Library "FunctionMatrixCovariance" In probability theory and statistics, a covariance matrix (also known as auto-covariance matrix, dispersion matrix, variance matrix, or variance–covariance matrix) is a square matrix giving the covariance between each pair of elements of a given random vector. Intuitively, the covariance matrix generalizes the notion of...
Well to be honest I don't know what to name this indicator lol. But anyway, here is my another original work! Gonna give some background of why I create this indicator, it's all pretty much a coincidence when I'm learning about time series analysis. _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ Well, the formula of Auto-covariance...
This script allows you to screen up to 38 symbols for their beta. It also allows you to compare the list to not only SPY but also CRYPTO10! Features include custom time frame and custom colors. Here is a refresher on what beta is: Beta (β) is a measure of the volatility—or systematic risk—of a security or portfolio compared to the market as a whole (usually the...
What is the Modified Covariance AR Estimator? The Modified Covariance AR Estimator uses the modified covariance method to fit an autoregressive (AR) model to the input data. This method minimizes the forward and backward prediction errors in the least squares sense. The input is a frame of consecutive time samples, which is assumed to be the output of an AR...
This script calculates the covariance and correlation coefficient between two markets using arrays. Lookback: How many bars to perform the calculation on. Source: Price source to calculate the correlation on. Reference Market: The reference market to compare to the current market. It's a simple indicator, but very useful for determining how correlated your...
█ WARNING Improvements to the following Pine built-ins have deprecated the vast majority of this publication's functions, as the built-ins now accept "series int" `length` arguments: ta.wma() ta.linreg() ta.variance() ta.stdev() ta.correlation() NOTE For an EMA function that allows a "series int" argument for `length`, please see `ema2()` in...
Covariance Function as described here: www.investopedia.com can be used for example to calculate Beta:
This is Covariance on Covariance. It shows you how much a given covariance period has deviated from it mean over another defined period. Because it is a time series, It can allow you to spot changes in how covariance changes. You can apply trend lines, Fibonacci retracements, etc. This is also volume weighting covariance. This is not a directional indicator nor...
Co-variance is a representation of the average percent data points deviate from there mean. A standard calculation of Co-variance uses One standard Deviation. Using the empirical rule, we can assume that about 68.26% of Data points lie in this range. The advantage to plotting co variance as a time series is that it will show you how volatility of a trailing...