A descriptive study of high-frequency trade and quote option data

Andersen, Torben and Archakov, Ilya and Grund, Leon and Hautsch, Nikolaus and Li, Yifan and Nasekin, Sergey and Nolte, Ingmar and Pham, Manh and Taylor, Stephen and Todorov, Viktor (2021) A descriptive study of high-frequency trade and quote option data. Journal of Financial Econometrics, 19 (1). pp. 128-177. ISSN 1479-8409

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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.

Item Type:
Journal Article
Journal or Publication Title:
Journal of Financial Econometrics
Additional Information:
This is a pre-copy-editing, author-produced PDF of an article accepted for publication in Journal of Financial Econometrics following peer review. The definitive publisher-authenticated version, A descriptive study of high-frequency trade and quote option data, Journal of Financial Econometrics, Vol. 19(1), 2021, is available online at: https://academic.oup.com/jfec/article/19/1/128/6066685
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/2000/2003
Subjects:
?? financeeconomics and econometrics ??
ID Code:
147058
Deposited By:
Deposited On:
07 Sep 2020 15:50
Refereed?:
Yes
Published?:
Published
Last Modified:
03 Nov 2024 01:18