On Balance Volume Heikin-Ashi Transformed
The OBV Heikin Ashi indicator is a modified version of the On-Balance Volume indicator that incorporates the Heikin Ashi transformation. This technical tool aims to provide traders with a smoother representation of volume dynamics and price trends.
The OBV Heikin Ashi indicator combines the principles of OBV and Heikin Ashi to offer insights into the volume and price behavior of an asset. Understanding OBV and Heikin Ashi individually will provide a foundation for comprehending the uniqueness and utility of this indicator.
On-Balance Volume:
OBV is a volume-based indicator that measures the cumulative buying and selling pressure in the market. It considers the relationship between volume and price movements to determine the overall strength and direction of a trend. Rising OBV values suggest bullish buying pressure, while falling values indicate bearish selling pressure.
Heikin Ashi:
Heikin Ashi is a Japanese candlestick charting technique that aims to filter out noise and provide a smoother representation of price trends. It calculates each candlestick based on the average of the previous candle's open, close, high, and low prices. Heikin Ashi candles can reveal the underlying trend more clearly by reducing market noise.
Methodology:
The 𝘖𝘉𝘝 𝘏-𝘈 indicator applies the Heikin Ashi transformation to the OBV values. Each OBV value is replaced with a Heikin Ashi equivalent, which is calculated based on the average of the previous Heikin Ashi candle's open and close prices. This transformation smooths out the OBV values and helps identify the overall trend with reduced noise. Additionaly, 2 optional EMAs are included for convergence-divergence analysis.
By applying the Heikin Ashi transformation to OBV, the indicator aims to enhance the readability of volume and trend information, providing traders with a clearer understanding of market dynamics.
Utility:
The 𝘖𝘉𝘝 𝘏-𝘈 indicator can be a valuable tool for traders and investors in analyzing volume and price trends. It offers a smoother representation of OBV values, allowing for easier identification of trend reversals, bullish or bearish market conditions, and potential trading opportunities. Traders can utilize the indicator to confirm price trends, validate support and resistance levels, and enhance their overall trading strategies.
It is worth noting that the effectiveness of the indicator may vary depending on the specific market and trading strategy. It is recommended to combine its analysis with other technical indicators and perform thorough backtesting before making trading decisions.
Key Features:
2 Adjustable EMAs
Normalized Oscillator Mode
Example Charts:
See Also:
Z-Score Heikin-Ashi Transformed
"backtesting"に関するスクリプトを検索
Z-Score Heikin-Ashi TransformedThe Z-Score Heikin-Ashi Transformed (𝘡 𝘏-𝘈) indicator is a powerful technical tool that combines the principles of Z-Score and Heikin Ashi to provide traders with a smoothed representation of price movements and a standardized measure of market volatility.
The 𝘡 𝘏-𝘈 indicator applies the Z-Score calculation to price data and then transforms the resulting Z-Scores using the Heikin Ashi technique. Understanding the individual components of Z-Score and Heikin Ashi will provide a foundation for comprehending the methodology and unique features of this indicator.
Z-Score:
Z-Score is a statistical measure that quantifies the distance between a data point and the mean, relative to the standard deviation. It provides a standardized value that allows traders to compare different data points on a common scale. In the context of the 𝘡 𝘏-𝘈 indicator, Z-Score is calculated based on price data, enabling the identification of extreme price movements and the assessment of their significance.
Heikin Ashi:
Heikin Ashi is a popular charting technique that aims to filter out market noise and provide a smoother representation of price trends. It involves calculating each candlestick based on the average of the previous candle's open, close, high, and low prices. This approach results in a chart that reduces the impact of short-term price fluctuations and reveals the underlying trend more clearly.
Methodology:
The 𝘡 𝘏-𝘈 indicator starts by calculating the Z-Score of the price data, which provides a standardized measure of how far each price point deviates from the mean. Next, the resulting Z-Scores are transformed using the Heikin Ashi technique. Each Z-Score value is modified according to the Heikin Ashi formula, which incorporates the average of the previous Heikin Ashi candle's open and close prices. This transformation smooths out the Z-Score values and reduces the impact of short-term price fluctuations, providing a clearer view of market trends.
This tool enables traders to identify significant price movements and assess their relative strength compared to historical data. Positive transformed Z-Scores indicate that prices are above the average, suggesting potential overbought conditions, while negative transformed Z-Scores indicate prices below the average, suggesting potential oversold conditions. Traders can utilize this information to identify potential reversals, confirm trend strength, and generate trading signals.
Utility:
The indicator offers valuable insights into price volatility and trend analysis. By combining the standardized measure of Z-Score with the smoothing effect of Heikin Ashi, traders can make more informed trading decisions and improve their understanding of market dynamics. 𝘡 𝘏-𝘈 can be used in various trading strategies, including identifying overbought or oversold conditions, confirming trend reversals, and establishing entry and exit points.
Note that the 𝘡 𝘏-𝘈 should be used in conjunction with other technical indicators and analysis tools to validate signals and avoid false positives. Additionally, traders are encouraged to conduct thorough backtesting and experimentation with different parameter settings to optimize the effectiveness of the indicator for their specific trading approach.
Key Features:
Optional Reversion Doritos
Adjustable Reversion Threshold
2 Adjustable EMAs
Example Charts:
See Also:
On Balance Volume Heikin-Ashi Transformed
ICT Sessions_One Setup for Life [MK]The script plots the High/Low of the following trading sessions:
London - 02:00-05:00
NY AM - 09:30-12:00
New York Lunch - 12:00-13:30
New York PM - 13:30-16:00
Due to the high level of liquidity (resting orders), highs and lows of these sessions may be used as buy/sell areas and also as profit target areas. Typically, buy orders would be initiated below a session low and sell orders would be initiated above a
session high.
The script also plots 'RTH (Regular Trading Hours) Opening Gaps'. The RTH gaps are drawn from the closing price of regular trading at 16:15 (EST) to the open price of regular trading at 09:30 (EST). Gaps can be areas that traders might anticipate to be filled at some time in the future. A gap 'midline' is available if needed and yesterday RTH close line can be shown and extended to the current bar.
This script is simply a means to draw boxes around certain areas/periods on the charts. It is in no way a trading strategy and users should spend much time to study the concept and should also perform extensive back-testing before taking any trades.
By setting the lookback value to a much higher value then the default of 6, users can utilise the script to perform their own backtesting studies.
The above chart shows the default setup of the indicator. Note that the user has to choose how far (in days) to lookback and draw the sessions/gaps.
It is also possible to show the session high//low lines and extend them to the current bar time. If this is used it is advised to keep the lookback period as low as possible to ensure charts stay clean/uncluttered.
All boxes/lines styles/colors are fully customisable.
Engulfing Pattern BUY and SELL SystemThis indicator is based on multiple parameters such as the Open, High, Low, and Close of candles. We add confluences such as SMMA crossovers, engulfing candles, and the number of pips that it has moved from it.
The main parameter is the DFS (Distance from SMMA). This will adjust the number of signals you'll get. This parameter is calculated based on the Open price of the signal bar and the 50 SMMA price. If the difference between these two values is greater than the input value, it will not be considered a signal.
The buy/sell signal consists of the following conditions:
1. Engulfing Candle based on conditions
2. SMMA crossover (21 and 50 periods)
3. For BUYS, the RSI value is greater than 49. For SELLS, the RSI value is less than 51.
4. Open price of the signal bar is less/greater than the 50 SMMA for SELLS/BUYS respectively.
5. DFS value is less than or equal to the input value
We recommend backtesting this on FX Pairs, and metals such as Gold. It is not well suited for Crypto or Indices.
itradesize /\ Overnight Session & Silver BulletOvernight Session & Silver Bullet indicator
The indicator can be divided into two separate stuff:
ONS ( Overnight Session ) based on TCM’s ( TheCurrencyMerchant ) theory and Silver Bullet based on what ICT ( InnerCircleTrader ) is teaching to us.
Overnight Session
• ONS will be always based on Chicago 4am to 8am time according to TCM’s CME teaching.
The indicator has the option to show TSO ( Today’s session only ) which is good to have the chart not messed up by it. At this time when it comes to backtesting just turn this off to have the past ONS and SB ranges showed up on your chart.
• Mid line at the ONS range is useful to have as you are able to decide wether price is in a premium or a discount under the ONS.
If Im a buyer target is above the range, if Im a seller target is below the range.
• You are also able to have SD ( Standard Deviation ) lines for price projections. In the variety of TCM’s videos you are able to have a deeper knowledge.
• You can also extend Today’s ONS lines to the very end of the chart which could make an easier looking on the levels you eyeing with.
Silver Bullet
It’s based on New York time as ICT ( Inner Circle Trader ) is always teaching to us that we should use New York time, every time when it comes to his concepts.
Silver Bullets are always be there aiming of an opposing liquidity pool. They are working even on choppy days.
Silver Bullet hours:
• 03:00 - 04:00am NY Time
• 10:00 - 11:00am NY Time
• 02:00 - 03:00pm NY Time
SB highlighted areas could be shown as a box or a range according to your taste, with or without Start/End lines.
Both of them ca be used to form trades.
You should dig yourself into Silver Bullet ( InnerCircleTrader ) and Overnight Session ( TheCurrencyMerchant ) teachings before the use of the indicator.
Simple setups
• Silver Bullet
Look 20-30 minutes before any SB where the Buy or Sell program has started.
Where the first 1m FVG ( Fair Value Gap ) appears under the range, enter the trade.
Expect only a 5 handle move as a beginner.
1m chart is a must for these kind of FVG entries. ( 30s , 15s can also be used )
• ONS
Price is trading aggressively out of the range to take liquidity.
Once price grabbed liquidity that candle on the 3-5m could considered as on order block for the further movement.
If you are trading in the range, then the opposite side can be the target, if its out of the range and trading one sided, then use standard deviations as 0.5 is a minimum target.
Trailing Stop with RSI - Momentum-Based StrategyTrailing Stop with RSI - Momentum-Based Strategy
Description:
The Trailing Stop with RSI strategy combines momentum analysis and trailing stop functionality to help traders identify potential entry and exit points in their trading decisions. This strategy is suitable for various markets and timeframes.
Key Features:
Momentum Analysis: The strategy incorporates momentum indicators to identify potential buying and selling opportunities based on momentum shifts in the price.
Trailing Stop Functionality: The strategy utilizes a trailing stop to protect profits and dynamically adjust the stop loss level as the trade moves in the desired direction.
RSI Confirmation: The Relative Strength Index (RSI) is included to provide additional confirmation for trade entries by considering overbought and oversold conditions.
How to Use:
Entry Conditions: Long positions are triggered when positive momentum is detected, and the RSI confirms an oversold condition. Short positions are triggered when negative momentum is detected, and the RSI confirms an overbought condition.
Trailing Stop Activation: Once a position is opened, the trailing stop is activated when the specified profit level (as a percentage) is reached.
Trailing Stop Level: The trailing stop maintains a stop loss level at a specified distance (as a percentage) from the highest profit achieved since opening the position.
Exit Conditions: The trailing stop will trigger an exit and close all positions when the trailing stop level is breached.
Markets and Conditions:
This strategy can be applied to various markets, including stocks, forex, cryptocurrencies, and commodities. It can be used in trending and ranging market conditions, making it versatile for different market environments.
Important Considerations:
Adjust Parameters: Traders can modify the length of the momentum and RSI indicators to suit their preferred timeframe and trading style.
Risk Management: It is recommended to consider appropriate position sizing, risk-to-reward ratios, and overall risk management practices when using this strategy.
Backtesting and Optimization: Traders are encouraged to backtest the strategy on historical data and optimize the parameters to find the best settings for their chosen market and timeframe.
By incorporating momentum analysis, trailing stop functionality, and RSI confirmation, this strategy aims to provide traders with a systematic approach to capturing profitable trades while managing risk effectively.
Divergence RSI V2This indicator is based on the concept of divergence. I recommend that you find out and study about this yourself as the concept of divergence will not be explained in depth in this description.
This indicator will show divergences between the asset price and the RSI oscillator. The indicator will look for divergent points between the rising highs and falling lows of the asset; and the rising lows and falling highs of the RSI.
The trend of the asset tends to follow the behavior of the oscillator when a divergence occurs. So if we find a divergence between the two, the price of the asset is likely to follow the trend of the oscillator.
This indicator looks for these types of divergences and will show (based on the RSI) if there is a bullish or bearish divergence.
If it is bullish, it will show a line joining those points in green and if it is bearish in red. In addition, it will show a label where you can see the number of occurrences that have been found from a certain point to another.
Note: this indicator can be complemented with the “Divergence V2” indicator which is also found in my library.
Settings
Backtesting Bars : is the number of bars back that the indicator will check. No more than 1000 is recommended as this will slow down the search.
Tolerance: number of times a divergent line can cross a bar. If you place 0, no bar can be crossed by a diverging line.
Min Bars To detect: will only search for divergences (or lines) that have the minimum number of bars selected in this option. Default option is 30.
Min Bars To detect: it will only search for divergences (or lines) that have the maximum number of bars selected in this option. Default option is 100.
Source Highs: The high points will be based on the close of each bar. You can use as another alternative.
Source Lows: The low points will be based on the close of each bar. You can use as another alternative.
Use squeeze parameter: only look for divergences (bullish or bearish) at times when such an indicator is in favor of the trend or coincides with the corresponding RSI divergence.
Divergence V2This indicator is based on the concept of divergence. I recommend that you find out and study about this yourself as the concept of divergence will not be explained in depth in this description.
This indicator will show divergences between the asset price and the RSI oscillator. The indicator will look for divergent points between the rising highs and falling lows of the asset; and the rising lows and falling highs of the RSI.
The trend of the asset tends to follow the behavior of the oscillator when a divergence occurs. So if we find a divergence between the two, the price of the asset is likely to follow the trend of the oscillator.
This indicator looks for these types of divergences and will show (based on the RSI) if there is a bullish or bearish divergence.
If it is bullish, it will show a line joining those points in green and if it is bearish in red. In addition, it will show a label where you can see the number of occurrences that have been found from a certain point to another.
Note: this indicator can be complemented with the “Divergence RSI V2” indicator which is also found in my library.
Settings
Backtesting Bars: is the number of bars back that the indicator will check. No more than 1000 is recommended as this will slow down the search.
Tolerance: number of times a divergent line can cross a bar. If you place 0, no bar can be crossed by a diverging line.
Min Bars To detect: will only search for divergences (or lines) that have the minimum number of bars selected in this option. Default option is 30.
Min Bars To detect: it will only search for divergences (or lines) that have the maximum number of bars selected in this option. Default option is 100.
Source Highs: The high points will be based on the close of each bar. You can use as another alternative.
Source Lows: The low points will be based on the close of each bar. You can use as another alternative.
Use squeeze parameter : only look for divergences (bullish or bearish) at times when such an indicator is in favor of the trend or coincides with the corresponding RSI divergence.
Volume Accumulation Oscillator (VAO)The Volume Accumulation Oscillator (VAO) is a powerful momentum-based indicator designed to assess the strength of volume accumulation in a given asset. It helps traders identify periods of intense buying or selling pressure and potential trend reversals.
The VAO calculates the Net Volume Accumulation (NVA) by considering the volume, open, close, high, and low prices. It then applies exponential moving averages (EMAs) to smooth the NVA and calculates the VAO by comparing the smoothed NVA with its EMA over a specified signal period.
The VAO is plotted as a line chart, providing a clear visual representation of its values. Positive VAO values indicate strong bullish volume accumulation, suggesting potential upward price movement. Conversely, negative VAO values indicate significant selling pressure and the possibility of a downtrend.
To enhance the analysis, the indicator includes reference levels such as the zero line and +/-1 levels. These levels serve as important reference points for interpreting the VAO values and identifying key turning points in the market.
Additionally, the VAO histogram is included, which further illustrates the strength and direction of volume accumulation. The histogram bars are color-coded, with green bars representing positive VAO values and red bars representing negative VAO values.
The Volume Accumulation Oscillator is a versatile tool that can be used in various trading strategies. Traders can look for divergences between the VAO and the price chart to identify potential trend reversals. Combining the VAO with other technical analysis techniques can provide valuable insights into market dynamics and help traders make informed trading decisions.
Note: It is recommended to customize the indicator's parameters and conduct thorough backtesting to align it with your specific trading strategy and preferences before using it for live trading.
Disclaimer: This indicator is provided for educational and informational purposes only. Trading involves risks, and it is important to exercise caution and conduct your own analysis before making any investment decisions.
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.
Precision Trader Indicator, v1.01Overview:
The PTI is a custom indicator designed to provide buy and sell signals based on price movements and volatility. It uses the Average True Range (ATR) to calculate stop levels and identifies potential trend changes.
Parameters:
The indicator has several customizable parameters that you can adjust according to your preferences. These parameters include:
- ATR Period (length): Determines the lookback period for calculating the ATR.
- ATR Multiplier (mult): Specifies the multiplier applied to the ATR to determine the stop levels.
- Show Buy/Sell Labels (showLabels): Allows you to choose whether to display buy/sell labels on the chart.
- Use Close Price for Extremums (useClose): Determines whether the indicator considers the close price for calculating extremums.
- Highlight State (highlightState): Enables highlighting of the long and short state on the chart.
Calculation:
1. ATR Calculation: The indicator calculates the Average True Range (ATR) using the specified length parameter and multiplies it by the ATR Multiplier (mult) to obtain the ATR value.
2. Long Stop Calculation: The long stop level is calculated based on the highest price over the specified length period (using either the high or close price, depending on the useClose parameter) minus the ATR value. It ensures that the long stop is below the recent highest point.
3. Short Stop Calculation: The short stop level is calculated based on the lowest price over the specified length period (using either the low or close price) plus the ATR value. It ensures that the short stop is above the recent lowest point.
4. Direction Calculation: The indicator determines the current direction based on the close price compared to the previous long stop and short stop levels. If the close price is above the previous long stop, the direction is set to 1 (indicating a bullish trend). If the close price is below the previous short stop, the direction is set to -1 (indicating a bearish trend). Otherwise, the direction remains unchanged.
Plotting:
The indicator plots several visual elements on the chart:
- Long Stop: Draws a line representing the long stop level.
- Long Stop Start: Plots a small circle marker indicating the start of a long stop (buy signal).
- Buy Label: Displays a "Buy" label near the long stop start marker.
- Short Stop: Draws a line representing the short stop level.
- Short Stop Start: Plots a small circle marker indicating the start of a short stop (sell signal).
- Sell Label: Displays a "Sell" label near the short stop start marker.
- Long State Filling: Fills the area between the mid price and the long stop line with a color (optional).
- Short State Filling: Fills the area between the mid price and the short stop line with a color (optional).
Alerts:
The indicator includes three types of alerts:
- PTI Direction Change: Triggers an alert when the PTI direction changes (from bullish to bearish or vice versa).
- PTI Buy: Triggers an alert when a buy signal occurs (long stop start).
- PTI Sell: Triggers an alert when a sell signal occurs (short stop start).
By using the PTI indicator, traders can monitor potential trend changes and receive alerts when buy or sell signals are generated based on price and volatility dynamics.
Please note that the interpretation and effectiveness of this indicator should be evaluated through rigorous backtesting and analysis before making any trading decisions.
Trend hunter strategy - buy & sellThe indicator combines multiple technical indicators and conditions to generate buy and sell signals.
Here's how the indicator works and how to use it:
Strategy Selection:
The indicator provides a dropdown menu to choose the type of strategy. The available options are "Pullback" and "Simple."
Supertrend Settings:
The Supertrend indicator is used to identify the trend direction.
The indicator takes two input parameters:
ATR Length: Specifies the length of the Average True Range (ATR) used in the Supertrend calculation. The default value is 10.
Factor: Specifies the factor used in the Supertrend calculation. The default value is 3.0.
EMA Settings:
The indicator also includes an Exponential Moving Average (EMA) condition.
You can enable or disable the EMA condition using the "Ema Condition On/Off" checkbox.
If enabled, the indicator calculates an EMA based on the close price.
You can specify the length of the EMA using the "Ema Length" input parameter. The default value is 200.
RSI Settings:
The Relative Strength Index (RSI) indicator is used to generate additional conditions.
You can enable or disable the RSI condition using the "Rsi Condition On/Off" checkbox.
If enabled, the indicator calculates the RSI based on the close price.
You can specify the length of the RSI using the "Rsi Length" input parameter. The default value is 14.
Additionally, you can set the overbought and oversold levels for the RSI using the "RSI BUY Level" and "RSI SELL Level" input parameters, respectively. The default value for both is 50.
Final Conditions:
The indicator combines the Supertrend, EMA, and RSI conditions to generate buy and sell signals.
The specific conditions depend on the chosen strategy:
For the "Simple" strategy, the buy condition is when the Supertrend is in an up trend, not in a previous long position, the RSI is above the overbought level, and the close price is above the EMA.
For the "Pullback" strategy, the buy condition is when there is a cross under of the previous low with the Supertrend, the Supertrend is in an up trend, the RSI is above the overbought level, and the close price is above the EMA.
The sell conditions are the opposite of the respective buy conditions.
Backtest Period:
You can specify the start and end dates for the backtesting using the "Start calculations from" and "End calculations" inputs, respectively. The default start date is "2005-01-01" and the default end date is "2045-03-01." (this is work in progress) Still working on the table part, it is a bit tricky.
Trade Direction:
You can choose the trade direction using the "Trade Direction" input parameter. The available options are "Long," "Short," and "Both."
Depending on the selected trade direction, the indicator will generate signals accordingly.
Visual Display:
The indicator plots the Supertrend line on the price chart.
Buy signals are shown as green labels below the price bars.
Sell signals are shown as red labels above the price bars.
Adjust the input parameters according to your preferences, and then apply the indicator to a chart to see the generated signals. Please note that this indicator should be used for educational purposes only and should be thoroughly tested before using it for real trading.
Adaptive Mean Reversion IndicatorThe Adaptive Mean Reversion Indicator is a tool for identifying mean reversion trading opportunities in the market. The indicator employs a dynamic approach by adapting its parameters based on the detected market regime, ensuring optimal performance in different market conditions.
To determine the market regime, the indicator utilizes a volatility threshold. By comparing the average true range (ATR) over a 14-period to the specified threshold, it determines whether the market is trending or ranging. This information is crucial as it sets the foundation for parameter optimization.
The parameter optimization process is an essential step in the indicator's calculation. It dynamically adjusts the lookback period and threshold level based on the identified market regime. In trending markets, a longer lookback period and higher threshold level are chosen to capture extended trends. In ranging markets, a shorter lookback period and lower threshold level are used to identify mean reversion opportunities within a narrower price range.
The mean reversion calculation lies at the core of this indicator. It starts with computing the mean value using the simple moving average (SMA) over the selected lookback period. This represents the average price level. The deviation is then determined by calculating the standard deviation of the closing prices over the same lookback period. The upper and lower bands are derived by adding and subtracting the threshold level multiplied by the deviation from the mean, respectively. These bands serve as dynamic levels that define potential overbought and oversold areas.
In real-time, the indicator's adaptability shines through. If the market is trending, the adaptive mean is set to the calculated mean value. The adaptive upper and lower bands are adjusted by scaling the threshold level with a factor of 0.75. This adjustment allows the indicator to be less sensitive to minor price fluctuations during trending periods, providing more robust mean reversion signals. In ranging market conditions, the regular mean, upper band, and lower band are used as they are more suited to capture mean reversion within a confined price range.
The signal generation component of the indicator identifies potential trading opportunities based on the relationship between the current close price and the adaptive upper and lower bands. If the close price is above the adaptive upper band, it suggests a potential short entry opportunity (-1). Conversely, if the close price is below the adaptive lower band, it indicates a potential long entry opportunity (1). When the close price is within the range defined by the adaptive upper and lower bands, no clear trading signal is generated (0).
To further strengthen the quality of signals, the indicator introduces a confluence condition based on the RSI. When the RSI exceeds the threshold levels of 70 or falls below the threshold level of 30, it indicates a strong momentum condition. By incorporating this confluence condition, the indicator ensures that mean reversion signals align with the prevailing market momentum. It reduces the likelihood of false signals and provides traders with added confidence when entering trades.
The indicator offers alert conditions to notify traders of potential trading opportunities. Alert conditions are set to trigger when a potential long entry signal (1) or a potential short entry signal (-1) aligns with the confluence condition. These alerts allow traders to stay informed about favorable mean reversion setups, even when they are not actively monitoring the charts. By leveraging alerts, traders can efficiently manage their time and take advantage of market opportunities.
To enhance visual interpretation, the indicator incorporates background coloration that provides valuable insights into the prevailing market conditions. When the indicator generates a potential short entry signal (-1) that aligns with the confluence condition, the background color is set to lime. This color suggests a bullish trend that is potentially reaching an exhaustion point and about to revert downwards. Similarly, when the indicator generates a potential long entry signal (1) that aligns with the confluence condition, the background color is set to fuchsia. This color represents a bearish trend that is potentially reaching an exhaustion point and about to revert upwards. By employing background coloration, the indicator enables traders to quickly identify market conditions that may offer mean reversion opportunities with a directional bias.
The indicator further enhances visual clarity by incorporating bar coloring that aligns with the prevailing market conditions and signals. When the indicator generates a potential short entry signal (-1) that aligns with the confluence condition, the bar color is set to lime. This color signifies a bullish trend that is potentially reaching an exhaustion point, indicating a high probability of a downward reversion. Conversely, when the indicator generates a potential long entry signal (1) that aligns with the confluence condition, the bar color is set to fuchsia. This color represents a bearish trend that is potentially reaching an exhaustion point, indicating a high probability of an upward reversion. By using distinct bar colors, the indicator provides traders with a clear visual distinction between bullish and bearish trends, facilitating easier identification of mean reversion opportunities within the context of the broader trend.
While the "Adaptive Mean Reversion Indicator" offers a robust framework for identifying mean reversion opportunities, it's important to remember that no indicator is foolproof. Traders should exercise caution and employ risk management strategies. Additionally, it is recommended to use this indicator in conjunction with other technical analysis tools and fundamental factors to make well-informed trading decisions. Regular backtesting and refinement of the indicator's parameters are crucial to ensure its effectiveness in different market conditions.
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.
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.
Enhanced Strategy (Buy/Sell Signals)The provided script is an enhanced strategy that combines multiple indicators to generate buy and sell signals. Here's a breakdown of its features and usage:
Indicators used:
1. Moving Averages (MA): It uses two moving averages, fast and slow, to identify trend direction.
2. Relative Strength Index (RSI): It measures the momentum and overbought/oversold conditions of the asset.
3. Moving Average Convergence Divergence (MACD): It indicates trend direction and potential trend reversals.
4. Stochastic Momentum Index (Stch Mtm): It identifies overbought and oversold conditions and potential reversals.
5. Awesome Oscillator: It helps to gauge the market momentum and potential trend changes.
How to use:
1. The strategy is designed to be used as a study on the TradingView platform.
2. Apply the script to your preferred chart and adjust the input parameters as desired.
3. The buy and sell signals will be plotted as green "Buy" and red "Sell" labels on the chart.
4. You can also observe the plotted indicators to gain insights into the market conditions.
Combination of indicators:
1. Buy Signal: The strategy generates a buy signal when the following conditions are met:
- The fast moving average crosses over the slow moving average (bullish crossover).
- RSI value is above the specified threshold (30 by default), indicating potential oversold conditions.
- MACD line is above the signal line, suggesting a bullish trend.
- Stch Mtm is above 50, indicating bullish momentum.
- The Awesome Oscillator is positive, implying bullish market sentiment.
2. Sell Signal: The strategy generates a sell signal when the following conditions are met:
- The fast moving average crosses under the slow moving average (bearish crossover).
- RSI value is below the specified threshold (100 - RSI threshold), indicating potential overbought conditions.
- MACD line is below the signal line, suggesting a bearish trend.
- Stch Mtm is below 50, indicating bearish momentum.
- The Awesome Oscillator is negative, implying bearish market sentiment.
Market conditions:
- The strategy aims to identify potential entry and exit points based on the combination of indicators.
- It can be used in various market conditions, but it's important to consider the overall market context, news events, and risk management principles.
- It's recommended to use this strategy as a tool for analysis and decision-making, and validate the signals with additional analysis before executing trades.
Please note that the effectiveness and profitability of any trading strategy can vary depending on various factors, including market conditions and individual trading preferences. It's always advisable to conduct thorough backtesting and consider risk management techniques before applying any strategy to live trading.
TTP Breaking PointThis signal uses information from BITFINEX:BTCUSDLONGS and BITFINEX:BTCUSDSHORTS to forecast tops and bottoms.
The idea behind is very simple.
We calculate the RSI of the ratio of longs vs shorts and find areas where both the SMA of this RSI and the RSI itself are overextended.
You might notice that the win rate is not high but most of the wins provide a decent move that, if combined with proper risk management, can be used to build profitable strategies.
The signal offers a backtesting stream: 1 for buy and 2 for sell.
Shortly I'll be adding new features including: alerts, support for other symbols, filters, etc.
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.
ICT Donchian Smart Money Structure (Expo)█ Concept Overview
The Inner Circle Trader (ICT) methodology is focused on understanding the actions and implications of the so-called "smart money" - large institutions and professional traders who often influence market movements. Key to this is the concept of market structure and how it can provide insights into potential price moves.
Over time, however, there has been a notable shift in how some traders interpret and apply this methodology. Initially, it was designed with a focus on the fractal nature of markets. Fractals are recurring patterns in price action that are self-similar across different time scales, providing a nuanced and dynamic understanding of market structure.
However, as the ICT methodology has grown in popularity, there has been a drift away from this fractal-based perspective. Instead, many traders have started to focus more on pivot points as their primary tool for understanding market structure.
Pivot points provide static levels of potential support and resistance. While they can be useful in some contexts, relying heavily on them could provide a skewed perspective of market structure. They offer a static, backward-looking view that may not accurately reflect real-time changes in market sentiment or the dynamic nature of markets.
This shift from a fractal-based perspective to a pivot point perspective has significant implications. It can lead traders to misinterpret market structure and potentially make incorrect trading decisions.
To highlight this issue, you've developed a Donchian Structure indicator that mirrors the use of pivot points. The Donchian Channels are formed by the highest high and the lowest low over a certain period, providing another representation of potential market extremes. The fact that the Donchian Structure indicator produces the same results as pivot points underscores the inherent limitations of relying too heavily on these tools.
While the Donchian Structure indicator or pivot points can be useful tools, they should not replace the original, fractal-based perspective of the ICT methodology. These tools can provide a broad overview of market structure but may not capture the intricate dynamics and real-time changes that a fractal-based approach can offer.
It's essential for traders to understand these differences and to apply these tools correctly within the broader context of the ICT methodology and the Smart Money Concept Structure. A well-rounded approach that incorporates fractals, along with other tools and forms of analysis, is likely to provide a more accurate and comprehensive understanding of market structure.
█ Smart Money Concept - Misunderstandings
The Smart Money Concept is a popular concept among traders, and it's based on the idea that the "smart money" - typically large institutional investors, market makers, and professional traders - have superior knowledge or information, and their actions can provide valuable insight for other traders.
One of the biggest misunderstandings with this concept is the belief that tracking smart money activity can guarantee profitable trading.
█ Here are a few common misconceptions:
Following Smart Money Equals Guaranteed Success: Many traders believe that if they can follow the smart money, they will be successful. However, tracking the activity of large institutional investors and other professionals isn't easy, as they use complex strategies, have access to information not available to the public, and often intentionally hide their moves to prevent others from detecting their strategies.
Instantaneous Reaction and Results: Another misconception is that market movements will reflect smart money actions immediately. However, large institutions often slowly accumulate or distribute positions over time to avoid moving the market drastically. As a result, their actions might not produce an immediate noticeable effect on the market.
Smart Money Always Wins: It's not accurate to assume that smart money always makes the right decisions. Even the most experienced institutional investors and professional traders make mistakes, misjudge market conditions, or are affected by unpredictable events.
Smart Money Activity is Transparent: Understanding what constitutes smart money activity can be quite challenging. There are many indicators and metrics that traders use to try and track smart money, such as the COT (Commitments of Traders) reports, Level II market data, block trades, etc. However, these can be difficult to interpret correctly and are often misleading.
Assuming Uniformity Among Smart Money: 'Smart Money' is not a monolithic entity. Different institutional investors and professional traders have different strategies, risk tolerances, and investment horizons. What might be a good trade for a long-term institutional investor might not be a good trade for a short-term professional trader, and vice versa.
█ Market Structure
The Smart Money Concept Structure deals with the interpretation of price action that forms the market structure, focusing on understanding key shifts or changes in the market that may indicate where 'smart money' (large institutional investors and professional traders) might be moving in the market.
█ Three common concepts in this regard are Change of Character (CHoCH), and Shift in Market Structure (SMS), Break of Structure (BMS/BoS).
Change of Character (CHoCH): This refers to a noticeable change in the behavior of price movement, which could suggest that a shift in the market might be about to occur. This might be signaled by a sudden increase in volatility, a break of a trendline, or a change in volume, among other things.
Shift in Market Structure (SMS): This is when the overall structure of the market changes, suggesting a potential new trend. It usually involves a sequence of lower highs and lower lows for a downtrend, or higher highs and higher lows for an uptrend.
Break of Structure (BMS/BoS): This is when a previously defined trend or pattern in the price structure is broken, which may suggest a trend continuation.
A key component of this approach is the use of fractals, which are repeating patterns in price action that can give insights into potential market reversals. They appear at all scales of a price chart, reflecting the self-similar nature of markets.
█ Market Structure - Misunderstandings
One of the biggest misunderstandings about the ICT approach is the over-reliance or incorrect application of pivot points. Pivot points are a popular tool among traders due to their simplicity and easy-to-understand nature. However, when it comes to the Smart Money Concept and trying to follow the steps of professional traders or large institutions, relying heavily on pivot points can create misconceptions and lead to confusion. Here's why:
Delayed and Static Information: Pivot points are inherently backward-looking because they're calculated based on the previous period's data. As such, they may not reflect real-time market dynamics or sudden changes in market sentiment. Furthermore, they present a static view of market structure, delineating pre-defined levels of support and resistance. This static nature can be misleading because markets are fundamentally dynamic and constantly changing due to countless variables.
Inadequate Representation of Market Complexity: Markets are influenced by a myriad of factors, including economic indicators, geopolitical events, institutional actions, and market sentiment, among others. Relying on pivot points alone for reading market structure oversimplifies this complexity and can lead to a myopic understanding of market dynamics.
False Signals and Misinterpretations: Pivot points can often give false signals, especially in volatile markets. Prices might react to these levels temporarily but then continue in the original direction, leading to potential misinterpretation of market structure and sentiment. Also, a trader might wrongly perceive a break of a pivot point as a significant market event, when in fact, it could be due to random price fluctuations or temporary volatility.
Over-simplification: Viewing market structure only through the lens of pivot points simplifies the market to static levels of support and resistance, which can lead to misinterpretation of market dynamics. For instance, a trader might view a break of a pivot point as a definite sign of a trend, when it could just be a temporary price spike.
Ignoring the Fractal Nature of Markets: In the context of the Smart Money Concept Structure, understanding the fractal nature of markets is crucial. Fractals are self-similar patterns that repeat at all scales and provide a more dynamic and nuanced understanding of market structure. They can help traders identify shifts in market sentiment or direction in real-time, providing more relevant and timely information compared to pivot points.
The key takeaway here is not that pivot points should be entirely avoided or that they're useless. They can provide valuable insights and serve as a useful tool in a trader's toolbox when used correctly. However, they should not be the sole or primary method for understanding the market structure, especially in the context of the Smart Money Concept Structure.
█ Fractals
Instead, traders should aim for a comprehensive understanding of markets that incorporates a range of tools and concepts, including but not limited to fractals, order flow, volume analysis, fundamental analysis, and, yes, even pivot points. Fractals offer a more dynamic and nuanced view of the market. They reflect the recursive nature of markets and can provide valuable insights into potential market reversals. Because they appear at all scales of a price chart, they can provide a more holistic and real-time understanding of market structure.
In contrast, the Smart Money Concept Structure, focusing on fractals and comprehensive market analysis, aims to capture a more holistic and real-time view of the market. Fractals, being self-similar patterns that repeat at different scales, offer a dynamic understanding of market structure. As a result, they can help to identify shifts in market sentiment or direction as they happen, providing a more detailed and timely perspective.
Furthermore, a comprehensive market analysis would consider a broader set of factors, including order flow, volume analysis, and fundamental analysis, which could provide additional insights into 'smart money' actions.
█ Donchian Structure
Donchian Channels are a type of indicator used in technical analysis to identify potential price breakouts and trends, and they may also serve as a tool for understanding market structure. The channels are formed by taking the highest high and the lowest low over a certain number of periods, creating an envelope of price action.
Donchian Channels (or pivot points) can be useful tools for providing a general view of market structure, and they may not capture the intricate dynamics associated with the Smart Money Concept Structure. A more nuanced approach, centered on real-time fractals and a comprehensive analysis of various market factors, offers a more accurate understanding of 'smart money' actions and market structure.
█ Here is why Donchian Structure may be misleading:
Lack of Nuance: Donchian Channels, like pivot points, provide a simplified view of market structure. They don't take into account the nuanced behaviors of price action or the complex dynamics between buyers and sellers that can be critical in the Smart Money Concept Structure.
Limited Insights into 'Smart Money' Actions: While Donchian Channels can highlight potential breakout points and trends, they don't necessarily provide insights into the actions of 'smart money'. These large institutional traders often use sophisticated strategies that can't be easily inferred from price action alone.
█ Indicator Overview
We have built this Donchian Structure indicator to show that it returns the same results as using pivot points. The Donchian Structure indicator can be a useful tool for market analysis. However, it should not be seen as a direct replacement or equivalent to the original Smart Money concept, nor should any indicator based on pivot points. The indicator highlights the importance of understanding what kind of trading tools we use and how they can affect our decisions.
The Donchian Structure Indicator displays CHoCH, SMS, BoS/BMS, as well as premium and discount areas. This indicator plots everything in real-time and allows for easy backtesting on any market and timeframe. A unique candle coloring has been added to make it more engaging and visually appealing when identifying new trading setups and strategies. This candle coloring is "leading," meaning it can signal a structural change before it actually happens, giving traders ample time to plan their next trade accordingly.
█ How to use
The indicator is great for traders who want to simplify their view on the market structure and easily backtest Smart Money Concept Strategies. The added candle coloring function serves as a heads-up for structure change or can be used as trend confirmation. This new candle coloring feature can generate many new Smart Money Concepts strategies.
█ Features
Market Structure
The market structure is based on the Donchian channel, to which we have added what we call 'Structure Response'. This addition makes the indicator more useful, especially in trending markets. The core concept involves traders buying at a discount and selling or shorting at a premium, depending on the order flow. Structure response enables traders to determine the order flow more clearly. Consequently, more trading opportunities will appear in trending markets.
Structure Candles
Structure Candles highlight the current order flow and are significantly more responsive to structural changes. They can provide traders with a heads-up before a break in structure occurs
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Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
Pure Morning 2.0 - Candlestick Pattern Doji StrategyThe new "Pure Morning 2.0 - Candlestick Pattern Doji Strategy" is a trend-following, intraday cryptocurrency trading system authored by devil_machine.
The system identifies Doji and Morning Doji Star candlestick formations above the EMA60 as entry points for long trades.
For best results we recommend to use on 15-minute, 30-minute, or 1-hour timeframes, and are ideal for high-volatility markets.
The strategy also utilizes a profit target or trailing stop for exits, with stop loss set at the lowest low of the last 100 candles. The strategy's configuration details, such as Doji tolerance, and exit configurations are adjustable.
In this new version 2.0, we've incorporated a new selectable filter. Since the stop loss is set at the lowest low, this filter ensures that this value isn't too far from the entry price, thereby optimizing the Risk-Reward ratio.
In the specific case of ALPINE, a 9% Take-Profit and and Stop-Loss at Lowest Low of the last 100 candles were set, with an activated trailing-stop percentage, Max Loss Filter is not active.
Name : Pure Morning 2.0 - Candlestick Pattern Doji Strategy
Author : @devil_machine
Category : Trend Follower based on candlestick patterns.
Operating mode : Spot or Futures (only long).
Trades duration : Intraday
Timeframe : 15m, 30m, 1H
Market : Crypto
Suggested usage : Short-term trading, when the market is in trend and it is showing high volatility .
Entry : When a Doji or Morning Doji Star formation occurs above the EMA60.
Exit : Profit target or Trailing stop, Stop loss on the lowest low of the last 100 candles.
Configuration :
- Doji Settings (tolerances) for Entry Condition
- Max Loss Filter (Lowest Low filter)
- Exit Long configuration
- Trailing stop
Backtesting :
⁃ Exchange: BINANCE
⁃ Pair: ALPINEUSDT
⁃ Timeframe: 30m
⁃ Fee: 0.075%
⁃ Slippage: 1
- Initial Capital: 10000 USDT
- Position sizing: 10% of Equity
- Start: 2022-02-28 (Out Of Sample from 2022-12-23)
- Bar magnifier: on
Disclaimer : Risk Management is crucial, so adjust stop loss to your comfort level. A tight stop loss can help minimise potential losses. Use at your own risk.
How you or we can improve? Source code is open so share your ideas!
Leave a comment and smash the boost button!
Thanks for your attention, happy to support the TradingView community.
Chandelier Exit ZLSMA StrategyIntroducing a Powerful Trading Indicator: Chandelier Exit with ZLSMA
If you're a trader, you know the importance of having the right tools and indicators to make informed decisions. That's why we're excited to introduce a powerful new trading indicator that combines the Chandelier Exit and ZLSMA: two widely-used and effective indicators for technical analysis.
The Chandelier Exit (CE) is a popular trailing stop-loss indicator developed by Chuck LeBeau. It's designed to follow the price trend of a security and provide an exit signal when the price crosses below the CE line. The CE line is based on the Average True Range (ATR), which is a measure of volatility. This means that the CE line adjusts to the volatility of the security, making it a reliable indicator for trailing stop-losses.
The ZLEMA (Zero Lag Exponential Moving Average) is a type of exponential moving average that's designed to reduce lag and improve signal accuracy. The ZLSMA takes into account not only the current price but also past prices, using a weighted formula to calculate the moving average. This makes it a smoother indicator than traditional moving averages, and less prone to giving false signals.
When combined, the CE and ZLSMA create a powerful indicator that can help traders identify trend changes and make more informed trading decisions. The CE provides the trailing stop-loss signal, while the ZLSMA provides a smoother trend line to help identify potential entry and exit points.
In our indicator, the CE and ZLSMA are plotted together on the chart, making it easy to see both the trailing stop-loss and the trend line at the same time. The CE line is displayed as a dotted line, while the ZLSMA line is displayed as a solid line.
Using this indicator, traders can set their stop-loss levels based on the CE line, while also using the ZLSMA line to identify potential entry and exit points. The combination of these two indicators can help traders reduce their risk and improve their trading performance.
In conclusion, the Chandelier Exit with ZLSMA is a powerful trading indicator that combines two effective technical analysis tools. By using this indicator, traders can identify trend changes, set stop-loss levels, and make more informed trading decisions. Try it out for yourself and see how it can improve your trading performance.
Warning: The results in the backtest are from a repainting strategy. Don't take them seriously. You need to do a dry live test in order to test it for its useability.
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Here is a description of each input field in the provided source code:
length: An integer input used as the period for the ATR (Average True Range) calculation. Default value is 1.
mult: A float input used as a multiplier for the ATR value. Default value is 2.
showLabels: A boolean input that determines whether to display buy/sell labels on the chart. Default value is false.
isSignalLabelEnabled: A boolean input that determines whether to display signal labels on the chart. Default value is true.
useClose: A boolean input that determines whether to use the close price for extrema calculations. Default value is true.
zcolorchange: A boolean input that determines whether to enable rising/decreasing highlighting for the ZLSMA (Zero-Lag Exponential Moving Average) line. Default value is false.
zlsmaLength: An integer input used as the length for the ZLSMA calculation. Default value is 50.
offset: An integer input used as an offset for the ZLSMA calculation. Default value is 0.
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Ty for checking this out and good luck on your trading journey! Likes and comments are appreciated. 👍
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Credits to:
▪ @everget – Chandelier Exit (CE)
▪ @netweaver2022 – ZLSMA
Strategy Creator5 indicators. Backtesting available. Uses ADX, RSI, Stochastic, MACD, and crossing EMAs (1,2, or 3). This strategy creator allows you to turn on or off these indicators and adjust the parameters for each indicator. It allows you to make one trade at a time e.g the next trade doesn't open until the last one closes. (You are also able to enter how many trades in one direction you want for example if you want only 2 long trades in a row, then the strategy waits for the next short position without making anymore long trades. Once there are 2 short positions in a row, it waits for a long position). The code can be edited to for automated trading by editing the comment in the source code for the strategy parameters. This took many hours to finish. ENJOY.
Slight Swing Momentum Strategy.Introduction:
The Swing Momentum Strategy is a quantitative trading strategy designed to capture mid-term opportunities in the financial markets by combining swing trading principles with momentum indicators. It utilizes a combination of technical indicators, including moving averages, crossover signals, and volume analysis, to generate buy and sell signals. The strategy aims to identify market trends and capitalize on price momentum for profit generation.
Highlights:
The strategy offers several key highlights that make it unique and potentially attractive to traders:
Swing Trading with Momentum: The strategy combines the principles of swing trading, which aim to capture short-to-medium-term price swings, with momentum indicators that help identify strong price trends and potential breakout opportunities.
Technical Indicator Optimization: The strategy utilizes a selection of optimized technical indicators, including moving averages and crossover signals, to filter out the noise and focus on high-probability trading setups. This optimization enhances the strategy's ability to identify favourable entry and exit points.
Risk Management: The strategy incorporates risk management techniques, such as position sizing based on equity and dynamic stop loss levels, to manage risk exposure and protect capital. This helps to minimize drawdowns and preserve profits.
Buy Condition:
The buy condition in the strategy is determined by a combination of factors, including A1, A2, A3, XG, and weeklySlope. Let's break it down:
A1 Condition: The A1 condition checks for specific price relationships. It verifies that the ratio of the highest price to the closing price is less than 1.03, the ratio of the opening price to the lowest price is less than 1.03, and the ratio of the highest price to the previous day's closing price is greater than 1.06. This condition looks for a specific pattern indicating potential bullish momentum.
A2 Condition: The A2 condition checks for price relationships related to the closing price. It verifies that the ratio of the closing price to the opening price is greater than 1.05 or that the ratio of the closing price to the previous day's closing price is greater than 1.05. This condition looks for signs of upward price movement and momentum.
A3 Condition: The A3 condition focuses on volume. It checks if the current volume crosses above the highest volume over the last 60 periods. This condition aims to identify increased buying interest and potentially confirms the strength of the potential upward price movement.
XG Condition: The XG condition combines the A1 and A2 conditions and checks if they are true for both the current and previous bars. It also verifies that the ratio of the closing price to the 5-period EMA crosses above the 9-period SMA of the same ratio. This condition helps identify potential buy signals when multiple factors align, indicating a strong bullish momentum and potential entry point.
Weekly Trend Factor: The weekly slope condition calculates the slope of the 50-period SMA over a weekly timeframe. It checks if the slope is positive, indicating an overall upward trend on a weekly basis. This condition provides additional confirmation that the stock is in an upward trend.
When all of these conditions align, the buy condition is triggered, indicating a favourable time to enter a long position.
Sell Condition:
The sell condition is relatively straightforward in the strategy:
Sell Signal: The sell condition simply checks if the closing price crosses below the 10-period EMA. When this condition is met, it indicates a potential reversal or weakening of the upward price momentum, and a sell signal is generated.
Backtest Outcome:
The strategy was backtested over the period from January 22nd, 1999 to May 3rd, 2023, using daily candlestick charts for the NASDAQ: NVDA. The strategy used an initial capital of 1,000,000 USD, The order quantity is defined as 10% of the equity. The strategy allows for pyramiding with 1 order, and the transaction fee is set at 0.03% per trade. Here are the key outcomes of the backtest:
Net Profit: 539,595.84 USD, representing a return of 53.96%.
Percent Profitable: 48.82%
Total Closed Trades: 127
Profit Factor: 2.331
Max Drawdown: 68,422.70 USD
Average Trade: 4,248.79 USD
Average Number of Bars in Trades: 11, indicating the average duration of the trades.
Conclusion:
In conclusion, the Swing Momentum Strategy is a quantitative trading approach that combines swing trading principles with momentum indicators to identify and capture mid term trading opportunities. The strategy has demonstrated promising results during backtesting, including a significant net profit and a favourable profit factor.
