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GARCH

Version: v.1.0.0.0

GARCH

Description

A GARCH model (Generalized Autoregressive Conditional Heteroskedasticity) is a statistical model that is commonly used to model the volatility of financial time-series data, such as stock prices or exchange rates. The basic idea behind a GARCH model is that the volatility of the data is not constant over time, but instead changes in response to the past values of the data.

Properties

  • Omega [default: 0.1] — The parameter ω is the long-term variance.
  • Alpha [default: 0.1] — α measures the response of volatility to past returns.
  • Beta [default: 0.8] — β - the degree of persistence of volatility.
  • EMA period [default: 200, range: 1–∞] — EMA period, to calculate the average value of Volatility for the period.