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Investigating the Information Content of the Model‐Free Volatility Expectation by Monte Carlo Methods
Author(s) -
Zhang Yuanyuan,
Taylor Stephen J.,
Wang Lili
Publication year - 2013
Publication title -
journal of futures markets
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.88
H-Index - 55
eISSN - 1096-9934
pISSN - 0270-7314
DOI - 10.1002/fut.21570
Subject(s) - implied volatility , volatility smile , volatility (finance) , forward volatility , stochastic volatility , volatility swap , economics , econometrics , heston model , valuation of options , realized variance , moneyness , volatility risk premium , sabr volatility model , black–scholes model , valuation (finance) , financial economics , finance
We explore the impact of both the number of option prices and the measurement errors in option prices upon the information content of the model‐free volatility expectation, and compare it with the Black–Scholes at‐the‐money (ATM) implied volatility. We simulate the realized volatility process and option prices using Heston's price dynamics and option valuation formula. The results show that the model‐free volatility expectation always contains important information about future realized volatilities. When the option prices contain random measurement noise, the informational efficiency of the model‐free volatility expectation increases monotonically with the number of out‐of‐the‐money options. The model‐free volatility expectation outperforms the ATM implied volatility, except when there are only a few option price observations. For the traded strikes for S&P 500 index options, we further show that fitting implied volatility curves before applying the current CBOE procedure for constructing the VIX index can improve the VIX's efficiency when forecasting future realized volatilities.