Information and Trading: New Approaches to Classical Problems
Friday, Jan. 6, 2017 10:15 AM – 12:15 PM
Sheraton Grand Chicago, Sheraton Ballroom IV
- Chair: Haoxiang Zhu, Massachusetts Institute of Technology
Identifying Information Asymmetry in Securities Markets
AbstractWe propose and estimate a model of endogenous informed trading that is a hybrid of the PIN and Kyle models. When an informed trader trades optimally, both returns and order flows are needed to identify information asymmetry parameters. Empirically, relationships between the model's estimates and price impacts, excess kurtosis, and volatility are consistent with theory. The estimates can be used to detect information events in the time series and to characterize the information content of prices in the cross section. Relative to price impact benchmarks, a composite measure from the model compares favorably to those from other structural information asymmetry models.
Intraday Trading Invariance in the E-mini S&P 500 Futures Market
AbstractThe intraday trading patterns in the E-mini S&P 500 futures contract between January 2008 and November 2011 are consistent with the following invariance relationship: The return variation per transaction is log-linearly related to trade size, with a slope coefficient of -2. This association applies both across the pronounced intraday diurnal pattern and across days in the time series. The documented factor of proportionality deviates sharply from prior hypotheses relating volatility to transactions count or trading volume. Intraday trading invariance is motivated a priori by the intuition that market microstructure invariance, introduced by Kyle and Obizhaeva (2016) to explain bets at low frequencies, also applies to transactions over high intraday frequencies.
University of Toronto
University of Chicago
- G1 - Asset Markets and Pricing