Conditional volatility modelling with specific reference to select stocks of Nifty 50

Abstract

This paper models conditional volatility of select stocks from NIFTY 50 basket. Since volatility is the most important indicator in terms of measuring of risk of any assets, it is proposed to measure volatility of financial assets through four different techniques; sGARCH, gjrGARCH, eGARCH and APARCH. We empirically examined the closing prices of five sample stocks; Reliance, HDFC bank, ICICI bank, Infosys and TCS from 1^st January 2019 to 31^st May 2024 covering both covid and non-covid period. A total of 1335 data points were used after converting raw closing price data into return series which were finally input into the models. All the models were found statistically stable with APARCH (1,1) as the best one to capture volatility. With respect to other parameters, return series of TCS has highest non-linearity followed by Reliance with lowest that of Infosys. Similarly, HDFC stock has shown highest asymmetry followed by TCS. Overall, it can be said all the sample stocks show volatility clustering along with certain degree of leverage effect.