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Robert J. Hodrick
Researcher at Columbia University
Publications - 111
Citations - 27807
Robert J. Hodrick is an academic researcher from Columbia University. The author has contributed to research in topics: Risk premium & Capital asset pricing model. The author has an hindex of 46, co-authored 111 publications receiving 26166 citations. Previous affiliations of Robert J. Hodrick include Carnegie Mellon University & National Bureau of Economic Research.
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Postwar U.S. Business Cycles: An Empirical Investigation
TL;DR: In this article, a procedure for representing a times series as the sum of a smoothly varying trend component and a cyclical component is proposed, and the nature of the comovements of the cyclical components of a variety of macroeconomic time series is documented.
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The Cross-Section of Volatility and Expected Returns
TL;DR: In this article, the authors examine the pricing of aggregate volatility risk in the cross-section of stock returns and find that stocks with high sensitivities to innovations in aggregate volatility have low average returns.
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The Cross-Section of Volatility and Expected Returns
TL;DR: In this paper, the authors examined the pricing of aggregate volatility risk in the cross-section of stock returns and found that stocks with high sensitivities to innovations in aggregate volatility have low average returns.
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Forward Exchange Rates as Optimal Predictors of Future Spot Rates: An Econometric Analysis
TL;DR: In this article, the authors examined the hypothesis that the expected rate of return to speculation in the forward foreign exchange market is zero; that is, the logarithm of the forward exchange rate is the market's conditional expectation of the future spot rate, and they were able to reject the simple market efficiency hypothesis for exchange rates from the 1970s and the 1920s.
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Dividend Yields and Expected Stock Returns: Alternative Procedures for Interference and Measurement
TL;DR: In this article, alternative ways of conducting inference and measurement for long-horizon forecasting are explored with an application to dividend yields as predictors of stock returns, including an estimator derived under the null hypothesis as in Richardson and Smith (1989), a reformulation of the regression as in Jegadeesh (1990), and a vector autoregression (VAR) as in Campbell and Shiller (1988), Kandel and Stambaugh (1988, and Campbell (1991).