I'm excited to share with you a Pine Script™ that I developed to analyze GARCH (Generalized Autoregressive Conditional Heteroskedasticity) volatility. This script allows you to calculate and plot GARCH volatility on TradingView. Let's see together how it works! Introduction Volatility is a key concept in finance that measures the variation in prices of a...
Mean Absolute Deviation (MAD) is a statistical measure that tells you how spread out or variable a set of data points is. It calculates the average distance of each data point from the mean (average) of the data set. MAD helps you understand how much individual values differ from the average value. It's a way to measure the overall "average distance" of the data...
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...
GARCH stands for heteroscedastic conditional generalized autoregressive model. Generalized because it takes into account recent and historical observations. Autoregressive because the dependent variable returns on itself. Conditional because future variation depends on historical variation. Heteroscedastic because the variance varies as a function of the...
The Garch (General Autoregressive Conditional Heteroskedasticity) model is a non-linear time series model that uses past data to forecast future variance. The Garch (1,1) formula is: Garch = (gamma * Long Run Variance) + (alpha * Squared Lagged Returns) + (beta * Lagged Variance) The gamma, alpha, and beta values are all weights used in the Garch calculations....