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Title: A descriptive study of the high-frequency trade and quote option data from OPRA Authors:  Ilya Archakov - University of Vienna (Austria)
Leon Grund - University of Vienna (Austria)
Nikolaus Hautsch - University of Vienna (Austria)
Sergey Nasekin - Lancaster University (United Kingdom)
Ingmar Nolte - Lancaster University (United Kingdom)
Manh Cuong Pham - Lancaster University (United Kingdom) [presenting]
Stephen Taylor - Lancaster University (United Kingdom)
Abstract: A guide to high frequency option trade and quote data disseminated by the Options Price Reporting Authority (OPRA) is provided. First, we present a comprehensive overview of the fragmented U.S. option market, including details on market regulation and the trading processes for all 15 constituent option exchanges. Then, we review the general structure of the OPRA dataset and present 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 superior information content of the high frequency OPRA data to the widely used end-of-day OptionMetrics data.