Abstract
Measurement of volatility is of paramount importance in finance because of the effects on risk measurement and risk management. Corridor implied volatility measures allow us to disentangle the volatility of positive returns from that of negative returns, providing investors with additional information beyond standard market volatility. The aim of the paper is twofold. First, to propose different types of corridor implied volatility and some combinations of them as risk indicators, in order to provide useful information about investors’ sentiment and future market returns. Second, to investigate their usefulness in prediction of market returns under different market conditions (with a particular focus on the subprime crisis and the European debt crisis). The data set consists of daily index options traded on the Italian market and covers the 2005–2014 period. We find that upside corridor implied volatility measure embeds the highest information content about contemporaneous market returns, claiming the superiority of call options in measuring current sentiment in the market. Moreover, both upside and downside volatilities can be considered as barometers of investors’ fear. The volatility measures proposed have forecasting power on future returns only during high volatility periods and in particular during the European debt crisis. The explanatory power on future market returns improves when two of the proposed volatility measures are combined together in the same model.
Highlights
Introduction and Literature ReviewThe disentanglement of the volatility of positive and negative returns is of paramount importance in finance because of their potentially distinct effects on the level of overall risk, risk measurement and risk management
When we split the sample into high and low volatility periods, we find that model-free implied volatility and corridor volatility measures are useful in forecasting future market returns only during high volatility periods
Given the importance of disentangling positive and negative shocks to volatility, which are seen from investors as good and bad news, respectively, we use different volatility measures to investigate the information content embedded in different portions of the risk-neutral distribution
Summary
The disentanglement of the volatility of positive and negative returns is of paramount importance in finance because of their potentially distinct effects on the level of overall risk, risk measurement and risk management. We aggregate the information of the left and the information of the right hand side of the distribution in a new volatility measure computed as the difference between the downside and the upside corridor implied volatility We call this measure relative semi-volatility (RSV), following a suggestion in Feunou et al (2016) who use the same definition to model realized semi-variance. We introduce the upside and downside corridor implied volatility measures and their combination into two new measures of risk: the market symmetric index (SIX), and the relative semi-volatility index (RSV), which are obtained as model-free versions of the indices proposed by Liu and Faff (2017), and Feunou et al (2016), respectively.
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