A Descriptive Study of High-Frequency Trade and Quote Option Data. (6th January 2021)

• Record Type: Journal Article
• Authors: Andersen, Torben; Archakov, Ilya; Grund, Leon; Hautsch, Nikolaus; Li, Yifan; Nasekin, Sergey; Nolte, Ingmar; Pham, Manh Cuong; Taylor, Stephen; Todorov, Viktor
• Is Part Of: Journal of financial econometrics. Volume 19:Number 1(2021)
• Page Start: 128
• Page End: 177
• Publication Date: 2021-01-06
• Subjects: high-frequency data -- market microstructure -- options; C55 -- G10; Capital market -- Law and legislation -- Periodicals; Financial institutions -- Law and legislation -- Periodicals; 338.544205
• DOI: 10.1093/jjfinec/nbaa036
• Languages: English
• ISSNs: 1479-8409

Abstract

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.