Ravi Kumar SAMINENI, Raja Babu PUPPALA, Syamsundar KULAPATHI, Shiva Kumar MADAPATHI / Journal of Asian Finance, Economics and Business Vol 8 No 4 (2021) 0857–0861 857 857 Print ISSN: 2288-4637 / Online ISSN 2288-4645 doi:10.13106/jafeb.2021.vol8.no4.0857 A Study on Unfolding Asymmetric Volatility: A Case Study of National Stock Exchange in India Ravi Kumar SAMINENI 1 , Raja Babu PUPPALA 2 , Syamsundar KULAPATHI 3 , Shiva Kumar MADAPATHI 4 Received: December 20, 2020 Revised: March 07, 2021 Accepted: March 15, 2021 Abstract The study aims to find the asymmetric effect in National Stock Exchange in which the Nifty50 is considered as proxy for NSE. A return can be stated as the change in value of a security over a certain time period. Volatility is the rate of change in security value. It is an arithmetical assessment of the dispersion of yields of security prices. Stock prices are extremely unpredictable and make the investment in equities risky. Predicting volatility and modeling are the most profuse areas to explore. The current study describes the association between two variables, namely, stock yields and volatility in equity market in India. The volatility is measured by employing asymmetric GARCH technique, i.e., the EGARCH (1,1) tool, which was used in building the study. The closing prices of Nifty on day-to-day basis were used for analysis from the period 2011 to 2020 with 2,478 observations in the study. The model arrests the lopsided volatility during the mentioned period. The outcome of asymmetric GARCH model revealed the subsistence of leverage effect in the index and confirms the impact of conditional variance as well. Furthermore, the EGARCH technique was evidenced to be apt in seizure of unsymmetrical volatility. Keywords: Volatility, Asymmetric Effect, Conditional Variance, Nifty Index, India JEL Classification Codes: C22, G10, G17 can possibly fluctuate drastically whereas a lesser variability means a security value does not deviate considerably, but change happens over a period of time. Volatility in spot market is generally more visible in a falling market than in surging markets. Uptrend in the market tends to be gradual and downtrends have a tendency to be abrupt and sharper. Percentage change in price generally is higher in downward trend than in upward trend. A distinct characteristic of the volatility is that it is not directly noticeable, so analysts are particularly keen to find a detailed estimate of asymmetric volatility. As soon as fluctuations in stock prices reach peaks, the repercussion can be catastrophic. Firstly, if such volatility exists, organizations may not be in a position to utilize the existing capital efficiently as large part of the cash- equivalents have to be maintained to restore confidence among lenders and regulators. Secondly, such type of volatility intensifies market-risk and necessitates market participants to maintain enough liquidity, thus bringing down the liquidity in the market completely. Finally, huge fluctuations dampen investors’ confidence from carrying securities, thus guiding to demand for additional risk, which influences further volatility. 1 First Author and Corresponding Author. Research Scholar, Department of Management Studies, K L Deemed to be University, India [Postal Address: Green Fields, Vaddeswaram, Guntur District, Andhra Pradesh, 522502, India] Email: samineni08@gmail.com 2 Associate Professor, Department of Management Studies, K L Deemed to be University, India. Email: dr.prb@kluniversity.in 3 Associate Professor, Department of MBA, Vignan Degree and PG College, India. Email: syamkulapathi@gmail.com 4 Assistant Professor, Vishwa Vishwani Institute of Systems & Management, India. Email: madapathishivakumar75@gmail.com © Copyright: The Author(s) This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (https://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. 1. Introduction Modeling and predicting volatility have become important topics for research and have gained prominence among academicians and researchers. This is due to the fact that instability is considered as a vital concept for pecuniary applications, like hedging, portfolio optimization, and pricing of assets. Volatility denotes the amount of risk about the variations in a security’s price. A larger volatility means value