Z-Score of RSIA way to see whether RSI is overbought or oversold inside its Bollinger Bands in the form of an oscillator. Z-score tells you how far the data is from the mean in terms of standard deviations. The numbers shown in the indicator are the number of standard deviations away from the average or mean. Like Bollinger Bands, if it is above the standard deviation border lines then it is considered to be outside the distribution or Bollinger Band. If it is above the upper border line then is it is overbought, if it is below the lower border line then is is oversold.
Example of how standard deviation works: 1 standard deviation contains 68% of the data, 2 SD (the default for BB) contains 95% of data, 3 SD for 99%, etc. If the data goes past that, it is considered to be outside the distribution. In statistics, data that is within the distribution is considered to be "significant".
The z-score line is colored green if it is above zero and red if it is below zero. Above zero means that the RSI is above the average line or the middle line of the Bollinger Bands, and vice-versa if it is below. A red vertical bar is shown when the the z-score is above the upper border line to show that it is overbought and a green vertical bar is shown when the z-score is below the lower border line to show that it is oversold. This is the equivalent of when the RSI is above and below its Bollinger Bands.
Zscore
Z-Score 'Bollinger Bands'The following script is an application of the Z-Score (previous script).
Z-Scores can be used in place of standard deviation (sigma) in 'Bollinger Bands'.
The average of the sample (x-bar) over 21 days (N)
21 average trading days per month, fixed value
The average of the population (mu) over 63 days (n)
63 days per quarter, default is set to 63
Z-Score is calculated by formula in previous script, and the absolute value is taken of "Z".
Z-High = absolute value of Z + (x-bar).
Z-Low = absolute value of Z - (x-bar).
Will update with Z from mu and Z from avg (working on UX and visualization details).
Z-Score The z-score is a way of counting the number of standard deviations between a given data value and the mean of the data set.
Z-score = (x̄ - μ) / (σ / √ n)
x̄ = sample mean (using the array.avg function = array(a,close ), where i = 1 to 21)
μ = population mean ( = avg(close, n))
σ = standard deviation of the population ( = stdev(close,n))
n = number of 'close' or trading day closes
n = input
... Note: The previous indicator is part of a larger series of indicators
Cumulative distribution function - Probability Cumulative distribution function (tScore and zScore)
This script provides the calculation of the cumulative distribution function (i.e., probability). The measure allows you to calculate the chances of a value of interest being above or below a hypothesized value over the measurement period—nothing fancy here, just good old statistics and mathematics. The closer you are to 0 or 1, the more significant your measurement. We’ve included a significance level highlighting feature. The ability to turn price and/or volume off.
We have included both the Z and T statistics. Where the ‘Z’ is looking at the difference of the current value, minus the mean, and divided by the standard deviation. This is usually pretty noisy on a single value, so a smoother is included. Nice shoutout to the Pinecoders Github Page with this function also. The t-statistic is measuring the difference between a short measurement, an extended measurement, and divided by the standard error (sigma/sqrt(n)). Both of these are neatly wrapped into a function, so please feel free to use them in your code. Add a bit of science to your guessing game. For the purists out there, we have chosen to use sigma in the t-statistic because we know the population's behavior (as opposed to the s-measure). We’ve also included two levels of the t-statistic cumulative distribution function if you are using a short sample period below 6.
Finally, because everyone loves choices, we’ve included the ability to measure the probability of:
the current value (Price and volume)
change
percent change
momentum (change over a period of time)
Acceleration (change of the change)
contribution (amount of the current bar over the sum)
volatility (natural log ratio of today and the previous bar)
Here is a chart example explaining some of the data for the function.
Here are the various options you have the print the different measurements
A comparison of the t-statistic and z-statistic (t-score and z-score)
And the coloring options
Statistical Histogram with configurable bins and Data WindowCreates a Histogram for Statistical Analysis of any source.
Input Parameters:
Sample Source: Select your source here, can be any numerical source.
Sample Period: Sample size for Mean and Standard Deviation Calculations.
Enable Cumulative Mode: Will attempt to calculate the bin for every sample in the entire dataset.
Window Period: Used only in Window Mode (Enable Cumulative Mode unchecked), Calculates the bin for the past Window Period sample size.
Bin Label Spacing: Adjust horizontal spacing of Bin Labels below the histogram for easier viewing.
Center Bin: Selects the center Bin, usually set to (0 - Bin Width) < Sample <= 0 standard deviations or (z_score)
Bin Width: Selects the Bin Width in standard deviations.
How you can use it:
View characteristics of dataset such as unimodal/bimodal and skewness to determine preferred statistical analysis.
Additional Reference:
en.wikipedia.org
en.wikipedia.org
Credits:
Thanks goes out to www.tradingview.com , for cleaning up some of the code and www.tradingview.com for the original idea.
Usage Tips:
When adjusting the bin parameters, center bin and bin width, verify that the total sum of the bins (Sum Frequency in the Data Window) is close to the Total Samples. If your Sum Frequency is drastically lower it means you need to adjust your center bin and/or bin width to capture more of the data available.
Z Score Enhanced Time Segmented Volume (Multi MA)**THIS VERSION HAS BEEN STANDARDIZED WITH A Z SCORE CALCULATION AND ALLOWS THE USER TO SELECT WHICH MOVING AVERAGE THEY WOULD LIKE TO UTILIZE FOR THE SIGNAL LINE**
Chart shows the Non-Standardized Enhanced Time Segmented Volume (Multi MA) with default settings on top and the Standardized version with default settings on the bottom.
Time Segmented Volume was developed by Worden Brothers, Inc to be a leading indicator by comparing various time segments of both price and volume . Essentialy it is designed to measure the amount of money flowing in and out of an instrument.
Time Segmented Volume was originally ported to TradingView by user @liw0 and later corrected by user @vitelot. I never quite understood how to read Time Segmented Volume until I ran across a version by user @storma where they indicated when price would be long or short, but that code also utilized the incorrect calculation from user @liw0.
In an effort to make Time Segmented Volume more accessible and easier to read, I have re-coded it here. The calculations are based on the code from @vitelot and I have added direction indicators below the chart.
If the histogram (TSV) is greater than zero and greater than the moving average, price should be moving long and there will be a green box below the chart.
If TSV falls below the moving average while still being greater than zero, the trend may be exhausting and has been coded to read Price Action Long - FAILURE with a black x below the chart.
If the histogram (TSV) is less than zero and less than the moving average, price should be moving short and there will be a red box below the chart.
If TSV rises above the moving average while still being less than zero, the trend may be exhausting and has been coded to read Price Action Short - FAILURE with a black x below the chart.
At times, the moving average may be above zero while TSV is below zero or vice versa. In these situations the chart will indicate long or short based on whether or not TSV is greater or less than zero. It is possible a new trend may be forming as the moving average obviously lags, but also possible price is consolidating with little volume and causing TSV to oscillate close to zero.
**Z Score // Standardized Option **
Thist Standardized code implements all of the above but also allows the user to select a threshold level that should not need to be adjusted for each instrument (since the output is standardized).
If the TSV value meets the long and short signal requirements above and TSV is greater than the threshold values a green or red box will print ABOVE the oscillator. The histogram will also change color based on which threshold TSV has met.
This calculation allows us to compare current volatility to the mean (moving average) of the population (Z-Length). The closer the TSV Z-Score is to the mean, the closer it will be to the Zero Line and therefore price is likely consolidating and choppy. The farther TSV Z-Score is from the mean, the more likely price is trending.
The MA Mode determines the Moving Average used to calculate TSV itself. The Z-Score is ALWAYS calculated with a simple moving average (as that is the standard calculation for Z-Score).
The Threshold Levels are the levels at which TSV Z-Score will change from gray to yellow, orange, green ( bullish ), or red ( bearish ).
Statistically speaking, confidence levels in relation to Z-Score are noted below. The built in Threshold Levels are the positive and negative values for 90%, 95%, and 99%. This would indicate when volatility is greater than these values they are out of the ordinary from the standard range. You may wish to adjust these levels for TSV Z-Score to be more responsive to your trading needs
80% :: 1.28
85% :: 1.44
90% :: 1.64
95% :: 1.96
99% :: 2.58
The Z Length is the period for which the Z Score is calculated
More information regarding Time Segmented Volume can be found here: www.worden.com
Original code ported by @liw0
Corrected by @vitelot
Updated/Enhancements by @eylwithsteph with inspiration from @storma
Multiple MA Options Credits to @Fractured and @lejmer
Bits and Pieces from @AlexGrover, @Montyjus, and @Jiehonglim
As always, trade at your own risk.
WhipLashThis is a study to determine if small candle bodies (little difference between open and close), regardless of overall candle length (high/low), can be used to filter choppy markets.
The indicator will calculate the selected average "MA Mode" of (close-open). To standardize this result and ensure any filters/thresholds do not need to be recalculated for each instrument the result will be used to calculate the Z Score.
The idea is that when candle bodies are small there is very little actual price movement, and therefore price is choppy. When considering the Z Score of that result, any outliers ie larger candle bodies, could show a potential trend forming. This indicator is similar to QStick but allows more customization by the user.
MA Mode determines which MA is used to smooth the results of (close-open)
Price Smoothing is the number of running periods the MA Mode is calculated for.
The three Thresholds are preset to the 90%, 95%, and 99% levels for Z Score. If these thresholds are altered you may wish to also alter the horizontal lines programmed for each level on the positive and negative sides.
The Z Length is the period for which the Z Score is calculated
Multiple MA Options Credits to @Fractured
Bits and Pieces from @AlexGrover, @Montyjus, and @Jiehonglim
As always, trade at your own risk.
Quantile BandsMiddle quantile/band color is set by confluence of the outer quantiles and not by it's own slope. Optional MTF.
[RS]Normalized Standard SelectorEXPERIMENTAL:
market state, text says it all most of the time at least.
OBV Z-ScoresThis study calculates the On-Balance Volume (OBV) and displays it in terms of its Z-Score.
OBV is a great momentum indicator . As the name suggests, OBV predicts changes in price based on the security's volume flow.
Formula:
if (Current Price > Previous Price)
then Current OBV = Previous OBV + Current Volume
if (Current Price < Previous Price)
then Current OBV = Previous OBV - Current Volume
if (Current Price == Previous Price)
then Current OBV = Previous OBV
As the formula shows, the OBV goes a step beyond just looking at the pure volume of a security. Instead, it factors in relative price action from period to period to reflect investor sentiment. As a result, we often look to the OBV to spot bullish or bearish trends while they are in the early stages of development or simply predict impending uptrends or downtrends.
To make the OBV easier to visualize, we converted the value to a Z-Score. The Z-Score is a simple statistical measurement and represents the current OBV value's distance from the mean OBV value in terms of # of standard deviations.
Users can adjust the values for the 2 upper bounds for Z Scores and 2 lower bounds. Additionally, the n value for z score calculation can be adjusted in the input menu. A higher n value means the z score will be based on a longer lookback period. A lower value will result in more sensitive readings.
Overall, I think this is an interesting way to represent OBV values and will be a valuable leading indicator.
~Happy Trading~
Multi Z Score [DW]This is an experimental study using z scores of multiple sampling periods to analyze price trends.
Z score measures the number of standard deviations price is from its mean.
In this study, z scores are calculated over a Fibonacci sequence of sampling periods from 3 to 4181.
The scores are then averaged with equal weighting, resulting in a display of long term trend with short term sensitivity.
Custom bar colors are included. The color scheme is based on the perceived trend from the average z score.
Z-Score (Close)A Z-score is a numerical measurement of a value's relationship to the mean in a group of values. If a Z-score is 0, it represents the score as identical to the mean score.
Z-scores may also be positive or negative, with a positive value indicating the score is above the mean and a negative score indicating it is below the mean. Positive and negative scores also reveal the number of standard deviations that the score is either above or below the mean.
Z distance from VWAP [LazyBear]This calculates normal distance of price from VWAP. This is a mean reverting idea (something like ZScore), but using both "volume" and "close".
Useful for finding OB/OS areas and potential turning points.
Complete list of my indicators:
