高频交易和报价期权数据的描述性研究*

IF 1.8 3区经济学 Q2 BUSINESS, FINANCE

Journal of Financial Econometrics Pub Date : 2021-03-25 DOI:10.1093/JJFINEC/NBAA036

T. Andersen, Ilya Archakov, Leon Eric Grund, N. Hautsch, Yifan Li, S. Nasekin, Ingmar Nolte, Manh Cuong Pham, Stephen L Taylor, V. Todorov

{"title":"高频交易和报价期权数据的描述性研究*","authors":"T. Andersen, Ilya Archakov, Leon Eric Grund, N. Hautsch, Yifan Li, S. Nasekin, Ingmar Nolte, Manh Cuong Pham, Stephen L Taylor, V. Todorov","doi":"10.1093/JJFINEC/NBAA036","DOIUrl":null,"url":null,"abstract":"This paper provides a guide to high frequency option trade and quote data disseminated by the \nOptions 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, summarize 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 rich information content of the high frequency OPRA data.","PeriodicalId":47596,"journal":{"name":"Journal of Financial Econometrics","volume":"19 1","pages":"128-177"},"PeriodicalIF":1.8000,"publicationDate":"2021-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1093/JJFINEC/NBAA036","citationCount":"3","resultStr":"{\"title\":\"A Descriptive Study of High-Frequency Trade and Quote Option Data*\",\"authors\":\"T. Andersen, Ilya Archakov, Leon Eric Grund, N. Hautsch, Yifan Li, S. Nasekin, Ingmar Nolte, Manh Cuong Pham, Stephen L Taylor, V. Todorov\",\"doi\":\"10.1093/JJFINEC/NBAA036\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper provides a guide to high frequency option trade and quote data disseminated by the \\nOptions 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, summarize 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 rich information content of the high frequency OPRA data.\",\"PeriodicalId\":47596,\"journal\":{\"name\":\"Journal of Financial Econometrics\",\"volume\":\"19 1\",\"pages\":\"128-177\"},\"PeriodicalIF\":1.8000,\"publicationDate\":\"2021-03-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1093/JJFINEC/NBAA036\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Financial Econometrics\",\"FirstCategoryId\":\"96\",\"ListUrlMain\":\"https://doi.org/10.1093/JJFINEC/NBAA036\",\"RegionNum\":3,\"RegionCategory\":\"经济学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"BUSINESS, FINANCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Financial Econometrics","FirstCategoryId":"96","ListUrlMain":"https://doi.org/10.1093/JJFINEC/NBAA036","RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BUSINESS, FINANCE","Score":null,"Total":0}

引用次数: 3

摘要

本文为期权价格报告机构(OPRA)发布的高频期权交易和报价数据提供了指南。我们对美国期权市场进行了全面的概述，包括市场监管的细节和所有16家期权交易所的交易流程。我们回顾了利用高频期权数据的现有文献，总结了OPRA数据集的一般结构，并对包含超过250亿条记录的基础资产样本的观察期权交易和报价进行了彻底的实证描述。我们概述了几种类型的不规则观测，并提供了数据过滤和清理的建议。最后，我们通过期权隐含方差估计和风险中性密度估计两种经验应用来说明高频期权数据的实用性。这两种应用都突出了高频OPRA数据丰富的信息内容。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

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

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, summarize 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 rich information content of the high frequency OPRA data.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

Journal of Financial Econometrics Multiple-

CiteScore

5.60

自引率

8.00%

发文量

期刊介绍： "The Journal of Financial Econometrics is well situated to become the premier journal in its field. It has started with an excellent first year and I expect many more."