Forecasting stock market volatility and information content of implied volatility index

2017 ◽  
Vol 50 (23) ◽  
pp. 2552-2568 ◽  
Author(s):  
Pratap Chandra Pati ◽  
Parama Barai ◽  
Prabina Rajib
SAGE Open ◽  
2019 ◽  
Vol 9 (3) ◽  
pp. 215824401986417
Author(s):  
Imlak Shaikh

Given that political events have substantial effect on new economic policies and economic performance of the country, this article aims to examine the behavior of the investors’ sentiment in terms of implied volatility index trailed by the U.S. presidential elections. The study empirically tests whether the presidential elections in 2012/2016 do contain the important market inclusive information to explain the expected stock market volatility. The findings indicate that investors’ concern was distracted around the presidential elections window, albeit the market performed identically in both the presidential election years. The significant fall in the implied volatility level (post-election period) is the calm before the storm, just wait and watch. The positive estimate uncovers the fact that investor worries were higher before the election day. In particular, the significant estimate of the presidential election debate shows that investors do regard the minutes of the presidential election debates in their portfolio selection. At the two elections era, on the candidacy of both the parties, the empirical result speaks marginally contrasting outcomes and falsifies the presidential election cycle hypothesis of past 29 U.S. election years. Empirical estimates conclude that the presidential elections in 2012/2016 have a strong, significant relationship with investor’s sentiment and stock market performance.


Author(s):  
Surya Bahadur G. C. ◽  
Ranjana Kothari

<div><p><em>Stock market volatility is a measure of risk in investment and it plays a key role in securities pricing and risk management. </em><em>The paper empirically analyzes the relationship between India VIX and volatility in Indian stock market. </em><em>India VIX is a measure of implied volatility which reflects markets’ expectation of future short-term stock market volatility.</em><em> It is a volatility index based on the index option prices of Nifty. </em><em>The study is based on time series data comprising of daily closing values of CNX Nifty 50 index comprising of 1656 observations from March 2009 to December 2015. </em><em>The results of the study </em><em>reveal that India VIX has predictive power for future short-term stock market volatility. It has higher forecasting ability for upward stock market movements as compared to downward movements. Therefore, it is more a bullish indicator. Moreover, the accuracy of forecasts provided by India VIX is higher for low magnitude future price changes relative to higher stock price movements. The current value of India VIX is found to be affected by past period volatility up to one month and it has forecasting ability for next one-month’s volatility which means the volatility in the Indian stock markets can be forecasted for up to 60 days period. </em></p></div>


2019 ◽  
Vol 87 (1) ◽  
pp. 40-76 ◽  
Author(s):  
David Berger ◽  
Ian Dew-Becker ◽  
Stefano Giglio

AbstractWe provide evidence on the relationship between aggregate uncertainty and the macroeconomy. Identifying uncertainty shocks using methods from the news shocks literature, the analysis finds that innovations in realized stock market volatility are robustly followed by contractions, while shocks to forward-looking uncertainty have no significant effect on the economy. Moreover, investors have historically paid large premia to hedge shocks to realized but not implied volatility. A model in which fundamental shocks are skewed left can match those facts. Aggregate volatility matters, but it is the realization of volatility, rather than uncertainty about the future, that has been associated with declines.


2013 ◽  
Vol 03 (01) ◽  
pp. 1350005 ◽  
Author(s):  
Silvia Muzzioli

The aim of this paper is to comprehensively compare option-based measures of volatility, with the ultimate plan of devising a new volatility index for the Italian stock market. The performance of the different implied volatility measures in forecasting future volatility is evaluated both in a statistical and in an economic setting. The properties of the implied volatility measures are also explored, by looking at both the contemporaneous relationship between implied volatility changes and market returns and the usefulness of the proposed index in forecasting future market returns. The results of the paper are of practical importance for both policy-makers and investors. The volatility index, based on corridor measures, could be used to forecast market volatility, for value at risk purposes, in order to determine trading strategies on the underlying index and as an early warning for future market conditions.


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