Michael F. Gallmeyer
University of Virginia
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Featured researches published by Michael F. Gallmeyer.
Mathematical Finance | 1999
Suleyman Basak; Michael F. Gallmeyer
This paper examines a continuous-time two country dynamic monetary equilibrium in which countries with possible heterogeneous tastes and endowments hold their own money for the purpose of transaction services formulated via the money in the utility function. Given a price system, no-arbitrage pricing results are provided for the price of each money and the nominal exchange rate. Characterizations are provided for equilibrium prices for general time-additive preferences and non-Markovian exogenous processes.
Journal of Monetary Economics | 2015
Sudheer Chava; Michael F. Gallmeyer; Heungju Park
Credit Conditions and Expected Stock Returns We analyze the predictability of U.S. stock returns using a measure of credit standards (Standards) derived from the Federal Reserve Board’s Senior Loan Officer Opinion Survey on Bank Lending Practices. We find that Standards is a strong predictor of stock returns at a business cycle frequency, especially in the post-1990 data period. Standards performs well both in-sample and out-of-sample and is robust to a host of consistency checks including a small sample analysis. Standards is a survey variable that is not linked to the level of stock prices; hence, it is unlikely that the predictive power of Standards is driven by stock mispricing. Instead, its predictive power is consistent with capturing a time-varying investment opportunity set through either time-varying aggregate risk aversion or timevarying risk.
Journal of International Money and Finance | 2013
Stephan Dieckmann; Michael F. Gallmeyer
In a setting where the lender and the borrower have heterogeneous beliefs about the likelihood of a disastrous shock to the borrowers economy, we study the debt contract that defaults at the occurrence of that shock, as proposed by Barro (2006). We find that a higher belief by the lender compared to the borrower can lead to countercyclical interest rates and credit spreads in non-default times, and to an increase in the borrowers indebtedness in default times, as often observed in emerging market economies. When calibrating the model to prices in the credit default swap market, we show that heterogeneous beliefs can account for more than 40% of the variation in CDS spreads associated with shocks to the borrowers economy in non-default times.
The Review of Asset Pricing Studies | 2018
David A. Chapman; Michael F. Gallmeyer
The aggregate tail risk measure constructed in Kelly and Jiang (2014) has no additional explanatory power when added to a standard model of the unconditional crosssection of expected returns. In conditional predictive regression systems and vectorautoregressions of the market portfolio and the longand short-sides of the SMB and HML portfolios, the tail measure appears to forecast expected returns – and not cash flows – on both small and large stocks and on growth stocks. This is inconsistent with a rare disaster model of asset prices which should operate primarily through a cash flow channel. The tail measure appears to be related to decades long movements in expected returns which may be more consistent with a long-run risks model. ∗Mailing Address (both authors): McIntire School of Commerce, University of Virginia, Rouss & Robertson Halls, East Lawn, P.O. Box 400173, Charlottesville, VA 22904-4173, e-mail: [email protected]. and [email protected]. We would like to thank Alex Chinko, Tim Johnson, Dana Kiku, Neil Pearson, Josh Pollett and the participants in the FEBB seminar at the Darden School at the University of Virginia and the University of Illinois at Urbana-Champaign for helpful comments. We would like to thank Bryan Kelly and Hao Jiang for providing the time series of their tail risk factor. The current version of this paper (along with supporting programs and public domain data) is available online at https://sites.google.com/site/davidchapmanswebsite/research/cg_tailrisk. †Corresponding author 1The aggregate tail risk measure constructed in Kelly and Jiang (2014) has no additional explanatory power when added to a standard model of the unconditional crosssection of expected returns. In conditional predictive regression systems and vectorautoregressions of the market portfolio and the long- and short-sides of the SMB and HML portfolios, the tail measure appears to forecast expected returns ‐ and not cash flows ‐ on both small and large stocks and on growth stocks. This is inconsistent with a rare disaster model of asset prices which should operate primarily through a cash flow channel. The tail measure appears to be related to decades long movements in expected returns which may be more consistent with a long-run risks model.
Management Science | 2017
Paul Ehling; Michael F. Gallmeyer; Sanjay Srivastava; Stathis Tompaidis; Chunyu Yang
We study portfolio choice with multiple stocks and capital gain taxation assuming that capital losses can only offset current or future realized capital gains. We show through backtesting, using empirical distributions, that optimal equity holdings over an extended period are significantly lower on average than benchmark holdings suggested in the literature. Using Value and Growth or Small and Large portfolios, the backtests show that allocations remain persistently under-diversified. Carry-over losses have large economic significance since they can dramatically shrink the no-trade region. Finally, the backtested economic cost of incorrectly modeling capital losses is at least 8 percent of lifetime wealth.
Journal of Financial Economics | 2011
T. Colin Campbell; Michael F. Gallmeyer; Shane A. Johnson; Jessica Rutherford; Brooke Stanley
Journal of Monetary Economics | 2005
Michael F. Gallmeyer; Burton Hollifield; Stanley E. Zin
Review of Finance | 2007
Michael F. Gallmeyer; Burton Hollifield
Journal of Financial Economics | 2006
Michael F. Gallmeyer; Ron Kaniel; Stathis Tompaidis
National Bureau of Economic Research | 2007
Michael F. Gallmeyer; Burton Hollifield; Francisco Palomino; Stanley E. Zin