PercentX Trend Follower [Trendoscope]"Trendoscope" was born from our trading journey, where we first delved into the world of trend-following methods. Over time, we discovered the captivating allure of pattern analysis and the exciting challenges it presented, drawing us into exploring new horizons. However, our dedication to trend-following methodologies remains steadfast and continues to be an integral part of our core philosophy.
Here we are, introducing another effective trend-following methodology, employing straightforward yet powerful techniques.
🎲 Concepts
Introducing the innovative PercentX Oscillator , a representation of Bollinger PercentB and Keltner Percent K. This powerful tool offers users the flexibility to customize their PercentK oscillator, including options for the type of moving average and length.
The Oscillator Range is derived dynamically, utilizing two lengths - inner and outer. The inner length initiates the calculation of the oscillator's highest and lowest range, while the outer length is used for further calculations, involving either a moving average or the opposite side of the highest/lowest range, to obtain the oscillator ranges.
Next, the Oscillator Boundaries are derived by applying another round of high/low or moving average calculations on the oscillator range values.
Breakouts occur when the close price crosses above the upper boundary or below the lower boundary, signaling potential trading opportunities.
🎲 How to trade a breakout?
To reduce false signals, we employ a simple yet effective approach. Instead of executing market trades, we use stop orders on both sides at a certain distance from the current close price.
In case of an upper side breakout, a long stop order is placed at 1XATR above the close, and a short stop order is placed at 2XATR below the close. Conversely, for a lower side breakout, a short stop order is placed at 1XATR below the close, and a long stop order is placed at 2XATR above the ATR. As a trend following method, our first inclination is to trade on the side of breakout and not to find the reversals. Hence, higher multiplier is used for the direction opposite to the breakout.
The script provides users with the option to specify ATR multipliers for both sides.
Once a trade is initiated, the opposite side of the trade is converted into a stop-loss order. In the event of a breakout, the script will either place new long and short stop orders (if no existing trade is present) or update the stop-loss orders if a trade is currently running.
As a trend-following strategy, this script does not rely on specific targets or target levels. The objective is to run the trade as long as possible to generate profits. The trade is only stopped when the stop-loss is triggered, which is updated with every breakout to secure potential gains and minimize risks.
🎲 Default trade parameters
Script uses 10% equity per trade and up to 4 pyramid orders. Hence, the maximum invested amount at a time is 40% of the equity. Due to this, the comparison between buy and hold does not show a clear picture for the trade.
Feel free to explore and optimize the parameters further for your favorite symbols.
🎲 Visual representation
The blue line represents the PercentX Oscillator, orange and lime colored lines represent oscillator ranges. And red/green lines represent oscillator boundaries. Oscillator spikes upon breakout are highlighted with color fills.
在腳本中搜尋"bollingerband"
Reversion Zone IndexThe Reversion Zone Index (RZI) is an indicator that combines the Commodity Channel Index (CCI), Choppiness Index (CI), and Bollinger Bands Percentage (BBPct) to identify mean reversion signals in the market. It is plotted as an Exponential Moving Average (EMA) smoothed oscillator with overbought and oversold zones, and mean reversion signals are represented by red and green arrows.
The three indicators are combined to benefit from their complementary aspects and create a more comprehensive view of mean reversion conditions. Here's a brief overview of each indicator's benefits:
1. Commodity Channel Index (CCI): CCI measures the current price level relative to its average over a specified period. It helps identify overbought and oversold conditions, as well as potential trend retracements. By incorporating CCI, the RZI gains insights into momentum and potential turning points.
2. Choppiness Index (CI): CI quantifies the market's choppiness or trendiness by analyzing the range between the highest high and lowest low over a specific period. It indicates whether the market is in a trending or ranging phase. CI provides valuable information about the market state, which can be useful in mean reversion analysis.
3. Bollinger Bands Percentage (BBPct): BBPct measures the current price's position relative to the Bollinger Bands. It calculates the percentage difference between the current price and the bands, identifying potential overbought or oversold conditions. BBPct helps gauge the market's deviation from its typical behavior and highlights potential reversal opportunities.
The RZI combines the three indicators by taking an average of their values and applying further calculations. It smooths the combined oscillator using an EMA to reduce noise and enhance the visibility of the trends. Smoothing with EMA provides a more responsive representation of the overall trend and helps filter out short-term fluctuations.
The overbought and oversold zones are marked on the chart as reference levels. When the combined oscillator is above the overbought zone or below the oversold zone, it suggests a potential mean reversion signal. Red and green arrows are displayed to visually indicate these mean retracement signals.
The RZI is a valuable tool for identifying mean reversion opportunities in the market. It incorporates multiple indicators, each providing unique insights into different aspects of mean reversion, such as momentum, volatility, and price positioning. Traders can use this indicator to spot potential turning points and time their trades accordingly.
Volatility Capture RSI-Bollinger - Strategy [presentTrading]- Introduction and how it is different
The 'Volatility Capture RSI-Bollinger - Strategy ' is a trading strategy that combines the concepts of Bollinger Bands (BB), Relative Strength Index (RSI), and Simple Moving Average (SMA) to generate trading signals. The uniqueness of this strategy is it calculates which is a dynamic level between the upper and lower Bollinger Bands based on the closing price. This unique feature allows the strategy to adapt to market volatility and price movements.
The market in Crypto and Stock are highly volatile, making them suitable for a strategy that uses Bollinger Bands. The RSI can help identify overbought or oversold conditions in this often speculative market.
BTCUSD 4hr chart
(700.hk) 3hr chart
Remember, the effectiveness of a trading strategy also depends on other factors such as the timeframe used, the specific settings of the indicators, and the overall market conditions. It's always recommended to backtest and paper trade a strategy before using it in live trading.
- Strategy, How it Works
Dynamic Bollinger Band: The strategy works by first calculating the upper and lower Bollinger Bands based on the user-defined length and multiplier. It then uses the Bollinger Bands and the closing price to dynamically adjust the presentBollingBand value. In the end, it generates a long signal when the price crosses over the present Bolling Band and a short signal when the price crosses under the present Bolling Band.
RSI: If the user has chosen to use RSI for signals, the strategy also calculates the RSI and its SMA, and uses these to generate additional long and short signals. The RSI-based signals are only used if the 'Use RSI for signals' option is set to true.
The strategy then checks the chosen trading direction and enters a long or short position accordingly. If the trading direction is set to 'Both', the strategy can enter both long and short positions.
Finally, the strategy exits a position when the close price crosses under the present Bolling Band for a long position, or crosses over the present Bolling Band for a short position.
- Trade direction
The strategy also includes a trade direction parameter, allowing the user to choose whether to enter long trades, short trades, or both. This makes the strategy adaptable to different market conditions and trading styles.
- Usage
1. Set the input parameters as per your trading preferences. You can choose the price source, the length of the moving average, the multiplier for the ATR, whether to use RSI for signals, the RSI and SMA periods, the bought and sold range levels, and the trading direction.
2. The strategy will then generate buy and sell signals based on these parameters. You can use these signals to enter and exit trades.
- Default settings
1. Source: hlc3
2. Length: 50
3. Multiplier: 2.7183
4. Use RSI for signals: True
5. RSI Period: 10
6. SMA Period: 5
7. Bought Range Level: 55
8. Sold Range Level: 50
9. Trade Direction: Both
- Strategy's default Properties
1. Default Quantity Type: 'strategy.percent_of_equity'
2. commission_value= 0.1, commission_type=strategy.commission.percent, slippage= 1: These parameters set the commission and slippage for the strategy. The commission is set to 0.1% of the trade value, and the slippage (the difference between the expected price of a trade and the price at which the trade is executed) is set to 1.
3. default_qty_type = strategy.percent_of_equity, default_qty_value = 15: These parameters set the default quantity for trades. The default_qty_type is set to strategy.percent_of_equity, which means that the size of each trade will be a percentage of the account equity. The default_qty_value is set to 15, which means that each trade will be 15% of the account equity.
4. initial_capital= 10000: This parameter sets the initial capital for the strategy to $10,000.
Bollinger Bands Modified (Stormer)This strategy is based and shown by trader and investor Alexandre Wolwacz "Stormer".
Overview
The strategy uses two indicators Bollinger Bands and EMA (optional for EMA).
Calculates Bollinger Bands, EMA, highest high, and lowest low values based on the input parameters, evaluating the conditions to determine potential long and short entry signals.
The conditions include checks for crossovers and crossunders of the price with the upper and lower Bollinger Bands, as well as the position of the price relative to the EMA.
The script also incorporates the option to add an inside bar pattern check for additional information.
Entry Position
Long Position:
Price cross over the superior band of bollinger bands.
The EMA is used to add support for trend analysis, it is an optional input, when used, it checks if price is above EMA.
Short Position:
Price cross under the inferior band of bollinger bands.
The EMA is used to add support for trend analysis, it is an optional input, when used, it checks if price is under EMA.
Risk Management
Stop Loss:
The stop loss is calculated based on the input highest high (for short position) and lowest low (for long position).
It gets the length based on the input from the last candles to set which is the highest high and which is the lowest low.
Take Profit:
According to the author, the profit target should be at least 1:1.6 the risk, so to have the strategy mathematically positive.
The profit target is configured input, can be increased or decreased.
It calculates the take profit based on the price of the stop loss with the profit target input.
Multi Kernel Regression [ChartPrime]The "Multi Kernel Regression" is a versatile trading indicator that provides graphical interpretations of market trends by using different kernel regression methods. It's beneficial because it smoothes out price data, creating a clearer picture of price movements, and can be tailored according to the user's preference with various options.
What makes this indicator uniquely versatile is the 'Kernel Select' feature, which allows you to choose from a variety of regression kernel types, such as Gaussian, Logistic, Cosine, and many more. In fact, you have 17 options in total, making this an adaptable tool for diverse market contexts.
The bandwidth input parameter directly affects the smoothness of the regression line. While a lower value will make the line more sensitive to price changes by sticking closely to the actual prices, a higher value will smooth out the line even further by placing more emphasis on distant prices.
It's worth noting that the indicator's 'Repaint' function, which re-estimates work according to the most recent data, is not a deficiency or a flaw. Instead, it’s a crucial part of its functionality, updating the regression line with the most recent data, ensuring the indicator measurements remain as accurate as possible. We have however included a non-repaint feature that provides fixed calculations, creating a steady line that does not change once it has been plotted, for a different perspective on market trends.
This indicator also allows you to customize the line color, style, and width, allowing you to seamlessly integrate it into your existing chart setup. With labels indicating potential market turn points, you can stay on top of significant price movements.
Repaint : Enabling this allows the estimator to repaint to maintain accuracy as new data comes in.
Kernel Select : This option allows you to select from an array of kernel types such as Triangular, Gaussian, Logistic, etc. Each kernel has a unique weight function which influences how the regression line is calculated.
Bandwidth : This input, a scalar value, controls the regression line's sensitivity towards the price changes. A lower value makes the regression line more sensitive (closer to price) and higher value makes it smoother.
Source : Here you denote which price the indicator should consider for calculation. Traditionally, this is set as the close price.
Deviation : Adjust this to change the distance of the channel from the regression line. Higher values widen the channel, lower values make it smaller.
Line Style : This provides options to adjust the visual style of the regression lines. Options include Solid, Dotted, and Dashed.
Labels : Enabling this introduces markers at points where the market direction switches. Adjust the label size to suit your preference.
Colors : Customize color schemes for bullish and bearish trends along with the text color to match your chart setup.
Kernel regression, the technique behind the Multi Kernel Regression Indicator, has a rich history rooted in the world of statistical analysis and machine learning.
The origins of kernel regression are linked to the work of Emanuel Parzen in the 1960s. He was a pioneer in the development of nonparametric statistics, a domain where kernel regression plays a critical role. Although originally developed for the field of probability, these methods quickly found application in various other scientific disciplines, notably in econometrics and finance.
Kernel regression became really popular in the 1980s and 1990s along with the rise of other nonparametric techniques, like local regression and spline smoothing. It was during this time that kernel regression methods were extensively studied and widely applied in the fields of machine learning and data science.
What makes the kernel regression ideal for various statistical tasks, including financial market analysis, is its flexibility. Unlike linear regression, which assumes a specific functional form for the relationship between the independent and dependent variables, kernel regression makes no such assumptions. It creates a smooth curve fit to the data, which makes it extremely useful in capturing complex relationships in data.
In the context of stock market analysis, kernel regression techniques came into use in the late 20th century as computational power improved and these techniques could be more easily applied. Since then, they have played a fundamental role in financial market modeling, market prediction, and the development of trading indicators, like the Multi Kernel Regression Indicator.
Today, the use of kernel regression has solidified its place in the world of trading and market analysis, being widely recognized as one of the most effective methods for capturing and visualizing market trends.
The Multi Kernel Regression Indicator is built upon kernel regression, a versatile statistical method pioneered by Emanuel Parzen in the 1960s and subsequently refined for financial market analysis. It provides a robust and flexible approach to capturing complex market data relationships.
This indicator is more than just a charting tool; it reflects the power of computational trading methods, combining statistical robustness with visual versatility. It's an invaluable asset for traders, capturing and interpreting complex market trends while integrating seamlessly into diverse trading scenarios.
In summary, the Multi Kernel Regression Indicator stands as a testament to kernel regression's historic legacy, modern computational power, and contemporary trading insight.
MyVolatilityBandsLibrary "MyVolatilityBands"
Just a lil' library of volatility bands that I use in some scripts
bollingerbands(src, lkbk, mult, basis)
Bollinger Bands
Parameters:
src (float) : float
lkbk (int) : int
mult (float) : float
basis (float)
Returns: Bollinger Bands
donchianchannels(src, lkbk, band_width)
Donchian Channels
Parameters:
src (float) : float
lkbk (int) : int
band_width (float) : float
Returns: Donchian Channels with an outer band of varying thickness adjusted by the band_width input
doublehalfdonchianchannels(src, lkbk, divisor)
Double Half Donchian Channels
Parameters:
src (float) : float
lkbk (int) : int
divisor (float) : float
Returns: two adjustable bases calculated using Donchian Channels calculation that act as a measure of volatility
Bollinger Bands Lab - by InFinitoVariation of the Moving Average Lab that includes Bollinger Bands functionality for any manually created Moving Average. It includes:
- Standard Deviations for any MA
- Fixed Symmetrical Deviations for any MA that remain at a constant % away from the MA
- The same Moving Average creation settings from the Moving Average Lab
"The Moving Average Lab allows to create any possible combination of up to 3 given MAs. It is meant to help you find the perfect MA that fits your style, strategy and market type.
This script allows to average, weight, double and triple multiple types and lengths of Moving Averages
Currently supported MA types are:
SMA
EMA
VWMA
WMA
SMMA (RMA)
HMA
LSMA
DEMA
TEMA
Features:
- Double or Triple any type of Moving Average using the same logic used for calculating DEMAs and TEMAs
- Average 2 or 3 different types and lengths of Moving Average
- Weight each MA manually
- Average up to 3 personalized MAs
- Average different Moving Averages with different length each "
The preview screenshot shows:
- The combination of:
- 200 LSMA - Weight: 1
- 200 HMA - Weight: 2
- 200 VWMA - Weight: 1 - Double
- The regular Bollinger Band setting, 2 standard deviations
- Two fixed symmetrical deviations at 15% and 20% away from the XMA
Bollinger Bands and SMA Channel Buy and Sell
This Indicator is a combination of a standard BB indicator incorporated with a SSL Channel by ErwinBeckers which is Simple Moving average with a length of set at 10 (Default) and calculates the high and low set for the default 10 to form a Channel.
The Settings for the Bollinger Band is the standard settings on a normal Bollinger Band - Length 20, source close and Standard dev 2
The setting for the SMA is length 10 and the high and low calculated or that length to form a channel.
The SMA Channel gives a green line for the Up channel and the Red line for the down Channel.
The basis of the indicator is that the Candle close above the Basis line of the BB and the SMA green line will give a buy indicator
and the same for Sell indicator the candle close below the basis BB and the SMA line Red will give a Sell indicator.
Please note that this indicator is a mix of 2 basic indicators found in Trading view, giving Buy and Sell indicators to make things easier to not look for this visually.
This code will be open source for anyone to use or back test or use it for whatever they want.
This code is for my own personal trading and cannot be relied upon. This indicator cannot be used and cannot guarantee anything, and caution should always be taken when trading. Use this with other indicators to give certanty.
Again use this for Paper Trading only.
I want to thank TradingView for its platform that facilitates development and learning.
TTP VIX SpyTTP VIX Spy is an indicator that uses data from TVC:VIX to better time entries in the market.
The assumption used is that when the VIX is coming down from the top of its range then the risk on assets can move to the upside and when the VIX is is pushing higher there's a high likelihood or risk on assets going down.
This indicator observes the momentum of VIX using MACD. It offers two different signals both for longs and shorts: signal 1 and 2.
Signal 1 is activate when the begging of a new trend for the VIX is confirmed.
Signal 2 is activated when the VIX pulls back from an extreme value.
You can configure the parameters of the internal super trend and the look back for the slope applied to price and RSIs.
The indicator offers the following filter parameters:
- Price RSI slope: it filters signals that have RSI slope pointing in the opposite direction of the signal.
- Counter trend: it filters signals that are not counter trending super trend.
- Wide BBW: it filters signals that happen when there hasn't been high price volatility
- Price slope: it filters signals when the price is not pointing in the direction of the signal (buy: up, sell: down)
- VIX RSI filter: it filters VIX RSI values overextended. MACD can be in the right range, but sometimes RSI contradicts it. By default is OFF since it can cause false negatives.
- Working days only: it filters signals that occur in the weekend.
The colours below the price action show how the VIX momentum is changing. Transitions from red into pink and then green show how the fear is fading which tends to lead to lead to bullish moves, and the opposite when the transitions are from green to red.
Performance and initial thoughts.
I have tried VIX Spy on both BINANCE:BTCUSDT.P and BINANCE:ETHUSDT.P and it seems to offer a decent win ratio. As you can see I had to add many filter to remove bad entries and left toggles available to decide which ones you want to use.
I tried the signal in the 4H, 1H and 15min with mixed results. I tend to incline for the results in the 1H.
VIX signal offers a backtestable stream and alerts both for signals 1 and 2.
Probability Envelopes (PBE)Introduction
In the world of trading, technical analysis is vital for making informed decisions about the future direction of an asset's price. One such tool is the use of indicators, mathematical calculations that can help traders predict market trends. This article delves into an innovative indicator called the Probability Envelopes Indicator, which offers valuable insights into the potential price levels an asset may reach based on historical data. This in-depth look explores the statistical foundations of the indicator, highlighting its key components and benefits.
Section 1: Calculating Price Movements with Log Returns and Percentages
The Probability Envelopes Indicator provides the option to use either log returns or percentage changes when calculating price movements. Each method has its advantages:
Log Returns: These are calculated as the natural logarithm of the ratio of the current price to the previous price. Log returns are considered more stable and less sensitive to extreme price fluctuations.
Percentage Changes: These are calculated as the percentage difference between the current price and the previous price. They are simpler to interpret and easier to understand for most traders.
Section 2: Understanding Mean, Variance, and Standard Deviation
The Probability Envelopes Indicator utilizes various statistical measures to analyze historical price movements:
Mean: This is the average of a set of numbers. In the context of this indicator, it represents the average price movement for bullish (green) and bearish (red) scenarios.
Variance: This measure represents the dispersion of data points in a dataset. A higher variance indicates a greater spread of data points from the mean. Variance is calculated as the average of the squared differences from the mean.
Standard Deviation: This is the square root of the variance. It is a measure of the amount of variation or dispersion in a dataset. In the context of this indicator, standard deviations are used to calculate the width of the bands around the expected mean.
Section 3: Analyzing Historical Price Movements and Probabilities
The Probability Envelopes Indicator examines historical price movements and calculates probabilities based on their frequency:
The indicator first identifies and categorizes price movements into bullish (green) and bearish (red) scenarios.
It then calculates the probability of each price movement occurring by dividing the frequency of the movement by the total number of occurrences in each category (bullish or bearish).
The expected green and red movements are calculated by multiplying the probabilities by their respective price movements and summing the results.
The total expected movement, or weighted average, is calculated by combining the expected green and red movements and dividing by the total number of occurrences.
Section 4: Constructing the Probability Envelopes
The Probability Envelopes Indicator utilizes the calculated statistics to construct its bands:
The expected mean is calculated using the total expected movement and applied to the current open price.
An exponential moving average (EMA) is used to smooth the expected mean, with the smoothing length determining the degree of responsiveness.
The upper and lower bands are calculated by adding and subtracting the mean green and red movements, respectively, along with their standard deviations multiplied by a user-defined multiplier.
Section 5: Benefits of the Probability Envelopes Indicator
The Probability Envelopes Indicator offers numerous advantages to traders:
Enhanced Decision-Making: By providing probability-based estimations of future price levels, the indicator can help traders make more informed decisions and potentially improve their trading strategies.
Versatility: The indicator is applicable to various financial instruments, such as stocks, forex, commodities, and cryptocurrencies, making it a valuable tool for traders in different markets.
Customization: The indicator's parameters, including the use of log returns, multiplier values, and smoothing length, can be adjusted according to the user's preferences and trading style. This flexibility allows traders to fine-tune the Probability Envelopes Indicator to better suit their needs and goals.
Risk Management: The Probability Envelopes Indicator can be used as a component of a risk management strategy by providing insight into potential price movements. By identifying potential areas of support and resistance, traders can set stop-loss and take-profit levels more effectively.
Visualization: The graphical representation of the indicator, with its clear upper and lower bands, makes it easy for traders to quickly assess the market and potential price levels.
Section 6: Integrating the Probability Envelopes Indicator into Your Trading Strategy
When incorporating the Probability Envelopes Indicator into your trading strategy, consider the following tips:
Confirmation Signals: Use the indicator in conjunction with other technical analysis tools, such as trend lines, moving averages, or oscillators, to confirm the strength and direction of the market trend.
Timeframes: Experiment with different timeframes to find the optimal settings for your trading strategy. Keep in mind that shorter timeframes may generate more frequent signals but may also increase the likelihood of false signals.
Risk Management: Always establish a proper risk management strategy that includes setting stop-loss and take-profit levels, as well as managing your position sizes.
Backtesting: Test the Probability Envelopes Indicator on historical data to evaluate its effectiveness and fine-tune its parameters to optimize your trading strategy.
Section 7: Cons and Limitations of the Probability Envelopes Indicator
While the Probability Envelopes Indicator offers several advantages to traders, it is essential to be aware of its potential cons and limitations. Understanding these can help you make better-informed decisions when incorporating the indicator into your trading strategy.
Lagging Nature: The Probability Envelopes Indicator is primarily based on historical data and price movements. As a result, it may be less responsive to real-time changes in market conditions, and the predicted price levels may not always accurately reflect the market's current state. This lagging nature can lead to late entry and exit signals.
False Signals: As with any technical analysis tool, the Probability Envelopes Indicator can generate false signals. These occur when the indicator suggests a potential price movement, but the market does not follow through. It is crucial to use other technical analysis tools to confirm the signals and minimize the impact of false signals on your trading decisions.
Complex Statistical Concepts: The Probability Envelopes Indicator relies on complex statistical concepts and calculations, which may be challenging to grasp for some traders, particularly beginners. This complexity can lead to misunderstandings and misuse of the indicator if not adequately understood.
Overemphasis on Past Data: While historical data can be informative, relying too heavily on past performance to predict future movements can be limiting. Market conditions can change rapidly, and relying solely on past data may not provide an accurate representation of the current market environment.
No Guarantees: The Probability Envelopes Indicator, like all technical analysis tools, cannot guarantee success. It is essential to approach trading with realistic expectations and understand that no indicator or strategy can provide foolproof results.
To overcome these limitations, it is crucial to combine the Probability Envelopes Indicator with other technical analysis tools and utilize a comprehensive risk management strategy. By doing so, you can better understand the market and increase your chances of success in the ever-changing financial markets.
Section 8: Probability Envelopes Indicator vs. Bollinger Bands
Bollinger Bands and the Probability Envelopes Indicator are both technical analysis tools designed to identify potential support and resistance levels, as well as potential trend reversals. However, they differ in their underlying concepts, calculations, and applications. This section will provide a deep dive into the differences between these two indicators and how they can complement each other in a trading strategy.
Underlying Concepts and Calculations:
Bollinger Bands:
Bollinger Bands are based on a simple moving average (SMA) of the price data, with upper and lower bands plotted at a specified number of standard deviations away from the SMA.
The distance between the bands widens during periods of increased price volatility and narrows during periods of low volatility, indicating potential trend reversals or breakouts.
The standard settings for Bollinger Bands typically involve a 20-period SMA and a 2 standard deviation distance for the upper and lower bands.
Probability Envelopes Indicator:
The Probability Envelopes Indicator calculates the expected price movements based on historical data and probabilities, utilizing mean and standard deviation calculations for both upward and downward price movements.
It generates upper and lower bands based on the calculated expected mean movement and the standard deviation of historical price changes, multiplied by a user-defined multiplier.
The Probability Envelopes Indicator also allows users to choose between using log returns or percentage changes for the calculations, adding flexibility to the indicator.
Key Differences:
Calculation Method: Bollinger Bands are based on a simple moving average and standard deviations, while the Probability Envelopes Indicator uses statistical probability calculations derived from historical price changes.
Flexibility: The Probability Envelopes Indicator allows users to choose between log returns or percentage changes and adjust the multiplier, offering more customization options compared to Bollinger Bands.
Risk Management: Bollinger Bands primarily focus on volatility, while the Probability Envelopes Indicator incorporates probability calculations to provide additional insights into potential price movements, which can be helpful for risk management purposes.
Complementary Use:
Using both Bollinger Bands and the Probability Envelopes Indicator in your trading strategy can offer valuable insights into market conditions and potential price levels.
Bollinger Bands can provide insights into market volatility and potential breakouts or trend reversals based on the widening or narrowing of the bands.
The Probability Envelopes Indicator can offer additional information on the expected price movements based on historical data and probabilities, which can be helpful in anticipating potential support and resistance levels.
Combining these two indicators can help traders to better understand market dynamics and increase their chances of identifying profitable trading opportunities.
In conclusion, while both Bollinger Bands and the Probability Envelopes Indicator aim to identify potential support and resistance levels, they differ significantly in their underlying concepts, calculations, and applications. By understanding these differences and incorporating both tools into your trading strategy, you can gain a more comprehensive understanding of the market and make more informed trading decisions.
In conclusion, the Probability Envelopes Indicator is a powerful and versatile technical analysis tool that offers unique insights into expected price movements based on historical data and probability calculations. It provides traders with the ability to identify potential support and resistance levels, as well as potential trend reversals. When compared to Bollinger Bands, the Probability Envelopes Indicator offers more customization options and incorporates probability-based calculations for a different perspective on market dynamics.
Although the Probability Envelopes Indicator has its limitations and potential cons, such as the reliance on historical data and the assumption that past performance is indicative of future results, it remains a valuable addition to any trader's toolkit. By using the Probability Envelopes Indicator in conjunction with other technical analysis tools, such as Bollinger Bands, traders can gain a more comprehensive understanding of the market and make more informed trading decisions.
Ultimately, the success of any trading strategy relies on the ability to interpret and apply multiple indicators effectively. The Probability Envelopes Indicator serves as a unique and valuable tool in this regard, providing traders with a deeper understanding of the market and its potential price movements. By utilizing this indicator in combination with other tools and techniques, traders can increase their chances of success and optimize their trading strategies.
Bollinger Band ribbonThis indicator plots 9 upper and lower lines with increasing length. Lines are 0.618 upper and lower level of Bollinger band.
Trend IndicatorThis indicator has different features:
1. Ichimoku = this indicator can plot Ichimoku calculated both in the common formula and with the volume average, you can choose the calculator method for each line.
2. Channel and Bands = this mode allows the user to choose from channel and band, "channel" shows the Keltner channel, and "band" shows the Bollinger bands. Both the indicators are calculated including the volume in the formula of the average midpoint.
3. Color candle = this function allows the user to see two different colors of candles on the chart, the positive color occurs when both the long-term average and the short team average of price calculated using the volume is above the two averages calculated without the volume. This function is great to analyze the volume pressure, useful to identify trend continuation and exhaustion.
4. Extreme reversal zones = this is a version of the Keltner channels calculated over a high number of candles and with high deviation, to identify the potential zones of reversal.
Note that in the "Ichimoku" indicator, the backline is the T.R.A.M.A. indicator, created and published open source by Lux Algo, which I thank for the script.
Weighted Deviation Bands [Loxx]What are Weighted Deviation Bands?
Variation of the Bollinger bands but it uses linear weighted average and weighted deviation via Mladen Rakic.
What is Weighted Deviation?
This weighted deviation is a sort of all linear weighted deviation. It uses linear weighting in all the steps calculated (which makes it different from the built in deviation in a case when linear weighted ma is used in the ma method). It is more responsive than the standard deviation
Included
Bar coloring
Faytterro Bandswhat is Faytterro Bands?
it is a channel indicator like "Bollinger Bands".
what it does?
creates a channel using standard deviations and means. thus giving users an idea about the expensive and cheap zones. It uses a special weighted moving average different from standard bollinger bands, it also averages not only price but also deviations.
how it does it?
it uses this formulas:
how to use it?
its usage is the same as "bollinger band".
length represents the number of candles to be taken into account, source represents the source of those candles and stdev represents the coefficient of the standard deviation.
you can use it with other indicators:
RSI TREND FILTERRSI TREND Filter on Chart
RSI scaled to fit on chart instead of oscillator, Trend Analysis is easy and Hidden Divergence is revealed using this indicator. This indicator is an aim to reduce confusing RSI Situations. The Oversold and Overbought lines help to determine the price conditions so its easy to avoid Traps.
Oversold and Overbought conditions are marked on Chart to make it useful to confirm a Buy or Sell Signals.
RSI 50 level is plotted with reference to EMA50 and Oversold and Overbought Conditions are calculated accordingly.
Uptrend: RSI Cloud / Candles above RSI 50 Level
Down Trend: RSI Cloud / Candles below RSI 50 Level
Sideways : Candles in the Gray Area above and below RSI 50 Level
Default RSI (14) : is the Candlestick pattern itself
Disclaimer: Use Solely at your own Risk.
Squeeze Range: Bollinger Bands / Keltner Channels [Whvntr]Presenting Squeeze Range: Bollinger Bands / Keltner Channels
TTMSqueeze method is a volatility and momentum indicator introduced by John Carter of Simpler Trading, which capitalizes on the tendency for price to break out strongly after consolidating in a tight trading range.
How did I make this indicator? The Bollinger Bands & Keltner Channels base scripts are from the standard indicators of their class in the Technicals section... I made this indicator first then noticed there were 3 others with a similar concept, but this differs in it's unique features and application of the TTMSqueeze strategy. This indicator plots the True Range of the Keltner Channel (Customizable in 'Bands Style" in the Inputs Menu) the instances the Bollinger Bands are within the range of the Keltner channel (the market just entered a squeeze).
Featuring: customizable Moving Averages
1. Exponential (Default for both BB & KC)
2. Simple
3. RMA (MA used in RSI )
Keltner channels have a multiplier of 2 & 3 on the Chart (3 being the outer).
How do I use this indicator? Once the teal dots are inside the solid red lines this would indicate that TTMperiod of low market volatility (the market is preparing itself for an explosive move up or down). Do some research and study how to use the TTMSqueeze method by John Carter. Disclaimer: not a guarantee of future favorable results.
Strategy Myth-Busting #7 - MACDBB+SSL+VSF - [MYN]This is part of a new series we are calling "Strategy Myth-Busting" where we take open public manual trading strategies and automate them. The goal is to not only validate the authenticity of the claims but to provide an automated version for traders who wish to trade autonomously.
Our seventh one we are automating is the "Magic MACD Indicator: Crazy Accurate Scalping Trading Strategy ( 74% Win Rate )" strategy from "TradeIQ" who claims to have backtested this manually and achieved 427% profit with a 74% winrate over 100 trades in just a 4 months. I was unable to emulate these results consistently accommodating for slippage and commission but even so the results and especially the high win-rate and low markdown is pretty impressive and quite respectable.
This strategy uses a combination of 3 open-source public indicators:
AK MACD BB v 1.00 by Algokid
SSL Hybrid by Mihkel00
Volume Strength Finder by Saravanan_Ragavan
This is considered a trend following Strategy. AK MACD BB is being used as the primary short term trend direction indicator with an interesting approach of using Bollinger Bands to define an upper and lower range and upon the MACD going above the upper Bollinger Bands, it's indicative of an up trend, where as if the MACD is below the lower Bollinger Band, it's indicative of a down trend. To eliminate false signals, SSL Hyrbid is used as a trend confirmation filter, confirming and eliminating false signals from the MACD BB. It does this by validating the price action is above the the EMA and the SSL is positive that is a confirmation of an uptrend. When the price action is below the EMA and the SSL is negative, that is an confirmation of a downtrend. To avoid taking trades during ranged markets, VSF Buyer's Strength is used so the buyers/sellers strength and must be above 50% or the trade will not be inititiated.
Trading Rules
5 min candles but other lower time frames even below 5m work quite well too.
Best results can be found by tweaking these 2 input parameters:
Number Of bars to look back to ensure MACD isn't above/below Zero Line
Number Of bars back to look for SSL pullback
Long Entry when these conditions are true
AK MACD BB BB issues a new continuation long signal. A new green circle must appear on the indicator and these circles should not be touching across the zero level while they were previously red
SSL Hybrid price action closes above the EMA and the line is blue color and then creates a pullback . The pullback is confirmed when the color changes from blue to gray or from blue to red.
VSF Buyers strength above 50% at the time the MACD indicator issues a new long signal.
Short Entry when these conditions are true
AK MACD BB issues a new continuation short signal. A new red circle must appear on the indicator and these circles should not be touching across the zero level while they were previously green
SSL Hybrid price action closes below the EMA and the line is red color then it has to create a pullback . The pullback is confirmed when the color changes from red to gray or from red to blue.
VSF Sellers strength above 50% at the time the MACD indicator issues a new short signal.
Stop Loss at EMA Line with TP Target 1.5x the risk
If you know of or have a strategy you want to see myth-busted or just have an idea for one, please feel free to message me.
Volume Weighted Standard Deviation (VWSD)The Volume Weighted Standard Deviation indicator is a custom technical analysis tool that uses the volume of trading to calculate the standard deviation of a stock's price. This indicator takes the source of data, the length of data, and the deviation as inputs, and calculates the volume weighted standard deviation using the values.
The indicator first calculates the mean price and mean volume by using simple moving average over the given length of data. Then it calculates the squared difference between the mean price and the actual price, multiplied by the volume. This gives a volume-weighted squared difference. The indicator then calculates the square root of the sum of the volume-weighted squared differences divided by the sum of the volumes over the given length of data. This gives the volume weighted standard deviation.
The indicator then plots the standard deviation and deviation as a band around the simple moving average of the source data, providing a clear view of the volatility of the stock.
In summary, the Volume Weighted Standard Deviation indicator is a powerful tool for measuring the volatility of a stock by taking into account the volume of trading. It uses the volume of trading to calculate the standard deviation of a stock's price, giving a more accurate representation of the volatility of the stock. It can be useful for traders to identify entry and exit points and make more informed trading decisions.
Fibonacci Bollinger Bands (FBB)The Fibonacci Moving Average (FMA) is an indicator for financial markets that is calculated using the Fibonacci sequence and the metallic mean. The metallic mean is a type of average that is calculated by adding the source and the square root of the sum of the square of the source and 4, and then dividing the result by 2. The FMA is then calculated by using the metallic mean of the source as the weight for each period in the given length, and summing these weighted values. The standard deviation of the metallic mean of the source is also calculated using the FMA over the given length.
Users can input the source data and the length for the FMA calculation, as well as a series of boolean values to determine which levels of the FMA to plot on the chart. The levels include the standard deviation of the metallic mean of the source, as well as various multiples of the Fibonacci ratios between 0 and 2.618. The resulting FMA and standard deviation values can be plotted on the chart to help traders identify trends and potential entry and exit points in the market.
Double RSI + BBRSI stands for Relative Strength Index.
Bollinger Bands stands for a channel open by standard deviation values plotting upper, lower lines.
Double RSI with Bollinger bands adapted Bollinger bands to RSI not using overlay mode. It tries to filter fake signals while giving more good signals according to volatility even below overbought areas or above oversold areas. This way you can use greater values for RSI, like 25 and 100, increasing smoothness with less market noise.
We added an extra gap spacer to smooth Bollinger bands while widening the channel with a lower multiplier.
I found better results when Fast RSI crosses back into Bollinger bands channel.
You can play with the following settings:
• Source
Close is the most used
• Fast RSI length
Default to 25
• Slow RSI length
Default to 100
• RSI Smoothing
To filter out some graphic noise
• RSI Overbought, Oversold
Regular overbought, oversold lines handled by a single value. For 70/30, set it to 20 although with longer RSI something around 15 is enough.
• Bollinger Spacer
Ads thickness to the channel with lower multiplier
• Bollinger Length
Regular Bollinger length applied to slow RSI
• Bollinger Multiplier
Regular Bollinger multiplier applied to slow RSI
Disclaimer:
For study purposes only, trading without a good risk management can be regrettable, do your own research, always add confirmations, use it as is, at your own risk.
Volume Weighted Hull Moving Average Bollinger Bands (VWHBB)Title: "Volume Weighted Hull Moving Average Bollinger Bands Indicator for TradingView"
Abstract: This script presents a TradingView indicator that displays Bollinger Bands based on the volume weighted Hull Moving Average (VEHMA) of a financial asset. The VEHMA is a technical analysis tool that combines the reduced lag of the Hull Moving Average (HMA) with volume weighting to provide a more sensitive indicator of market trends and dynamics. The Bollinger Bands are a volatility indicator that plot upper and lower bands around a moving average, which can help traders identify potential trend changes and overbought or oversold conditions. The script allows the user to customize the VEHMA length and Bollinger Band deviation parameters.
Introduction: Bollinger Bands are a popular technical analysis tool used to identify potential trend changes and overbought or oversold conditions in the market. They are constructed by plotting upper and lower bands around a moving average, with the width of the bands determined by the volatility of the asset. The VEHMA is a variant of the Hull Moving Average (HMA) that combines the reduced lag of the HMA with volume weighting to provide a more sensitive indicator of market trends and dynamics.
Methodology: The VEHMA is calculated using a weighted average of two exponential moving averages (EMAs), with the weighting based on the volume of the asset and the length of the moving average. The Bollinger Bands are calculated by plotting the VEHMA plus and minus a standard deviation of the asset's price over a specified period. The standard deviation is a measure of the volatility of the asset and helps to adjust the width of the bands based on market conditions.
Implementation: The script is implemented in TradingView's PineScript language and can be easily added to any chart on the platform. The user can customize the VEHMA length and Bollinger Band deviation parameters to suit their trading strategy. The VEHMA, Bollinger Bands, and fill colors are plotted on the chart to provide a visual representation of the indicator.
Conclusion: The VEHMA Bollinger Bands indicator is a useful tool for traders looking to identify potential trend changes and overbought or oversold conditions in the market. This script provides a convenient and customizable implementation of the indicator for use in TradingView.
Oscillator ExtremesThe Oscillator Extremes indicator plots the normalized positioning of the selected oscillator versus the Bollinger Bands' upper and lower boundaries. Currently, this indicator has four different oscillators to choose from; RSI, CMO, CCI, and ROC.
When the oscillator pushes towards one extreme, it will bring the value of the prevailing line closer to zero. If the bullish or bearish line crosses the zero line, the oscillator is past the extreme of the Bollinger Band.
Example: If the RSI crosses over the upper boundary of the Bollinger, the bullish(green) line will cross under the zero line.
Crossovers of the bullish and bearish lines can indicate a shift in momentum and are a signal. Where the line crossing under, towards zero, is the prevailing trend. The plotted lines will highlight green(bullish) or red(bearish) to show the prevailing trend. This is similar to a DI+- crossover that is commonly associated with the ADX.
We have included an optional normalized ADX to help validate signals. The ADX will change color based on the slope of the ADX. Purple indicates a positive slope and white for a negative slope.
Average True Range Refurbished💡 Objective
This script is a rebuild of the pre-existing ATR indicator, with improvements and fine-tuning.
🪄Improvements
1. Normalization option (range 0 to 100)
2. Optional calculation of the ratio between current volatility and average volatility
3. Optional smoothing
4. Show a moving average
5. Show Bollinger Bands with 3 bands
6. Change bar colors according to ATR and Bollinger Bands
📚 Definition
'The Average True Range (ATR) is a tool used in technical analysis to measure volatility. Unlike many of today's popular indicators, the ATR is not used to indicate the direction of price. Rather, it is a metric used solely to measure volatility, especially volatility caused by price gaps or limit moves.'
(TradingView)
