Informational efficiency of implied volatilities of S&P CNX Nifty index options: A study in Indian securities market

Abstract

Purpose

The purpose of this paper is to assess the informational efficiency of S&P CNX Nifty index options in Indian securities market. The S&P CNX Nifty index is a leading stock index of India, consists of 50 most frequently traded securities listed on NSE. For the purpose, the study covers a period of six years from 4 June 2001 (the starting date for index options in India) to 30 June 2007.

Design/methodology/approach

The informational efficiency of implied volatilities (IVs) has been tested vis‐à‐vis select conditional volatilities models, namely, GARCH(1,1) and EGARCH(1,1). The tests have been carried out for “in‐the‐sample” as well as “out‐of‐the‐sample” forecast efficiency of implied volatilities.

Findings

The results of the study reveal that implied volatilities do not impound all the information available in the past returns; therefore, these are indicative of the violation of efficient market hypothesis in the case of S&P CNX Nifty index options market in India.

Practical implications

The finance managers, in Indian context, should rely on conditional volatility models (especially the EGARCH(1,1) model) compared to IV‐based forecasts to predict volatility for the horizon of one week. The stock exchanges and market regulator (SEBI) need to take certain initiatives in terms of extending the short‐selling facility and start trading of volatility index (VIX) to enhance the accuracy of IV‐based forecasts.

Originality/value

The paper addresses an issue which is still unexplored in the context of Indian securities market and in that sense makes an important contribution to literature on microstructure studies.

Citation

Dixit, A., Yadav, S.S. and Jain, P.K. (2010), "Informational efficiency of implied volatilities of S&P CNX Nifty index options: A study in Indian securities market", Journal of Advances in Management Research, Vol. 7 No. 1, pp. 32-57. https://doi.org/10.1108/09727981011042847