This research grant is awarded jointly to Patrick Augustin (Desautels), Gunnar Grass (HEC Montreal), Marti G. Subrahmanyam, Charles E. Merril (New York Stern School of Business)
In this project, we propose a framework for identifying option trades that maximize expected returns under liquidity constraints for investors with private but noisy information. Our primary objective is to improve the detection of illegal insider trading by understanding how insiders can benefit from trading differentially depending on the type and quality of their private information, i.e., the precision of its signal. We first implement our approach numerically for a wide range of option trading strategies and various private signals and then apply it empirically to document suspicious activity in option markets prior to large changes in stock prices associated with different types of corporate news events. In most instances, an investor with a private signal about an upcoming change in the price of the underlying stock maximizes his profits by acquiring options trading near the money, or by pursuing trading strategies involving more than one security. Differences in trading as a function of signal and parameter uncertainty improve our understanding of how informed investors trade in the options market.
CME Group Foundation is interested in encouraging academic research on exchange-traded derivatives and central clearing house policy issues. The Foundation Board has identified the following topics as those of greater interest within three broad-based categories of research: Exchange-Traded Derivative Market Activity; Structure of Derivative Markets; Global Regulation of Derivative Markets.