EVALUATING THE PERFORMANCE OF GARCH FAMILY MODELS IN ESTIMATING INVESTMENT RISK AND VOLATILITY: A COMPARATIVE ANALYSIS OF SENSEX AND NIFTY INDEX IN INDIA

Abstract

In order to evaluate and estimate significant aspects of time series data, various models with varying degrees of variation have been built in the last few years. The overarching goal of study is to examine the variance dynamics of several Indian stock market indexes using Normal and Students-t distributions. The sample data spans a long time period (more than 40 years), from April 1979 to May 2023, and includes dramatic happenings. The econometric method relies heavily on the GARCH models and other statistical investigations. The outcomes contribute to the growing body of knowledge in the field. The possible rewards and risks of an investment are the focus of this empirical study. The results encompass the dynamics of financial series, volatility sketching, a statistical and GARCH model feature assessment, and the fitness of series returns. This opens the door to different assessments of the Indian financial market.

Keywords

• volatility clustering
• financial market
• empirical volatility
• forecasting
• garch models
• stock index