Feedback Trading between Fundamental Information and Non-fundamental Information
Abstract
The speaker, together with Prof Ming Guo from Shanghai Advanced Institute of Finance, develop a continuous-time model of infinite horizon to study the optimal consumption and trading of a monopolistic insider who enjoys fundamental and non-fundamental information advantages. Because of insider's risk-aversion or mean-reverting noise supply, observing the expected growth rate of dividends (fundamental information) gives the insider advantage over the future realizations of non-fundamental information (insider's inventory or noise supply). A feedback effect, arisen from insider's trading on both fundamental information and non-fundamental information, prevents the price from being fully-revealing, though the insider tends to trade infinitely aggressively. This result holds even when the insider is risk-neutral but the noise supply is mean-reverting. Due to the feedback effect, the price impact can increase with insider's risk aversion. The insider's current trade and his inventory in the previous period exhibit simultaneously positive forecasting powers for future stock returns.
About the speaker
Prof. Ou-Yang Hui received his first PhD in Chemical Physics from Tulane University in 1990, and a second one in Finance from University of California at Berkeley at 1998. He was Assistant Professor at University of North Carolina at Chapel Hill and then Associate Professor at Duke University. He also served as a Managing Director at UBS AG, Nomura Securities, and Lehman Brothers. He is currently Professor of Finance at the Cheung Kong Graduate School of Business.
Prof. Ou-Yang’s research focuses on the development of asset pricing and corporate finance models. He was voted the best teacher by Duke’s Global Executive EMBA Class of 2004. He won the Barclays Global Investors/ Michael Brennan Runner-Up Award presented by the Review of Financial Studies in 2003, as well as the best paper award (jointly with Prof Henry Cao) presented by the Society of Quantitative Analysts in 2005.
