In: Finance
Why are GARCH models are likely to be more useful models than ARMA type models for modelling time series of financial returns?
GARCH model or Generalized Autoregressive Conditionally Heteroscedastic model developed by Tim Bollerslev in 1986.
GARCH model have various application for analysing of time series data in finance and economies. It is useful eso in fast changing variation.
GARCH model follows 3 basic steps:
- Estimate the best fit auto regressive model.
- Calculate auto correlation of the error term.
- Test for Statistical significance.
An ARMA model i.e Autoregressive Moving Average Model is used to describe weakly stationary stochastic time series in terms of two polynomials.
The first of these polynomials is for Autoregressive, the second for the moving average.
GARCH process is more preferable to Finance professional because it provides a more real than other models when try to predict the prices and rates of financial instruments.
It is a statistical model that can be used to analyse a number of different types of financial data like; macroeconomic data. It is used to estimate the volatility of returns for stocks,bonds and market indices.