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research
My research has evolved around the following subject areas.
Empirical Asset Pricing:
These studies look at the pricing of assets in a global setting using different risk-return models. My PhD dissertation and the RFS-2003 paper were testing the consumption based asset pricing model with incomplete markets and consumption heterogeneity. The next set of projects evolved around the examination of industry risk in the pricing of equity returns across countries. My JIFMIM-2000 with Pavel Fedorov from Morgan Stanley focused solely on the newly emerging Russian market. It established the existence of differences across various industries in terms of their integration with the world market. In the subsequent MS-2004 paper with Francesca Carrieri and Vihang Errunza, we explicitly find some evidence for global industry specific risk across several industries. These findings prompted us to further examine the diversification benefits resulting from cross-country versus cross-industry investing. Finally, in a recent WP with Ruslan Goyenko, we analyze the impact of changes in the liquidity of US Treasury bills on global equity returns.
Observe that the cross-country variance in consumption growth (blue series) increases when the world aggregate consumption (pink series) drops. 
Foreign Listings:
The series of papers on this subject with Michael Schill dates back to our PhD studies at the University of Washington. After attending a couple of seminars on ADRs, we wondered why literally everyone in our field is examining foreign listing on US exchanges but not in other countries. This question has prompted us to hand-collect the first global sample of foreign listed securities based on which we conducted several projects that could not be completed having data on foreign listings in only one market. We discovered the following. First, in the RFS-2004 paper, we find that firms, similar to investors, have a preference for listings in familiar markets. Second, contrary to the conventional wisdom, we show in the RFS-2009 paper that firms with foreign listing placements do not experience permanent cost of capital gains, even if they are placed in the US. Finally, in a recent WP, we also find that the history of foreign listings shows big waves over time in their origin and destination, so that the well-known US market attractiveness for foreign shares is a relatively recent phenomenon.
Below is the moving average of cumulative risk-adjusted returns of cross-listed firms from 10 years before to 10 years after the listing. The returns (cost of capital) of these firms in Periods 4 is almost the same as in Period 1. 
Fund Performance:
Two papers on mutual funds with Susan Christoffersen look primarily at the impact of external factors (such as location) on fund performance and turnover in a cross-section and over time. The first paper, JFE-2009, shows that funds in US financial centers on average perform better than in smaller towns. Yet this outperformance comes only thanks to those managers who stay in financial centers at least several years. In a new WP we observe that fund trading behavior is also quite different across locations, yet these differences do not explain the patterns found in the earlier work.
Observe that the average mutual fund returns increase with city size. 
Statistical Issues and Market Anomalies:
Together with Wayne Ferson, my dissertation advisor, and Tim Simin, we completed several projects that question the validity of statistical inferences in several well-known settings in financial economics. The first paper, JFM-2000, illustrates that sorting of stocks on some firm-specific attribute and two-stage regression methodology used to document the importance of size and book-to-market effects for the cross-section of returns can lead to these types of findings even if returns are unrelated to the attribute risk. Our JF-2003 and JFQA-2008 papers look at statistical inferences in cases of simple predictive regressions of stock returns and conditional asset pricing models, respectively. We find that the predictive power for stock returns of many standard predictors such as dividend yield, short-term interest rates, etc., is grossly overstated due to the highly autocorrelated nature of these instruments. This problem is smaller when testing conditional asset pricing models with time-varying intercepts and betas.
Here are the results of the regression of monthly S&P 500 index returns on various known predictors, one at a time. Note that the majority of these predictors are highly autocorrelated. 
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