Volatility Information Trading in Option Market
Sophie X. Ni
Hong Kong University of Science and Technology
Massachusetts Institute of Technology (MIT) - Economics, Finance, Accounting (EFA); National Bureau of Economic Research (NBER); China Academy of Financial Research (CAFR)
Allen M. Poteshman
University of Illinois at Urbana-Champaign - Department of Finance
March 15, 2005
AFA 2006 Boston Meetings Paper
Investors can trade on positive or negative information about firms in either the stock or the option market, and a well-developed literature examines the use of options to make directional trades. Surprisingly, very little is known about option market trading on volatility information, despite the fact that options are uniquely suited for such trading. This paper investigates volatility trading in the equity option market. Two principal predictions of the hypothesis that investors bring volatility information to the option market are that net non-market maker demand for volatility is positively related to the future volatility of underlying stocks and that market makers protect themselves from informed volatility traders by raising (lowering) option prices in response to increases (decreases) in net volatility demand. Using a dataset that allows us to construct net non-market maker demand for volatility at the Chicago Board Options Exchange over the 1990 through 2001 period, we find strong empirical support for both of these predictions. We also present two additional results which each provide further confirmation for the proposition that investors bring volatility information to the option market. First, non-market maker net volatility demand constructed from transactions which open new option positions is a stronger predictor of the future volatility of underlying stocks than net volatility demand constructed from transactions which close existing option positions. Second, the impact on option prices from each unit of net non-market maker volatility demand significantly increases as informational asymmetry intensifies in the days leading up to earnings announcement dates.
Date posted: March 25, 2005
© 2015 Social Science Electronic Publishing, Inc. All Rights Reserved.
This page was processed by apollo8 in 0.250 seconds