Bollinger Bands Heatmap (BBH)The Bollinger Bands Heatmap (BBH) Indicator provides a unique visualization of Bollinger Bands by displaying the full distribution of prices as a heatmap overlaying your price chart. Unlike traditional Bollinger Bands, which plot the mean and standard deviation as lines, BBH illustrates the entire statistical distribution of prices based on a normal distribution model.
This heatmap indicator offers traders a visually appealing way to understand the probabilities associated with different price levels. The lower the weight of a certain level, the more transparent it appears on the heatmap, making it easier to identify key areas of interest at a glance.
Key Features
Dynamic Heatmap: Changes in real-time as new price data comes in.
Fully Customizable: Adjust the scale, offset, alpha, and other parameters to suit your trading style.
Visually Engaging: Uses gradients of colors to distinguish between high and low probabilities.
Settings
Scale
Tooltip: Scale the size of the heatmap.
Purpose: The 'Scale' setting allows you to adjust the dimensions of each heatmap box. A higher value will result in larger boxes and a more generalized view, while a lower value will make the boxes smaller, offering a more detailed look at price distributions.
Values: You can set this from a minimum of 0.125, stepping up by increments of 0.125.
Scale ATR Length
Tooltip: The ATR used to scale the heatmap boxes.
Purpose: This setting is designed to adapt the heatmap to the instrument's volatility. It determines the length of the Average True Range (ATR) used to size the heatmap boxes.
Values: Minimum allowable value is 5. You can increase this to capture more bars in the ATR calculation for greater smoothing.
Offset
Tooltip: Offset mean by ATR.
Purpose: The 'Offset' setting allows you to shift the mean value by a specified ATR. This could be useful for strategies that aim to capitalize on extreme price movements.
Values: The value can be any floating-point number. Positive values shift the mean upward, while negative values shift it downward.
Multiplier
Tooltip: Bollinger Bands Multiplier.
Purpose: The 'Multiplier' setting determines how wide the Bollinger Bands are around the mean. A higher value will result in a wider heatmap, capturing more extreme price movements. A lower value will tighten the heatmap around the mean price.
Values: The minimum is 0, and you can increase this in steps of 0.2.
Length
Tooltip: Length of Simple Moving Average (SMA).
Purpose: This setting specifies the period for the Simple Moving Average that serves as the basis for the Bollinger Bands. A higher value will produce a smoother average, while a lower value will make it more responsive to price changes.
Values: Can be set to any integer value.
Heat Map Alpha
Tooltip: Opacity level of the heatmap.
Purpose: This controls the transparency of the heatmap. A lower value will make the heatmap more transparent, allowing you to see the price action more clearly. A higher value will make the heatmap more opaque, emphasizing the bands.
Values: Ranges from 0 (completely transparent) to 100 (completely opaque).
Color Settings
High Color & Low Color: These settings allow you to customize the gradient colors of the heatmap.
Purpose: Use contrasting colors for better visibility or colors that you prefer. The 'High Color' is used for areas with high density (high probability), while the 'Low Color' is for low-density areas (low probability).
Usage Scenarios for Settings
For Volatile Markets: Increase 'Scale ATR Length' for better smoothing and set a higher 'Multiplier' to capture wider price movements.
For Trend Following: You might want to set a larger 'Length' for the SMA and adjust 'Scale' and 'Offset' to focus on more probable price zones.
These are just recommendations; feel free to experiment with these settings to suit your specific trading requirements.
How To Interpret
The heatmap gives a visual representation of the range within which prices are likely to move. Areas with high density (brighter color) indicate a higher probability of the price being in that range, whereas areas with low density (more transparent) indicate a lower probability.
Bright Areas: Considered high-probability zones where the price is more likely to be.
Transparent Areas: Considered low-probability zones where the price is less likely to be.
Tips For Use
Trend Confirmation: Use the heatmap along with other trend indicators to confirm the strength and direction of a trend.
Volatility: Use the density and spread of the heatmap as an indication of market volatility.
Entry and Exit: High-density areas could be potential support and resistance levels, aiding in entry and exit decisions.
Caution
The Bollinger Bands Heatmap assumes a normal distribution of prices. While this is a standard assumption in statistics, it is crucial to understand that real-world price movements may not always adhere to a normal distribution.
Conclusion
The Bollinger Bands Heatmap Indicator offers traders a fresh perspective on Bollinger Bands by transforming them into a visual, real-time heatmap. With its customizable settings and visually engaging display, BBH can be a useful tool for traders looking to understand price probabilities in a dynamic way.
Feel free to explore its features and adjust the settings to suit your trading strategy. Happy trading!
볼린저 밴드 (BB)
Bollinger Bands Liquidity Cloud [ChartPrime]This indicator overlays a heatmap on the price chart, providing a detailed representation of Bollinger bands' profile. It offers insights into the price's behavior relative to these bands. There are two visualization styles to choose from: the Volume Profile and the Z-Score method.
Features
Volume Profile: This method illustrates how the price interacts with the Bollinger bands based on the traded volume.
Z-Score: In this mode, the indicator samples the real distribution of Z-Scores within a specified window and rescales this distribution to the desired sample size. It then maps the distribution as a heatmap by calculating the corresponding price for each Z-Score sample and representing its weight via color and transparency.
Parameters
Length: The period for the simple moving average that forms the base for the Bollinger bands.
Multiplier: The number of standard deviations from the moving average to plot the upper and lower Bollinger bands.
Main:
Style: Choose between "Volume" and "Z-Score" visual styles.
Sample Size: The size of the bin. Affects the granularity of the heatmap.
Window Size: The lookback window for calculating the heatmap. When set to Z-Score, a value of `0` implies using all available data. It's advisable to either use `0` or the highest practical value when using the Z-Score method.
Lookback: The amount of historical data you want the heatmap to represent on the chart.
Smoothing: Implements sinc smoothing to the distribution. It smoothens out the heatmap to provide a clearer visual representation.
Heat Map Alpha: Controls the transparency of the heatmap. A higher value makes it more opaque, while a lower value makes it more transparent.
Weight Score Overlay: A toggle that, when enabled, displays a letter score (`S`, `A`, `B`, `C`, `D`) inside the heatmap boxes, based on the weight of each data point. The scoring system categorizes each weight into one of these letters using the provided percentile ranks and the median.
Color
Color: Color for high values.
Standard Deviation Color: Color to represent the standard deviation on the Bollinger bands.
Text Color: Determines the color of the letter score inside the heatmap boxes. Adjusting this parameter ensures that the score is visible against the heatmap color.
Usage
Once this indicator is applied to your chart, the heatmap will be overlaid on the price chart, providing a visual representation of the price's behavior in relation to the Bollinger bands. The intensity of the heatmap is directly tied to the price action's intensity, defined by your chosen parameters.
When employing the Volume Profile style, a brighter and more intense area on the heatmap indicates a higher trading volume within that specific price range. On the other hand, if you opt for the Z-Score method, the intensity of the heatmap reflects the Z-Score distribution. Here, a stronger intensity is synonymous with a more frequent occurrence of a specific Z-Score.
For those seeking an added layer of granularity, there's the "Weight Score Overlay" feature. When activated, each box in your heatmap will sport a letter score, ranging from `S` to `D`. This score categorizes the weight of each data point, offering a concise breakdown:
- `S`: Data points with a weight of 1.
- `A`: Weights below 1 but greater than or equal to the 75th percentile rank.
- `B`: Weights under the 75th percentile but at or above the median.
- `C`: Weights beneath the median but surpassing the 25th percentile rank.
- `D`: All that fall below the 25th percentile rank.
This scoring feature augments the heatmap's visual data, facilitating a quicker interpretation of the weight distribution across the dataset.
Further Explanations
Volume Profile
A volume profile is a tool used by traders to visualize the amount of trading volume occurring at specific price levels. This kind of profile provides a deep insight into the market's structure and helps traders identify key areas of support and resistance, based on where the most trading activity took place. The concept behind the volume profile is that the amount of volume at each price level can indicate the potential importance of that price.
In this indicator:
- The volume profile mode creates a visual representation by sampling trading volumes across price levels.
- The representation displays the balance between bullish and bearish volumes at each level, which is further differentiated using a color gradient from `low_color` to `high_color`.
- The volume profile becomes more refined with sinc smoothing, helping to produce a smoother distribution of volumes.
Z-Score and Distribution Resampling
Z-Score, in the context of trading, represents the number of standard deviations a data point (e.g., closing price) is from the mean (average). It’s a measure of how unusual or typical a particular data point is in relation to all the data. In simpler terms, a high Z-Score indicates that the data point is far away from the mean, while a low Z-Score suggests it's close to the mean.
The unique feature of this indicator is that it samples the real distribution of z-scores within a window and then resamples this distribution to fit the desired sample size. This process is termed as "resampling in the context of distribution sampling" . Resampling provides a way to reconstruct and potentially simplify the original distribution of z-scores, making it easier for traders to interpret.
In this indicator:
- Each Z-Score corresponds to a price value on the chart.
- The resampled distribution is then used to display the heatmap, with each Z-Score related price level getting a heatmap box. The weight (or importance) of each box is represented as a combination of color and transparency.
How to Interpret the Z-Score Distribution Visualization:
When interpreting the Z-Score distribution through color and alpha in the visualization, it's vital to understand that you're seeing a representation of how unusual or typical certain data points are without directly viewing the numerical Z-Score values. Here's how you can interpret it:
Intensity of Color: This often corresponds to the distance a particular data point is from the mean.
Lighter shades (closer to `low_color`) typically indicate data points that are more extreme, suggesting overbought or oversold conditions. These could signify potential reversals or significant deviations from the norm.
Darker shades (closer to `high_color`) represent data points closer to the mean, suggesting that the price is relatively typical compared to the historical data within the given window.
Alpha (Transparency): The degree of transparency can indicate the significance or confidence of the observed deviation. More opaque boxes might suggest a stronger or more reliable deviation from the mean, implying that the observed behavior is less likely to be a random occurrence.
More transparent boxes could denote less certainty or a weaker deviation, meaning that the observed price behavior might not be as noteworthy.
- Combining Color and Alpha: By observing both the intensity of color and the level of transparency, you get a richer understanding. For example:
- A light, opaque box could suggest a strong, significant deviation from the mean, potentially signaling an overbought or oversold scenario.
- A dark, transparent box might indicate a weak, insignificant deviation, suggesting the price is behaving typically and is close to its average.
Rectified BB% for option tradingThis indicator shows the bollinger bands against the price all expressed in percentage of the mean BB value. With one sight you can see the amplitude of BB and the variation of the price, evaluate a reenter of the price in the BB.
The relative price is visualized as a candle with open/high/low/close value exspressed as percentage deviation from the BB mean
The indicator include a modified RSI, remapped from 0/100 to -100/100.
You can choose the BB parameters (length, standard deviation multiplier) and the RSI parameter (length, overbougth threshold, ovrsold threshold)
You can exclude/include the candles and the RSI line.
The indicator can be used to sell options when the volatility is high (the bollinger band is wide) and the price is reentering inside the bands.
If the price is forming a supply or demand area it can be a good opportunity to sell a bull put or a bear call
The RSI can be used as confirm of the supply/demand formation
If the bollinger band is narrow and the RSI is overbought/oversold it indicate a better opportunity to buy options
the indicator is designed to work with daily timeframe and default parameters.
Bollinger Band Percentile SuiteThe Bollinger Band Percentile Suite (𝐵𝐵𝒫𝒸𝓉 𝒮𝓊𝒾𝓉𝑒) is a comprehensive and customizable toolkit built upon the foundation of the %B indicator. The methodology behind this toolkit remains consistent with the original %B indicator, while introducing a host of powerful features to enhance its functionality and adaptability.
Key Features and Customization:
The 𝐵𝐵𝒫𝒸𝓉 offers a wide array of customizable options to suit your trading preferences and strategies. It includes a variety of 14 moving average types that can be chosen as the basis for the Bollinger Band calculation. Additionally, traders have the flexibility to set their upper and lower boundaries for mean reversion detection, allowing for analysis tailored to the user's preference.
Deviation Calculation:
The toolkit provides an option to choose between standard and weighted deviation calculation methods. This added customization ensures that the indicator's behavior aligns with your unique trading style and preferences.
Signals and Reversals:
The 𝐵𝐵𝒫𝒸𝓉 excels in identifying potential overbought and oversold market conditions. It highlights these levels on the chart and marks potential reversal signals with small circles positioned either at the top or bottom of the indicator pane, providing traders with actionable insights.
Trend and Color Coding:
Incorporating a color-coded approach, the BBpct Suite enhances your understanding of market dynamics. It offers bar coloring options based on trend, allowing traders to identify bullish or bearish market conditions as the percentile goes above or below the midline.
Extremities and Reversions:
Recognizing extreme market conditions is crucial for traders. The 𝐵𝐵𝒫𝒸𝓉 includes color-coded indicators for extremities, indicating when the percentile ventures above or below the predefined thresholds. Moreover, it promptly identifies reversions by marking the moment the percentile crosses under the upper threshold (overbought) or over the lower threshold (oversold).
The Bollinger Band Percentile Suite equips traders with a versatile toolkit to gain valuable insights into market overbought and oversold conditions, and potential reversal signals. Its extensive customization options and array of features empower traders to make well-informed decisions based on their unique trading strategies and risk tolerance.
Please note that while the BBpct Suite provides robust analysis, it is advisable to combine its insights with other technical indicators and tools for a comprehensive trading approach.
Example Chart:
Greedy DCA█ OVERVIEW
Detect price crashes in volatile conditions. This is an indicator for a greedy dollar cost average (DCA) strategy. That is, for people who want to repeatedly buy an asset over time when its price is crashing.
█ CONCEPTS
Price crashes are indicated if the price falls below one or more of the 4 lower Bollinger Bands which are calculated with increasing multipliers for the standard deviation.
In these conditions, the price is far below the average. Therefore they are considered good buying opportunities.
No buy signals are emitted if the Bollinger Bands are tight, i.e. if the bandwidth (upper -lower band) is below the value of the moving average multiplied with a threshold factor. This ensures that signals are only emitted if the conditions are highly volatile.
The Bollinger Bands are calculated based on the daily candles, irrespective the chart time frame. This allows to check the strategy on lower time frames
Floor and Roof IndicatorThe Floor and Roof indicator is a tool developed to help traders identify potential areas of support and resistance both for trend following and for mean reversal trading decisions.
The indicator plots the "Roof" which is the main level of resistance, and the "Floor" which is the main level of support. These lines are calculated on the "Lenght" parameter and smoothed by the "Smooth" parameter, and they use both the volatility and the main market structure as calculation methods.
Additionally, this indicator plots an area that can be modified by the "Zone width" parameter and two other lines, called "Second floor" and "Second roof" respectively, which are plotted only whenever they are significant to the price current level.
This indicator can be used in several ways:
- In a clear trend, you could wait for a break of the second floor or roof as an indication of a change in the market direction
- As the price goes out of the reversal zones, this can be an indication of a reversal
- In a clear trend, you can wait for the price to bounce on the second floor or roof lines to enter a trade
DBMA - Dual Bollinger Moving AverageThe Dual Bollinger moving average (DBMA) consists of a moving average (MA) & two Bollinger Bands (BB), with the color of the bands representing the level of price compression. In its default settings, it is a 20-day simple moving average with 2 upper Bollinger Bands, having the standard deviation (SD) settings of 0.5 & 1, respectively.
How close the price is to the moving average?
For a pullback trader, the entry point should be close to the moving average, preferably with price compression. How close should it be, is where the bands serve as a guide. The low of the pullback candle should be within the bands, that is, at least within the far band (1 SD of the MA), or even better if it's within the near band (0.5 SD). When the price is outside the bands, it should not be considered favourable for a pullback entry.
For how long has the price been closer to the moving average?
John Carter’s TTM Squeeze indicator looked at the relationship between Bollinger Bands and Keltner's Channels to help identify period of volatility contractions. Bollinger Bands being completely enclosed within the Keltner Channels is indicative of a very low volatility. This is a state of volatility contraction known as squeeze. Using different ATR lengths (1.0, 1.5 and 2.0) for Keltner Channels, we can differentiate between levels of squeeze (High, Mid & Low compression, respectively). Greater the compression, higher the potential for explosive moves.
The squeeze portion of the script is based on LazyBear's script ( Squeeze Momentum Indicator )
The High, Mid & Low compression squeezes are depicted via the color of the bands being red, orange, or yellow, respectively. With the low of the pullback candle within the bands, & the squeeze color changing to red, it should be considered favourable for a pullback entry.
Trailing the price with the lower bands
The lower bands can be used for trailing with the moving average. While trailing, once the price closes below the moving average, the trailing stoploss (TSL) is said to be triggered, & the trade is exited. Here we use the bands to give it some cushion. Let the price close below the 1SD band for labelling the TSL as being triggered to exit the trade. If the price closes below the MA but is still within the bands, the signal is to keep holding the trade.
Extreme Reversal SignalThe Extreme Reversal Signal is designed to signal potential pivot points when the price of an asset becomes extremely overbought or oversold. Extreme conditions typically signal a brief or extensive price reversal, offering valuable entry or exit points. It's important to note that this indicator may produce multiple signals, making it essential to corroborate these signals with other forms of analysis to determine their validity. While the default settings provide valuable insights, it might be beneficial to experiment with different configurations to ensure the indicator's efficacy.
Two primary conditions define extremely overbought and oversold states. The first condition is that the price must deviate by two standard deviations from the 20-day Simple Moving Average (SMA). The second condition is that the 3-day SMA of the 14-day Stochastic Oscillator (STO) derived from the 14-day Relative Strength Index (RSI) is above or below the upper or lower limit.
Oversold states arise when the first condition is met and the 3-day SMA of the 14-day Stochastic RSI falls below the lower limit, suggesting a buy signal. These are visually represented by green triangles below the price bars. Overbought states arise when the first condition is met and the 3-day SMA of the 14-day Stochastic RSI rises above the upper limit, suggesting a sell signal. These are visually represented by red triangles above the price bars. It's also possible to set up automated alerts to get notifications when either of these two conditions is met to avoid missing out.
While this indicator has traditionally identified overbought and oversold conditions in various different assets, past performance does not guarantee future results. Therefore, it is advisable to supplement this indicator with other technical tools. For instance, trend indicators can greatly improve the decision-making process when planning for entries and exit points.
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.
Quantitative Trend Strategy- Uptrend longTrend Strategy #1
Indicators:
1. SMA
2. Pivot high/low functions derived from SMA
3. Step lines to plot support and resistance based on the pivot points
4. If the close is over the resistance line, green arrows plot above, and vice versa for red arrows below support.
Strategy:
1. Long Only
2. Mutable 2% TP/1.5% SL
3. 0.01% commission
4. When the close is greater than the pivot point of the sma pivot high, and the close is greater than the resistance step line, a long position is opened.
*At times, the 2% take profit may not trigger IF; the conditions for reentry are met at the time of candle closure + no exit conditions have been triggered.
5. If the position is in the green and the support step line crosses over the resistance step line, positions are exited.
How to use it and what makes it unique:
Use this strategy to trade an up-trending market using a simple moving average to determine the trend. This strategy is meant to capture a good risk/reward in a bullish market while staying active in an appropriate fashion. This strategy is unique due to it's inclusion of the step line function with statistics derived from myself.
This description tells the indicators combined to create a new strategy, with commissions and take profit/stop loss conditions included, and the process of strategy execution with a description on how to use it. If you have any questions feel free to PM me and boost if you enjoyed it. Thank you, pineUSERS!
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.
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.
Banded Chikou Breakout — Quantifying Ichimoku MomentumTitle: Banded Chikou Breakout — Quantifying Ichimoku Momentum
Overview:
Banded Chikou Breakout (BCB) is a unique, algorithmic script designed to augment the capabilities of traders seeking substantial breakout opportunities. Constructed on the robust principles of the Ichimoku trading strategy, BCB is designed to quantify and filter the Chikou Span's significant breakouts above or below the price action. This script does not aim to replace the Ichimoku system; instead, it enhances it, providing an optimized tool for momentum trading.
Rationale:
Ichimoku traders often scrutinize the Chikou Span's position relative to price action to identify market trends. However, determining whether the Chikou Span is above or below due to a genuine trend or mere market noise can be challenging in choppy markets. BCB resolves this predicament by offering a unique way to interpret the Chikou Span's movement. It does so by quantifying the Chikou Span's momentum and utilizing Bollinger Bands to determine its significance. By effectively differentiating substantial movements from the insignificant, BCB can help traders better navigate the market and increase their potential for profitable trades.
How it Works:
BCB combines three key elements: a Momentum Script (simulating Chikou Span), a Bollinger Band Script, and a Timeframe Switcher, all working together to provide a refined trading perspective.
Momentum Script: Calculates the price difference between the current price and the price 'n' periods ago, transforming the Chikou Span into a quantifiable momentum value that signifies the strength and speed of a market move.
Bollinger Band Script: Computes a Simple Moving Average (SMA) around the momentum, plotting two 'bands' at a specified standard deviation from this SMA. This functionality allows traders to discern when the Chikou Span's momentum is abnormally high or low, signifying a potential significant breakout.
Timeframe Switcher: This feature lets traders apply the BCB script to a different timeframe from the one they are currently viewing. This capability can help traders identify higher timeframe breakouts and trade them with precision on the lower timeframe.
How to Use:
BCB is designed to complement the Ichimoku strategy for effective breakout identification.
Add the BCB script to your trading chart. It plots the momentum (yellow line) and Bollinger Bands (green lines) with the area between the bands shaded blue.
Utilize the Ichimoku strategy to identify larger and smaller timeframe trends.
Optional: Leverage the timeframe switcher to synchronize your trades with higher timeframe trends while operating on lower timeframes.
If the BCB momentum line crosses the upper Bollinger Band while the Ichimoku indicates a bullish trend, it signifies a potential significant upward breakout. Similarly, a cross below the lower band during a bearish trend could denote a significant downward breakout.
Remember, without the context provided by the Ichimoku system's trend analysis, BCB can yield false breakouts. It is, therefore, crucial to use these tools in tandem. I like to check for an Ichimoku trend on the 4H and 1H charts, and then use BCB on charts <60 minutes to capture trends with precision.
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.
custom Bollinger bands with filters - indicator (AS)-----------Description-------------
This indicator is basically Bollinger bands with many ways to customize. It uses highest and lowest values of upper and lower band for exits. I think something is wrong with the script but cant find any mistakes – most probably smoothing. The ATR filter is implemented but is working incorrectly. In code you can also turn it into strategy but I do not recommend it for now as it is not ready yet.
So this is my first script and I am looking for any advice, ideas to improve this script, sets of parameters, markets to apply, logical mistakes in code or any ideas that you may have. Indicator was initially designed for EURUSD 5MIN but I would be interested in other ideas.
-----------SETTINGS--------------
---START - In starting settings we can choose
Line 1: what parts to use BB/DC/ATR
Line 2: what parts to plot on chart
Line 3 Whether or not apply smoothing to BB or ATR filter
Line 4 Calculate deviation for BB from price or Moving average
Line 5 Fill colors and plot other parts for debug (overlay=false)
Line 6:( for strategy) – enable Long/Short Trades
---BB and DC – here we modify Bollinger bands and Donchian
Line 1: Length and type of BB middle line and also length of DC from BB
Line 2: Length and type of BB standard deviation and multiplier
Line 3: Length and type of BB smoothing and %width for BB filter
---ATR filter – (not ready fully yet)
Line 1: type and length of ATR
Line 2: threshold and smoothing value of ATR
---DATE and SESSION
Line 1: apply custom date or session?
Line 2: session hours settings
Line 3:Custom starting date
Line 4: Custom Ending date
-----------HOW TO USE--------------
We open Long if BB width is bigger than threshold and close when upper band is no longer highest in the period set. Exact opposite with Short
5EMA BollingerBand Nifty Stock Scanner
What ?
We all heard about (well: over-heard) 5-EMA strategy. Which falls into the broader category of mean reversal type of trading setup.
What is mean reversal?
Price (or any time series, in fact) tries to follow a mean . Whenever price diverges from the mean it tries to meet it back.
It is empirically observed by some traders (I honestly don't know who first time observed it) that in Indian context specially, 5 Exponential Moving Average (5-EMA) works pretty good as that mean.
So whenever price moves away from that 5-EMA, it ultimately comes back and attain total nirvana :) Means: if price moved way higher than the 5EMA without touching it, then price will correct to meet it's 5-EMA and if price moved way lower, it will be uplifted to meet it's 5-EMA. Funny - but it works !
Now there are already enough social media coverage on this 5-EMA strategy/setup. Even TradingView has some excellent work done on these setups. Kudos to all those great souls.
So when we came to know about this, we were thinking what we should do for the community. Because it is well cover topic (specially in Indian context). Also, there are public indicators.
Then we thought why not come up with a scanner which will scan all the Nifty-50 constituent stocks and find out on the fly, real-time which all stocks are matching this 5-EMA setup and causing a Buy/Sell trade recommendation.
Hence here we are with the first version of our first scanner on the 5EMA setup (well it has some more masala than merely a 5-EMA setup).
Why?
Parts of why is already covered up.
Now instead of blindly following 5-EMA setup, we added the Bollinger band as well. Again: it's also not new. There are enough coverage in social media about the 5-EMA+BB strategy/setup. We mercilessly borrowed from all of these.
Suppose you have an indicator.
Now you apply the indicator in your chart. And then you need to (rock) and roll through your watchlist of Nifty-50 stocks (note: TradingView has no default watchlist of Nifty-50 stock by default - you have to create one custom watchlist to list all manually) to find out which all are matching the setup, need to take a note about the trade recomendations (entry, SL, target) and other stuffs like VWAP, Volume, volatility (Bollinger Band Width).
Not any more.
This scanner will track all the Nifty-50 stocks (technically: 40 stocks other than Banking stocks) and provide which one to Buy or Sell (if any), what's the entry, SL, target, where is the VWAP of the day, what's the picture in volume (high, low, rising, falling) and the implied volatility (using Bolling band width). Also it has a naive alerting mechanism as well.
In fact the code is there to monitor the (Future) OI also and all the OI drama (OI vs price and all the 4 stuffs like long build up, long unwinding, short covering, short buildup). But unfortunately, due to some limitations of the TradingView (that one can not monitor more than 40 `ta.security` call) we have to comment out the code. If you wish you can monitor only 20 stocks and enable the OI monitoring also (20 for stocks + 20 for their OI monitoring .. total 40 `ta.security` call).
How?
To know the divergence from 5-EMA we just check if the high of the candle (on closing) is below the 5-EMA. Then we check if the closing is inside the Bollinger Band (BB). That's a Buy signal. SL: low of the candle, T: middle and higher BB.
Just opposite for selling. 5-EMA low should be above 5-EMA and closing should be inside BB (lesser than BB higher level). That's a Sell signal. SL: high of the candle, T: middle and lower BB.
Along with we compare the current bar's volume with the last-20 bar VWMA (volume weighted moving average) to determine if the volume is high or low.
Present bar's volume is compared with the previous bar's volume to know if it's rising or falling.
VWAP is also determined using `ta.vwap` built-in support of TradingView.
The Bolling Band width is also notified, along with whether it is rising or falling (comparing with previous candle).
Simple, but effective.
Customization
As usual the EMA setup (5 default), the BB setup (20 SMA with 1.5 standard deviation), we provided option wherther to include or exclude BB role in the 5-EMA setup (as we found out there are two schools of thought .. some people use BB some don't. Lets make all happy :))
We also provide options to choose other symbols using Settings if they wish so. We have the default 40 non banking Nifty stocks (why non-banking? - Bank Nifty is in ATH :) .. enough :)). But if user wishes can monitor others too (provided the symbol is there in TradingView).
Although we strongly recommend the timeframe as 30 minutes , you can choose what's fit you most.
The output of the scanner is a table. By default the table is placed in the right-bottom (as we are most comfortable with that). However you can change per your wish. We have the option to choose that.
What is unique in it ?
This is more of an indicator. This is a scanner (of Nifty-50 stocks). So you can apply (our recommendation is in 30m timeframe) it to any chart (does not matter which chart it is) and it will show every 30 mins (which is also configurable) which all stocks (along with trade levels) to Buy and Sell according to the setup.
It will ease your trading activity.
You can concentrate only on the execution, the filtering you can leave it to this one.
Limitations
There is a build in limitation of the TradingView platform is that one can call only upto 40 securities API. Not beyond that. So naturally we are constraint by that. Otherwise we could monitor 190 Nifty F&O stocks itself.
30m is the recommended timeframe. In very lower (say 5m) this script tends to go out of heap (out of memory). Please note that also.
How to trade using this?
Put any chart in 30m (recommended) timeframe.
Apply this screener from Indicators (shortcut to launch indicators is just type / in your keyboard).
This will provide the Buy (shown in green color) or Sell (shown in red color) recommendations in a table, at every 30m candle closing.
Note the volume and BB width as well.
Wait for at least 2 5-minutes candles to close above/below the recommended level .
Take the trade with the SL and target mentioned.
Mentions
@QuantNomad. The whole implementation concept we mercilessly borrowed from him, even some of his code snippet we took it (after asking him through one of his videos comment section and seeking explicit permission which he readily granted within an hour). Thank You sir @QuantNomad. Indebted to you.
Monika (Rawat) ji: for reviewing, correcting, providing real time examples during live market hours, often compromising her own trading activities, about the effectiveness and usefulness of this setup. Thank You madam ji. Indebted to you.
There are innumerable contents in social media about this. Don't even know whom all we checked. Thanks to all of them.
Happy Trading (in stocks - isn't enough of Indices already?)
Disclaimer
This piece of software does not come up with any warrantee or any rights of not changing it over the future course of time.
We are not responsible for any trading/investment decision you are taking out of the outcome of this indicator.
SuperBollingerTrend (Expo)█ Overview
The SuperBollingerTrend indicator is a combination of two popular technical analysis tools, Bollinger Bands, and SuperTrend. By fusing these two indicators, SuperBollingerTrend aims to provide traders with a more comprehensive view of the market, accounting for both volatility and trend direction. By combining trend identification with volatility analysis, the SuperBollingerTrend indicator provides traders with valuable insights into potential trend changes. It recognizes that high volatility levels often accompany stronger price momentum, which can result in the formation of new trends or the continuation of existing ones.
█ How Volatility Impacts Trends
Volatility can impact trends by expanding or contracting them, triggering trend reversals, leading to breakouts, and influencing risk management decisions. Traders need to analyze and monitor volatility levels in conjunction with trend analysis to gain a comprehensive understanding of market dynamics.
█ How to use
Trend Reversals: High volatility can result in more dramatic price fluctuations, which may lead to sharp trend reversals. For example, a sudden increase in volatility can cause a bullish trend to transition into a bearish one, or vice versa, as traders react to significant price swings.
Volatility Breakouts: Volatility can trigger breakouts in trends. Breakouts occur when the price breaks through a significant support or resistance level, indicating a potential shift in the trend. Higher volatility levels can increase the likelihood of breakouts, as they indicate stronger market momentum and increased buying or selling pressure. This indicator triggers when the volatility increases, and if the price is near a key level when the indicator alerts, it might trigger a great trend.
█ Features
Peak Signal Move
The indicator calculates the peak price move for each ZigZag and displays it under each signal. This highlights how much the market moved between the signals.
Average ZigZag Move
All price moves between two signals are stored, and the average or the median is calculated and displayed in a table. This gives traders a great idea of how much the market moves on average between two signals.
Take Profit
The Take Profit line is placed at the average or the median price move and gives traders a great idea of what they can expect in average profit from the latest signals.
-----------------
Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
FibonRSI / ErkOziHello,
This software is a technical analysis script written in the TradingView Pine language. The script creates a trading indicator based on Fibonacci retracement levels and the RSI indicator, providing information about price movements and asset volatility by using Bollinger Bands.
There are many different scripts in the market that draw RSI and Fibonacci retracement levels. However, this script was originally designed by me and shared publicly on TradingView.
***The indicator uses RSI (Relative Strength Index) and Bollinger Bands (BB) as the basis for the FibonRSI strategy. RSI measures the strength of a price movement, and BB measures the volatility of an asset. The FibonRSI strategy is based on the idea that the Fibonacci ratios and RSI can be used to predict a asset's price retracement levels.
***The script allows for various parameters to be adjusted. Users can specify the price source type and adjust the periods for RSI and Bollinger Bands. The standard deviation number for Bollinger Bands can also be customized.
***The script calculates the current RSI indicator position and the basic, upper, and lower levels of Bollinger Bands. It then calculates and draws the Fibonacci retracement levels. The color of the RSI line is determined by the upper and lower distribution levels of Bollinger Bands. Additionally, the color of the Fibonacci retracement levels can also be customized by the user.
***This script can be used to determine potential buy and sell signals using Fibonacci retracement levels and RSI. For example, when the RSI is oversold and the price is close to a Fibonacci retracement level, it can be interpreted as a buying opportunity. Similarly, when the RSI is overbought and the price is close to a Fibonacci retracement level, it can be interpreted as a selling opportunity.
***The script takes input parameters such as the price source used for calculation, the period for the RSI indicator, the period for the Moving Average in Bollinger Bands, and the number of standard deviations used in Bollinger Bands.
***The script's conditions include elements such as calculating the current position of the RSI indicator, calculating the upper and lower Bollinger Bands, calculating the dispersion factor, and calculating Fibonacci levels.
***The parameters in the code can be adjusted for calculation, including the price type used, the RSI period, the Moving Average period for BB, and the standard deviation count for BB. After this, the current position of the RSI, Moving Average, and standard deviation for BB are calculated. After calculating the upper and lower BB, the levels above and below the average are calculated using a specific dispersion constant.
CONDITIONS FOR THE SCRIPT
current_rsi = ta.rsi(src, for_rsi) // Current position of the RSI indicator
basis = ta.ema(current_rsi, for_ma)
dev = for_mult * ta.stdev(current_rsi, for_ma)
upper = basis + dev
lower = basis - dev
dispersion = 1
disp_up = basis + (upper - lower) * dispersion
disp_down = basis - (upper - lower) * dispersion
// Fibonacci Levels
f100 = basis + (upper - lower) * 1.0
f78 = basis + (upper - lower) * 0.78
f65 = basis + (upper - lower) * 0.65
f50 = basis
f35 = basis - (upper - lower) * 0.65
f23 = basis - (upper - lower) * 0.78
f0 = basis - (upper - lower) * 1.0
***When calculating Fibonacci levels, the distance between the average of BB and the upper and lower BB is used. These levels are 0%, 23.6%, 35%, 50%, 65%, 78.6%, and 100%. Finally, the RSI line that changes color according to a specific RSI position, Fibonacci levels, and BB are visualized. Additionally, the levels of 70, 30, and 50 are also shown.
The script then sets the color of the RSI position according to the EMA and draws Bollinger Bands, RSI, Fibonacci levels, and the 70, 30, and 50 levels.
In conclusion, this script enables traders to analyze market trends and make informed decisions. It can also be customized to suit individual trading strategies.
This script analyzes the RSI indicator using Bollinger Bands and Fibonacci levels. The default settings are 14 periods for RSI, 233 periods and 2 standard deviations for BB. The MA period inside BB is selected as the BB period and is used when calculating Fibonacci levels.
***The reason for selecting these settings is to provide enough time for BB period to confirm a possible trend. Additionally, the MA period inside BB is matched with the BB period and used when calculating Fibonacci levels.
***Fibonacci levels are calculated from the distance between the upper and lower bands of BB and show how RSI movement is related to these levels. Better results can be achieved when RSI periods are set to Fibonacci numbers such as 21, 55, and 89. Therefore, the use of Fibonacci numbers is recommended when adjusting RSI periods. Fibonacci numbers are among the technical analysis tools that can capture the reflection of naturally occurring movements in the market. Therefore, the use of Fibonacci numbers often helps to better track fluctuations in the market.
Finally, the indicator also displays the 70 and 30 levels and the middle level (50) with Fibonacci levels drawn in circles. Changing these settings can help optimize the Fibonacci levels and further improve the indicator.
Thank you in advance for your suggestions and opinions......
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.
