Is the realized volatility good for option pricing during the recent financial crisis?

Yow Jen Jou, Chih Wei Wang, Wan Chien Chiu

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

The contributions of this paper are threefold. The first contribution is the proposed logarithmic HAR (log-HAR) option-pricing model, which is more convenient compared with other option pricing models associated with realized volatility in terms of simpler estimation procedure. The second contribution is the test of the empirical implications of heterogeneous autoregressive model of the realized volatility (HAR)-type models in the S&P 500 index options market with comparison of the non-linear asymmetric GARCH option-pricing model, which is the best model in pricing options among generalized autoregressive conditional heteroskedastic-type models. The third contribution is the empirical analysis based on options traded from July 3, 2007 to December 31, 2008, a period covering a recent financial crisis. Overall, the HAR-type models successfully predict out-of-sample option prices because they are based on realized volatilities, which are closer to the expected volatility in financial markets. However, mixed results exist between the log-HAR and the heterogeneous auto-regressive gamma models in pricing options because the former is better than the latter in times of turmoil, whereas it is worse during the rather stable periods.

Original languageEnglish
Pages (from-to)171-188
Number of pages18
JournalReview of Quantitative Finance and Accounting
Volume40
Issue number1
DOIs
StatePublished - Jan 2013

Keywords

  • HAR
  • Log-HAR
  • NGARCH
  • Option pricing
  • Out-of-sample pricing performance
  • Realized volatility

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