All of my research projects have a common thread: time-varying expected returns and risks and their implications for both understanding the behavior of asset prices in both domestic and international settings.

The ideas that expected returns and risks shift through time is well-accepted today. However, when I started my research program this idea was controversial. For years, finance had focused on models where both risk and expected returns were constant through time. When evidence of predictable returns surfaced, many thought that the existence of any predictable variation implied a violation of the "efficient market hypothesis." I think my main contribution is to show that predictability can be consistent with rational asset pricing. My JPE91 with Wayne Ferson measured the amount of predictability induced by changing risk exposures and changing risk premiums. We showed that an economic asset pricing model produced predictability that closely matched what others had documented statistically. I continued to refine these models that incorporated time-varying risk and expected returns. I found avenues to explore in international asset pricing, performance evaluation and the practical problem of portfolio selection.

While my early research focussed on the implications of the consumption-based model, I always remembered the advice of my dissertation advisor, Gene Fama, "you must hedge your research portfolio especially with respect to this model." This particular research line ended with my JF92 with Wayne Ferson. In this paper, we explored numerous twists to the basic model and were unable to salvage the standard framework to explain both the time-series and cross-section of expected returns. While I believe that this is a good paper, its impact is limited by the move in the profession away from the consumption model. Nevertheless, I learned a tremendous amount from this research program (and in particular from Wayne Ferson) that led to some other asset pricing frameworks.

My final examination of domestic asset pricing question incorporates investigators' prior beliefs into the problem ( with Guofu Zhou in JFE90). This paper examines unconditional asset pricing restrictions. However, the twist is that information (in the form of the investigator's prior belief) are incorporated into the analysis. The paper proposes a methodology for a full Bayesian analysis of asset pricing models. We use Monte Carlo integration to evaluate complicated posterior densities. This is a methodology paper. While Bayesian approaches are very appealing, there has been a hesitation to apply these methodologies because of the intense requirement of computational resources. I envision future researchers using our ideas as Bayesian analysis becomes more common place.

Ferson and I provided a comprehensive examination of expected international returns in our RFS93. We addressed two issues. First, we abandoned the multistep estimation approach that we used in our JPE91. Second, we presented a multifactor framework which generalized the single factor results of my JF91. We found that the multifactor model could account for most of the predictable variation in asset returns. We found that most of the variation was being driven by a single world factor (consistent with my JF91). However, we also found an important, but smaller role for a foreign currency factor.

Next, I moved to emerging capital markets. These high profile markets had little academic attention mainly because of the costs associated with obtaining the data. In return for presenting a paper at a World Bank conference, the International Finance Corporation gave me their data. My "Predictable Risk and Returns in Emerging Markets" RFS95 provides a comprehensive analysis of these data. Within the framework of a world asset pricing model, I present sharp rejections. In particular, in terms of the usual risk measures, these markets have essentially zero risk. As a result, their returns are "too high" to be consistent with the world asset pricing models. The models also fail to account for predictability of these returns.

The RFS95 explored a world asset pricing model applied to emerging equity markets. That is, the risk was measured with respect to world factor benchmarks. This model assumes that each capital market is perfectly integrated into world capital markets. But this is one of three possible approaches to the problem. The second involved the assumption that the capital market was completely segmented (then risk is measured with respect to local factors). The third is the assumption of partial integration. Those that implemented this third approach fixed the degree of integration through time (constant influence of world and local factors).

This third model provided the origins of my collaboration with Geert Bekaert. At the World Bank conference, we talked about generalizing the partial integration framework to allow for the possibility that the degree of integration changes through time. This squared with our intuition that some countries had become more integrated through time (like Thailand) and other countries less integrated (like Zimbabwe). We provided the first attempt to capture time-variation market integration in . Of course, in a general model of time-varying integration, there may be demand to hedge changes in integration over time. This is not modeled in our framework and we make the reader aware of this limitation. Nevertheless, our paper presents a number of interesting results. In addition, we provide an alternate characterization of our work as tracing the influence of world vs. local factors on time-varying expected returns.

Another limitation of the JF95 is that the influence of the world and local factors through the variance is not modeled. Bekaert and I recently realized that given the persistence in variances and covariances, it might be more fruitful to examine a similar framework with respect to variances and covariances. In (working paper), we present a world factor model that allows for changing influences of world vs. local factors on both the mean returns and the variance dynamics. This paper also presents an attempt to understand why variances differ across countries and why variances shift through time.

The second project is with John Graham. In we study the asset allocation recommendation of 237 newsletter strategies. The data are newsletters' suggested investment proportions in equity and cash (Treasury bills or CDs). We provide the first analysis of the performance of these newsletters and whether the letters have any ability to "time the market" (increase equity weight before the market rises and decrease weight before market declines). Consistent with my other research, we try to control for market wide time-varying expected returns and risks.

The third project is with Ravi Bansal, . We cast the challenging performance evaluation problem in the context of Hansen and Richard (1987) and Hansen and Jagannathan (1991). We propose an alternative method of assigning risk to strategies. We detail a trading strategy which uses three benchmark assets which have futures contracts trading on them. We show that this strategy, which is based on publicly available information, "beats the market" when the traditional performance evaluation criteria are used. This paper is chocked full of interesting results which hopefully will affect the practice of performance measurement in the future.

The fourth project is with Arman Glodjo, My collaboration with Glodjo began when he was a student in the Computer Science department. I quickly realized that some of the techniques used for data compression and caching problems were ideal for the study of time-varying expected returns at the high frequency level. In this paper, we present a remarkably simple framework to detect variation in returns.

The fifth project is with Bruno Solnik and Guofu Zhou, "What Determines Expected International Asset Returns?" In contrast to my previous work, this project uses a latent factor technique to study stock and bond returns. The advantage of this technique is that you need not specify the risk factors in advance. We offer a number of new twists. First, we recover the fitted risk premiums and characterize their time-variation with respect to the world business cycle. Second, we show that similar forces drive expected stock and bond returns. Third, we study the role of exchange rate risk in expected returns.

The sixth project is with Christopher Kirby, "Analytic Tests of Linear Factor Models." The paper provides a general framework for deriving analytical test statistics for a wide variety of models. Consistent with my previous work, among these models are those which allow for time-varying risk and returns.

The seventh project is with Siddique, "Conditional skewness in asset pricing tests." We believe that conditional skewness has long been overlooked by the mean-variance paradigm. We examine a model that incorporates skewness and assess its ability to explain both the time-series and cross-section of expected returns. Our results suggest that some of recent evidence that fundamental variables explain the cross-section of expected returns is due to these variables proxying for conditional skewness.

The eighth project is my working paper with Bekaert, "Emerging Equity Market Volatility," which I have already detailed.

I also have an exciting project in the early stages with Bernard Dumas. We study predictability and time-varying risk and try to relate both to fundamental economic conditions within each country. While the usual approach is to specify financial variables which proxy for time-varying expected returns, we develop economic leading and coincident indicators for a number of countries. We extract both local business cycles and the world business cycle and use this information to try to understand asset dynamics.

In a way, my research has come full circle. I started with an economic model where implications about economic activity were recovered from expected returns. I then used models relying exclusively on financial information to understand variation in expected returns. I am now back to the stage where I am now trying to understand the linkages between the financial markets and the real economy. While I might be back where I started, I have learned much on my journey.