Exponential Bollinger Bands [Updated Feb 2018]The same as my previous Exponential Bollinger Bands script, but now you can set a desired offset for the indicator. I have published this as a new script that way those who prefer the old script can continue to use it without seeing any changes.
Стандартное отклонение
Coefficient of Variation [DW]This is a simple gauge of volatility using the Coefficient of Variation.
COV is calculated by dividing standard deviation of price by the expected (average) price.
Custom color scheme indicates increases and decreases in volatility, which is indicated when the COV forms new half period highs and lows.
SigmaSpikes(R) per Adam H. GrimesEach bar’s return against a volatility-adjusted baseline, as a standard deviation of the last 20 bars’ returns as per Adam H. Grimes SigmaSpikes(R).
adamhgrimes.com
www.marketlifetrading.com
SDSpikePrice Change as Standard Deviation Spikes
Plots price changes scaled to daily StdDev for the period
The Close price change is plotted as a thick bar coloured green for up close, red for down close
The High price change is plotted as a thin bar coloured aqua
The Low price change is plotted as a thin bar coloured orange
Can be used to understand the statistical price behaviour of the symbol.
Very useful for earnings trades and in general for options trades.
BKSqueezeThis is a price volatility compression and expansion indicator that uses the ratio of the Bollinger Band and Keltner Ratio.
Red segments indicate extreme price volatility compression that can be ideal entry points for stock/futures/forex and/or options positions.
Aqua segments indicate price volatility is expanding.
Blue segments indicate price volatility is compressing - can be used as an exit point or partial scale out point.
Note that the indicator doesn't indicate direction. One suggestion is to use the DMI indicator for this purpose - really depends on how early you enter the trade.
Suggest using a time period of 15 bars for volatile stocks, such as TSLA for example, otherwise a period of 20 bars suits most stocks/futures/forex symbols.
OHLC Volatility Estimators by @Xel_arjonaDISCLAIMER:
The Following indicator/code IS NOT intended to be a formal investment advice or recommendation by the author, nor should be construed as such. Users will be fully responsible by their use regarding their own trading vehicles/assets.
The embedded code and ideas within this work are FREELY AND PUBLICLY available on the Web for NON LUCRATIVE ACTIVITIES and must remain as is by Creative-Commons as TradingView's regulations. Any use, copy or re-use of this code should mention it's origin as it's authorship.
WARNING NOTICE!
THE INCLUDED FUNCTION MUST BE CONSIDERED AS DEBUGING CODE The models included in the function have been taken from openly sources on the web so they could have some errors as in the calculation scheme and/or in it's programatic scheme. Debugging are welcome.
WHAT'S THIS?
Here's a full collection of candle based (compressed tick) Volatility Estimators given as a function, openly available for free, it can print IMPLIED VOLATILITY by an external symbol ticker like INDEX:VIX.
Models included in the volatility calculation function:
CLOSE TO CLOSE: This is the classic estimator by rule, sometimes referred as HISTORICAL VOLATILITY and is the must common, accepted and widely used out there. Is based on traditional Standard Deviation method derived from the logarithm return of current close from yesterday's.
ELASTIC WEIGHTED MOVING AVERAGE: This estimator has been used by RiskMetriks®. It's calculation is based on an ElasticWeightedMovingAverage Standard Deviation method derived from the logarithm return of current close from yesterday's. It can be viewed or named as an EXPONENTIAL HISTORICAL VOLATILITY model.
PARKINSON'S: The Parkinson number, or High Low Range Volatility, developed by the physicist, Michael Parkinson, in 1980 aims to estimate the Volatility of returns for a random walk using the high and low in any particular period. IVolatility.com calculates daily Parkinson values. Prices are observed on a fixed time interval. n=10, 20, 30, 60, 90, 120, 150, 180 days.
ROGERS-SATCHELL: The Rogers-Satchell function is a volatility estimator that outperforms other estimators when the underlying follows a Geometric Brownian Motion (GBM) with a drift (historical data mean returns different from zero). As a result, it provides a better volatility estimation when the underlying is trending. However, this Rogers-Satchell estimator does not account for jumps in price (Gaps). It assumes no opening jump. The function uses the open, close, high, and low price series in its calculation and it has only one parameter, which is the period to use to estimate the volatility.
YANG-ZHANG: Yang and Zhang were the first to derive an historical volatility estimator that has a minimum estimation error, is independent of the drift, and independent of opening gaps. This estimator is maximally 14 times more efficient than the close-to-close estimator.
LOGARITHMIC GARMAN-KLASS: The former is a pinescript transcript of the model defined as in iVolatility . The metric used is a combination of the overnight, high/low and open/close range. Such a volatility metric is a more efficient measure of the degree of volatility during a given day. This metric is always positive.
Daily Deviations (Self Input Version)
Plots the standard deviation resistance/support levels.
Input the previous settlement price and the implied volatility.
credit to u/UberBotMan and u/Living_Granger for the idea and formulas
(preview example is using settlement of 2420 and IV of 11)
VWAP Stdev Bands v2 Modoriginal script by /u/SandroTurriate/ - I just made some small changes.
Vwap + standard deviation bands. Good for reversal trading among other things. Used intraday.
Very useful when price is ranging.
I added the option to fill the spaces between the deviation lines with color and also the option to add some extra bands. That's about it. Color/length/style etc is customizable.
GEOMETRIC STANDARD DEVIATION BANDS v1 by @XeL_ArjonaGEOMETRIC STANDARD DEVIATION BANDS
Ver.1 By Ricardo M Arjona @XeL_Arjona
DISCLAIMER:
The Following indicator/code IS NOT intended to be a formal investment advice or recommendation by the author, nor should be construed as such. Users will be fully responsible by their use regarding their own trading vehicles/assets.
The embedded code and ideas within this work are FREELY AND PUBLICLY available on the Web for NON LUCRATIVE ACTIVITIES and must remain as is.
WHAT'S THIS?
This IS NOT the wheel "Re-Invention"... This is exactly what the name says: A pair of Envelope Bands to measure "volatility", constructed at statistical relation from within price series and their Rolling back MEAN (Simple Moving Average). YES, What Mr. Bollinger did and put it's name to this simple, cleaver and popular formula.
This time, I took the time to make another simple mod, but seems to me to be quite functional in REAL VOLATILE assets like in the example chart: TO USE THEIR GEOMETRIC MODE!!
Cheers!
Any feedback or public modification(s) are quite welcome to the community....!
@XeL_Arjona
Apr 28 2016
Standard Error Bands by @XeL_arjonaStandard Error Bands - Code by @XeL_arjona
Original implementation by:
Traders issue: Stocks & Commodities V. 14:9 (375-379):
Standard Error Bands by Jon Andersen
Version 1
For a quick and publicly open explanation of this Statistical indicator, you can refer at Here!
Extract from the former URL:
Standard Error bands are quite different than Bollinger's. First, they are bands constructed around a linear regression curve. Second, the bands are based on two standard errors above and below this regression line. The error bands measure the standard error of the estimate around the linear regression line. Therefore, as a price series follows the course of the regression line the bands will narrow, showing little error in the estimate. As the market gets noisy and random, the error will be greater resulting in wider bands.
Acc/Dist. Cloud with Fractal Deviation Bands by @XeL_ArjonaACCUMULATION / DISTRIBUTION CLOUD with MORPHIC DEVIATION BANDS
Ver. 2.0.beta.23:08:2015
by Ricardo M. Arjona @XeL_Arjona
DISCLAIMER
The Following indicator/code IS NOT intended to be a formal investment advice or recommendation by the author, nor should be construed as such. Users will be fully responsible by their use regarding their own trading vehicles/assets.
The embedded code and ideas within this work are FREELY AND PUBLICLY available on the Web for NON LUCRATIVE ACTIVITIES and must remain as is.
Pine Script code MOD's and adaptations by @XeL_Arjona with special mention in regard of:
Buy (Bull) and Sell (Bear) "Power Balance Algorithm by Vadim Gimelfarb published at Stocks & Commodities V. 21:10 (68-72).
Custom Weighting Coefficient for Exponential Moving Average (nEMA) adaptation work by @XeL_Arjona with contribution help from @RicardoSantos at TradingView @pinescript chat room.
Morphic Numbers (PHI & Plastic) Pine Script adaptation from it's algebraic generation formulas by @XeL_Arjona
Fractal Deviation Bands idea by @XeL_Arjona
CHANGE LOG:
ACCUMULATION / DISTRIBUTION CLOUD: I decided to change it's name from the Buy to Sell Pressure. The code is essentially the same as older versions and they are the center core (VORTEX?) of all derived New stuff which are:
MORPHIC NUMBERS: The "Golden Ratio" expressed by the result of the constant "PHI" and the newer and same in characteristics "Plastic Number" expressed as "PN". For more information about this regard take a look at: HERE!
CUSTOM(K) EXPONENTIAL MOVING AVERAGE: Some code has cleaned from last version to include as custom function the nEMA , which use an additional input (K) to customise the way the "exponentially" is weighted from the custom array. For the purpose of this indicator, I implement a volatility algorithm using the Average True Range of last 9 periods multiplied by the morphic number used in the fractal study. (Golden Ratio as default) The result is very similar in response to classic EMA but tend to accelerate or decelerate much more responsive with wider bars presented in trending average.
FRACTAL DEVIATION BANDS: The main idea is based on the so useful Standard Deviation process to create Bands in favor of a multiplier (As John Bollinger used in it's own bands) from a custom array, in which for this case is the "Volume Pressure Moving Average" as the main Vortex for the "Fractallitly", so then apply as many "Child bands" using the older one as the new calculation array using the same morphic constant as multiplier (Like Fibonacci but with other approach rather than %ratios). Results are AWSOME! Market tend to accelerate or decelerate their Trend in favor of a Fractal approach. This bands try to catch them, so please experiment and feedback me your own observations.
EXTERNAL TICKER FOR VOLUME DATA: I Added a way to input volume data for this kind of study from external tickers. This is just a quicky-hack given that currently TradingView is not adding Volume to their Indexes so; maybe this is temporary by now. It seems that this part of the code is conflicting with intraday timeframes, so You are advised.
This CODE is versioned as BETA FOR TESTING PROPOSES. By now TradingView Admins are changing lot's of things internally, so maybe this could conflict with correct rendering of this study with special tickers or timeframes. I will try to code by itself just the core parts of this study in order to use them at discretion in other areas. ALL NEW IDEAS OR MODIFICATIONS to these indicator(s) are Welcome in favor to deploy a better and more accurate readings. I will be very glad to be notified at Twitter or TradingView accounts at: @XeL_Arjona
3BBands (3 Spirolinas)The script combines 3 single Bollinger bands into one script for easy plotting and range modification. It can be used for analyzing a market with multiple time frames and ranges using Fibonacci series as the range.
