ANALYSING THE IMPACT OF VOLATILITY DECAY ON FORECASTED RETURNS USING ARMA, SYMMETRIC AND ASYMMETRIC GARCH AND TGARCH MODELS

Abstract

In accordance with the general perception that the risk appetite of an investor determines his reward, the discussion neglects the important issue of the impact of volatility. An informed investor is able to take the right decisions and create a portfolio that maximizes returns. Academics, however, engage themselves to understand the volatility by employing empirical analysis and provide evidence-based results. The current research identifies sixteen sectoral indices of the National Stock Exchange of India (NSE). A combination of Autoregressive Moving Average (ARMA) and Generalized Autoregressive Conditional Heteroskedastic (GARCH) and T-GARCH (Threshold-GARCH) have been applied to the closing price of indices from Jan. 1, 2019 until January 31, 2024. The returns on each of these indices have been forecasted for the next three months ending on April 30, 2024. The outcome of the research shows that news and information have a direct bearing on the returns of the indices. Moreover, the negative shocks in the previous period have more volatility than the positive shock of the same magnitude illustrating an inverse relationship between volatility decay rate and future returns.