A Descriptive Study of High-Frequency Trade and Quote Option Data

Author(s)
Torben G. Andersen, Ilya Archakov, Leon Eric Grund, Nikolaus Hautsch, Yifan Li, Sergey Nasekin, Ingmar Nolte, Manh Cuong Pham, Stephen Taylor, Viktor Todorov
Abstract

This paper provides a guide to high-frequency option trade and quote data disseminated by the Options Price Reporting Authority (OPRA). We present a comprehensive overview of the U.S. option market, including details on market regulation and the trading processes for all 16 constituent option exchanges. We review the existing literature that utilizes high-frequency options data, summarizes the general structure of the OPRA dataset, and presents a thorough empirical description of the observed option trades and quotes for a selected sample of underlying assets that contains more than 25 billion records. We outline several types of irregular observations and provide recommendations for data filtering and cleaning. Finally, we illustrate the usefulness of the high-frequency option data with two empirical applications: option-implied variance estimation and risk-neutral density estimation. Both applications highlight the rich information content of the high-frequency OPRA data.

Organisation(s)
Department of Statistics and Operations Research, Research Network Data Science
External organisation(s)
University of Manchester, Lancaster University, Northwestern University, Universität Wien
Journal
Journal of Financial Econometrics
Volume
19
Pages
128–177
ISSN
1479-8409
DOI
https://doi.org/10.1093/jjfinec/nbaa036
Publication date
2020
Peer reviewed
Yes
Austrian Fields of Science 2012
502009 Corporate finance, 502025 Econometrics
Portal url
https://ucris.univie.ac.at/portal/en/publications/a-descriptive-study-of-highfrequency-trade-and-quote-option-data(ddc57001-11ed-4f33-8140-bcd1ca45a44b).html