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.
Strategy
BBO-ALPHA-PHANTOMHello friends, this is the second time I am publishing this script, hopefully the description will be sufficient and you can use it reliably.
Script Description:
The script consists of several indicators and generates buy and sell signals based on their calculations. Here's a breakdown of the functions and indicators used in the script:
Moving Average Convergence Divergence (MACD):
Fast Length: The number of periods used for calculating the fast moving average.
Slow Length: The number of periods used for calculating the slow moving average.
Source: The price source used for calculations (default is the closing price).
Signal Smoothing: The number of periods used for smoothing the signal line.
Oscillator MA Type: The type of moving average used for the oscillator line (default is Exponential Moving Average).
Signal Line MA Type: The type of moving average used for the signal line (default is Exponential Moving Average).
Benefit: MACD is a trend-following momentum indicator that helps identify potential trend reversals, bullish or bearish market conditions, and generate buy and sell signals based on the crossovers of the oscillator and signal lines.
Relative Strength Index (RSI):
RSI Length: The number of periods used for calculating RSI.
RSI Source: The price source used for RSI calculations (default is (high + low + close) / 3).
MA Type: The type of moving average used for smoothing RSI values (default is Simple Moving Average).
MA Length: The number of periods used for smoothing RSI values.
Benefit: RSI is a momentum oscillator that measures the speed and change of price movements. It helps identify overbought and oversold conditions, potential trend reversals, and generate buy and sell signals based on the crossovers of RSI and its moving average.
Money Flow Index (MFI):
MFI Length: The number of periods used for calculating MFI.
Source: The price source used for MFI calculations (default is (high + low + close) / 3).
Benefit: MFI is a momentum indicator that uses both price and volume data to measure buying and selling pressure. It helps identify overbought and oversold conditions and potential trend reversals.
Directional Movement Index (DMI):
Signal Length: The number of periods used for smoothing the ADX line.
Length: The number of periods used for calculating DMI.
Benefit: DMI consists of three lines: ADX, +DI (Plus Directional Indicator), and -DI (Minus Directional Indicator). ADX measures the strength of a trend, while +DI and -DI indicate the direction of the trend. DMI helps identify trend strength, trend direction, and potential trend reversals.
Stochastic Oscillator:
SmoothK: The number of periods used for smoothing %K line.
SmoothD: The number of periods used for smoothing %D line.
Length RSI: The number of periods used for calculating RSI within Stochastic.
Length Stoch: The number of periods used for calculating Stochastic.
Benefit: Stochastic Oscillator is a momentum indicator that compares the closing price of an asset to its price range over a specific period. It helps identify overbought and oversold conditions and potential trend reversals.
Moving Averages (MA):
MA50: Simple Moving Average with a length of 50 periods.
MA200: Simple Moving Average with a length of 200 periods.
Benefit: Moving averages are commonly used to
Advantages of the script compared to common indicators:
Comprehensive analysis: The script combines several indicators such as MACD, RSI, MFI, DMI, Stochastic Oscillator and Moving Averages. It thus provides a broader and more comprehensive view of the market and its development.
Synergy of indicators: Using multiple indicators increases the reliability and confirmation of signals. Combining different indicators can provide potentially stronger and more accurate signals of a trend change.
Identifying Oversold and Overbought Levels: RSI, MFI and Stochastic Oscillator are used to identify oversold and overbought levels in the market. This can help uncover opportunities to buy or sell in line with these levels.
Identifying trends and their strength: DMI and Moving Averages help identify trends in the market and provide information about their strength. This can help traders in deciding the appropriate time to enter and exit the market.
Early signal generation: The script generates signals based on a combination of various indicators, which can help traders identify potential trading opportunities at an early stage.
The main thing for me is that it helps me from overtrading, I only trade when I get an alert or see it on the chart. I recommend
I find it best to trade in the 1h and 2h time frame. The shorter ones like 15min and 30min are perfect for me to get out of the position.
It is important to note that no indicator guarantees 100% accuracy in generating signals and trading on financial
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.
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.
Model Indicator |ASE|The purpose of this indicator is to allow the user to build their own model. Each feature works cohesively together and depending on the filters you enable, the model gives less and more specific entries. This benefits the trader because they have complete control over the kinds of trades they want to take, while maintaining its automatic form.
We want to be as customizable as possible while still meeting our users’ needs. We started this indicator to propel us into our ultimate project, the ASE Algo.
Features:
SMC Display
Current Structure:
Liquidity Levels:
Daily Premium Discount Array
SMT Divergence
Displacement Candles:
Entry Factors
FVG
Continuation FVGs
MTF FVGs
Order Blocks
MTF Order Blocks
Confluence Filters
MS Reversal
Liquidity Level Raid
Inducement
Daily Prem/Disc Array
Target Factors
Liquidity Level Targets
Current Structure Targets
Trade Management
Trade Overlay
Risk:Reward Target
Benefits & Examples:
In the image below the indicator signaled multiple entries based on two simple confluence filters, a MS reversal (CHoCH/MSS) and a Liquidity Raid. Going from left to right we can see a short entry at the highs with a supporting Order Block. Liquidity levels are taken before we see a double IDM right below the respected OB that leads to the next signaled entry. In the middle of the chart we see a long entry that leads right into a short entry showing the effectiveness of such a simple model.
In this supporting image we are showcasing the first implementation of the Trade Overlay feature. This feature displays the Entry and Stop Loss to make it more visible and adds a risk to reward target. Additionally displayed is the SMC Toolkit indicator showing us additional confirmation with our signaled entries playing right out of a higher timeframe FVG.
An additional entry feature is the MTF zone. Setups can form on all timeframes and subjecting yourself to only one may lead you to miss out on some perfect setups or a larger move. In the image below we are on the 1 minute timeframe. We can see the Initial Reversal Entry which played out beautifully and filled a higher timeframe SFVG. With the MTF zone we can see a 3 minute and 5 minute Zone which produces the rest of the trend reaching another higher timeframe SFVG after filling the previous one. Once again showing the benefit of the Toolkit indicator but the plotted entries from such a simple model.
In addition to the model indicators filtered out entry zone, we can use additional confluences to confirm these entries. In the image below we can see a short entry printed after a move out of the Std. Dev. vwap wave which shows over extension. Taking the entry we can have a tight stop loss at the vwap wave or the recent high where we have a liquidity level, targeting a lower liquidity level or higher timeframe FVG.
For this example we are only filtering based on MS Reversals (CHoCH/MSS) to get our entries. Because of this we need additional confirmation to be confident in taking the plotted entry. In the image below you can see a long signal printed, confirmation being the previous Failed Reversal.
GKD-BT Solo Confirmation Complex Backtest [Loxx]Giga Kaleidoscope GKD-BT Solo Confirmation Complex Backtest is a Backtesting module included in Loxx's "Giga Kaleidoscope Modularized Trading System".
█ GKD-BT Solo Confirmation Complex Backtest
The Solo Confirmation Complex Backtest module enables users to perform backtesting on Standard Long and Short signals from GKD-C confirmation indicators, filtered by GKD-B Baseline and GKD-V Volatility/Volume indicators. This module represents a complex form of the Solo Confirmation Backtest in the GKD trading system. It includes two types of backtests: Trading and Full. The Trading backtest allows users to test individual trades, both Long and Short, one at a time. On the other hand, the Full backtest allows users to test either Longs or Shorts by toggling between them in the settings to view the results for each signal type. The Trading backtest simulates real trading, while the Full backtest tests all signals, whether Long or Short.
Additionally, this backtest module provides the option to test the GKD-C Confirmation indicator with 1 to 3 take profits and 1 stop loss. The Trading backtest allows for the use of 1 to 3 take profits, while the Full backtest is limited to 1 take profit. The Trading backtest also offers the capability to apply a trailing take profit.
In terms of the percentage of trade removed at each take profit, this backtest module has the following hardcoded values:
Take profit 1: 50% of the trade is removed.
Take profit 2: 25% of the trade is removed.
Take profit 3: 25% of the trade is removed.
Stop loss: 100% of the trade is removed.
After each take profit is achieved, the stop loss level is adjusted. When take profit 1 is reached, the stop loss is moved to the entry point. Similarly, when take profit 2 is reached, the stop loss is shifted to take profit 1. The trailing take profit feature comes into play after take profit 2 or take profit 3, depending on the number of take profits selected in the settings. The trailing take profit is always activated on the final take profit when 2 or more take profits are chosen.
The backtest module also offers the capability to restrict by a specific date range, allowing for simulated forward testing based on past data. Additionally, users have the option to display or hide a trading panel that provides relevant information about the backtest, statistics, and the current trade. It is also possible to activate alerts and toggle sections of the trading panel on or off. On the chart, historical take profit and stop loss levels are represented by horizontal lines overlaid for reference.
The GKD system utilizes volatility-based take profits and stop losses. Each take profit and stop loss is calculated as a multiple of volatility. Users can also adjust the multiplier values in the settings.
To utilize this strategy, follow these steps:
1. GKD-B Baseline Import: Import the value "Input into NEW GKD-BT Backtest" from the GKD-B Baseline module into the GKD-BT Solo Confirmation Complex Backtest module setting named "Import GKD-B Baseline indicator."
Adjust the "Confirmation Type" in the GKD-C Confirmation Indicator to "GKD New."
2. GKD-C Confirmation Import: Import the value "Input into NEW GKD-BT Backtest" from the GKD-C Confirmation module into the GKD-BT Solo Confirmation Complex Backtest module setting named "Import GKD-C Confirmation indicator."
3. GKD-V Volatility/Volume Import: Import the value "Input into NEW GKD-BT Backtest" from the GKD-V Volatility/Volume module into the GKD-BT Solo Confirmation Complex Backtest module setting named "Import GKD-V Volatility/Volume indicator."
4. The Solo Confirmation Complex Backtest module exclusively supports Standard Entries, both Long and Short. However, please note that this module uses a modified version of the Standard Entry. In this modified version, long and short signals are directly imported from the Confirmation indicator, and then baseline and volatility filtering is applied.
The GKD-B Baseline filter ensures that only trades aligning with the GKD-B Baseline's current trend are accepted. This filter takes into consideration the Goldie Locks Zone, which allows trades where the closing price of the last candle has moved within a minimum XX volatility and a maximum YY volatility range. The GKD-V Volatility/Volume filter allows only trades that meet a minimum threshold of ZZ GKD-V Volatility/Volume, which varies based on the specific GKD-V Volatility/Volume indicator used.
The Solo Confirmation Complex Backtest execution engine determines whether signals from the GKD-C Confirmation indicator are accepted or rejected based on two criteria:
1. The GKD-C Confirmation signal must be qualified by the direction of the GKD-B Baseline trend and the GKD-B Baseline's sweet-spot Goldie Locks Zone.
2. Sufficient Volatility/Volume, as indicated by the GKD-V Volatility/Volume indicator, must be present to execute a trade.
The purpose of the Solo Confirmation Complex Backtest is to test a GKD-C Confirmation indicator in the presence of macro trend and volatility/volume filtering.
Volatility Types Included
17 types of volatility are included in this indicator
Close-to-Close
Parkinson
Garman-Klass
Rogers-Satchell
Yang-Zhang
Garman-Klass-Yang-Zhang
Exponential Weighted Moving Average
Standard Deviation of Log Returns
Pseudo GARCH(2,2)
Average True Range
True Range Double
Standard Deviation
Adaptive Deviation
Median Absolute Deviation
Efficiency-Ratio Adaptive ATR
Mean Absolute Deviation
Static Percent
Close-to-Close
Close-to-Close volatility is a classic and widely used volatility measure, sometimes referred to as historical volatility.
Volatility is an indicator of the speed of a stock price change. A stock with high volatility is one where the price changes rapidly and with a larger amplitude. The more volatile a stock is, the riskier it is.
Close-to-close historical volatility is calculated using only a stock's closing prices. It is the simplest volatility estimator. However, in many cases, it is not precise enough. Stock prices could jump significantly during a trading session and return to the opening value at the end. That means that a considerable amount of price information is not taken into account by close-to-close volatility.
Despite its drawbacks, Close-to-Close volatility is still useful in cases where the instrument doesn't have intraday prices. For example, mutual funds calculate their net asset values daily or weekly, and thus their prices are not suitable for more sophisticated volatility estimators.
Parkinson
Parkinson volatility is a volatility measure that uses the stock’s high and low price of the day.
The main difference between regular volatility and Parkinson volatility is that the latter uses high and low prices for a day, rather than only the closing price. This is useful as close-to-close prices could show little difference while large price movements could have occurred during the day. Thus, Parkinson's volatility is considered more precise and requires less data for calculation than close-to-close volatility.
One drawback of this estimator is that it doesn't take into account price movements after the market closes. Hence, it systematically undervalues volatility. This drawback is addressed in the Garman-Klass volatility estimator.
Garman-Klass
Garman-Klass is a volatility estimator that incorporates open, low, high, and close prices of a security.
Garman-Klass volatility extends Parkinson's volatility by taking into account the opening and closing prices. As markets are most active during the opening and closing of a trading session, it makes volatility estimation more accurate.
Garman and Klass also assumed that the process of price change follows a continuous diffusion process (Geometric Brownian motion). However, this assumption has several drawbacks. The method is not robust for opening jumps in price and trend movements.
Despite its drawbacks, the Garman-Klass estimator is still more effective than the basic formula since it takes into account not only the price at the beginning and end of the time interval but also intraday price extremes.
Researchers Rogers and Satchell have proposed a more efficient method for assessing historical volatility that takes into account price trends. See Rogers-Satchell Volatility for more detail.
Rogers-Satchell
Rogers-Satchell is an estimator for measuring the volatility of securities with an average return not equal to zero.
Unlike Parkinson and Garman-Klass estimators, Rogers-Satchell incorporates a drift term (mean return not equal to zero). As a result, it provides better volatility estimation when the underlying is trending.
The main disadvantage of this method is that it does not take into account price movements between trading sessions. This leads to an underestimation of volatility since price jumps periodically occur in the market precisely at the moments between sessions.
A more comprehensive estimator that also considers the gaps between sessions was developed based on the Rogers-Satchel formula in the 2000s by Yang-Zhang. See Yang Zhang Volatility for more detail.
Yang-Zhang
Yang Zhang is a historical volatility estimator that handles both opening jumps and the drift and has a minimum estimation error.
Yang-Zhang volatility can be thought of as a combination of the overnight (close-to-open volatility) and a weighted average of the Rogers-Satchell volatility and the day’s open-to-close volatility. It is considered to be 14 times more efficient than the close-to-close estimator.
Garman-Klass-Yang-Zhang
Garman-Klass-Yang-Zhang (GKYZ) volatility estimator incorporates the returns of open, high, low, and closing prices in its calculation.
GKYZ volatility estimator takes into account overnight jumps but not the trend, i.e., it assumes that the underlying asset follows a Geometric Brownian Motion (GBM) process with zero drift. Therefore, the GKYZ volatility estimator tends to overestimate the volatility when the drift is different from zero. However, for a GBM process, this estimator is eight times more efficient than the close-to-close volatility estimator.
Exponential Weighted Moving Average
The Exponentially Weighted Moving Average (EWMA) is a quantitative or statistical measure used to model or describe a time series. The EWMA is widely used in finance, with the main applications being technical analysis and volatility modeling.
The moving average is designed such that older observations are given lower weights. The weights decrease exponentially as the data point gets older – hence the name exponentially weighted.
The only decision a user of the EWMA must make is the parameter lambda. The parameter decides how important the current observation is in the calculation of the EWMA. The higher the value of lambda, the more closely the EWMA tracks the original time series.
Standard Deviation of Log Returns
This is the simplest calculation of volatility. It's the standard deviation of ln(close/close(1)).
Pseudo GARCH(2,2)
This is calculated using a short- and long-run mean of variance multiplied by ?.
?avg(var;M) + (1 ? ?) avg(var;N) = 2?var/(M+1-(M-1)L) + 2(1-?)var/(M+1-(M-1)L)
Solving for ? can be done by minimizing the mean squared error of estimation; that is, regressing L^-1var - avg(var; N) against avg(var; M) - avg(var; N) and using the resulting beta estimate as ?.
Average True Range
The average true range (ATR) is a technical analysis indicator, introduced by market technician J. Welles Wilder Jr. in his book New Concepts in Technical Trading Systems, that measures market volatility by decomposing the entire range of an asset price for that period.
The true range indicator is taken as the greatest of the following: current high less the current low; the absolute value of the current high less the previous close; and the absolute value of the current low less the previous close. The ATR is then a moving average, generally using 14 days, of the true ranges.
True Range Double
A special case of ATR that attempts to correct for volatility skew.
Standard Deviation
Standard deviation is a statistic that measures the dispersion of a dataset relative to its mean and is calculated as the square root of the variance. The standard deviation is calculated as the square root of variance by determining each data point's deviation relative to the mean. If the data points are further from the mean, there is a higher deviation within the data set; thus, the more spread out the data, the higher the standard deviation.
Adaptive Deviation
By definition, the Standard Deviation (STD, also represented by the Greek letter sigma ? or the Latin letter s) is a measure that is used to quantify the amount of variation or dispersion of a set of data values. In technical analysis, we usually use it to measure the level of current volatility.
Standard Deviation is based on Simple Moving Average calculation for mean value. This version of standard deviation uses the properties of EMA to calculate what can be called a new type of deviation, and since it is based on EMA, we can call it EMA deviation. Additionally, Perry Kaufman's efficiency ratio is used to make it adaptive (since all EMA type calculations are nearly perfect for adapting).
The difference when compared to the standard is significant--not just because of EMA usage, but the efficiency ratio makes it a "bit more logical" in very volatile market conditions.
Median Absolute Deviation
The median absolute deviation is a measure of statistical dispersion. Moreover, the MAD is a robust statistic, being more resilient to outliers in a data set than the standard deviation. In the standard deviation, the distances from the mean are squared, so large deviations are weighted more heavily, and thus outliers can heavily influence it. In the MAD, the deviations of a small number of outliers are irrelevant.
Because the MAD is a more robust estimator of scale than the sample variance or standard deviation, it works better with distributions without a mean or variance, such as the Cauchy distribution.
Efficiency-Ratio Adaptive ATR
Average True Range (ATR) is a widely used indicator for many occasions in technical analysis. It is calculated as the RMA of the true range. This version adds a "twist": it uses Perry Kaufman's Efficiency Ratio to calculate adaptive true range.
Mean Absolute Deviation
The mean absolute deviation (MAD) is a measure of variability that indicates the average distance between observations and their mean. MAD uses the original units of the data, which simplifies interpretation. Larger values signify that the data points spread out further from the average. Conversely, lower values correspond to data points bunching closer to it. The mean absolute deviation is also known as the mean deviation and average absolute deviation.
This definition of the mean absolute deviation sounds similar to the standard deviation (SD). While both measure variability, they have different calculations. In recent years, some proponents of MAD have suggested that it replace the SD as the primary measure because it is a simpler concept that better fits real life.
Static Percent
Static Percent allows the user to insert their own constant percent that will then be used to create take profits and stoploss
█ Giga Kaleidoscope Modularized Trading System
Core components of an NNFX algorithmic trading strategy
The NNFX algorithm is built on the principles of trend, momentum, and volatility. There are six core components in the NNFX trading algorithm:
1. Volatility - price volatility; e.g., Average True Range, True Range Double, Close-to-Close, etc.
2. Baseline - a moving average to identify price trend
3. Confirmation 1 - a technical indicator used to identify trends
4. Confirmation 2 - a technical indicator used to identify trends
5. Continuation - a technical indicator used to identify trends
6. Volatility/Volume - a technical indicator used to identify volatility/volume breakouts/breakdown
7. Exit - a technical indicator used to determine when a trend is exhausted
What is Volatility in the NNFX trading system?
In the NNFX (No Nonsense Forex) trading system, ATR (Average True Range) is typically used to measure the volatility of an asset. It is used as a part of the system to help determine the appropriate stop loss and take profit levels for a trade. ATR is calculated by taking the average of the true range values over a specified period.
True range is calculated as the maximum of the following values:
-Current high minus the current low
-Absolute value of the current high minus the previous close
-Absolute value of the current low minus the previous close
ATR is a dynamic indicator that changes with changes in volatility. As volatility increases, the value of ATR increases, and as volatility decreases, the value of ATR decreases. By using ATR in NNFX system, traders can adjust their stop loss and take profit levels according to the volatility of the asset being traded. This helps to ensure that the trade is given enough room to move, while also minimizing potential losses.
Other types of volatility include True Range Double (TRD), Close-to-Close, and Garman-Klass
What is a Baseline indicator?
The baseline is essentially a moving average, and is used to determine the overall direction of the market.
The baseline in the NNFX system is used to filter out trades that are not in line with the long-term trend of the market. The baseline is plotted on the chart along with other indicators, such as the Moving Average (MA), the Relative Strength Index (RSI), and the Average True Range (ATR).
Trades are only taken when the price is in the same direction as the baseline. For example, if the baseline is sloping upwards, only long trades are taken, and if the baseline is sloping downwards, only short trades are taken. This approach helps to ensure that trades are in line with the overall trend of the market, and reduces the risk of entering trades that are likely to fail.
By using a baseline in the NNFX system, traders can have a clear reference point for determining the overall trend of the market, and can make more informed trading decisions. The baseline helps to filter out noise and false signals, and ensures that trades are taken in the direction of the long-term trend.
What is a Confirmation indicator?
Confirmation indicators are technical indicators that are used to confirm the signals generated by primary indicators. Primary indicators are the core indicators used in the NNFX system, such as the Average True Range (ATR), the Moving Average (MA), and the Relative Strength Index (RSI).
The purpose of the confirmation indicators is to reduce false signals and improve the accuracy of the trading system. They are designed to confirm the signals generated by the primary indicators by providing additional information about the strength and direction of the trend.
Some examples of confirmation indicators that may be used in the NNFX system include the Bollinger Bands, the MACD (Moving Average Convergence Divergence), and the MACD Oscillator. These indicators can provide information about the volatility, momentum, and trend strength of the market, and can be used to confirm the signals generated by the primary indicators.
In the NNFX system, confirmation indicators are used in combination with primary indicators and other filters to create a trading system that is robust and reliable. By using multiple indicators to confirm trading signals, the system aims to reduce the risk of false signals and improve the overall profitability of the trades.
What is a Continuation indicator?
In the NNFX (No Nonsense Forex) trading system, a continuation indicator is a technical indicator that is used to confirm a current trend and predict that the trend is likely to continue in the same direction. A continuation indicator is typically used in conjunction with other indicators in the system, such as a baseline indicator, to provide a comprehensive trading strategy.
What is a Volatility/Volume indicator?
Volume indicators, such as the On Balance Volume (OBV), the Chaikin Money Flow (CMF), or the Volume Price Trend (VPT), are used to measure the amount of buying and selling activity in a market. They are based on the trading volume of the market, and can provide information about the strength of the trend. In the NNFX system, volume indicators are used to confirm trading signals generated by the Moving Average and the Relative Strength Index. Volatility indicators include Average Direction Index, Waddah Attar, and Volatility Ratio. In the NNFX trading system, volatility is a proxy for volume and vice versa.
By using volume indicators as confirmation tools, the NNFX trading system aims to reduce the risk of false signals and improve the overall profitability of trades. These indicators can provide additional information about the market that is not captured by the primary indicators, and can help traders to make more informed trading decisions. In addition, volume indicators can be used to identify potential changes in market trends and to confirm the strength of price movements.
What is an Exit indicator?
The exit indicator is used in conjunction with other indicators in the system, such as the Moving Average (MA), the Relative Strength Index (RSI), and the Average True Range (ATR), to provide a comprehensive trading strategy.
The exit indicator in the NNFX system can be any technical indicator that is deemed effective at identifying optimal exit points. Examples of exit indicators that are commonly used include the Parabolic SAR, the Average Directional Index (ADX), and the Chandelier Exit.
The purpose of the exit indicator is to identify when a trend is likely to reverse or when the market conditions have changed, signaling the need to exit a trade. By using an exit indicator, traders can manage their risk and prevent significant losses.
In the NNFX system, the exit indicator is used in conjunction with a stop loss and a take profit order to maximize profits and minimize losses. The stop loss order is used to limit the amount of loss that can be incurred if the trade goes against the trader, while the take profit order is used to lock in profits when the trade is moving in the trader's favor.
Overall, the use of an exit indicator in the NNFX trading system is an important component of a comprehensive trading strategy. It allows traders to manage their risk effectively and improve the profitability of their trades by exiting at the right time.
How does Loxx's GKD (Giga Kaleidoscope Modularized Trading System) implement the NNFX algorithm outlined above?
Loxx's GKD v2.0 system has five types of modules (indicators/strategies). These modules are:
1. GKD-BT - Backtesting module (Volatility, Number 1 in the NNFX algorithm)
2. GKD-B - Baseline module (Baseline and Volatility/Volume, Numbers 1 and 2 in the NNFX algorithm)
3. GKD-C - Confirmation 1/2 and Continuation module (Confirmation 1/2 and Continuation, Numbers 3, 4, and 5 in the NNFX algorithm)
4. GKD-V - Volatility/Volume module (Confirmation 1/2, Number 6 in the NNFX algorithm)
5. GKD-E - Exit module (Exit, Number 7 in the NNFX algorithm)
(additional module types will added in future releases)
Each module interacts with every module by passing data to A backtest module wherein the various components of the GKD system are combined to create a trading signal.
That is, the Baseline indicator passes its data to Volatility/Volume. The Volatility/Volume indicator passes its values to the Confirmation 1 indicator. The Confirmation 1 indicator passes its values to the Confirmation 2 indicator. The Confirmation 2 indicator passes its values to the Continuation indicator. The Continuation indicator passes its values to the Exit indicator, and finally, the Exit indicator passes its values to the Backtest strategy.
This chaining of indicators requires that each module conform to Loxx's GKD protocol, therefore allowing for the testing of every possible combination of technical indicators that make up the six components of the NNFX algorithm.
What does the application of the GKD trading system look like?
Example trading system:
Backtest: Solo Confirmation Complex Backtest as shown on the chart above
Baseline: Hull Moving Average as shown on the chart above
Volatility/Volume: Hurst Exponent as shown on the chart above
Confirmation 1: Fisher Trasnform as shown on the chart above
Confirmation 2: Williams Percent Range
Continuation: Volatility-Adaptive Rapid RSI T3
Exit: Rex Oscillator
Each GKD indicator is denoted with a module identifier of either: GKD-BT, GKD-B, GKD-C, GKD-V, or GKD-E. This allows traders to understand to which module each indicator belongs and where each indicator fits into the GKD system.
Giga Kaleidoscope Modularized Trading System Signals (based on the NNFX algorithm)
Standard Entry
1. GKD-C Confirmation 1 Signal
2. GKD-B Baseline agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume agrees
Baseline Entry
1. GKD-B Baseline signal
2. GKD-C Confirmation 1 agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume agrees
6. GKD-C Confirmation 1 signal was less than 7 candles prior
Volatility/Volume Entry
1. GKD-V Volatility/Volume signal
2. GKD-C Confirmation 1 agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 2 agrees
5. GKD-B Baseline agrees
6. GKD-C Confirmation 1 signal was less than 7 candles prior
Continuation Entry
1. Standard Entry, Baseline Entry, or Pullback; entry triggered previously
2. GKD-B Baseline hasn't crossed since entry signal trigger
3. GKD-C Confirmation Continuation Indicator signals
4. GKD-C Confirmation 1 agrees
5. GKD-B Baseline agrees
6. GKD-C Confirmation 2 agrees
1-Candle Rule Standard Entry
1. GKD-C Confirmation 1 signal
2. GKD-B Baseline agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
Next Candle:
1. Price retraced (Long: close < close or Short: close > close )
2. GKD-B Baseline agrees
3. GKD-C Confirmation 1 agrees
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume agrees
1-Candle Rule Baseline Entry
1. GKD-B Baseline signal
2. GKD-C Confirmation 1 agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 1 signal was less than 7 candles prior
Next Candle:
1. Price retraced (Long: close < close or Short: close > close )
2. GKD-B Baseline agrees
3. GKD-C Confirmation 1 agrees
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume Agrees
1-Candle Rule Volatility/Volume Entry
1. GKD-V Volatility/Volume signal
2. GKD-C Confirmation 1 agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 1 signal was less than 7 candles prior
Next Candle:
1. Price retraced (Long: close < close or Short: close > close)
2. GKD-B Volatility/Volume agrees
3. GKD-C Confirmation 1 agrees
4. GKD-C Confirmation 2 agrees
5. GKD-B Baseline agrees
PullBack Entry
1. GKD-B Baseline signal
2. GKD-C Confirmation 1 agrees
3. Price is beyond 1.0x Volatility of Baseline
Next Candle:
1. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
2. GKD-C Confirmation 1 agrees
3. GKD-C Confirmation 2 agrees
4. GKD-V Volatility/Volume Agrees
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!
Premium PRISM Algorithm [ByteBoost]The ByteBoost PRISM strategy is designed to operate in various market conditions by leveraging the concept of brownian motion theory, which refers to the unpredictable movement of particles suspended in a fluid. This characteristic of random motion can be effectively utilized for analyzing time series data, such as market candles. Based on this notion, we are making the following assumptions regarding the market.
The stock price exhibits characteristics of Brownian motion.
The stock price is distributed in a log-normal pattern.
Volatility remains constant over time.
Options can only be exercised upon expiration.
Risk-free interest does not fluctuate over time.
There are no random or arbitrary opportunities present in the market.
Development Notes
This Strategy was developed with the PineScript language, version 5. This indicator, and most of the descriptions below, were derived largely from the TradingView reference manual. Feedback and suggestions for improvement are more than welcome, as well as recommended input settings and best practices to assist and guide new users effectively.
Features
The ByteBoost PRISM indicator is capable of analyzing multiple aspects of market behavior simultaneously such as:
Detection of potential trend reversals.
Assessment of trend strength and market sentiment.
Identification of stop loss levels.
Discovery of potential entry and exit points.
Ensuring compatibility and effectiveness with other indicators.
Visualization of strategy using historical data.
Customization options available.
Strategy Description
PRISM is an all in one strategy that allows the visualization of entry and exit points as well as the historical performance for every set of parameters. PRISM is a slow paced indicator recommended for the 1h timeframe, because it operates on the belief that markets move in a Brownian motion, for which it leaves enough space and time for the market to decide a trend and catch it at the right time as well as finding appropriate exits given the trend.
PRISM can exist in either an uptrend or downtrend state, but it does not necessarily imply that it reflects the true trend being observed. Instead, it emphasizes capturing significant movements and capitalizing on them by utilizing oscillator levels and exit points calculated based on oversold or overbought values, along with the volatility associated with these movements.
Usage
To use this strategy it is first needed to select a correct set of inputs that correspond to the market you are using, the extra, win difference and oscillator length are dependent on the current market and the average price it manages, so these inputs need to be modified for every pair of assets used.
The long and short tags signify the opportune moment to initiate a new position in the market, whether it's a long or short position, respectively. The exit tags indicate when these positions should be closed. If no exits occur before a new long or short position emerges, it is essential to conclude the existing position and commence a new one in the opposite direction.
Regarding exits, up to two exits can be executed for each movement. The user has the flexibility to determine how these exits are utilized. In the input section, a specific percentage of equity can be selected to be sold during the first exit. If set to 100%, only a single exit will be presented. Otherwise, the remaining equity will be sold during the second exit or at the next trend reversal depending on which action occurs first.
In case the user requires additional exits beyond the initial two, the alternative exits option can be activated in the inputs. This will provide access to supplementary exits, although they may be less advisable compared to the primary exits.
Inputs / Settings
Capital - If using any leverage multiply the amount of money to invest by the leverage, else input the amount to be invested in every trade.
Start date - The date from which the strategy should begin its analysis. Leave unchanged to start from the earliest available date based on your account's plan.
End date - The date until which the strategy should conduct its analysis. Leave unchanged to continue until the current date.
Extra - The minimum gain required in the market to trigger an exit opportunity. It can be a negative number to allow exits at a loss, potentially minimizing losses.
First exit % - If an exit is decided to be partial, it is very likely that there will be a second exit, this parameter determines the percentage of equity to be sold at the first exit. Note that a second exit may not always be applicable.
Win difference - The minimum difference between the entry point and the first exit to determine whether it should be a full exit or a partial exit, as the exit price approaches the entry price, the probability of a trend reversal increases, a full exit is beneficial.
Limit length - Specifies the number of candles to consider for the overbought and oversold market calculation.
Low limit - Sets the minimum value of the limit to decide a short exit.
High limit - Sets the maximum value of the limit to decide a long exit.
Band length - Determines the number of candles to consider for the volatility analysis.
Band height - Sets the multiplication factor of the band to set the maximum and minimum height.
Increment - Determines the rate at which trend reversals occur. A higher value brings the line closer to the current price faster.
Candles exit - Specifies the minimum number of candles required to pass for an exit to become available after initiating a new position.
Oscillator - Enables or disables the main oscillator, which helps determine entry points. Not all assets may benefit from this parameter.
Oscillator length - Specifies the number of candles considered for the entry points oscillator.
Highlighter - Applies a light color between the trend and average price of each bar.
Trend Labels - Displays labels indicating an uptrend or downtrend.
Signal Labels - View the labels indicating a new long or short position.
Exit Labels - Displays the labels indicating exit points.
Candle color - Color codes the inside of the candles with the current signal.
Cloud - Visualize the average price cloud to determine trend direction.
Oscillator points - Adds visual dots to indicate when the oscillator has changed its trend.
Oscillator line - Displays the values of the oscillator to indicate upcoming trend changes.
Alternative exits - Shows additional exits to the ones we recommend, useful if the user missed an exit or needs to have more than two.
Color uptrend - Determines the color scheme for identifying uptrend movements.
Color downtrend - Determines the color scheme for identifying downtrend movements.
Color long - Sets the color scheme for a new long position.
Color short - Sets the color scheme for a new short position.
Color exit - Decides the color scheme for the exit tag and cross shown.
Color alternative exit - Changes the color scheme for the alternative exit cross.
Color oscillator line - Determines the color scheme used for the oscillator line.
Indicator Visuals
The strategy plots the direction of the trend on the chart and changes its color based on this. It also plots shapes on the chart to denote potential buy (Long) and sell (Short) points, where the signals of short and long will appear as well as exit points which can be found as three different,
Exit 1 - A partial exit which sells the previously selected percentage of equity.
Exit 2 - A second exit that can only happen after an Exit 1 has happened, and sell the remaining amount of equity.
Exit Full - A full exit is executed when the price at the exit point is lower than the entry price plus the win difference value. This condition indicates that it is more advantageous to take a single exit rather than waiting for a second exit.
Strategy Alerts
The strategy does not include built-in alerts. However, alerts can be added using the TradingView interface based on the strategy's buy and sell conditions. This way you will be able to receive notifications on your computer or phone when a new signal goes out.
Details
Repainting: It is important to mention that the strategy can mark false long or short signals, as the oscillator is allowed to repaint on the same candle. So users must make sure the candle has closed on buy/sell conditions.
Excessive capital issue: If you configure the strategy with a big amount of capital (+$1,000,000 for example) it is possible that it will completely stop calculating exit signals, as they will be too big for TradingView’s engine to process.
Conclusion
The ByteBoost PRISM strategy empowers traders by providing comprehensive market analysis, clear entry and exit signals, and the ability to visualize strategy performance using historical data. It is a superior algorithm that maximizes profit potential and minimizes risks, making it the preferred choice for traders seeking a competitive edge in the financial markets.
Disclaimer
This strategy is provided as-is, with no guarantee of profits or responsibility for losses. Trading involves risk, and you should only trade with money you can afford to lose. Always conduct your own research and consider your financial situation before engaging in trading.
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.
Premium Volatility Breakout Strategy [wbburgin]This the premium version of my Volatility Breakout strategy, which improves significantly on the original strategy (publicly available on my profile). Improvements are below. A note about any of my premium scripts: I will continue updating and improving the original (public) versions.
This strategy is not built for any specific asset or timeframe, and has been backtested on crypto, equities, and forex from 1min - 1day. However, I recommend using it on more volatile assets because it is a breakout strategy.
********** My Background
I am an investor, trader, and entrepreneur with 10 years of cryptocurrency and equity trading experience and founder of two fintech startups. I am a graduate of a prestigious university in the United States and carry broad and inclusive interests in mathematical finance, computer science, machine learning / artificial intelligence, as well as other fields.
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Improvements over the original Volatility Breakout strategy include:
Faster Trend Detection → The Premium Volatility Breakout strategy will catch trends faster by using adaptive volatility-weighted bands instead of standard-width volatility-weighted bands. This can improve win size and has performed well in my backtesting.
ADX Filter → False breakouts dampen the overall results of the original script, as well as the % profitable,so an ADX filter has been programmed into the script (toggle on/off in settings). This filter will only enter long and short trades when the ADX is above a certain threshold. This is by default toggled off because in most instances it will not be necessary, but in certain environments may be useful.
MA Configuration → Different types of moving averages and weights are now configurable in the settings. These can change the responsiveness of the strategy.
External Trend Filter → I use this strategy as a filter for some of my low-timeframe algorithms. I have added an external trend filter (a plot only displayed in the data window) that will return “1” when the trend is long and “-1” when the trend is short (displayed on-chart with red and green trend curves).
Customizable Alert Messages In-Strategy → In the settings, there will be text boxes where you can create your own alerts. All you will need to do is create an alert in the alert panel on TradingView and leave the message box blank - if you fill out the alert boxes in the settings, these will automatically populate into your alerts. There are in total four different customizable alerts messages: Entry and Exit alerts for both Long and Short sides. If you disable stop loss and/or take profit, these alerts will also be disabled. Similarly, if you disable shorts, all short alerts will be disabled.
About stop losses: This strategy does not come with a stop loss because the moving average acts as a stop loss / trade exit for both long and short entries.
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Display
You can turn off highlighting or barcolor in the settings. Additionally, future updates may include a color scheme for users using a light-themed window.
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Configuring Alerts
In TradingView desktop, go to the ‘Alerts’ tab on the right panel. Click the “+” button to create a new alert. Select this strategy for the condition and one of the two options that includes alert() function calls. Name the alert what you wish and clear the default message, because your text in the settings will replace this message.
Now that the alert is configured, you can go to the settings of the strategy and fill in your chosen text for the specific alert condition. You will need to check “Long and Short” in the “Trade Direction” setting in order for any Short Alerts to become active.
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Disclaimer
Copyright by wbburgin.
The information contained in my Scripts/Indicators/Algorithms 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.
Cyatophilum SmartStrategy MakerThis indicator allows you to use any other indicator from the TradingView library and create complex entry and exit conditions with ease thanks to several external inputs. Add risk management to your strategy and backtest it before creating alerts!
Key Features:
1 — Entry Conditions: Traders can define their entry conditions using up to three sources. They can choose from several options such as "Cross," "Crossover," "Crossunder," "Above," "Below," or "Equal" for comparing the selected sources.
2 — Entry Gates: Users can set logical gates (e.g., "AND," "OR," "XOR," "NAND," "XNOR") to combine multiple entry conditions.
3 — Exit Conditions: Similar to entry conditions, traders can define exit conditions based on two sources and select from various comparison options.
4 — Stop Loss: The indicator allows users to enable or disable a stop-loss feature. The stop-loss value is calculated based on a percentage of the base order price.
5 — Take Profit: Traders can set multiple take-profit levels by specifying the number of take profits, a base percentage, and a step value. Take profits can be defined as a percentage from the total volume or the base order.
6 — Safety Orders (DCA): The indicator supports the use of safety orders (Dollar Cost Averaging) to help manage risks. Users can set the number of safety orders, price deviation, step scale, and volume scale.
7 — Backtest Settings: Traders can define the start and end periods for backtesting their strategy. This feature allows them to analyze the performance of their strategy within specific timeframes.
8 — Alerts: The indicator provides the option to create alerts for entry, exit, stop loss, take profit, and safety orders. Users can customize the alert messages using placeholders for dynamic values like price, symbol, and order size.
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.
Source CorrelationIn this small indicator I make it possible for the user to set two different input sources. Then, the indicator displays the correlation of these two input sources. It's a very small script, but I think it could be helpful to somebody to find uncorrelated indicators for his trading strategy. To use uncorrelated indicators is in general recommended.
Enjoy this small, but powerful tool. 🧙♂️
Volatility Breakout Strategy [Angel Algo]As traders, we're always looking for opportunities to profit from sudden price breakouts, and the Volatility Breakout Strategy aims to do just that.
This script is the perfect starting point for traders who want to experiment with capturing price movements resulting from increased volatility. The script plots the Average True Range (ATR) on the chart, which is a measure of the asset's volatility over a specified period. By setting the "Length" parameter, you can customize the period over which the volatility is measured.
Using the ATR, the strategy calculates upper and lower breakout levels and plots them on the chart. The signals for long and short positions are generated when the price crosses above the upper breakout level or below the lower breakout level, respectively. They are confirmed by checking the current bar state.
The strategy also fills the space between the upper and lower breakout levels with a color that indicates the latest signal direction. This feature helps traders quickly identify the prevailing trend.
The strategy uses the generated signals to enter trades. When a long or short signal is confirmed, and there is no open position in the direction of the signal, the strategy enters a long or short trade, respectively.
Choice of parameters.
Choosing the right value for the Length input parameter is crucial for tailoring the Volatility Breakout Strategy to suit your trading preferences. In general, a higher Length value implies a focus on capturing longer price moves. For instance, in this script, we have set the Length value to 20, resulting in trades that span approximately 100 candles. These trades encompass price trends consisting of multiple swings.
However, if your goal is to trade individual swings rather than longer trends, it's advisable to experiment with smaller values for the Length parameter. By reducing the Length, you can target shorter-term price movements and potentially increase the frequency of trades.
It's important to note that while a higher Length value tends to lead to longer trades, there is no strict correlation between the Length parameter and the average length of trades. This can vary across different markets. Therefore, it's essential to conduct thorough experimentation with various Length values and closely observe the length of trades they generate. Comparing these trade lengths with the average trend or swing length in the specific market can provide valuable insights.
Ideally, you should aim to select a Length value that aligns with the average trend or swing length observed in the market you are trading. This way, you can optimize the strategy to capture price movements that closely match the prevailing market conditions.
Remember, finding the optimal Length value is a process of trial and error, combined with careful observation of trade lengths and their correlation with market trends. So, don't be afraid to experiment and refine the Length parameter to maximize the effectiveness of the Volatility Breakout Strategy in your chosen market.
Disclaimer: This trading strategy is provided for educational and informational purposes only.Trading involves risk, and past performance is not indicative of future results.
Premium MTF Layered RSI - Bitcoin Bot [wbburgin]This the premium version of my MTF Layered RSI strategy, which improves significantly on the original strategy (publicly available on my profile). Improvements are below. This strategy will also appear as an overlay on your chart. It is completely non-repainting.
The MTF Layered RSI strategy uses the current timeframe and two configurable higher timeframes to enter a long position when Bitcoin is oversold on all three timeframes, and exit the long position when Bitcoin is overbought on the current timeframe. This hedges against situations where the RSI on higher timeframes never reaches the overbought level and we are left "holding the bag" so to speak with the classic "enter long at oversold and enter short at overbought" strategy.
IMPORTANT: This strategy does not work on ranges. It will work on all timeframes and assets, but does not work on ranges (Renko blocks and some other advanced types of charts).
********** My Background
I am an investor, trader, and entrepreneur with 10 years of cryptocurrency and equity trading experience and founder of two fintech startups. I am a graduate of a prestigious university in the United States and carry broad and inclusive interests in mathematical finance, computer science, machine learning / artificial intelligence, as well as other fields.
**********
Improvements over the original MTF RSI strategy include:
Filters for Uptrends and Downtrends → The Premium RSI strategy will adjust its buy and sell thresholds depending on whether the instrument is trending. This means that, in uptrends, the Premium strategy will buy more frequently, bringing in potentially greater profit, and in downtrends, the strategy will stop buying altogether. These filters and dynamic buy/sell thresholds have made this strategy more profitable in my backtesting across random timeframes, but I cannot guarantee that the strategy will be profitable for you on the default settings. To that end, I have enabled a number of different configurations that you can change in the settings of the strategy.
Stop Loss / Take Profit Calculation Per Tick → Stop loss and take profit are now both enabled in the script and each has their own alerts. You can specify what type of stop loss or take profit you want: percentage or ATR. If you have alerts configured, you will be alerted mid-bar, instead of at close. This helps prevent loss from abrupt falls in price between closing price and next bar open.
Customizable Alert Messages In-Strategy → In the settings, there will be text boxes where you can create your own alerts. All you will need to do is create an alert in the alert panel on Tradingview and leave the message box blank - if you fill out the alert boxes in the settings, these will automatically populate into your alerts. There are in total eight different customizable alerts messages: Entry, Exit, Stop loss, and Take profit alerts for both Long and Short sides. If you disable stop loss and/or take profit, these alerts will also be disabled. Similarly, if you disable shorts, all short alerts will be disabled.
**********
Display
Configuring Stop Loss or Take Profit will make their corresponding displays appear.
Separately from the trading boxes, background colors (green, red) signify extended uptrends and downtrends, respectively.
Configuring Alerts
In TradingView desktop, go to the ‘Alerts’ tab on the right panel. Click the “+” button to create a new alert. Select this strategy for the condition and one of the two options that includes alert() function calls. Name the alert what you wish and clear the default message, because your text in the settings will replace this message.
Now that the alert is configured, you can go to the settings of the strategy and fill in your chosen text for the specific alert condition. You will need to check “Long and Short” in the “Trade Direction” setting in order for any Short Alerts to become active. Similarly, you will need to check “Enable Stop Loss” for stop loss alerts to become active and “Enable Take Profit” for take profit alerts to become active.
**********
Disclaimer
Copyright by wbburgin.
The information contained in my Scripts/Indicators/Algorithms 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.
**********
Notes on the Strategy Performance below: This is 3% of equity per trade, with a pyramiding number of 3. I did not include fees because Binance US on Bitcoin/USD does not charge fees on the instrument; however, I heavily encourage you to include fees in your backtesting if you use a different brokerage. To mitigate fees, this strategy is designed with a high average %/trade. If your current fees are greater than the strategy's average %/trade, I encourage you to choose a higher RSI period, such as 14 or 28, which will result in less trades but potentially a higher %/trade.
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.
Rainbow IndicatorName of the indicator: Rainbow indicator
A brief description of the indicator:
Using this indicator, you can see the "margin of safety" for opening a position in shares of fundamentally strong companies with an acceptable P/E level, as well as the price range for closing a position.
The background to the creation of the indicator:
I got the idea to create this indicator thanks to the concept of the "margin of safety", which was invented by the father of value investing - Benjamin Graham. According to his idea, it is reasonable to buy shares of a company only when the price offered by the market is lower than the "intrinsic value" calculated on the basis of financial statements. The value of this difference is the "margin of safety”. At the same time, the indicator does not copy Graham's idea but develops it relying on my own methodology.
So, according to Graham, the "margin of safety" is a good discount to the intrinsic value of the company. That is, if a company's stock is trading at prices that are well below the company's intrinsic value (on a per-share basis), it's a good opportunity to consider buying it. In this case, you will have a certain margin of safety in case the company is in financial distress and its stock price goes down. Accordingly, the greater the discount, the better.
When it comes to the intrinsic value of a company, there are many approaches to determining it - from calculating the Price-to-book value financial ratio to the discounted cash flow method. As for my approach, I am not trying to find the cherished intrinsic value, but I am trying to understand how fundamentally strong the company is in front of me, and in how many years the investment in it will pay off. To determine fundamental strength, I use the appropriate Fundamental Strength Indicator . To estimate the payback period, I use the P/E ratio (*). If I am satisfied with both of these indicators, I move on to the Rainbow Indicator.
(*) If you want to learn more about the P/E ratio, I suggest reading my two articles on TradingView:
Price / Earnings: Interpretation #1
Price/Earnings: amazing interpretation #2
Indicator calculation methodology:
The Rainbow indicator starts with a simple moving average of one year (this is the thick red line in the center). Hereinafter a year will mean the last 252 trading days.
Applying a moving average of this length - is a good way to smooth out sharp price fluctuations which can happen during a year as much as possible, keeping the trend direction as much as possible. Thus, the moving average becomes for me the center of fluctuations of the imaginary pendulum of the market price.
Then the deviations are calculated from the center of fluctuations. To do this, a certain amount of earnings per share is subtracted from and added to the moving average. This is the diluted EPS of the last year.
Deviations with a "-" sign form the Lower Rainbow of four colors:
- The blue spectrum of the lower rainbow begins with a deflection of -4 EPS and ends with a deflection of -8 EPS.
- Green spectrum of the lower rainbow begins with a deflection of -8 EPS and ends with a deflection of -16 EPS.
- The orange spectrum of the lower rainbow begins with a deflection of -16 EPS and ends with a deflection of -32 EPS.
- Red spectrum of the lower rainbow begins with a deflection of -32 EPS and goes to infinity.
The Lower Rainbow is used to determine the price ranges that can be considered for buying stocks. It is in the spectra of the Lower Rainbow that the very "margin of safety" according to my methodology is located. The Lower Rainbow has the boundaries between the spectra as a solid line . And only the red spectrum of the Lower Rainbow has only one boundary.
Deviations with a "+" sign form the Upper Rainbow of four similar colors:
- The red spectrum of the upper rainbow begins with a deflection of 0 EPS and ends with a deflection of +4 EPS.
- The orange spectrum of the upper rainbow begins with a deflection of +4 EPS and ends with a deflection of +8 EPS.
- Green spectrum top rainbow begins with a deflection of +8 EPS and ends with a deflection of +16 EPS.
- The blue spectrum of the upper rainbow begins with a deflection of +16 EPS and goes to infinity.
The Upper Rainbow is used to determine the price ranges that can be considered for selling stocks already purchased. The top rainbow has boundaries between the spectra in the form of crosses . And only the blue spectrum of the upper rainbow has only one boundary.
The presence of the Empty Area (the size of 4 EPS) above the Lower Rainbow creates some asymmetry between the two rainbows - the Lower Rainbow looks wider than the Upper Rainbow. This asymmetry is deliberate because the market tends to fall much faster and deeper than it grows . Therefore, a wider Lower Rainbow is conducive to buying stocks at a good discount during a period of massive "sell-offs.
The situation, when the Lower Rainbow is below the center of fluctuations (the thick red line) and the Upper Rainbow, is above the center of fluctuations is called an Obverse . It is only possible to buy a stock in an Obverse situation .
The situation when the Lower Rainbow is above the center of fluctuations and the Upper Rainbow is below the center of fluctuations is called Reverse . In this situation, the stock cannot be considered for purchase , according to my approach.
Selling a previously purchased stock is possible in both situations: Reverse and Obverse. After loading the indicator, you can see a hint next to the closing price - Reverse or Obverse now.
Due to the fact that the size of the deviation from the center of fluctuation depends on the size of the diluted EPS, several important conclusions can be made:
- The Obverse situation is characteristic of companies that show a profit over the last year.
- The Reverse situation is typical for companies that show a loss over the last year.
- An increase in the width of both rainbows in the Obverse situation tells us about an increase in profits for the company.
- A decrease in the width of both rainbows in the Obverse situation tells us about a decrease in the company's profits.
- An increase in the width of both rainbows in the Reverse situation tells us about an increase in the company's losses.
- A decrease in the width of both rainbows in the Reverse situation tells us about a decrease in the company's losses.
- The higher the profit level of the company, the greater your "margin of safety" should be. This will provide the necessary margin of safety in case you go into a cycle of declining financial results. The appropriate width of the Lower Rainbow will just create this "margin".
- Increased profits in the company (after buying its stock) will allow you to stay in position longer by widening the Upper Rainbow.
- A decrease in profits in the company (after buying its stock) will allow you to close your position more quickly by narrowing the Upper Rainbow.
Conditions for opening and closing positions:
So, the Lower Rainbow has four differently colored spectra: blue, green, orange, and red. Each one highlights the desired range of prices acceptable for buying in an Obverse situation. The blue spectrum is upper with respect to the green spectrum, and the green spectrum is lower with respect to the blue spectrum, etc.
- If the current price is in the Blue Spectrum of the Lower Rainbow, that is a reason to consider that company for buying the first portion (*) of the stock.
- If the current price has fallen below (into the Green Spectrum of the Lower Rainbow), that is a reason to consider this company to buy a second portion of the stock.
- If the current price has fallen below (into the Orange Spectrum of the Lower Rainbow), it is a reason to consider this company to buy a third portion of the stock.
- If the current price has fallen below (into the Red Spectrum of the Lower Rainbow), that is a reason to consider that company to buy a fourth portion of the stock.
(*) The logic of the Rainbow Indicator implies that no more than 4 portions of one company's stock can be purchased. One portion refers to the number of shares you can consider buying at the current price (depending on your account size and personal diversification ratio - see information below).
The Upper Rainbow also has four differently colored spectra: blue, green, orange, and red. Each of them highlights the appropriate range of prices acceptable for closing an open position.
- If the current price is in the red spectrum of the Upper Rainbow, I close one portion of an open position bought in the red spectrum of the Lower Rainbow.
- If the current price is in the orange spectrum of the Upper Rainbow, I close one portion of an open position bought in the orange spectrum of the Lower Rainbow.
- If the current price is in the green spectrum of the Upper Rainbow, I close one portion of an open position bought in the green spectrum of the Lower Rainbow.
- If the current price is in the blue spectrum of the Upper Rainbow, I close one portion of an open position bought in the blue spectrum of the Lower Rainbow.
This position-closing logic applies to both the Obverse and Reverse situations. In both cases, the position is closed in portions in four steps. However, there are 3 exceptions to this rule when it is possible to close an entire position in whole rather than in parts:
- If there is a Reverse situation and the current price is above the thick red line.
- If I decide to invest in another company and I do not have enough available cash to purchase the necessary number of portions.
- If I find out about events that pose a real threat to the further existence of the company (for example, a bankruptcy filing), I can close the position earlier, without waiting for the price to hit the corresponding Upper Rainbow spectrum.
So, the basic scenario of opening and closing a position assumes the gradual purchase of shares in 4 stages and their gradual sale in 4 stages. However, there is a situation where one of the stages is skipped in the case of buying shares and in the case of selling them. For example, because the Fundamental Strength Indicator and the P/E ratio became acceptable for me only at a certain stage (spectrum) or the moment was missed for a transaction due to technical reasons. In such cases, I buy or sell more than one portion of a stock in the spectrum I am in. The number of additional portions will depend on the number of missed spectra. For example, if I have no position in the stock of the company in question, all conditions for buying the stock have been met, and the current price is in the orange spectrum of the Lower Rainbow, I can buy three portions of the stock at once (for the blue, green, and orange spectrum). I will sell these three portions in the corresponding Upper Rainbow spectra (orange, green, and blue). However, if for some reason the orange spectrum of the Upper Rainbow was missed, and the current price is in the green spectrum - I will sell two portions of the three (in the green spectrum). I will sell the last, third portion only when the price reaches the blue spectrum of the Upper Rainbow.
The Rainbow Indicator also helps calculate the number of shares that can be considered for purchase at the current price position in the Lower Rainbow spectra. To do this, you need to go to the indicator settings.
+ Cash in - Cash out +/- Closed profit/loss + Dividends - Fees - Taxes
Here I indicate the amount of funds deposited to my account, withdrawn from it, profit/loss on closed positions, dividends credited to the account, and taxes deducted from the account.
Diversification coefficient
The diversification coefficient determines how diversified I want my portfolio to be. For example, a diversification coefficient of 20 means that I plan to buy 20 share portions of different companies, but no more than 4 portions per company (based on the number of Lower Rainbow spectra).
The cost of purchased shares of this company (fees excluded)
Here I specify the amount of already purchased shares of the company in question in the currency of my portfolio. For example, if at this point in time, I have purchased 1000 shares at $300 per share, and my portfolio is expressed in $, I enter - $300,000.
The cost of all purchased shares in the portfolio (fees excluded)
Here I enter the amount of all purchased shares for all companies in the currency of my portfolio (without commissions spent on the purchase). This is necessary to determine the amount of available funds available to purchase shares.
After entering all the necessary data, I go to the checkbox, by checking it I confirm that the company in question has been studied with the Fundamental Strength Indicator and the P/E ratio, and their values are satisfactory to me. No calculation is performed without the checkbox checked. This is done intentionally because the application of the Rainbow Indicator for stock acquisition purposes is possible only after studying the Fundamental Strength of the company and an acceptable P/E value.
Next, I click "Ok" and get the calculation in the form of a table on the left.
Free cash in the portfolio
This is the amount of free cash available to purchase stocks. Please note that the price of the stock and the funds in your portfolio must be denominated in the same currency. On TradingView, you can choose which currency to display the stock price in.
Cash amount for one portion
The amount of cash needed to buy one portion of a stock. Depends on the diversification ratio entered.
Potential portions amount
Number of portions, available for purchase at the current price. Can be a fractional number.
Cash amount to buy
The amount of cash needed to buy portions available for purchase at the current price.
Shares amount to buy
Number of shares in portions available for purchase at the current price.
The table also contains additional information in the form of the current value of the company's market capitalization and P/E ratio.
Mandatory requirements for using the indicator:
- works only on a daily timeframe;
- the indicator is only applicable to shares of public companies;
- quarterly income statements for the last year are required;
- an acceptable for you P/E ratio is required to consider the company's stock for purchase;
- the Rainbow Indicator only applies in tandem with the Fundamental Strength Indicator. To consider a company's stock for purchase, you need confirmation that the company is fundamentally strong.
What is the value of the Rainbow Indicator?
- clearly demonstrates a company's profit and loss dynamics;
- shows the price ranges that can be used to open and close a position;
- takes into account the principle of gradual increase and decrease of a position;
- allows calculating the number of shares to be purchased;
- shows the current value of the P/E ratio;
- shows the current capitalization of the company.
Example:
As an example, consider the situation with NVIDIA Corporation stock (ticker - NVDA).
September 02, 2022:
Fundamental Strength Indicator - 11.46 (fundamentally strong company).
P/E - 39.58 (acceptable to me).
Current Price - $136.47 (is in the Orange Spectrum of the Lower Rainbow).
Situation - Obverse.
The basic conditions for buying this company's stock are met. The Rainbow Indicator settings are filled out as follows:
The table to the left of the Rainbow Indicator shows how many shares are possible to buy in the Orange Spectrum of Lower Rainbow at the current price = 10 shares. This corresponds to 2.73 portions.
To give you an example, I buy 10 shares of NVDA at $136.47 per share.
October 14, 2022:
NVDA's stock price has moved into the red spectrum of the Lower Rainbow.
The Fundamental Strength Indicator is 10.81 (fundamentally strong company).
P/E is 35.80 (an acceptable level for me).
Current Price - $112.27 (is in the Red Spectrum of the Lower Rainbow).
Situation - Obverse.
The basic conditions for buying this company's stock are still met. The Rainbow Indicator settings are populated as follows:
The table to the left of the Rainbow Indicator shows how many shares are possible to buy in the Lower Rainbow Red Spectrum at the current price (5 shares). This corresponds to 1.12 portions.
To give you an example, I buy 5 shares of NVDA at $112.27 per share. A total of 3.85 portions were purchased, which is the maximum possible number of portions at the current price level. The remainder in the form of 0.15 portions can be purchased only at a price level below $75 per share.
January 23, 2023:
The price of NVDA stock passes through the red spectrum of the Upper Rainbow and stops in the orange spectrum. As an example, I sell 5 shares bought in the red spectrum of the Lower Rainbow, for example at $180 per share (+60%). And also a third of the shares bought in the orange spectrum, 3 shares out of 10, for example at $190 a share (+39%). That leaves me with 7 shares.
January 27, 2023:
NVDA's stock price has continued to rise and has moved into the green spectrum of the Upper Rainbow. This is a reason to close some of the remaining 7 shares. I divide the 7 shares by 2 and round up to a whole number - that's 4 shares. For my example, I sell 4 shares at $199 a share (+46%). Now I am left with 3 shares of stock.
February 02, 2023:
The price of NVDA stock moves into the blue spectrum of the Upper Rainbow, and I close the remaining 3 shares, for example, at $216 per share (+58%). The entire position in NVDA stock is closed.
As you can see, the Fundamental Strength Indicator and the P/E ratio were not used in the process of closing the position. Decisions were made only on the basis of the Rainbow Indicator.
As another example, let's look at the situation with the shares of Papa Johns International, Inc. (ticker PZZA).
November 01, 2017:
Fundamental Strength Indicator - 13.22 points (fundamentally strong company).
P/E - 21.64 (acceptable to me).
Current Price - $62.26 (is in the blue spectrum of the Lower Rainbow).
Situation - Obverse.
The basic conditions for buying shares of this company are met. The settings of the Rainbow Indicator are filled as follows:
The table to the left of the Rainbow Indicator shows how many shares are possible to buy in the Lower Rainbow Blue Spectrum at the current price - 8 shares. This corresponds to 1 portion.
To give you an example, I buy 8 shares of PZZA at a price of $62.26.
August 8, 2018:
PZZA's share price has moved into the green spectrum of the Lower Rainbow.
The Fundamental Strength Indicator is a 9.83 (fundamentally strong company).
P/E is 16.07 (an acceptable level for me).
Current Price - $38.94 (is in the green spectrum of the Lower Rainbow).
Situation - Obverse.
The basic conditions for buying shares of this company are still met. The Rainbow Indicator settings are populated as follows:
The table to the left of the Rainbow Indicator shows how many shares are possible to buy in the Lower Rainbow Green Spectrum at the current price - 12 shares. This corresponds to 0.93 portions.
To give you an example, I buy 12 shares of PZZA at a price of $38.94. A total of 1.93 portions were purchased.
October 31, 2018:
PZZA's stock price moves into the Upper Rainbow red spectrum and is $54.54 per share. Since I did not have any portions purchased in the Lower Rainbow red spectrum, there is no closing part of the position.
February 01, 2019:
After a significant decline, PZZA's stock price moves into the orange spectrum of the Lower Rainbow at $38.51 per share. However, I am not taking any action because the company's Fundamental Strength on this day is 5.02 (a fundamentally mediocre company).
March 27, 2019:
PZZA's stock price passes the green and blue spectrum of the Upper Rainbow. This allowed to close the previously purchased 12 shares, for example, at $50 a share (+28%) and 8 shares at $50.38 a share (-19%).
Closing the entire position at once was facilitated by a significant narrowing in both rainbows. As we now know, this indicates a decline in earnings at the company.
Risk disclaimer:
When working with the Rainbow Indicator, keep in mind that the release of the Income statement (from which diluted EPS is derived) occurs some time after the end of the fiscal quarter. This means that the new relevant data for the calculation will only appear after the publication of the new statement. In this regard, there may be a significant change in the Rainbow Indicator after the publication of the new statement. The magnitude of this change will depend on both the content of the new statement and the number of days between the end of the financial quarter and the publication date of the statement. Prior to the publication date of the new statement, the latest actual data will be used for the calculations. Also, once again, please note that the Rainbow Indicator can only be used in tandem with the Fundamental Strength Indicator and the P/E ratio. Without these additional filters, the Rainbow Indicator loses its intended meaning.
The Rainbow Indicator allows you to determine the price ranges for opening and closing a position gradually, based on available data and the methodology I created. You can also use it to calculate the number of shares you can consider buying taking into account the position you already have. However, this Indicator and/or its description and examples cannot be used as the sole reason for buying or selling stocks or for any other action or inaction related to stocks.
Fundamental Strength IndicatorName of the indicator: Fundamental Strength Indicator
A brief description of the indicator:
Using this indicator, you can evaluate a company in terms of the strength of its financial performance and see how that score has changed over time.
The background to the creation of the indicator:
The main idea that inspired me to create this indicator is: " Even if you buy just 1 share of a company, treat it like buying the whole business ". However, when I need to evaluate the business of thousands of public companies traded on exchanges, there is an objective difficulty: it is very time-consuming. To solve this problem, I had to create a scoring system of the fundamental analysis of the company, embodied in this indicator.
What the indicator looks like:
- First, it is a Histogram with bars of three colors: green, orange, and red. The width of the histogram depends on the depth of data from the company statements. The more historical data, the wider the histogram over time.
The green color of the bars means that the company has been showing excellent financial results by the sum of the factors in that time period. According to my terminology, the company has a " strong foundation " during this period. Green corresponds to values between 8 and 15 (where 15 is the maximum possible positive value on the sum of the factors).
The orange color of the bars means that according to the sum of factors during this period the company demonstrated mediocre financial results, i.e. it has a " mediocre foundation ". Orange color corresponds to values from 1 to 7.
The red color of the bars means that according to the sum of factors in this period of time, the company demonstrated weak financial results, i.e. it has a " weak foundation ". The red color corresponds to values from -15 to 0 (where -15 is the maximum possible negative value on the sum of factors).
- Second, this is the Blue Line , which is the moving average of the Histogram bars over the last year (*). Averaging over the year is necessary in order to obtain a weighted estimate that is not subject to medium-term fluctuations. It is by the last value of the blue line that the actual Fundamental Strength of the company is determined.
(*) The last year means the last 252 trading days, including the current trading day.
- Third, these are operating, investing, and financing Cash Flows expressed in Diluted net income. These flows look like thick green, orange, and red lines, respectively.
- Fourth, this is the Table on the left, which shows the latest actual value of the Fundamental Strength and Cash Flows.
Indicator settings:
In the indicator settings, I can disable the visibility of the Histogram, Blue Line, Cash Flows (each separately), and Table. It helps to study each of the parameters separately. It is also possible to change the color, transparency, and thickness of lines.
Mandatory requirements for using the indicator:
- works only on a daily timeframe;
- only applies to shares of public companies;
- company financial statements for the last 4 quarters and more are required;
- it is necessary to have the data from the Balance sheet, Income statement, and Cash flow statement, required for the calculation.
If at least one component required for calculating the Fundamental Strength is missing, the message " no data to calculate the Fundamental Strength correctly " is displayed. In the same case, but for the operating cash flow, the message " no data to calculate the Operating Cash Flow correctly " is shown, and similarly for other flows.
What is the value of the Fundamental Strength Indicator:
- allows for a quantitative assessment of a company's financial performance in points (from -15 to 15 points);
- allows you to visually track how the company's financial performance has changed (positively/negatively) over time;
- allows to visually trace the movement of main cash flows over time;
- speeds up the process of selecting companies for your shortlist (if you are focused on financial results when selecting companies);
- allows you to protect yourself from investing in companies with weak and mediocre fundamentals.
Indicator calculation methodology:
Guided by the "Treat stock investments as buying the whole business" approach, you can imagine what kind of business an investor is interested in owning and simultaneously determine the input parameters for calculating the indicator.
(!) Here it is important to emphasize that the idea of a benchmark business for investment is a subjective notion, so be sure to check whether it coincides with your own opinion.
For me, a benchmark business is:
- A business that operates efficiently without diminishing the return on shareholders' investment. To assess the efficiency and profitability of a business, I use the following financial ratios (*): Diluted EPS and Return on Equity (ROE). The first two parameters for calculating the indicator are there.
- A business that scales sales and optimizes its costs. From this point of view, the following financial ratios are suitable: Gross margin, Operating expense ratio, and Total revenue. Plus three other metrics.
- A business that turns goods/services into cash quickly and does not fall behind on payments to suppliers. The following financial ratios will fit here: Days payable, Days sales outstanding, and Inventory to revenue ratio. These are three more metrics.
- A business that does not resort to significant accounts payable and shows financial strength. Here I use the following financial ratios: Current ratio, Interest coverage, and Debt to revenue ratio. These are the last three parameters.
(*) If you want to learn more about these financial ratios, I suggest reading my two articles on TradingView:
Financial ratios: digesting them together
What can financial ratios tell us?
Next, each of the parameters is assigned a certain number of points based on its last value or the position of that value relative to the annual maximum and minimum.
For example, if the Current ratio:
- greater than or equal to 2 (+1 point);
- less than or equal to 1 (-1 point);
- more than 1 but less than 2 (0 points).
Or for example, if Diluted EPS:
- near or above the annual high (+2 points);
- near the annual minimum and below (-2 points);
- between the annual maximum and minimum (0 points).
And so on with each of the parameters.
As a result, the maximum number of points a company can score is 15 points. The minimum number of points a company can score is -15 points. These levels are marked with horizontal dotted lines: the green line is for the maximum value, and the red line is for the minimum.
I track the number of points for each day of a company's life on a three-color Histogram. The resulting average value for the last year is on the Blue Line. For me, it is the last value of the Blue Line that determines - this is the actual Fundamental Strength of the company.
The business valuation model I created is more suitable for companies that produce goods or services, and where tangible assets play a significant role in the business. For example, when analyzing companies in the financial sector, you may see the message "no data to calculate the Fundamental Strength correctly". Many of them may simply be missing data that is used as input for the calculation: Inventory to revenue ratio, Days sales outstanding, etc.
Examples:
Below I will evaluate various companies using the Fundamental Strength Indicator.
Tesla, Inc.
The indicator shows that since 2020, Tesla Inc. has been steadily increasing its Fundamental Strength (from 3.27 in Q1 2020 to 12.79 in Q1 2023). This is noticeable both by the color change of the Histogram from orange to green and by the rising Blue Line. If you look in detail at what has been happening with the financials during this time, it's clear what meaningful work the company has done. Revenues have almost quadrupled. Earnings per share have increased 134 times. At the same time, total debt to revenue fell almost 10 times.
Keurig Dr Pepper Inc.
The company, formed in 2018 by the merger of Keurig Green Mountain and Dr Pepper Snapple Group, has failed to deliver outstanding financial results, causing its Fundamental Strength to fall from 4.63 in Q1 2018 to -0.53 in Q1 2023. During this period, the drop in diluted earnings per share was accompanied by higher debt and deteriorating liquidity.
Costco Wholesale Corporation
Wholesaler Costco has been surprisingly stable in its financial performance and with steady growth in both earnings and revenue. This is the reason why the Histogram bars are exceptionally green throughout the calculation of the indicator. The Fundamental Strength has not changed in three years and is high at 11 points.
As an additional filter, for example, when comparing two companies where all other conditions are equal - I use the dynamics of Cash Flows expressed in Diluted net income (*). These are the thick green, orange, and red lines over the Histogram.
Why do I use income as a unit of measure of Cash Flows? Because it is a good way to make the scale of indicator values the same for companies from different countries, with different currencies. It also allows you to use a single value scale for both Cash Flows and Fundamental Strength.
(*) If you want to learn more about Cash Flows, I suggest reading my two articles on TradingView:
Cash flow statement or Three great rivers
Cash flow vibrations
So, an additional filter shows the dynamics of Cash Flows over time.
To interpret the dynamics of Cash Flows, I pay attention to the following patterns:
- How the cash flows are positioned in relation to each other;
- In which zone each of the cash flows is located - in the positive or negative;
- What is the trend of each of the cash flows;
- How volatile each of the cash flows is.
As an example, let's look at several companies in order to interpret the dynamics of their Cash Flows.
John B. Sanfilippo & Son, Inc.
This is the most ideal situation for me: operating cash flow (green line) is above the other cash flows, investment cash flow (orange line) is near zero and practically unchanged, and financial cash flow (red line) is consistently below zero. This picture shows that the company lives off its operating cash flow, does not increase its debt, does not spend a substantial amount of money on expensive purchases, and retains (does not sell off) assets.
Parker Hannifin Corporation
With stable operating cash flow (green line), the company implements investment programs by raising additional funding. This is noticeable due to an increase in financial cash flow (red line) and a simultaneous decrease in investment cash flow (orange line) with a significant deepening into negative areas. Apparently, there is not enough operating cash flow to realize the planned investments. One has to wonder how sustainable a company can be if it invests in its development using borrowed funds without a subsequent increase in operating cash flow.
Schlumberger N. V.
The chaotic intertwining of cash flows outside of the Fundamental Strength range (-15 to 15) is indicative of the company's rich life, but to me, it is an indicator of high riskiness of its actions. And as we can see, Fundamental Strength has only begun to strengthen in the last year, when the external appearance of cash flow has normalized.
Risk disclaimer:
When working with the Fundamental Strength Indicator and the additional filter in the form of Cash Flows, you should understand that the publication of the Balance sheet, Income statement, and Cash flow statement takes place sometime after the end of the financial quarter. This means that new relevant data for the calculation will only appear after the publication of the new statements. In this regard, there may be a significant change in the values of the Indicator after the publication of new statements. The magnitude of this change will depend both on the content of the new statements and on the number of days between the end of the financial quarter and the publication date of the statements. Until the date of publication of the new statements, the latest relevant data will be used for calculations.
I would like to draw your attention to the fact that the calculation of Fundamental Strength and Cash Flows requires the availability of data for all parameters of the valuation model . It uses data that is exclusively available on TradingView (there is no reconciliation with other sources). If at least one parameter is missing, I switch to another company's analysis to continue using the indicator.
Thus, the Fundamental Strength Indicator and an additional filter in the form of Cash Flows make it possible to evaluate the financial results of the company based on the available data and the methodology I created. A simple visualization in the form of a three-color Histogram, a Blue line, and three thick Cash Flow lines significantly reduces the time for selecting fundamentally strong companies that fit the criteria of the selected model. However, this Indicator and/or its description and/or examples cannot be used as the sole reason for buying or selling stocks or for any other action or inaction related to stocks.
Advanced Trend Detection StrategyThe Advanced Trend Detection Strategy is a sophisticated trading algorithm based on the indicator "Percent Levels From Previous Close".
This strategy is based on calculating the Pearson's correlation coefficient of logarithmic-scale linear regression channels across a range of lengths from 50 to 1000. It then selects the highest value to determine the length for the channel used in the strategy, as well as for the computation of the Simple Moving Average (SMA) that is incorporated into the strategy.
In this methodology, a script is applied to an equity in which multiple length inputs are taken into consideration. For each of these lengths, the slope, average, and intercept are calculated using logarithmic values. Deviation, the Pearson's correlation coefficient, and upper and lower deviations are also computed for each length.
The strategy then selects the length with the highest Pearson's correlation coefficient. This selected length is used in the channel of the strategy and also for the calculation of the SMA. The chosen length is ultimately the one that best fits the logarithmic regression line, as indicated by the highest Pearson's correlation coefficient.
In short, this strategy leverages the power of Pearson's correlation coefficient in a logarithmic scale linear regression framework to identify optimal trend channels across a broad range of lengths, assisting traders in making more informed decisions.
Wunder Breakout botWunder Breakout bot
1. Wunder Breakout bot is based on the breakout of the trend line. Breakout is a technical trading strategy that is used to determine the moment of a trend line breakout on the price chart. It is based on the assumption that when price crosses a trend line, it signals a change in trend direction and the possible start of a new price movement.
2. The entry points for the trendline breakout strategy are based on the principle of breaking through a set trendline. This means that we look for the moment when the price of the asset crosses the trend line that we have established in order to enter a sell or buy position.
3. We use fixed take-profit and stop-loss, but you can use other risk management systems, based on the suggested settings.
4. Wunder Breakout bot script has added a function to calculate the risk per portfolio (your deposit). When this option is enabled, you get the calculation of the entry amount in dollars relative to your Stop Loss. You can chooseselect the percentage of risk per your portfolio in the settings. the percentage of risk per your portfolio in the settings. The loss will be calculated from the amount that will be displayed on the chart.
For example, if your deposit is $1000 and you set your risk at 1%, with a Stop Loss of 5%, your entry volume would be $200. The SL loss would be $10. $10 is your 1% risk or 1% of your deposit.
*Important! ** The risk per trade must be less than the Stop Loss value. If the risk is more than SL, you should use leverage.
The amount of funds included in the deal is calculated in dollars. This option was created if you want to send a dollar amount from Tradingview to the exchange. However, by specifying the volume in dollars, you will get the net profit and drawdown displayed incorrectly in the backtest results because TradingView calculates the backtest volume in contracts.
To display the correct net profit and drawdown values in Tradingview backtest results, use the "Volume in Contracts" option.
Grid Spot Trading Algorithm V2 - The Quant ScienceGrid Spot Trading Algorithm V2 is the last grid trading algorithm made by our developer team.
Grid Spot Trading Algorithm V2 is a fixed 10-level grid trading algorithm. The grid is divided into an accumulation area (red) and a selling area (green).
In the accumulation area, the algorithm will place new buy orders, selling the long positions on the top of the grid.
BUYING AND SELLING LOGIC
The algorithm places up to 5 limit orders on the accumulation section of the grid, each time the price cross through the middle grid. Each single order uses 20% of the equity.
Positions are closed at the top of the grid by default, with the algorithm closing all orders at the first sell level. The exit level can be adjusted using the user interface, from the first level up to the fifth level above.
CONFIGURING THE ALGORITHM
1) Add it to the chart: Add the script to the current chart that you want to analyze.
2) Select the top of the grid: Confirm a price level with the mouse on which to fix the top of the grid.
3) Select the bottom of the grid: Confirm a price level with the mouse on which to fix the bottom of the grid.
4) Wait for the automatic creation of the grid.
USING THE ALGORITHM
Once the grid configuration process is completed, the algorithm will generate automatic backtesting.
You can add a stop loss that destroys the grid by setting the destruction price and activating the feature from the user interface. When the stop loss is activated, you can view it on the chart.