Research seminars

Information, Trading, and Volatility: Evidence from Firm-specific news

Finance

Speaker: Shimon Kogan
IDC - International Data Corporation

20 April 2017 - T015 - From 2:00 pm to 3:15 pm

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What moves stock prices? Systematic factors aside, prior literature concludes that the revelation of private information through trading, and not public news, is the primary driver. We revisit the question by utilizing new textual analysis tools that allow us to better-identify fundamental information in news. We find that such fundamental firm-level information is an important source for stock price volatility, accounting for 20%-40% of overnight volatility (compared to 5%-6% during trading hours). Moreover, we find that the percentages of news-explained variance varies across firm characteristics and industries.

The Economic Impact of Index Investing

Finance

Speaker: Matthew Ringgenberg
The University of Utah

30 March 2017 - T004 - From 2:00 pm to 3:15 pm

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We examine the impact of index investing on rm performance by examining the link between commodity indices and rms that use index commodities. Starting in 2004 there was a dramatic increase in commodity index investing, an event referred to as the nancialization of commodity markets. After nancialization, rms that use index commodities make worse production decisions and earn lower pro ts. Consistent with a feedback channel in which market participants learn from prices, our results suggest that index investing in nancial markets distorts the price signal thereby generating a negative externality that impedes rms' ability to make production decisions.

Opportunistic Proposals by Union Shareholders

Finance

Speaker: Oguzhan Ozbas
USC - University of Southern California

23 March 2017 - T037 - From 11:00 am to 12:15 pm

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An Information-Theoretic Asset Pricing Model

Finance

Speaker: Christian Julliard
LSE - The London School of Economics

9 March 2017 - T015 - From 2:00 pm to 3:15 pm


We show that a non-parametric estimate of the pricing kernel, extracted using an information-theoretic approach, delivers out-of-sample smaller pricing errors and better cross-sectional fit than leading factor models, and identifies the maximum Sharpe ratio portfolio. This information SDF identifies a novel source of risk not captured by Fama-French and momentum factors, revealing an ‘information anomaly’ that generates annualized alphas of about 9%–24%. A tradable information portfolio that mimics this kernel has high out-of-sample Sharpe ratio (about 1 or more), outperforming both the 1/N benchmark and Value and Momentum strategies combined. These results hold for wide cross-sections of test portfolios.

Real Anomalies

Finance

Speaker: Jules Van Binsbergen
Wharton - University of Pennsylvania

2 March 2017 - T004 - From 2:00 pm to 3:15 pm


We examine the importance of asset pricing anomalies (alphas) for the real economy. To this end, we develop a novel lumpy investment model that features such anomalies and yields closed-from solutions for the joint cross-sectional distribution of firm dynamics. Our findings indicate that informational inefficiencies measured by cross-sectional alphas can cause material real inefficiencies, raising the possibility that agents that help eliminate anomalies can provide significant value added to the economy. The framework reveals that alphas alone are poor indicators of real distortions, and that efficiency losses crucially depend on the persistence of alpha, the amount of mispriced capital, and the Tobin's q of firms that are affected.