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Informed Trading in the Stock Market and Option-Price Discovery
Published online by Cambridge University Press: 04 August 2020
Abstract
When activist shareholders file Schedule 13D filings, the average stock-price volatility drops by approximately 10%. Prior to filing days, volatility information is reflected in option prices. Using a comprehensive sample of trades by Schedule 13D filers that reveals on what days and in what markets they trade, we show that on days when activists accumulate shares, option-implied volatility decreases, implied volatility skew increases, and implied volatility time slope increases. The evidence is consistent with a theoretical model where it is common knowledge that informed trading occurs only in the stock market and market makers update option prices based on stock-price and order-flow dynamics.
- Type
- Research Article
- Information
- Journal of Financial and Quantitative Analysis , Volume 56 , Issue 6 , September 2021 , pp. 1945 - 1984
- Copyright
- © The Author(s), 2020. Published by Cambridge University Press on behalf of the Michael G. Foster School of Business, University of Washington
Footnotes
We thank Kerry Back, Tarun Chordia, Benjamin Golez (discussant), Charles Jones, Marcin Kacperczyk (discussant), Patrik Sandas (discussant), Vish Viswanathan (discussant), and Jiang Wang and seminar participants at Boston College, Baruch College, the Said School of Business, St. Gallen University, Penn State University, Case Western Reserve, HEC Montreal, the Montreal Structured Finance and Derivatives Institute (IFSID) 2015 Conference on Financial Derivatives in Montreal, the 2016 Econometric Society Meetings in Geneva, the 2016 Instituto Tecnológico Autónomo de México (ITAM) Finance Conference, the 2016 Cavalcade, the 2016 Swiss Finance Institute (SFI) Research Days, the 2015 Foundation for the Advancement of Research in Financial Economics (FARFE) Conference, the 2016 Chicago Conference on Derivatives and Volatility, and the 2017 American Finance Association (AFA) Conference for their helpful comments and suggestions. We are also grateful to Nicholas Panos from the U.S. Securities and Exchange Commission (SEC) for educating us on the institutional details related to this study. Virginia Jiang, Cong Gu, Yujia Liu, Xin Luo, Victoria Ngo-Lam, Karina Olague, Eunji Oh, Ye Sun, Sofiya Teplitskaya, Tong Tong, Tiantao Zheng, and Pei Zou provided excellent research assistance.
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