heikin Ashi candlesticks, which are plotted in the chart. This approach can be useful for spotting trends and reversals more easily than with regular candlestick charts. This is particularly useful when backtesting in TradingView's "Rewind" mode, as you can see how the Heikin Ashi candles behaved at each step of the strategy.
Buy and sell signals are generated based on two factors:
1. The crossing over or under of the Heikin Ashi close price and the 75th percentile price level.
2. The Heikin Ashi close price being above certain moving averages.
You have the flexibility to adjust several parameters in the script, including:
1. The stop loss and trailing stop percentages (`stopLossPercentage` and `trailStopPercentage`). These parameters allow the strategy to exit trades if the price moves against you by a certain percentage.
2. The lookback period (`lookback`) used to calculate percentile levels. This determines the range of past bars used in the percentile calculation.
3. The lengths of the two moving averages (`yellowLine_length` and `purplLine_length`). These determine how sensitive the moving averages are to recent price changes.
4. The minimum holding period (`holdPeriod`). This sets the minimum number of bars that a trade must be kept open before it can be closed.
Please adjust these parameters according to your trading preferences and risk tolerance. Happy trading!
Moving Average Crossover Strategymoving average crossover startegy 10*30
it indicates when to buy or sell
BB and KC StrategyThis script is designed as a TradingView strategy that uses Bollinger Bands (BB) and Keltner Channels (KC) as the primary indicators for generating trade signals. It aims to catch potential market trends by comparing the movements of these two popular volatility measures.
Key aspects of this strategy:
1. **Bollinger Bands and Keltner Channels:** Both are volatility-based indicators. The Bollinger Bands consist of a middle band (simple moving average) and two outer bands calculated based on standard deviation, which adjusts itself to market conditions. Keltner Channels are a set of bands placed above and below an exponential moving average of the price. The distance between the bands is calculated based on the Average True Range (ATR), a measure of price volatility.
2. **Entry Signals:** The strategy enters a long position when the upper KC line crosses above the upper BB line and the volume is above its moving average. Conversely, it enters a short position when the lower KC line crosses below the lower BB line and the volume is above its moving average.
3. **Exit Signals:** The strategy exits a position under two conditions. First, if the trade has been open for a certain number of bars defined by the user (default 20 bars). Second, a stop loss and trailing stop are in place to limit potential losses and lock in profits as the price moves favorably. The stop loss is set at a percentage of the entry price (default 1.5% for long and -1.5% for short), and the trailing stop is also a percentage of the entry price (default 2%).
4. **Trade Quantity:** The script allows specifying the investment amount for each trade, set to a default of 1000 currency units.
Remember, this is a strategy script, which means it is used for backtesting and not for real-time signals or live trading. It is also recommended that it is used as a tool to aid your trading, not as a standalone system. As with any strategy, it should be tested over different market conditions and used in conjunction with other aspects of technical and fundamental analysis to ensure robustness and effectiveness.
Equity Curve Trading with EMAWhat Is Equity Curve Trading?
In equity curve trading, traders apply a moving average to the curve. The idea is when the equity curve drops below the moving average, the strategy is put on hold. This is done to stop losses when either the hopes of the plan working start dimming or when the trader knows he cannot afford more losses on a strategy. The trader can resume trading this particular strategy when the equity curve is above the moving average.
Equity Curve Trading puts an investor at the ease of knowing that his investment is covered even when he is not actively tracking his strategy. When the equity curve dips below a level investor is comfortable with, it can be paused until such time that the equity curve is back above the determined moving average.
Example:
Equity Curve Trading Example
Trading Strategy
I choosed the SuperTrend strategy for BTCUSDT on 4 hour time frame. That shows nice equity curve with default settings. Let's find out and check can we improve the equity curve with this modern money management trade method?
Some shift is exist in original equity curve relatively to filtered equity curve, because of array usage, but it is not affected on calculations.
Conclusion
I tested a different time frames, settings and equity curves shapes, but it not gives advantages in equity curve. You can look at the table on the top right corner of the strategy with equity curve and you will see some statistic information for the original strategy and for the modified equity curve trade strategy. In most cases we have lower Win Rate and lower Net Profit after turning on Equity curve trading method. In some cases this can be help if you have the equity curve looks like at the picture above, but this equity curve is really bad for choosing this strategy to trade. I found that EMA works better than SMA, and RMA works better then EMA applied to Equity Curve. You can test your strategy with this trade method if you want, I make the source code opened for it. Please share your results, I hope it will helps.
Conclusion 2
Equity Curve Trading definitely has its proponents in the industry, some of them quite vocal. But, the overall efficacy of the approach is certainly not crystal clear. In fact, what is clear is that it is relatively easy to take a good strategy, and significantly degrade its performance by employing equity curve trading. While the overall objective of equity curve trading is unquestionable – cease trading poor performing strategies - it is probable that there are better ways of accomplishing that goal. From this study, the conclusion is equity curve trading with simple indicators has more downside than upside.
Master Supertrend Strategy [Trendoscope]Here is the strategy version of the indicator - Master Supertrend
Options and variations are same throughout.
🎲 Variations
Following variations are provided in the form of settings.
🎯 Range Type
Instead of ATR, different types of ranges can be used for stop calculation. Here is the complete list used in the script.
Plus/Minus Range* - Calculates plus range and minus range for each candle and uses them for different sides of stop calculation
Ladder ATR - Based on the existing concept of Ladder ATR defined in Supertrend-Ladder-ATR
True Range - True range derived from standard function ta.tr
Standard Deviation - Standard deviation of close prices
🎯 Applied Calculation
In standard ATR, rma of TR is used for calculations. But, the application calculation provides option to users to use different mechanisms. It can be a type of moving average or few other types of calculations.
Available values are
sma
ema
hma
rma
wma
high
median
🎯 Other options
Few other options provided are
Use Close Price - If selected stops are calculated based on the close price instead of high/low prices
Wait for Close If selected, change of supertrend direction is calculated based on close price instead of high/low prices
Diminishing Stop Distance - When selected, stop distance for the trend direction can only reduce and cannot increase. This option is useful for keeping the tight stops on strong trends.
🎯 Plus Minus Range*
One of the range type used is Plus/Minus Range. What it means and how are these ranges calculated? Let's have a look.
Plus Range is an upward movement of a candle from its last price or open price whichever is lower.
Minus Range is a downward movement of a candle from its last price or open price whichever is higher.
This divides True Range into two separate range for positive and negative side.
Note : Effectiveness on daily charts are quire visible. However, if you want to use it for lower timeframes, please play around with settings before settling on suitable configuration.
Monthly Strategy Performance TableWhat Is This?
This script code adds a Monthly Strategy Performance Table to your Pine Script strategy scripts so you can see a month-by-month and year-by-year breakdown of your P&L as a percentage of your account balance.
The table is based on realized equity rather than open equity, so it only updates the metrics when a trade is closed.
That's why some numbers will not match the Strategy Tester metrics (such as max drawdown), as the Strategy Tester bases metrics like max drawdown on open trade equity and not realized equity (closed trades).
The script is still a work-in-progress, so make sure to read the disclaimer below. But I think it's ready to release the code for others to play around with.
How To Use It
The script code includes one of my strategies as an example strategy. You need to replace my strategy code with your own. To do that just copy the source code below into a blank script, delete lines 11 -> 60 and paste your strategy code in there instead of mine. The script should work with most systems, but make sure to read the disclaimer below.
It works best with a significant amount of historical data, so it may not work very effectively on intraday timeframes as there is a severe limitation of available bars on TradingView. I recommend using it on 4HR timeframes and above, as anything less will produce very little usable data. Having a premium TradingView plan will also help boost the number of available bars.
You can hover your mouse over a table cell to get more information in the form of tooltips (such as the Long and Short win rate if you hover over your total return cell).
Credit
The code in this script is based on open-source code originally written by QuantNomad, I've made significant changes and additions to the original script but all credit for the idea and especially the display table code goes to them - I just built on top of it:
Why Did I Make This?
None of this is trading or investment advice, just my personal opinion based on my experience as a trader and systems developer these past 6+ years:
The TradingView Strategy Tester is severely limited in some important ways. And unless you use complex Excel formulas on exported test data, you can't see a granular perspective of your system's historical performance.
There is much more to creating profitable and tradeable systems than developing a strategy with a good win rate and a good return with a reasonable drawdown.
Some additional questions we need to ask ourselves are:
What did the system's worst drawdown look like?
How long did it last?
How often do drawdowns occur, and how quickly are they typically recovered?
How often do we have a break-even or losing month or year?
What is our expected compounded annual growth rate, and how does that growth rate compare to our max drawdown?
And many more questions that are too long to list and take a lifetime of trading experience to answer.
Without answering these kinds of questions, we run the risk of developing systems that look good on paper, but when it comes to live trading, we are uncomfortable or incapable of enduring the system's granular characteristics.
This Monthly Performance Table script code is intended to help bridge some of that gap with the Strategy Tester's limited default performance data.
Disclaimer
I've done my best to ensure the numbers this code outputs are accurate, and according to my testing with my personal strategy scripts it appears to work fine. But there is always a good chance I've missed something, or that this code will not work with your particular system.
The majority of my TradingView systems are extremely simple single-target systems that operate on a closed-candle basis to minimize many of the data reliability issues with the Strategy Tester, so I was unable to do much testing with multiple targets and pyramiding etc.
I've included a Debug option in the script that will display important data and information on a label each time a trade is closed. I recommend using the Debug option to confirm that the numbers you see in the table are accurate and match what your strategy is actually doing.
Always do your own due diligence, verify all claims as best you can, and never take anyone's word for anything.
Take care, and best of luck with your trading :)
Kind regards,
Matt.
PS. If you're interested in learning how this script works, I have a free hour-long video lesson breaking down the source code - just check out the links below this script or in my profile.
Hobbiecode - RSI + Close previous dayThis is a simple strategy that is working well on SPY but also well performing on Mini Futures SP500. The strategy is composed by the followin rules:
1. If RSI(2) is less than 15, then enter at the close.
2. Exit on close if today’s close is higher than yesterday’s high.
If you backtest it on Mini Futures SP500 you will be able to track data from 1993. It is important to select D1 as timeframe.
Please share any comment or idea below.
Have a good trading,
Ramón.
Hobbiecode - Five Day Low RSI StrategyThis is a simple strategy that is working well on SPY but also well performing on Mini Futures SP500. The strategy is composed by the followin rules:
1. If today’s close is below yesterday’s five-day low, go long at the close.
2. Sell at the close when the two-day RSI closes above 50.
3. There is a time stop of five days if the sell criterium is not triggered.
If you backtest it on Mini Futures SP500 you will be able to track data from 1993. It is important to select D1 as timeframe.
Please share any comment or idea below.
Have a good trading,
Ramón.
Hobbiecode - SP500 IBS + HigherThis is a simple strategy that is working well on SPY but also well performing on Mini Futures SP500. The strategy is composed by the followin rules:
1. Today is Monday.
2. The close must be lower than the close on Friday.
3. The IBS must be below 0.5.
4. If 1-3 are true, then enter at the close.
5. Sell 5 trading days later (at the close).
If you backtest it on Mini Futures SP500 you will be able to track data from 1993. It is important to select D1 as timeframe.
Please share any comment or idea below.
Have a good trading,
Ramón.
VWAP Trendfollow Strategy [wbburgin]This is an experimental strategy that enters long when the instrument crosses over the upper standard deviation band of a VWAP and enters short when the instrument crosses below the bottom standard deviation band of the VWAP. I have added a trend filter as well, which stops entries that are opposite to the current trend of the VWAP. The trend filter will reduce total false breakouts, thus improving the % profitable while maintaining the overall returns of the strategy. Because this is a trend-following breakout strategy, the % profitable will typically be low but the average % return will be higher. As a rule, be sure to look at the average winning trade % compared to the average losing trade %, and compare that to the % profitable to judge the effectiveness of a strategy. Factor in fees and slippage as well.
This strategy appears to work better with the lower timeframes, and I was impressed with its results. It also appears to work on a wide range of asset classes. There isn't a stop loss or take profit built-in (other than the reversal signals, which close the current trade), so I would encourage you to expand on the strategy based on your own trading parameters.
You can toggle off the bar colors and the trend filter if you so desire.
Future updates to this script (or ideas of improving on it) might include a take profit level set at one standard deviation past the current level and a stop loss level set at one standard deviation closer to the vwap from the current level - or applying a multiple to the two based off of your reward/risk ratio.
About the strategy results below: this is with commissions of 0.5 % per trade.
Range BreakerStrategy Description: Range Breaker
The Range Breaker strategy is a breakout trading strategy that aims to capture profits when the price of a financial instrument moves out of a defined range. The strategy identifies swing highs and swing lows over a specified lookback period and enters long or short positions when the price breaks above the swing high or below the swing low, respectively. It also employs stop targets based on a percentage to manage risk and protect profits.
Beginner's Guide:
Understand the concepts:
a. Swing High: A swing high is a local peak in price where the price is higher than the surrounding prices.
b. Swing Low: A swing low is a local trough in price where the price is lower than the surrounding prices.
c. Lookback Period: The number of bars or periods the strategy analyzes to determine swing highs and swing lows.
d. Stop Target: A predetermined price level at which the strategy will exit the position to manage risk and protect profits.
Configure the strategy:
a. Set the initial capital, order size, commission, and pyramiding as needed for your specific trading account.
b. Choose the desired lookback period to identify the swing highs and lows.
c. Set the stop target multiplier and stop target percentage as desired to manage risk and protect profits.
Backtest the strategy:
a. Set the backtest start date to analyze the strategy's historical performance.
b. Observe the backtesting results to evaluate the strategy's effectiveness and adjust the parameters if necessary.
Implement the strategy:
a. Apply the strategy to your preferred financial instrument on the TradingView platform.
b. Monitor the strategy's performance and adjust the parameters as needed to optimize its effectiveness.
Risk management:
a. Always use a stop target to protect your trading capital and manage risk.
b. Don't risk more than a small percentage of your trading capital on a single trade.
c. Be prepared to adjust the strategy or stop trading it if the market conditions change significantly.
Adjusting the Lookback Period and Timeframes for Optimal Strategy Performance
The Range Breaker strategy uses a lookback period to identify swing highs and lows, which serve as the basis for determining entry and exit points for long and short positions. By adjusting the lookback period and analyzing different timeframes, you can potentially find the best strategy configuration for each specific asset.
Adjusting the lookback period:
The lookback period is a critical parameter that affects the sensitivity of the strategy to price movements. A shorter lookback period will make the strategy more sensitive to smaller price fluctuations, resulting in more frequent trading signals. On the other hand, a longer lookback period will make the strategy less sensitive, generating fewer signals but potentially capturing larger price movements.
To optimize the lookback period for a specific asset, you can test different lookback values and compare their performance in terms of risk-adjusted returns, win rate, and other relevant metrics. Keep in mind that using an overly short lookback period may lead to overtrading and increased transaction costs, while an overly long lookback period may cause the strategy to miss profitable trading opportunities.
Analyzing different timeframes:
Timeframes refer to the duration of each bar or candlestick on the chart. Shorter timeframes (e.g., 5-minute, 15-minute, or 30-minute) focus on intraday price movements, while longer timeframes (e.g., daily, weekly, or monthly) capture longer-term trends. The choice of timeframe affects the number of trading signals generated by the strategy and the length of time each position is held.
To find the best strategy for each asset, you can test the Range Breaker strategy on different timeframes and analyze its performance. Keep in mind that shorter timeframes may require more active monitoring and management due to the increased frequency of trading signals. Longer timeframes, on the other hand, may require more patience as positions are held for extended periods.
Finding the best strategy for each asset:
Every asset has unique price characteristics that may affect the performance of a trading strategy. To find the best strategy for each asset, you should:
a. Test various lookback periods and timeframes, observing the strategy's performance in terms of profitability, risk-adjusted returns, and win rate.
b. Consider the asset's historical price behavior, such as its volatility, liquidity, and trend-following or mean-reverting tendencies.
c. Evaluate the strategy's performance during different market conditions, such as bullish, bearish, or sideways markets, to ensure its robustness.
d. Keep in mind that each asset may require a unique set of strategy parameters for optimal performance, and there may be no one-size-fits-all solution.
By experimenting with different lookback periods and timeframes, you can fine-tune the Range Breaker strategy for each specific asset, potentially improving its overall performance and adaptability to changing market conditions. Always practice proper risk management and be prepared to make adjustments as needed.
Remember that trading strategies carry inherent risk, and past performance is not indicative of future results. Always practice proper risk management and consider your own risk tolerance before trading with real money.
Wyckoff Range StrategyThe Wyckoff Range Strategy is a trading strategy that aims to identify potential accumulation and distribution phases in the market using the principles of Wyckoff analysis. It also incorporates the detection of spring and upthrust patterns.
Here's a step-by-step explanation of how to use this strategy:
Understanding Accumulation and Distribution Phases:
Accumulation Phase: This is a period where smart money (large institutional traders) accumulates a particular asset at lower prices. It is characterized by a sideways or consolidating price action.
Distribution Phase: This is a period where smart money distributes or sells a particular asset at higher prices. It is also characterized by a sideways or consolidating price action.
Input Variables:
crossOverLength: This variable determines the length of the moving average crossover used to identify accumulation and distribution phases. You can adjust this value based on the market you are trading and the time frame you are analyzing.
stopPercentage: This variable determines the percentage used to calculate the stop loss level. It helps you define a predefined level at which you would exit a trade if the price moves against your position.
Strategy Conditions:
Enter Long: The strategy looks for a crossover of the close price above the SMA of the close price with a length of crossOverLength and a crossover of the low price above the SMA of the low price with a length of 20. This combination suggests the start of an accumulation phase and a potential buying opportunity.
Exit Long: The strategy looks for a crossunder of the close price below the SMA of the close price with a length of crossOverLength or a crossunder of the high price below the SMA of the high price with a length of 20. This combination suggests the end of an accumulation phase and a potential exit signal for long positions.
Enter Short: The strategy looks for a crossunder of the close price below the SMA of the close price with a length of crossOverLength and a crossunder of the high price below the SMA of the high price with a length of 20. This combination suggests the start of a distribution phase and a potential selling opportunity.
Exit Short: The strategy looks for a crossover of the close price above the SMA of the close price with a length of crossOverLength or a crossover of the low price above the SMA of the low price with a length of 20. This combination suggests the end of a distribution phase and a potential exit signal for short positions.
Stop Loss:
The strategy sets a stop loss level for both long and short positions. The stop loss level is calculated based on the stopPercentage variable, which represents the percentage of the current close price. If the price reaches the stop loss level, the strategy will automatically exit the position.
Plotting Wyckoff Schematics:
The strategy plots different shapes on the chart to indicate the identified phases and patterns. Green and red labels indicate the accumulation and distribution phases, respectively. Blue triangles indicate spring patterns, and orange triangles indicate upthrust patterns.
To use this strategy, you can follow these steps:
Jim Forte — Anatomy of a Trading Range
robertbrain.com/Bull...+a+Trading+Range.pdf
Initial Balance Panel Strategy for BitcoinInitial Balance Strategy
Initial Balance Strategy uses a source code of "Initial Balance Monitoring Panel" that build from "Initial Balance Markets Time Zones - Overall Highest and Lowest".
Initial Balance is based on the highest and lowest price action within the first 60 minutes of trading. Reading online this can depict which way the market can trend for the session. More information about Initial Balance Panel you can read at the end of the article.
Strategy idea
The main idea is to catch the trend move when most of the 16 Crypto pairs break the Low or High levels together. I found good results when 15 of 16 pairs is break that levels and after we manage the trade within some trail stop indicator, I choose Volatility Stop for this strategy.
Additional Strategy idea
The second one idea that was not made is to catch the pullback after fully green/red zones in Initial Balance Panel become white. That mean the main trend can be finished and we can try to catch good pullback in opposite direction.
Binance Crypto pairs
The strategy use the 16 default Crypto currencies pairs from the Binance. As additional variations of the strategy can be changing the currencies pairs and their number.
List of default pairs:
BINANCE:BTCUSDT, BINANCE:ETHUSDT, BINANCE:EOSUSDT, BINANCE:LTCUSDT, BINANCE:XRPUSDT, BINANCE:DASHUSDT, BINANCE:IOTAUSDT, BINANCE:NEOUSDT, BINANCE:QTUMUSDT, BINANCE:XMRUSDT, BINANCE:ZECUSDT, BINANCE:ETCUSDT, BINANCE:ADAUSDT, BINANCE:XTZUSDT, BINANCE:LINKUSDT, BINANCE:DOTUSDT
Summary
The strategy works very well for a buy trades with settings 15 crypto pairs of 16 that follow the trend with breaking the long initial balance level.
Initial Balance Monitoring Panel
Allows you to have an instant view of 16 Crypto pairs within a monitoring panel, monitoring Initial Balance (Asia, London, New York Stock Exchanges).
The code can easily be changed to suit the crypto pairs you are trading.
The setup of my chart would also include this indicator and the "Initial Balance Markets Time Zones - Overall Highest and Lowest" (with all IBs enabled) as shown above.
Initial Balance is based on the highest and lowest price action within the first 60 minutes of trading. Reading online this can depict which way the market can trend for the session.
The indicator has been coded for Crypto (so other symbols may not work as expected).
Though Initial Balance is based off the first 60 minutes of the trading markets opening, but Crypto is 24/7, this indicator looks at how Asia, London and New York Stock Exchanges opening trading can affect Crypto price action.
Source: Initial Balance Monitoring Panel
