[NSE Working Paper] India Volatility Index (India VIX) as a Risk Management Tool

Risk management has always been one of the primary concerns for investors, traders, and other stock market participants. A major portion of risk originates from the uncertainty in returns i.e.volatility. National Stock Exchange of India Ltd. introduces India Volatility Index (also known as India VIX)which captures expected volatility over next 30 days. Volatility index measures the market’s expectation of near-term volatility which is significantly related with returns that investors experience in the stock market. 

We completed a research study commissioned by the NSE, that focuses on various aspects of the India VIX. In this study, we examine asymmetric relationship between India volatility index (India VIX) and stock market returns, and demonstrates that the returns on the Nifty index are negatively related to the changes in the India VIX levels, but in case of high upward movements in the market, the returns on the two indices tend to move independently. Our empirical findings also reveal that when the market takes sharp southward turns, the relationship is not as significant for higher quantiles. This property of the India VIX enables the investors to use it as a potential tool for risk management whereby derivative products based on the volatility index can be used as a mechanism for portfolio insurance against sharp declines.

We also provide evidence in support of India VIX as a superior measure of stock market volatility (compared to other traditional measures such as standard deviation, and so forth). Our simulation results suggest that a certain percentage change in India VIX can be used as an indicator to shift between the portfolios and thereby maintaining position returns thereon.

The full report is available as NSE Working Paper WP/9/2013. Full text of the paper can be found here. Any comments can be directed to the authors; feel free to revert back to me through an email, in case of any suggestions, query, or comments.

Thank you very much!