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
Tìm kiếm tập lệnh với "bands"
Multi Bollinger Bands with Over ZoneThis indicator is called "Multi Bollinger Bands with Over Zone". The indicator uses linear regression to calculate the regression line and standard deviation to calculate the upper and lower deviation lines. It also plots filled areas between the deviation lines to highlight overbought and oversold zones.
The indicator has several customizable inputs, including the length of the regression period, depth, and deviations used to calculate the deviation lines.
The regression line is plotted in green color with circle markers. The upper and lower deviation lines are plotted in blue and red colors, respectively. The area between the deviation lines is filled with light blue color for the overbought zone and light pink color for the oversold zone.
This indicator helps traders in identifying trends and potential price reversals. When the price is above the upper deviation line, it indicates a potential overbought zone, while when the price is below the lower deviation line, it indicates a potential oversold zone.
Please note that this indicator is only a tool for analysis and does not provide direct trading signals. It is important to combine this indicator with additional analysis and appropriate trading strategies.
Bollinger Bands %B (ValueRay)One of the key features of this BB%B is its ability to highlight overbought and oversold conditions. This allows you to make informed decisions on when to enter and exit a trade, helping you maximize your profits and minimize your losses.
- Bollinger Bands %B with the ability to change to a different Time Frame.(Defaults to current Chart Time Frame).
- Ability To Turn On/Off Background Highlighting if BB %B is Above/Below 0 / 1 thresholds.
- Ability To Turn On/Off Background Highlighting when BB %B Crosses back above/unser 0/1 thresholds.
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My personal recommandation use: combine with CM_Ultimate RSI Multi Time Frame (ChrisMoody) and have solid oversold/overbought levels, when hes RSI and my BB %B are bot red/green
Momentum Deviation Bands [Loxx]Momentum Deviation Bands uses a variation of standard deviation. Instead of using price to calculate standard deviation, this uses momentum. This is another type of volatility that will be used in future indicators. This indicator serves more as an educational tool, but can also be used in trading.
You can read about the included moving averages here:
Included
Bar coloring
VWMA Fibonacci Bands (VFIBs)This is a momentum indicator , utilizing Volume Weighted Moving Averages (VWMAs), Average True Range (ATR), and Fibonacci Levels.
This indicator can be used in most, if not all, financial markets. I have personally found it to be most useful in mid or large cap stocks, index funds, and cryptocurrencies in the top 25 by market cap. I have not tested this indicator in Forex markets, but I imagine that it would function well there, too.
The idea behind proper use of this indicator centers around mean reversion. If price is low compared to previous price action, mean reversion implies that it is likely to revert back to the mean, over time. If price is high, it implies that it will move lower. Generally, the different period VWMAs (center lines) will act as support when in an uptrend and resistance when in a downtrend. Additionally, it is rare for price to go above the upper bounds or lower bounds of the Fibonacci Bollinger Bands . Price action doing so may indicate a potential short or long position, respectively.
This indicator is intended to be used in tandem with the oscillator 'VFIBs Agreement', to be published shortly.
As we can see in the chart, the 50 week VWMA has been acting as resistance and recently dipped down to the bottom range of the band, only to bounce back. Holding above the 50 VWMA might indicate a bullish reversal, treating it as support moving forward.
Distance Bands Oscillator_KT █ OVERVIEW
This tool is based on both Bollinger Bands and Keltner Channels, and measures 3 distances between the two, respectively.
Upper Kelt to Upper Bollinger Band
Lower Kelt to Lower Bollinger Band
Kelt Basis to Bollinger Basis Basis
Similar to the Band Width indicator, this can be used as a measure of volatility, and can be used to measure uptrend, downtrend and chop regions on a given chart.
Happy Trading,
ET
HMA w/ SSE-Dynamic EWMA Volatility Bands [Loxx]This indicator is for educational purposes to lay the groundwork for future closed/open source indicators. Some of thee future indicators will employ parameter estimation methods described below, others will require complex solvers such as the Nelder-Mead algorithm on log likelihood estimations to derive optimal parameter values for omega, gamma, alpha, and beta for GARCH(1,1) MLE and other volatility metrics. For our purposes here, we estimate the rolling lambda (λ) value used to calculate EWMA by minimizing of the sum of the squared errors minus the long-run variance--a rolling window of the one year mean of squared log-returns. In practice, practitioners will use a λ equal to a standardized value put out by institutions such as JP Morgan. Even simpler than this, others use a ratio of (per - 1) / (per + 1) to derive λ where per is the lookback period for EWMA. Due to computation limits in Pine, we'll likely not see a true GARCH(1,1) MLE on Pine for quite some time, but future closed source indicators will contain some very interesting industry hacks to get close by employing modifications to EWMA. Enjoy!
Exponentially weighted volatility and its relationship to GARCH(1,1)
Exponentially weighted volatility--also called exponentially weighted moving average volatility (EWMA)--puts more weight on more recent observations. EWMA is calculated as follows:
σ*2 = λσ(n - 1)^2 + (1 − λ)u(n - 1)^2
The estimate, σn, of the volatility for day n (made at the end of day n − 1) is calculated from σn −1 (the estimate that was made at the end of day n − 2 of the volatility for day n − 1) and u^n−1 (the most recent daily percentage change).
The EWMA approach has the attractive feature that the data storage requirements are modest. At any given time, we need to remember only the current estimate of the variance rate and the most recent observation on the value of the market variable. When we get a new observation on the value of the market variable, we calculate a new daily percentage change to update our estimate of the variance rate. The old estimate of the variance rate and the old value of the market variable can then be discarded.
The EWMA approach is designed to track changes in the volatility. Suppose there is a big move in the market variable on day n − 1 so that u2n−1 is large. This causes our estimate of the current volatility to move upward. The value of λ governs how responsive the estimate of the daily volatility is to the most recent daily percentage change. A low value of λ leads to a great deal of weight being given to the u(n−1)^2 when σn is calculated. In this case, the estimates produced for the volatility on successive days are themselves highly volatile. A high value of λ (i.e., a value close to 1.0) produces estimates of the daily volatility that respond relatively slowly to new information provided by the daily percentage change.
The RiskMetrics database, which was originally created by JPMorgan and made publicly available in 1994, used the EWMA model with λ = 0.94 for updating daily volatility estimates. The company found that, across a range of different market variables, this value of λ gives forecasts of the variance rate that come closest to the realized variance rate. In 2006, RiskMetrics switched to using a long memory model. This is a model where the weights assigned to the u(n -i)^2 as i increases decline less fast than in EWMA.
GARCH(1,1) Model
The EWMA model is a particular case of GARCH(1,1) where γ = 0, α = 1 − λ, and β = λ. The “(1,1)” in GARCH(1,1) indicates that σ^2 is based on the most recent observation of u^2 and the most recent estimate of the variance rate. The more general GARCH(p, q) model calculates σ^2 from the most recent p observations on u2 and the most recent q estimates of the variance rate.7 GARCH(1,1) is by far the most popular of the GARCH models. Setting ω = γVL, the GARCH(1,1) model can also be written:
σ(n)^2 = ω + αu(n-1)^2 + βσ(n-1)^2
What this indicator does
Calculate log returns log(close/close(1))
Calculates Lambda (λ) dynamically by minimizing the sum of squared errors. I've restricted this to the daily timeframe so as to not bloat the code with additional logic required to derive an annualized EWMA historical volatility metric.
After the Lambda is derived, EWMA is calculated one last time and the result is the daily volatility
This daily volatility is multiplied by the source and the multiplier +/- the HMA to create the volatility bands
Finally, daily volatility is multiplied by the square-root of days per year to derive annualized volatility. Years are trading days for the asset, for most everything but crypto, its 252, for crypto is 365.
BT-Bollinger Bands - Trend FollowingEsse script foi criado para estudo de Backtest.
O script usa as Bandas de Bollinger para indicar o início de uma tendência, a entrada é configurada quando o preço abre abaixo e fecha acima da banda superior ou para venda quando o preço abre acima e fecha abaixo da banda inferior.
Não há um stop fixo e nem alvo fixo a saída se dá quando o preço toca a média da banda.
Você pode usar uma média móvel como filtro combinado com a estratégia.
O Script também pode ser usado com algum serviço de bot como 3commas.io , basta colocar as mensagens de entrada e saída para o bot.
Autor : Credsonb - Nick: M4TR1X_BR
Neste gráfico estou usando as seguintes configurações:
Bandas Bollinger: 7
Desvio Padrão: 1.5
Time Frame: 12hs
Ticker: ETH
This script was created for Backtest study.
script uses Bollinger Bands to indicate the start of a trend, entry is set when price opens below and closes above the upper band or for short when price opens above and closes below the lower band.
There is no fixed stop and no fixed target, the exit occurs when the price touches the average of the band.
You can use a moving average as a filter combined with the strategy.
The Script can also be used with some bot service like 3commas. io , just put the input and output messages to the bot.
Author : Credsonb - Nick: M4TR1X_BR
Polynomial Regression Bands w/ Extrapolation of Price [Loxx]Polynomial Regression Bands w/ Extrapolation of Price is a moving average built on Polynomial Regression. This indicator paints both a non-repainting moving average and also a projection forecast based on the Polynomial Regression. I've included 33 source types and 38 moving average types to smooth the price input before it's run through the Polynomial Regression algorithm. This indicator only paints X many bars back so as to increase on screen calculation speed. Make sure to read the tooltips to answer any questions you have.
What is Polynomial Regression?
In statistics, polynomial regression is a form of regression analysis in which the relationship between the independent variable x and the dependent variable y is modeled as an nth degree polynomial in x. Polynomial regression fits a nonlinear relationship between the value of x and the corresponding conditional mean of y, denoted E(y |x). Although polynomial regression fits a nonlinear model to the data, as a statistical estimation problem it is linear, in the sense that the regression function E(y | x) is linear in the unknown parameters that are estimated from the data. For this reason, polynomial regression is considered to be a special case of multiple linear regression .
Related indicators
Polynomial-Regression-Fitted Oscillator
Polynomial-Regression-Fitted RSI
PA-Adaptive Polynomial Regression Fitted Moving Average
Poly Cycle
Fourier Extrapolator of Price w/ Projection Forecast
Bitcoin Support BandsSMA and EMA support/resistance bands for Bitcoin. Based on 4 week multiples; 1 month, 3 month, 6 month, 1 year, 2 year, 4 year.
Bollinger Bands SqueezeBollinger Bands set to only display when a squeeze is taking place. Squeeze will be highlighted.
SMA EMA Bands [CraftyChaos]This indicator creates bands for SMA and EMA averages and adds an average of the two with the idea that price often touches one of them at support and resistance levels. Saves indicator space by combining all into one indicator
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.
Steven Primo's bollinger bands strategyHi, this strategy is taken from a video made by Steven Primo. You can look it up on YouTube if you want to know about it.
It is a mean-reversion strategy based on the Bollinger Bands, in which we wait for 5 consecutive closes above the upper band, and for a short-term top. Once it happens, we place an entry order on this top, with a stop at the nearest bottom before the movement started, and use the difference from the stop and entry point to determine the target. For shorting, it's the same process, but for the downside. From my testing, only long orders were profitable, but you can configure whichever you want.
It works well for directional markets with a low level of noise, as you can see with the BTCUSD chart. One of its caveats is the short number of occurrences, and the long stop loss and target. You can enable a trailing stop, but from my testings, it just made the results worse.
I made some modifications, like removing the MA requirement, since the entry point was above it almost all the time, and I forced the BB to use a log version of the prices, so that discrepancies are eliminated. You'll also notice that you can't select an extension that is lower than 100, and that is intentional, since you're not supposed to enter a trade in which you can lose more than what you can earn.
I chose not to implement any kind of risk management, but I might do that in the future. You can leave your suggestions in the comments.
Greedy MA & Greedy Bollinger Bands This moving average takes all of the moving averages between 1 and 700 and takes the average of them all. It also takes the min/max average (donchian) of every one of those averages. Also included is Bollinger Bands calculated in the same way. One nice feature I have added is the option to use geometric calculations for. I also added regular bb calculations because this can be a major hog. Use this default setting on 1d or 1w. Enjoy!
ps, I call it greedy because the default settings wont work on lower time frames
Accumulation/Distribution Bands & Signals (BTC, 1D, BITSTAMP) This is an accumulation/distribution indicator for BTC/USD (D) based on variations of 1400D and 120D moving averages and logarithmic regression. Yellow plot signals Long Term Accumulation, which is based on 1400D (200W) ALMA, orange plot signals Mid Term Accumulation and is based on 120D ALMA, and finally the red plot signals Long Term Distribution that's based on log regression. It should be noted that for red plot to work BTC 1D BITSTAMP graph must be used, because the function of the logarithmic regression was modified according to the x axis of the BITSTAMP data.
Signal bands have different coefficients; long term accumulation (yellow) and and the log regression (red) plots have the highest coefficients and mid term accumulation (orange) has the lowest coefficients. Coefficients are 6x, 3x and 1.5x for the red (sell) and yellow (buy) plots and 1x, 2x and 3x for the orange (buy) plot. Selling coefficient for the yellow and the orange plots are respectively 2x and 1x. Buy and sell signals are summed up accordingly and plotted at the top of the highest band.
Acknowledgement: Credits for the logarithmic regression function are due @memotyka9009 and Benjamin Cowen
Deviation BandsThis indicator plots the 1, 2 and 3 standard deviations from the mean as bands of color (hot and cold). Useful in identifying likely points of mean reversion.
Default mean is WMA 200 but can be SMA, EMA, VWMA, and VAWMA.
Calculating the standard deviation is done by first cleaning the data of outliers (configurable).
Bands-Trailing Stop UtilityIntroduction
Bands and trailing stops are important indicators in technical analysis, while we could think that both are different they can be in fact closely related, at least in the way they are made. Bands and trailing stops can be made from a simple central tendency estimator, like a moving average, and from a volatility estimator like standard deviation, atr...etc.
This is why i propose this utility that allow you to make bands and trailing stops from any indicator in the price chart.
How To Use
All you have to do is select the indicator you want to make bands from in the settings, so just open the Bands-Trailing Stop Utility indicator settings and select your indicator in "Source". Make sure your source indicator is not in "hide" mode.
For example here i'am using a moving average as source for the indicator. Mult control how spread the bands are from each others, by default mult = 1, if we use mult = 2 we get :
Mult can be non-integer as well as lower than 1 (when lower than 1 the bands would be closer to each others)
Error/Volatility Estimators
You can choose from a wide variety of volatility estimators, select the estimator from the "Method" scrolling parameter in settings, by default the indicator will use the running mean absolute error (MAE) which don't use length. Other estimators use length, making length = to the period of the source indicator can help get better results.
The root moving averaged squared error (RMASE) is just the square root of the simple moving average of the squared difference between the closing price and the source indicator. length control the period of the moving average of RMASE.
You can also use the average true range with period length. It might work better with low lagging moving averages.
The range is simply the difference between the highest and lowest over length periods of the source indicator.
Stdev is simply the price running standard deviation.
Trailing Stop
When the trailing stop mode is checked the bands will be replaced by a trailing stop, the trailing stop will still depend on every settings of the indicator like mult/volatility estimator...etc.
Conclusion
You might find an use to this tool if you want to make bands/trailing stops from pretty much everything. The indicator used as source for the examples is a smooth exponential averager that i could share if i see interest from peoples.
Thanks for reading !
Bollinger Bands TimeBollinger bands that are fixed to a time interval. The time interval can be set in minutes or days.
Parameters
Daily Interval: If checked then days are used for the interval. If unchecked then minutes will be used.
Interval: The interval to use for the indicator.
Balgat EkibiBands are calculated with the std error and variance of the price actions. So if price cross up or cross down the variance bands, you could expect a reversal movement.
So if price cross up with the bands and after that there is a reversal candle movement, a short position could be taken.
If price cross down to the bands and after that there is a reversal candle movement, a long positon could be taken.
All risk management and money management is up to you.
Pivot-Based Channels & Bands [Misu]█ This Indicator is based on Pivot detection to show bands and channels.
The pivot price is similar to a resistance or support level. If the pivot level is breached, the price should continue in that direction. Or the price could reverse at or near this level.
█ Usages:
Use channels as a support & resistance zone.
Use bands as a support & resistance zone. It is also very powerfull to use it as a breakout.
Use mid bands & mid channels as a trend direction or trade filter as a more usual moving average.
█ Parameters:
Show Pivot Bands: show bands.
Show Pivot Mid Band: show mid bands.
Show Pivot Channels: show channels.
Show Pivot Mid Channel: show mid channels.
Deviation: deviation used to calculate pivot points.
Depth: depth used to calculate pivot points.
HL2 Moving Average with BandsThis indicator is designed to assist traders in identifying potential trade entries and exits for S&P 500 (ES) and Nasdaq-100 (NQ) futures. It calculates a Simple Moving Average (SMA) based on the HL2 value (average of high and low prices) of the current candle over a user-defined lookback period (default: 200 periods). The indicator plots this SMA as a blue line, providing a smoothed reference for price trends.
Additionally, it includes upper and lower bands calculated as a percentage (default: 0.5%) above and below the SMA, plotted as green and red lines, respectively. These bands act as dynamic thresholds to identify overbought or oversold conditions. The indicator generates trade signals based on price action relative to these bands:
Long Entry: A green upward triangle is plotted below the candle when the close crosses above the upper band, signaling a potential buy.
Close Long: A red square is plotted above the candle when the close crosses back below the upper band, indicating an exit for the long position.
Short Entry: A red downward triangle is plotted above the candle when the close crosses below the lower band, signaling a potential sell.
Close Short: A green square is plotted below the candle when the close crosses back above the lower band, indicating an exit for the short position.
The script is customizable, allowing users to adjust the SMA length and band percentage to suit their trading style or market conditions. It is plotted as an overlay on the price chart for easy integration with other technical analysis tools.
Recommended Time Frame and Settings for Trading S&P 500 and Nasdaq-100 Futures
Based on research and market dynamics for S&P 500 (ES) and Nasdaq-100 (NQ) futures, the 5-minute chart is recommended as the optimal time frame for day trading with this indicator. This time frame strikes a balance between capturing intraday trends and filtering out excessive noise, which is critical for futures trading due to their high volatility and leverage. The 5-minute chart aligns well with periods of high liquidity and volatility, such as the U.S. market open (9:30 AM–11:00 AM EST) and the afternoon session (2:00 PM–4:00 PM EST), when institutional traders are most active.
Why 5-minute? It allows traders to react to short-term price movements while avoiding the rapid fluctuations of 1-minute charts, which can be prone to false signals in choppy markets. It also provides enough data points to make the SMA and bands meaningful without the lag associated with longer time frames like 15-minute or hourly charts.
Recommended Settings
SMA Length: Set to 200 periods. This longer lookback period smooths the HL2 data, reducing noise and providing a reliable trend reference for the 5-minute chart. A 200-period SMA helps identify significant trend shifts without being overly sensitive to minor price fluctuations.
Band Percentage: 0.5% is more suitable for the volatility of ES and NQ futures on a 5-minute chart, as it generates fewer but higher-probability signals. Wider bands (e.g., 1%) may miss short-term opportunities, while narrower bands (e.g., 0.1%) may produce excessive false signals.
Trading Session Recommendations
Futures markets for ES and NQ are open nearly 24 hours (Sunday 6:00 PM EST to Friday 5:00 PM EST, with a daily break from 4:00 PM–5:00 PM EST), but not all hours are equally optimal due to varying liquidity and volatility. The best times to trade with this indicator are:
U.S. Market Open (9:30 AM–11:00 AM EST): This period is characterized by high volume and volatility, driven by the opening of U.S. equity markets and economic data releases (e.g., 8:30 AM EST reports like CPI or GDP). The indicator’s signals are more reliable during this window due to strong order flow and price momentum.
Afternoon Session (2:00 PM–4:00 PM EST): After the lunchtime lull, volume picks up as institutional traders return, and news or FOMC announcements often drive price action. The indicator can capture breakout moves as prices test the upper or lower bands.
Pre-Market (7:30 AM–9:30 AM EST): For traders comfortable with lower liquidity, this period can offer opportunities, especially around 8:30 AM EST economic releases. However, use tighter risk management due to wider spreads and potential volatility spikes.
Additional Tips
Avoid Low-Volume Periods: Steer clear of trading during low-liquidity hours, such as the overnight session (11:00 PM–3:00 AM EST), when spreads widen and price movements can be erratic, leading to false signals from the indicator.
Combine with Other Tools: Enhance the indicator’s effectiveness by pairing it with support/resistance levels, Fibonacci retracements, or volume analysis to confirm signals. For example, a long entry signal above the upper band is stronger if it coincides with a breakout above a key resistance level.
Risk Management: Given the leverage in futures (e.g., Micro E-mini contracts require ~$1,200 margin for ES), use tight stop-losses (e.g., below the lower band for longs or above the upper band for shorts) to manage risk. Aim for a risk-reward ratio of at least 1:2.
Test Settings: Backtest the indicator on a demo account to optimize the SMA length and band percentage for your specific trading style and risk tolerance. Micro E-mini contracts (MES for S&P 500, MNQ for Nasdaq-100) are ideal for testing due to their lower capital requirements.
Why These Settings and Time Frame?
The 5-minute chart with a 200-period SMA and 0.5% bands is tailored for the volatility and liquidity of ES and NQ futures during peak trading hours. The longer SMA period ensures the indicator captures meaningful trends, while the 0.5% bands are tight enough to signal actionable breakouts but wide enough to avoid excessive whipsaws. Trading during high-volume sessions maximizes the likelihood of valid signals, as institutional participation drives clearer price action.
By focusing on these settings and time frames, traders can leverage the indicator to capitalize on the dynamic price movements of S&P 500 and Nasdaq-100 futures while managing the inherent risks of these markets.
