The Informational Content of High-Frequency Option Prices

Diego Amaya (), Jean-François Bégin () and Geneviève Gauthier ()
Additional contact information
Diego Amaya: Lazaridis School of Business & Economics, Wilfrid Laurier University, Waterloo, Ontario N2L 3C5, Canada
Jean-François Bégin: Department of Statistics and Actuarial Science, Simon Fraser University, Burnaby, British Columbia V5A 1S6, Canada
Geneviève Gauthier: Department of Decision Sciences, HEC Montréal, Montréal, Québec H3T 2A7, Canada

Management Science, 2022, vol. 68, issue 3, 2166-2201

Abstract: We propose the option realized variance as an observable variable to summarize the information from high-frequency option data. This variable aggregates intraday option returns from midquote prices to compute an option’s total variability for a given day, providing additional information about the jump activity in the data generating process. Using the S&P 500 index time series and options data, this paper documents the performance of this realized measure in predicting the index realized variance as well as the equity and variance risk premiums. We estimate an option pricing model and analyze its parameter estimates. Our results show that excluding high-frequency option information produces significant differences in variance jump parameters, estimated risk premiums, and option pricing errors.

Keywords: high-frequency data; option realized variance; options; jump-diffusion processes (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://dx.doi.org/10.1287/mnsc.2020.3949 (application/pdf)

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:inm:ormnsc:v:68:y:2022:i:3:p:2166-2201

Access Statistics for this article

More articles in Management Science from INFORMS Contact information at EDIRC.
Bibliographic data for series maintained by Chris Asher ().