Variance Risk Premiums and Predictive Power of Alternative Forward Variances in the Corn Market
Z. G. Wang, Scott W. Fausti, Bashir A. Qasmi, Wang, Zhiguang, Fausti, Scott W., Qasmi, Bashir A.
Abstract
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Z. G. Wang, Scott W. Fausti, Bashir A. Qasmi, Wang, Zhiguang, Fausti, Scott W., Qasmi, Bashir A.
Abstract
Open-access reader
We propose a fear index for corn using the variance swap rate synthesized from out-of-the-money call and put options as a measure of implied variance. Previous studies estimate implied variance based on Black (1976) model or forecast variance using the GARCH models. Our implied variance approach, based on variance swap rate, is model independent. We compute the daily 60-day variance risk premiums based on the difference between the realized variance and implied variance for the period from 1987 to 2009. We find negative and time-varying variance risk premiums in the corn market. Our results contrast with Egelkraut, Garcia, and Sherrick (2007), but are in line with the findings of Simon (2002). We conclude that our synthesized implied variance contains superior information about future realized variance relative to the implied variance estimates based on the Black (1976) model and the variance forecasted using the GARCH(1,1) model.
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We propose a fear index for corn using the variance swap rate synthesized from out-of-the-money call and put options as a measure of implied variance. Previous studies estimate implied variance based on Black (1976) model or forecast variance using the GARCH models. Our implied variance approach, based on variance swap rate, is model independent. We compute the daily 60-day variance risk premiums based on the difference between the realized variance and implied variance for the period from 1987 to 2009. We find negative and time-varying variance risk premiums in the corn market. Our results contrast with Egelkraut, Garcia, and Sherrick (2007), but are in line with the findings of Simon (2002). We conclude that our synthesized implied variance contains superior information about future realized variance relative to the implied variance estimates based on the Black (1976) model and the variance forecasted using the GARCH(1,1) model.
Key concepts: Variance swap, Variance risk premium, Variance (accounting), Realized variance, Econometrics, Price variance, Variance decomposition of forecast errors, Variance-based sensitivity analysis