Polygonal Pivot Bands [FXSMARTLAB]The Polygonal Pivot Bands highlights key price pivots, dynamic support and resistance levels, and recent price action on a trading chart. This indicator connects pivot highs and lows with a zigzag line, extends a real-time dashed line to the latest price point, and plots diagonal support/resistance levels that adapt to price movement. These elements together provide traders with a view of significant price zones and potential trend shifts.
Key Components of the Indicator
Pivots are calculated based on user-defined lengths, specifying how many bars on either side of a high or low are required to validate it as a pivot.
Adjustable left and right pivot lengths allow traders to control the sensitivity of pivot detection, with higher values resulting in fewer, more prominent pivots, and lower values increasing sensitivity to price changes.
Zigzag Line
The zigzag line connects consecutive pivot points, filtering out smaller fluctuations and emphasizing the broader direction of price movement.
Users can customize the line's color and thickness to match their preferences, helping them focus on larger trends and potential reversal points.
By linking pivot highs and lows, the zigzag pattern highlights the overall trend and potential points of reversal.
Real-Time Connector Line
A dashed line extends from the last confirmed pivot to the latest price point, providing a real-time, bar-by-bar update of the current price relative to the previous pivot.
This line does not project future price direction but maintains an up-to-date connection with the current price, showing the distance from the last pivot.
Its color and thickness are customizable for improved visibility on the chart.
Dynamic Support and Resistance Levels
The indicator plots dynamic support and resistanc e levels by connecting recent pivot highs and lows, resulting in lines that may appear diagonal rather than strictly horizontal.
These levels move in line with price action, adapting to the natural direction of trends, and offer visual cues where price may encounter support or resistance.
Colors and thickness of these lines can be set individually, allowing traders to adjust visibility according to their preferences.
Enabling these lines gives traders an ongoing reference for critical price boundaries that align more closely with the overall trend.
Cerca negli script per "band"
Dynamic GANN Square Of 9 BandsDynamic GANN Square Of 9 Bands
Created on 3 Sept 2023
Adjust Increment Value:
Customize increment to match symbol and price characteristics for accuracy.
Green Line:
200 EMA. Identifies trend direction; moves with the prevailing trend.
Red Lines:
Mark prominent reversal levels closer to the red range; ideal for mean reversion strategies.
Crossing red levels may indicate trend continuation to the next red level.
Grey Lines:
Show immediate target reversal levels; watch for potential reversals.
Key Features:
Levels are different from Standard Deviation Lines.
Levels remain fixed and parallel, unaffected by volatility.
Despite its dynamism, it can serve as a leading indicator, revealing potential trend changes.
Primarily designed for trend-following strategies.
Additional Tips:
Use additional confirmations
Manage predefined risk and quantity
Additional Resources:
GANN Square Of 9 Pivots:
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
Rekt Edge Reversion BandRekt Edge Reversion band is a technical indicator that utilizes a combination of moving averages and standard deviations to determine optimal entry and exit points in the market. By comparing the current price to its moving average, the indicator identifies potential trends and determines how you can position around them by plotting buy/sell signals and two channels based on user input parameters. The user can choose between Simple Moving Average ( SMA ) or Exponential Moving Average ( EMA ) and select the moving average period, the unit of separation, the multiples of the unit, and other important parameters. The indicator's inputs can be adjusted to suit different trading styles, and it can be used on any time frame. The indicator can be used to identify potential trend reversals or breakouts (or breakdowns) when the price moves outside of the channels. The indicators potential use cases include identifying overbought or oversold conditions. With its ability to provide a clear signal on when to enter and exit a trade, this indicator is a popular tool among traders looking to make more informed and profitable trading decisions. This indicator can also be used in conjunction with other technical analysis tools to confirm or invalidate trading signals.
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
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.
MA20 Hi-Lo-Close Magic BandThis is an improvement over my previous MA20 High Low Magic Band, as it keeps a central 20 MA reference point. So it can help find the up from MA20 lows and down from MA20 highs resisted or supported by MA20 average before final entry. Usable in any time frame of choice - 15m, 30m, Hourly or Daily. In the Hourly / Daily time frame, the signal used with the volume data may work in 6/10 events or more ... Happy trading!
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 Band Width Percentile - Multi Time FrameMy plan with this indicator was when trading at short timeframes, to modify my expectations on the potential impact of short term volatility based on volatility in longer timeframes, and when trading on longer timeframes to attempt to find an optimal entry point based on shorter term volatility.
The BBWP is calculated for a short, medium and long timeframe, alerts are triggered at extremities with the ability to filter by moving averages and chart movement. The alerts also trigger a plot to the "Backtest Signal" which can be used to trigger trades in a backtester.
Please see the discussions of how I'm using this indicator in the comments below.
Thanks to The_Caretaker for "Bollinger Band Width Percentile" upon which this multi time frame version is based.
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
Bull Market Support Band DivergencyThis script calculates the effective difference between the 21w EMA and the 20w SMA, which forms the Bull Market Support Band on BTC.
We can see some positive maximum on the indicator, which happens (often) to be zones of great volatility and sell zones, and the opposite for negative minimums.
Some periodicity is shown too, up to your own conclusions.
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.
Strategie Bollinger Bands buy & sellMiddle Band (Basis): Calculated using a Simple Moving Average (SMA) over a user-defined period.
Upper Band: The middle band plus the standard deviation of the price multiplied by a user-defined multiplier.
Lower Band: The middle band minus the standard deviation of the price multiplied by the same multiplier.
User Inputs:
Length: The number of periods used for the SMA and standard deviation (default: 20).
Deviation: The multiplier for the standard deviation to calculate the upper and lower bands (default: 2.0).
Buy and Sell Signals:
Buy Signal: Generated when the price crosses above the lower band, indicating a potential oversold condition.
Sell Signal: Generated when the price crosses below the upper band, indicating a potential overbought condition.
Visual Markers:
Buy Signals: Displayed below the price bars as green labels with the text "BUY."
Sell Signals: Displayed above the price bars as red labels with the text "SELL."
The Bollinger Bands (upper, middle, and lower) are plotted directly on the price chart for easy visualization.
How to Use the Script:
Customize Parameters:
Modify the length and deviation inputs to adapt to different market conditions or timeframes.
Interpret Signals:
A BUY signal indicates a possible reversal or upward movement from the lower band.
A SELL signal suggests a potential price decline from the upper band.
Combine with Other Indicators:
While effective in certain conditions, this strategy performs better when combined with other technical tools, such as RSI or MACD, to confirm trends and avoid false signals.
Limitations:
This script assumes that price will revert to the mean, which may not hold during strong trends or highly volatile conditions.
It is not a standalone trading system and should be backtested and optimized before applying to real trading.
Supertrend BandsSupertrend Bands
What is the Supertrend indicator?
"The Supertrend indicator is a trend following overlay on your trading chart, much like a moving average, that shows you the current trend direction.
The indicator works well in a trending market but can give false signals when a market is trading in a range.
It uses the ATR (average true range) as part of its calculation which takes into account the volatility of the market. The ATR is adjusted using the multiplier setting which determines how sensitive the indicator is."
"For the basic Supertrend settings, you can adjust period and factor:
- The period setting is the lookback for the ATR calculation
- Factor is the what the ATR is multiplied by to offset the bands from price"
How to use this indicator
This indicator is inspired by a strategy I found. It includes four Supertrend indicators, each with different settings that displays trend strength and support/resistance zones. The default settings are optimal for cryptocurrency but do work quite well for traditional also. I highly recommend you try experimenting with different settings, increasing them to suit the instrument.
The bands are set from low to high, Band 1 being the fastest and Band 4 being the slowest. Band 4 is the one that sets the overall trend so when price is above Band 4, the trend is bullish and vice versa. Trend is strongest when price is above/below Band 1 and gets weaker as it filters through each band. Band 4 provides the strongest support/resistance and if that breaks the trend flips.
In the menu, you will see an option called "Remove Anti Trend?". It is enabled by default and it removes any bearish/resistance bands when the trend is up and any bullish/support bands when the trend is down. When turned off, it will show all Supertrend Bands as they are by default.
Bar Colors
Bar colors are optional and they reflect the current trend strength based on the Supertrend bands.
Alternate ways of using this indicator
You could leave everything as default or you can display individual bands. For instance, because I use many overlay indicators, most of the time I turn off all the bands and only show bar colors:
You can also turn off Bands 1 and 2 and only show the two slowest lengths:
This removes the noise of the two faster Supertrends.
Or just show the two fastest bands:
Any suggestions to improve this indicator are most welcome :)
