Research seminars

The Effect of Cash Injections: Evidence from the 1980s Farm Debt Crisis


Speaker: Nittai Bergman
Massachusetts Institute of Technology

19 November 2015


Speaker: Matthieu Bouvard
Desautels Faculty of Management

14 June 2018 - From 2:00 pm to 3:15 pm


Speaker: Mikhail Simutin
Rotman School of Management

7 June 2018 - From 2:00 pm to 3:15 pm

Disclosure, Competition, and Learning from Asset Prices


Speaker: Liyan Yang
Rotman School of Management

31 May 2018 - T208 - From 2:00 pm to 3:15 pm


This paper studies the classic information-sharing problem in a duopoly setting in which firms learn information from a financial market. By disclosing information, a firm incurs a proprietary cost of losing competitive advantage to its rival firm but benefits from learning from a more informative asset market. Firms' disclosure decisions can exhibit strategic complementarity, which is strong enough to support both a disclosure equilibrium and a nondisclosure equilibrium. Allowing minimal learning from asset prices dramatically changes firms' disclosure behaviors: without learning from prices, firms do not disclose at all; but with minimal learning from prices, firms can almost fully disclose their information. Learning from asset prices benefits firms, consumers, and liquidity traders, but harms financial speculators.

Alpha Decay*


Speaker: Anton Lines
Columbia Business School

24 May 2018 - T020 - From 2:00 pm to 3:15 pm


Using a novel sample of professional asset managers, we document positive incremental alpha on newly purchased stocks that decays over twelve months. While managers are successful forecasters at these short-to-medium horizons, their average holding period is substantially longer (2.2 years). Both slow alpha decay and the horizon mismatch can be explained by strategic trading behavior. Managers accumulate positions gradually and unwind gradually once the alpha has run out; they trade more aggressively when the number of competitors and/or correlation among information signals is high, and do not increase trade size after unexpected capital flows. Alphas are lower when competition/correlation increases.

What is the Expected Return on a Stock?


Speaker: Ian Martin

17 May 2018 - From 2:00 pm to 3:15 pm

We derive a formula that expresses the expected return on a stock in terms of the risk-neutral variance of the market and the stock’s excess risk-neutral variance relative to the average stock. These quantities can be computed fromindex and stock option prices; the formula has no free parameters. We run panel regressions of realized stock returns onto risk-neutral variances, and find that the theory performs well at 6-month, 1-year, and 2-year forecasting horizons. The formula drives out beta, size, book-to-market and momentum, and outperforms a range of competitors in forecasting stock returns out of sample. Our results suggest that there is considerably more variation in expected returns, both over time and across stocks, than has previously been acknowledged.