Bollinger Bands Weighted Alert System (BBWAS)The idea of this indicator is very similar to my previous published script called BBAS (Bollinger Bands Alert System).
Just with little additions. In this case, we're using a Weighted Moving Average (ta.wma) instead of Simple Moving Average to calculate the basis line.
A breakout in trading refers to a situation where the price of a security or asset moves beyond a defined level of support or resistance, which is typically indicated by technical analysis tools like Bollinger Bands. Bollinger Bands consist of three lines: the upper band, the lower band, and the middle band (or basis). The upper and lower bands are set at a specified number of standard deviations away from the middle band, and they help to define the range within which the price of an asset is expected to fluctuate.
When the price of the asset moves beyond the upper or lower band, it is said to have "broken out" of the range. If the price closes below the lower band, it is considered a bearish breakout, and if it closes above the upper band, it is considered a bullish breakout.
Once a breakout occurs, traders may look for a confirmation signal before entering a trade. In this case, crossing the middle line (or basis) after a breakout may signal a potential trend reversal and a good opportunity to enter a long or short trade, depending on the direction of the breakout.
Dear traders, while we strive to provide you with the best trading tools and resources, we want to remind you to exercise caution and diligence in your investing decisions.
It is important to always do your own research and analysis before making any trades. Remember, the responsibility for your investments ultimately lies with you.
Happy trading!
在腳本中搜尋"弘历投教boll指标代码分析"
Bollinger Band Alert with RSI Filter IndicatorThis code is for a technical analysis indicator called Bollinger Band Alert with RSI Filter. It uses two tools: Bollinger Bands and Relative Strength Index (RSI) to identify potential trading signals in the market.
Bollinger Bands are lines plotted two standard deviations away from a simple moving average of the price of a stock or asset. They help traders determine whether prices are high or low on a relative basis.
The RSI is a momentum indicator that measures the strength of recent price changes to evaluate whether an asset is overbought or oversold.
The code has some input parameters that a user can change, such as length and multiplier, which are used to calculate the Bollinger Bands, and upper and lower RSI levels to define the overbought and oversold zones.
The code then uses if statements to generate alerts if certain conditions are met. The alert condition is triggered if the close price of an asset crosses above or below the upper or lower Bollinger Bands, and if the RSI is either above or below the overbought or oversold threshold levels.
Finally, the code generates plots to visualize the Bollinger Bands and displays triangles above or below the bars indicating when to enter a long or short position based on the strategy's criteria.
Trending Bollinger Bands by SiddWolfBollinger Bands are mostly used for trend reversal. I believe they should be used for Trend Continuation and Trend Confirmation.
In this Trending Bollinger Bands script you will see two bands drawn on chart. The Upper band is suggestive of Uptrend and Lower Band is suggestive of Downtrend Market. It just provides the guidance of where the market is now and where it is headed. It is not to be used as a standalone indicator. Use this to confirm your hypothesis of Uptrend or Downtrend.
Bollinger Bands Trend
When the price crosses the moving average it is interpreted as the price is gonna continue in that direction. But most of the time it is a fake breakout. With this script you get an additional confirmation so that you know it is not a fake breakout and the price have caught the trend.
Bollinger Bands Reversal:
This indicator can also work for reversal. For example when price closes outside the outer bands, it is most likely that the trend is gonna reverse. Don't just enter the trade wait for some other confirmation as reversal trading is more complicated.
Confluence:
Confluence is the key factor for profitable trading. Don't use this indicator as standalone indicator instead combine it with other indicators and price action. Like the divergence occurring when the price is outside the bands is suggestive of trend reversal. I have created a non-delay, non-repaint indicator for finding divergence. I'd soon publish that script. Stay tuned.
Settings is the Key:
Try to play around with the settings. It is a simple yet effective indicator. Change the moving average type or length. I've found moving average RMA or WMA works better than SMA. Find the best setting that works with your setup. Set the Band Source as High/Low to make the outer bands more extreme.
Conclusion:
This is my first script but it isn't my last. I've created quite a few gems that I'm gonna publish soon. If you have any questions or suggestions feel free to comment below. I'd love to connect with you. Thank you.
Volume Adaptive Bollinger Bands (MZ VABB)This indicator is a functional enhancement to John Bollinger's Bollinger Bands. I've used Volume to adapt dynamic length which is used in basis (middle line) of Bollinger Bands and Simple Moving Average is replaced with Adaptive Ehlers Deviation Scaled Moving Average ( AEDSMA ).
BOLLINGER BANDS BASIC USAGE AND LIMITATIONS
Bollinger bands are popular among traders because of their simple way to detect volatility in market and redefine support and resistance accordingly. These are some basic usages of original Bollinger Bands:
Most commonly Bollinger Band works on 20 period Simple Moving Average as Basis / Middle Line and standard deviation of 2 for volatility detection.
Upper and lower bands can act as support and resistance which accordingly update with standard deviation of same period as of Simple Moving Average.
As upper and lower bands act as volatility measure which benefits in Squeeze detection and breakout trading.
Among all the usages there are some limitations as follows:
Original Bollinger Bands use 20 period Simple Moving Average as Basis which itself restricted to some number of data pints and if market moves in one direction or simply goes sideways for long time; candles can stay on either bands for long time. This gives benefit for staying in directional trade but will completely nullify the use of both bands as support and resistance.
Above point simply be explained as markets can stay overbought / oversold for long time and one way to make Bollinger Bands more useful is to simply use higher periods in SMA but as we know with higher periods SMA becomes more laggy and less adaptive.
Most traders use BBs alongside some other Volume Oscillator for example "On Balance Volume" but that does solve BBs limitations issue that it should be more adaptive to detect volatility in market.
VOLUME ADAPTIVE BOLLINGER BAND WORKING PRINCIPLE
Best way to make original Bollinger band more adaptive was to just use dynamic length instead on constant 20 period. This dynamic length had to be based on some other powerful parameter which can't be volatility as BB itself is a volatility indicator and adapting its length based volatility would have been superimposing volatility on Bollinger bands giving unrealistic results.
For adaptive length, I tried using Volume and for this purpose I used my Relative Volume Strength Index " RVSI " indicator. RVSI is the best way to detect if Volume is going for a breakout or not and based on that indication length of Bollinger Band Basis Moving Average changes.
RVSI breaking above provided value would indicate Volume breakout and hence dynamic length would accordingly make Bollinger band basis moving average more over fitted and similarly standard deviation of achieved dynamic length would give better bands for support and resistance. Similar case would happen if Volume goes down and dynamic length becomes more underfit.
According to my back testing studies I found that Simple Moving Average wasn't the best choice for dynamic length usage in Bollinger Band Basis. So, I used Adaptive Ehlers Deviation Scaled Moving Average ( AEDSMA ) which is more adaptive and already modified to adapt with RVSI.
SLOPE USAGE FOR TREND STRENGTH DETCTION
Volume Adaptive Bollinger Bands are more reactive to market trends so, I used slope for trend strength detection.
If slope of Volume Adaptive Bollinger Band Basis (i.e. AEDSMA ), Upper and Lower Bands is supporting a trend at same time then script will provide signal in that direction. That signal can also use Volume as confirmation if Bollinger Bands trend direction is supported by Volume or not.
DYNAMIC COLORS AND TREND CORRELATION
I’ve used dynamic coloring in Basis ( AEDSMA ) to identify trends with more detail which are as follows:
Lime Color: Slope supported Strong Uptrend also supported by Volume and Volatility or whatever you’ve chosen from both of them.
Fuchsia Color: Weak uptrend only supported by Slope or whatever you’ve selected.
Red Color: Slope supported Strong Downtrend also supported by Volume and Volatility or whatever you’ve chosen from both of them.
Grey Color: Weak Downtrend only supported by Slope or whatever you’ve selected.
Yellow Color: Possible reversal indication by Slope if enabled. Market is either sideways, consolidating or showing choppiness during that period.
SIGNALS
Green Circle: Market good for long with support of Volume and Volatility or whatever you’ve chosen from both of them.
Red Circle: Market good to short with support from Volume and Volatility or whatever you’ve chosen from both of them.
Flag: Market either touched upper or lower band and can act as good TP and warning for reversal.
FIBONACCI BANDS
I’ve included Fibonacci multiple bands which would act as good support/resistance zones. For example, 0.618 Fib level act as good local support and resistance in both upper and lower zones. Fibonacci values can be modified but should be lower than 1.
DEFAULT SETTINGS
I’ve set default Minimum length to 50 and Maximum length to 100 which I’ve found works best for almost all timeframes but you can change this delta to adapt your timeframe accordingly with more precision.
Dynamic length adoption is enabled based on Volume only but volatility can be selected which is already explained above.
Trend signals are enabled based on Slope and Volume but Volatility can be enabled for more precise confirmations.
In “ RVSI ” settings "Klinger Volume Oscillator" is set to default but others work good too especially Volume Zone Oscillator. For more details about Volume Breakout you can check “MZ RVSI Indicator".
ATR breakout is set to be positive if period 14 exceeds period 46 but can be changed if more adaption with volatility is required.
EDSMA super smoother filter length is set to 20 which can be increased to 50 or more for better smoothing but this will also change slope results accordingly.
EDSMA super smoother filter poles are set to 2 because found better results with 2 instead of 3.
FURTHER ENHANCEMENTS
So far, I've achieved better results with "Klinger Volume Oscillator" in RVSI but TFS Volume Oscillator and On Balance Volume can be used which would change dynamic length differently. It doesn't mean that results would be wrong with some oscillator and precise with others but every oscillator works in its specific way for and RVSI just detect strength of Volume based on provided oscillator.
Bollinger Bands strategy with RSI and MACD v1.0 This is a strategy based on the Bollinger Bands, where buy trades are made when the price crosses the lower line of the Bollinger Bands upwards, and sell trades are made when the price crosses the upper line downwards.
In addition, it is possible through the inputs to enable trading with RSI and MACD, so that buy or sell trades are supported by these two indicators.
Trades are partially and fully closed in the following way, a buy trade will close half of the position when the price touches the middle line of the Bollinger bands and will be fully closed when the price touches the upper band. In the case of a sell position, half of the position will be closed if the price touches the middle band and the entire position will be closed when the price touches the lower band. Alternatively, a fixed take profit can be placed. In case the price moves against us, trailing stops can be placed.
In case of selecting to use RSI, MACD, or MACD variation, trades will be executed as long as The Bollinger Bands, and all the above-mentioned indicators give the same signals, either buy or sell.
For example in the case of selecting only Use RSI, buy trades would be made as long as RSI and BB give buy signals.
Strategy inputs:
-BB source: Bollinger Bands price source.
-Bollinger Bands SMA length: Bollinger Bands simple moving average length.
-Bollinger Bands StdDev length: Bollinger Bands standard deviation length.
-Trail Long Loss (%): Distance in percentage at which the stop loss will initially be placed for buy trades.
-Trail Short Loss (%): Distance in percentage at which the stop loss will be initially placed for sell trades.
-Maximum orders: Maximum of simultaneous operations, for example, if it is 3, up to 3 parallel operations of buy and up to 3 parallel operations of sell will be carried out.
-Position size: Number of contracts per trade.
-Use RSI: If selected, the strategy will also trade based on oversold or overbought signals provided by the RSI.
-RSI source: RSI price source.
-RSI period: The RSI period to use.
-RSI value for buy: If the RSI is below this value, it will give a buy signal.
-RSI value for sell: If the RSI value is above this value, it will give a sell signal.
-Use MACD: If selected, buy trades will be made when the MACD crosses 0 upwards, and sell trades will be made when the MACD crosses 0 downwards.
-Use MACD variation: Only available if MACD is previously selected. In this case, buy trades are made if the MACD value in the last 3 candles has been decreasing, and sell trades are made if the MACD value has been increasing.
-MACD source: MACD price source.
-MACD fast length: MACD fast EMA lenght.
-MACD slow length: MACD slow EMA lenght.
-MACD signal length: MACD signal EMA lenght.
-Use maximum TP long: If selected, a fixed take profit will be placed for buy trades. The position could be closed before reaching this take profit if the price touches one of the lower or upper lines first.
-Maximum take profit long (%): Distance in percentage at which the take profit will be placed for buy trades.
-Use maximum TP short: if selected, a fixed take profit will be placed for sell trades. The position could be closed before reaching this take profit if the price touches one of the lower or upper lines first.
-Maximum take profit short (%): Distance in percentage at which the take profit will be set for sell trades.
I hope you like it and as always all feedback is welcome.
LAGging span leaves Bollinger Bands strategyAbstract
This script points out the positions a lagging span leaves a Bollinger Band.
This script does not plot a lagging span but moves the Bollinger Band forward.
You can find profit opportunities by combining this script and risk management.
Introduction
Bollinger Bands is a popular indicator.
It contains a moving average, an upper band and a lower band.
The moving average can indicate trend, the upper band and the lower band can indicate if the price is far away from the moving average.
However, in trading markets, anything can happen.
Both continuation and reversal are possible when the price touches the moving average, the upper band or the lower band.
Therefore, many traders adjust the parameters of the Bollinder Band or add other indicators to improve their trading strategies.
@Daveatt et. al. provided an idea that uses a lagging span.
A lagging span is a line chart. It displays the reference price but in earlier time.
For example, if the offset of a lagging span is 26 days, the value of the lagging span on 29 days ago is the reference price 3 days ago.
A lagging span is a part of Ichimoku Cloud.
It can compare the price to the earlier price and the values of indicators in the past.
To compare the price to the values of indicators in the past, we can also shift indicators forward instead of adding a lagging span into the chart.
This script uses shift-the-indicators-forward method.
In other words, this script plots the Bollinger Band forward so that the price can be compared to the values of the Bollinger Band in the past.
Computing and Adjusting
(1) Compute Moving Average
(2) Compute Standard Derivation
(3) Upper Band = Moving Average + Standard Derivation * Multi
(4) Lower Band = Moving Average - Standard Derivation * Multi
(5) Shift the Bollinger Band forward according to the offset parameter.
(6) Mark the points the price leaves the shifted Bollinger Band
(7) Compute the most possible loss and profit before the next opposite signal.
Parameters
source : the data for computing the bollinger band. can be open, high, low, close or their combination.
length : how many days are calculated by the bollinger band
mult : the distance from the moving average to the upper band and the distance from the moving average to the upper band is equal to ( mult * standard derivation ) .
x_offset : the offset of the lagging span
Conclusion
This script can find signals for potential breakout or trend continuation.
If you want to use this signal well, you need to know when to cut loss and protect the profit.
Reference
@Daveatt , Bollinger bands/Lagging span cross , BGyrPgOA , Tradingview 2019
How to trade with Bollinger Bands
How to use Ichimoku Cloud
How to trade with a line chart
Bollinger Band Open Gap Alert V1This is the bare bones of what I'm trying to achieve through pine script. The purpose of the script is to:
1. On a 15m chart, calculate and plot upper & lower Bollinger bands and simple moving average of 20 periods. (DONE)
2. On a new day, when the first 15m candle of a session forms, I want to check if a) the low of the new candle is outside the upper Bollinger band (also known as an open gap up) or b) if the high of the candle is the outside the lower Bollinger band (also known as open gap down). In other words, I want to know if the Bollinger Bands are not touching the new candle's wicks/shadows. (DONE)
3. Alert me if the above happens. (DONE)
4. Run the indicator through an entire watch list. I'm not sure if that's possible, yet. (HELP)
For the above job, this is what I could come up with. I need guidance for the last step . And any suggestions for corrections or improvements would be greatly appreciated!
Fibonacci Bollinger Volume Weighted DeviationDiscover market dynamics with the 'Fibonacci Bollinger Volume Weighted Deviation' indicator – a unique tool blending Fibonacci ratios, Bollinger Bands, and volume-weighted analysis. Ideal for spotting overbought/oversold conditions and potential market turnarounds, this indicator is a must-have for traders seeking nuanced insights into price behavior and volatility.
Description:
"The 'Fibonacci Bollinger Volume Weighted Deviation' indicator presents a novel approach to market trend analysis by integrating Fibonacci ratios with the classic concept of Bollinger Bands. Designed for traders who incorporate Fibonacci levels in their market analysis, this indicator adapts Bollinger Bands to a user-defined Fibonacci ratio. It creates dynamic upper and lower bands around a Simple Moving Average (SMA), offering insights into price deviations and potential overbought or oversold market states.
Incorporating volume data, this indicator provides a volume-weighted perspective of price deviations. This feature is crucial in gauging the market sentiment, as significant volumes linked with price deviations can signal strong market moves. By plotting these deviations and emphasizing those that significantly diverge from the volume-weighted average, it aids in pinpointing potential turning points or key support and resistance zones.
Versatile in nature, the 'Fibonacci Bollinger Volume Weighted Deviation' indicator is adaptable to various trading styles and market conditions. It proves especially valuable in markets where Fibonacci levels are a key factor. Traders can explore long positions when prices fall below the lower band and consider short positions when prices breach the upper band. The addition of volume-weighted deviation analysis refines these trading signals, offering a more sophisticated and nuanced decision-making process for entries and exits.
As a standalone tool or in conjunction with other technical instruments, this indicator is an invaluable addition to any technical analyst's toolkit. It not only enhances traditional Fibonacci and Bollinger Band methodologies but also integrates volume analysis to provide a comprehensive view of market trends and movements."
Bollinger Bands StrategyBollinger Bands Strategy :
INTRODUCTION :
This strategy is based on the famous Bollinger Bands. These are constructed using a standard moving average (SMA) and the standard deviation of past prices. The theory goes that 90% of the time, the price is contained between these two bands. If it were to break out, this would mean either a reversal or a continuation. However, when a reversal occurs, the movement is weak, whereas when a continuation occurs, the movement is substantial and profits can be interesting. We're going to use BB to take advantage of this strong upcoming movement, while managing our risks reasonably. There's also a money management method for reinvesting part of the profits or reducing the size of orders in the event of substantial losses.
BOLLINGER BANDS :
The construction of Bollinger bands is straightforward. First, plot the SMA of the price, with a length specified by the user. Then calculate the standard deviation to measure price dispersion in relation to the mean, using this formula :
stdv = (((P1 - avg)^2 + (P2 - avg)^2 + ... + (Pn - avg)^2) / n)^1/2
To plot the two Bollinger bands, we then add a user-defined number of standard deviations to the initial SMA. The default is to add 2. The result is :
Upper_band = SMA + 2*stdv
Lower_band = SMA - 2*stdv
When the price leaves this channel defined by the bands, we obtain buy and sell signals.
PARAMETERS :
BB Length : This is the length of the Bollinger Bands, i.e. the length of the SMA used to plot the bands, and the length of the price series used to calculate the standard deviation. The default is 120.
Standard Deviation Multipler : adds or subtracts this number of times the standard deviation from the initial SMA. Default is 2.
SMA Exit Signal Length : Exit signals for winning and losing trades are triggered by another SMA. This parameter defines the length of this SMA. The default is 110.
Max Risk per trade (in %) : It's the maximum percentage the user can lose in one trade. The default is 6%.
Fixed Ratio : This is the amount of gain or loss at which the order quantity is changed. The default is 400, meaning that for each $400 gain or loss, the order size is increased or decreased by a user-selected amount.
Increasing Order Amount : This is the amount to be added to or subtracted from orders when the fixed ratio is reached. The default is $200, which means that for every $400 gain, $200 is reinvested in the strategy. On the other hand, for every $400 loss, the order size is reduced by $200.
Initial capital : $1000
Fees : Interactive Broker fees apply to this strategy. They are set at 0.18% of the trade value.
Slippage : 3 ticks or $0.03 per trade. Corresponds to the latency time between the moment the signal is received and the moment the order is executed by the broker.
Important : A bot has been used to test the different parameters and determine which ones maximize return while limiting drawdown. This strategy is the most optimal on BITSTAMP:BTCUSD in 8h timeframe with the following parameters :
BB Length = 120
Standard Deviation Multipler = 2
SMA Exit Signal Length = 110
Max Risk per trade (in %) = 6%
ENTER RULES :
The entry rules are simple:
If close > Upper_band it's a LONG signal
If close < Lower_band it's a SHORT signal
EXIT RULES :
If we are LONG and close < SMA_EXIT, position is closed
If we are SHORT and close > SMA_EXIT, the position is closed
Positions close automatically if they lose more than 6% to limit risk
RISK MANAGEMENT :
This strategy is subject to losses. We manage our risk using the exit SMA or using a SL sets to 6%. This SMA gives us exit signals when the price closes below or above, thus limiting losses. If the signal arrives too late, the position is closed after a loss of 6%.
MONEY MANAGEMENT :
The fixed ratio method was used to manage our gains and losses. For each gain of an amount equal to the fixed ratio value, we increase the order size by a value defined by the user in the "Increasing order amount" parameter. Similarly, each time we lose an amount equal to the value of the fixed ratio, we decrease the order size by the same user-defined value. This strategy increases both performance and drawdown.
NOTE :
Please note that the strategy is backtested from 2017-01-01. As the timeframe is 8h, this strategy is a medium/long-term strategy. That's why only 51 trades were closed. Be careful, as the test sample is small and performance may not necessarily reflect what may happen in the future.
Enjoy the strategy and don't forget to take the trade :)
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.
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.
Dynamic Zone of Bollinger Band Stops Line [Loxx]Dynamic Zone of Bollinger Band Stops Line is a Bollinger Band indicator with Dynamic Zones. This indicator serves as both a trend indicator and a dynamic stop-loss indicator.
What are Bollinger Bands?
A Bollinger Band is a technical analysis tool defined by a set of trendlines plotted two standard deviations (positively and negatively) away from a simple moving average (SMA) of a security's price, but which can be adjusted to user preferences.
Bollinger Bands were developed and copyrighted by famous technical trader John Bollinger, designed to discover opportunities that give investors a higher probability of properly identifying when an asset is oversold or overbought.
What are Dynamic Zones?
As explained in "Stocks & Commodities V15:7 (306-310): Dynamic Zones by Leo Zamansky, Ph .D., and David Stendahl"
Most indicators use a fixed zone for buy and sell signals. Here’ s a concept based on zones that are responsive to past levels of the indicator.
One approach to active investing employs the use of oscillators to exploit tradable market trends. This investing style follows a very simple form of logic: Enter the market only when an oscillator has moved far above or below traditional trading lev- els. However, these oscillator- driven systems lack the ability to evolve with the market because they use fixed buy and sell zones. Traders typically use one set of buy and sell zones for a bull market and substantially different zones for a bear market. And therein lies the problem.
Once traders begin introducing their market opinions into trading equations, by changing the zones, they negate the system’s mechanical nature. The objective is to have a system automatically define its own buy and sell zones and thereby profitably trade in any market — bull or bear. Dynamic zones offer a solution to the problem of fixed buy and sell zones for any oscillator-driven system.
An indicator’s extreme levels can be quantified using statistical methods. These extreme levels are calculated for a certain period and serve as the buy and sell zones for a trading system. The repetition of this statistical process for every value of the indicator creates values that become the dynamic zones. The zones are calculated in such a way that the probability of the indicator value rising above, or falling below, the dynamic zones is equal to a given probability input set by the trader.
To better understand dynamic zones, let's first describe them mathematically and then explain their use. The dynamic zones definition:
Find V such that:
For dynamic zone buy: P{X <= V}=P1
For dynamic zone sell: P{X >= V}=P2
where P1 and P2 are the probabilities set by the trader, X is the value of the indicator for the selected period and V represents the value of the dynamic zone.
The probability input P1 and P2 can be adjusted by the trader to encompass as much or as little data as the trader would like. The smaller the probability, the fewer data values above and below the dynamic zones. This translates into a wider range between the buy and sell zones. If a 10% probability is used for P1 and P2, only those data values that make up the top 10% and bottom 10% for an indicator are used in the construction of the zones. Of the values, 80% will fall between the two extreme levels. Because dynamic zone levels are penetrated so infrequently, when this happens, traders know that the market has truly moved into overbought or oversold territory.
Calculating the Dynamic Zones
The algorithm for the dynamic zones is a series of steps. First, decide the value of the lookback period t. Next, decide the value of the probability Pbuy for buy zone and value of the probability Psell for the sell zone.
For i=1, to the last lookback period, build the distribution f(x) of the price during the lookback period i. Then find the value Vi1 such that the probability of the price less than or equal to Vi1 during the lookback period i is equal to Pbuy. Find the value Vi2 such that the probability of the price greater or equal to Vi2 during the lookback period i is equal to Psell. The sequence of Vi1 for all periods gives the buy zone. The sequence of Vi2 for all periods gives the sell zone.
In the algorithm description, we have: Build the distribution f(x) of the price during the lookback period i. The distribution here is empirical namely, how many times a given value of x appeared during the lookback period. The problem is to find such x that the probability of a price being greater or equal to x will be equal to a probability selected by the user. Probability is the area under the distribution curve. The task is to find such value of x that the area under the distribution curve to the right of x will be equal to the probability selected by the user. That x is the dynamic zone.
Included
Bar coloring
Signals
Alerts
3 types of signal smoothing
Bollinger Bands + EMA 9A 1 minute scalping strategy.
Uses Bollinger Bands (no basis line) and a 9 period EMA.
Waits for price to close below the lower Bollinger Band and the next candle to close bullish above the lower Bollinger Band but below the 9 Period EMA.
If all conditions are met, the script enters a long position with TP at the 9 Period EMA.
Bollinger Band with Moving Average & Pin BarsThis indicator was specifically built to be used for trading the Scalpius Trading System promoted by @scottphillipstrading. Additionally I've added Daily and Weekly Highs, Lows and Central Pivot lines
The central indicators used in the Scalpius trading system which are included here are: The Bollinger Band, chart plotting of Pin Bars (Hammers & Shooting Stars) and an Exponential Moving Average.
In the settings the user has the option select EMA, SMA or WMA along with desired length, the default settings are 8EMA as per the Scalpius system rules. Also the Bollinger Band settings can be amended by the user and the Pin Bar chart plots and daily + weekly high and low plots can be removed by the user.
Pluto Star - Bollinger Band Trap//DESCRIPTION
//Pluto star appears on a chart when price goes in the in the extreme price range territory, i.e. beyond 2 standard deviation from the mean (or mid Bollinger Band).
//What makes a Pluto Star appear on a chart:
//1. Check if the candle 's' high and low, both are completely outside of the Bollinger Bands (close, 20, 2) - Lets call it Pluto Star Candle
//2. Pluto Star Candle must not be a result of sudden price movement. Hence the previous candle must give a BB Blast.
// In other words, the candle must have it's either open or close outside of Bollinger Bands, to confirm a BB Blast before the Pluto Star
//3. Candle, following the Pluto Star must not break the high (in case of upper BB i.e. short call) or low (in case of lower BB, i.e. long call), to confirm the reversal to the mean
// This implies that Pluto Star appears on chart, above/below the next candle of actual Pluto Star Candle
//----- The above 3 conditions make a Pluto Star appear on a chart. But one must wait for a trade signal. Read the following conditions
//4. There is a signal line, which is nothing but ema(close,5)
//5. The red dotted line is the signal range (and also acts as Stop Loss). The price must close above/below the signal line within the signal range
//6. For a red Pluto Star (short call), the price must close below the signal line, within next 6 candles (signal range). Else there is no trigger for a trade
//7. For a green Pluto Star (long call), the price must close above the signal line, within next 6 candles (signal range). Else there is no trigger for a trade
//8. If any of the candle crosses the Stop Loss line within signal range, there is no trigger for a trade
//9. In a normal scenario, the price must return to the mean, i.e. mid Bollinger Band. In best case scenario, it must go to the opposite side Bollinger Band.
//Recommendation: Test it with Nifty and Bank Nifty charts on 30 mins and 1 hour timeframes
Simple Bollinger Bands + 3 EMAWe know that the number of indicators that we can use is limited, that is why with this indicator the Bollinger Bands + 3 EMAs join and be able to use 4 indicators in 1.
Bollinger Bands (BB)
Bollinger Bands (BB) are a widely popular technical analysis instrument created by John Bollinger in the early 1980’s. Bollinger Bands consist of a band of three lines which are plotted in relation to security prices. The line in the middle is usually a Simple Moving Average (SMA) set to a period of 20 days (the type of trend line and period can be changed by the trader; however a 20 day moving average is by far the most popular). The SMA then serves as a base for the Upper and Lower Bands which are used as a way to measure volatility by observing the relationship between the Bands and price. Typically the Upper and Lower Bands are set to two standard deviations away from the SMA (The Middle Line); however the number of standard deviations can also be adjusted by the trader.
Exponential Moving Average (EMA)
Moving averages visualize the average price of a financial instrument over a specified period of time. However, there are a few different types of moving averages. They typically differ in the way that different data points are weighted or given significance. An Exponential Moving Average (EMA) is very similar to (and is a type of) a weighted moving average. The major difference with the EMA is that old data points never leave the average. To clarify, old data points retain a multiplier (albeit declining to almost nothing) even if they are outside of the selected data series length.
The 3 EMAs that the Script has, are configured as follows:
Fast EMA (purple) 10 periods.
Slow EMA (blue) 55 periods.
Big EMA (olive) 200 periods.
However, you can configure each one with the color and the number of periods you want.
There are other indicators in the Public Library that have similar functions to this Script, but they all do it in a more complex and less friendly way when configuring it, for this reason we wanted to keep this Script as simple as possible.
Asynchronous Bollinger Bands - Async BBThis indicator allows you to draw Bollinger bands using higher timeframes.
Note: The timer of your Bollinger Bands must be a multiple of the current chart of the chart.
For example: If your chart is 4 h and you set the sync value to 3, the Bollinger Bands will be drawn with a 12H time frame. 3 * 4H = 12
If the sync is equal to 1, normal Bollinger bands are drawn and will be no different from the normal Bollinger band .
Using this indicator may be appropriate for fractal perspectives.
Bollinger Bands Stochastic RSI Extreme SignalThis is the finalized code released to the public that I created in a video linked here.
This indicators combines a Bollinger Band and Stochastic RSI to produce signals for possible price reversal. The signals are displayed by default as green arrows for bullish and red arrows for bearish.
To trigger a signal the indicator checks for the following:
(Bullish)
A candle closes above the upper Bollinger Band
The following candle closes within the upper Bollinger Band
The RSI Stochastic is below the set threshold (10 by default)
(Bearish)
A candle closes below the lower Bollinger Band
The following candle closes within the lower Bollinger Band
The RSI Stochastic is above the set threshold (90 by default)
Bollinger + RSI, Double Strategy Long-Only (by ChartArt) v1.2This strategy uses the RSI indicator together with the Bollinger Bands to go long when the price is below the lower Bollinger Band (and to close the long trade when this value is above the upper Bollinger band).
This simple strategy only places a long, when both the RSI and the Bollinger Bands indicators are at the same time in a oversold condition.
In this new version 1.2 the strategy was simplified even more than before by going long-only, which made the strategy more successful in backtesting than the previous version (that older version also opened short trades).
This strategy does not repaint and was updated to PineScript version 3.
All trading involves high risk; past performance is not necessarily indicative of future results. Hypothetical or simulated performance results have certain inherent limitations. Unlike an actual performance record, simulated results do not represent actual trading. Also, since the trades have not actually been executed, the results may have under- or over-compensated for the impact, if any, of certain market factors, such as lack of liquidity. Simulated trading programs in general are also subject to the fact that they are designed with the benefit of hindsight. No representation is being made that any account will or is likely to achieve profits or losses similar to those shown.
P.S. For advanced users: If you want also be able to short with the same strategy approach, then please use my older version 1.1:
Bollinger + RSI, Double Strategy (by ChartArt)Bollinger Bands + RSI, Double Strategy
This strategy uses a slower RSI with period 16 to sell when the RSI increases over the value of 55 (or to buy when the value falls below 45), with the classic Bollinger Bands strategy to sell when the price is above the upper Bollinger Band and falls below it (and to buy when the price is below the lower band and rises above it). This strategy only triggers when both the RSI and the Bollinger Bands indicators are at the same time in the described overbought or oversold condition. In addition there are color alerts which can be deactivated.
This basic strategy is based upon the "RSI Strategy" and "Bollinger Bands Strategy" which were created by Tradingview and uses no money management like a trailing stop loss and no scalping methods. Every win/loss trade is simply counted from the last overbought/oversold condition to the next one.
This strategy does not use close prices from higher-time frame and should not repaint after the current candle has closed. It might repaint like every Tradingview indicator while the current candle hasn't closed.
All trading involves high risk; past performance is not necessarily indicative of future results. Hypothetical or simulated performance results have certain inherent limitations. Unlike an actual performance record, simulated results do not represent actual trading. Also, since the trades have not actually been executed, the results may have under- or over-compensated for the impact, if any, of certain market factors, such as lack of liquidity. Simulated trading programs in general are also subject to the fact that they are designed with the benefit of hindsight. No representation is being made that any account will or is likely to achieve profits or losses similar to those shown.
Welford Bollinger Bands (WBB)The Welford method is an algorithm for calculating the running average and variance of a series of numbers in a single pass, without the need to store all the previous values. It works by maintaining an ongoing running average and variance, updating them with each new value in the series. The running average is updated using a simple formula that adds the new value to the previous average, weighed by the number of values that have been processed so far. The variance is updated using a similar formula that takes into account the deviation of the new value from the running average.
The Welford method has several advantages that make it a good fit for use in calculating Bollinger Bands. First, it is more numerically stable than other methods, as it avoids accumulating round-off errors and can handle large numbers of data points without overflow or underflow. This is important when working with financial data, which can contain large price movements and wide ranges of values.
Second, the Welford method is well-suited for use in real-time or streaming data scenarios where all the data may not be available upfront. This is useful in the context of Bollinger Bands, which are often used to identify trend changes and trading opportunities in real-time, as the bands are updated with each new data point.
Finally, the Welford method is simple and efficient, making it easy to implement and fast to compute. This is important when creating technical indicators and trading strategies, as performance is often a critical factor.
Overall, the Welford method is a reliable and efficient way to calculate the running average and variance of a series of numbers, making it a good fit for use in calculating Bollinger Bands and other technical indicators.
Bollinger Band strategy with split, limit, stopEntering a short position after breaking the upper Bollinger Band, entering a long position when entering after breaking the lower Bollinger Band
Provides templates for how to display position average price, stop loss, and profit price using the plot function on the chart, and how to buy splits
After entering the position, if the price crosses the mid-band line, the stop loss is adjusted to the mid-band line.
Bollinger Bands and RSI Short Selling (by Coinrule)The Bollinger Bands are among the most famous and widely used indicators. A Bollinger Band is a technical analysis tool defined by a set of trendlines plotted two standard deviations (positively and negatively) away from a simple moving average ( SMA ) of a security's price, but which can be adjusted to user preferences. They can suggest when an asset is oversold or overbought in the short term, thus provide the best time for buying and selling it.
The relative strength index ( RSI ) is a momentum indicator used in technical analysis . RSI measures the speed and magnitude of a security's recent price changes to evaluate overvalued or undervalued conditions in the price of that security. The RSI can do more than point to overbought and oversold securities. It can also indicate securities that may be primed for a trend reversal or corrective pullback in price. It can signal when to buy and sell. Traditionally, an RSI reading of 70 or above indicates an overbought situation. A reading of 30 or below indicates an oversold condition.
The short order is placed on assets that present strong momentum when it's more likely that it is about to decrease further. The rule strategy places and closes the order when the following conditions are met:
ENTRY
The closing price is greater than the upper standard deviation of the Bollinger Bands
The RSI is less than 70
EXIT
The trade is closed in profit when the RSI is less than 70
Upper standard deviation of the Bollinger Band is greater than the the closing price.
This strategy comes with a stop loss and a take profit, and as you can see by the results, it is well suited for a bear market.
This trade works very well with ETH (1h timeframe), AVA (4h timeframe), and SOL (3h timeframe) and is backtested from the 1 December 2021 to capture how this strategy would perform in a bear market.
To make the results more realistic, the strategy assumes each order to trade 30% of the available capital. A trading fee of 0.1% is taken into account. The fee is aligned to the base fee applied on Binance, which is the largest cryptocurrency exchange.
