Journal Press India^®

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The study examines the volatility of the Indian Financial Sub-Markets (Equity, Commodity, and Forex) along with their components (Spot & Derivatives) by using daily series data from 1st January 2016 to 31st December 2023. Based on the daily price series, the volatility series is constructed using the Autoregressive Conditional Heteroskedasticity and Generalized Autoregressive Conditional Heteroskedasticity methods. The Time Series Lab Software has made forecasts for the volatility series. The study intends to find the most effective methodologies for measuring volatility, using the Error Diagnostic Criteria and evaluating the mean difference between the predicted and the forecasted volatility series of the various submarkets of India. The study result shows that the GARCH volatility series has a lower error for the Equity and Commodity Market while for the Forex Market, both ARCH & GARCH volatility series are compatible with low error values. There are no differences in the predicted and the actual volatility series for the Foreign Exchange Variables of the Spot and Derivative segment.

Keywords

Volatility; ARCH; GARCH; Financial market

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