Inference for variance risk premium

Shuang Zhang, Song Chen and Lei Lu

China Finance Review International, 2020, vol. 11, issue 1, 26-52

Abstract: Purpose - With the presence of pricing errors, the authors consider statistical inference on the variance risk premium (VRP) and the associated implied variance, constructed from the option prices and the historic returns. Design/methodology/approach - The authors propose a nonparametric kernel smoothing approach that removes the adverse effects of pricing errors and leads to consistent estimation for both the implied variance and the VRP. The asymptotic distributions of the proposed VRP estimator are developed under three asymptotic regimes regarding the relative sample sizes between the option data and historic return data. Findings - This study reveals that existing methods for estimating the implied variance are adversely affected by pricing errors in the option prices, which causes the estimators for VRP statistically inconsistent. By analyzing the S&P 500 option and return data, it demonstrates that, compared with other implied variance and VRP estimators, the proposed implied variance and VRP estimators are more significant variables in explaining variations in the excess S&P 500 returns, and the proposed VRP estimates have the smallest out-of-sample forecasting root mean squared error. Research limitations/implications - This study contributes to the estimation of the implied variance and the VRP and helps in the predictions of future realized variance and equity premium. Originality/value - This study is the first to propose consistent estimations for the implied variance and the VRP with the presence of option pricing errors.

Keywords: Implied variance; Variance risk premium; Pricing errors; Kernel estimation; C50; C58 (search for similar items in EconPapers)
Date: 2020
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.emerald.com/insight/content/doi/10.110 ... d&utm_campaign=repec (text/html)
https://www.emerald.com/insight/content/doi/10.110 ... d&utm_campaign=repec (application/pdf)
Access to full text is restricted to subscribers

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eme:cfripp:cfri-04-2020-0044

DOI: 10.1108/CFRI-04-2020-0044

Access Statistics for this article

China Finance Review International is currently edited by Professor Chongfeng Wu and Professor Haitao Li

More articles in China Finance Review International from Emerald Group Publishing Limited
Bibliographic data for series maintained by Emerald Support ().