Campbell Russell Harvey

Email: charvey@mail.duke.edu
 Phone: (919) 660-7768
Fax: (919) 681-6246
Cel: (919) 815-8825

Education

Ph.D. University of Chicago, 1986.

M.B.A. York University, 1983.

B.A. Trinity College, University of Toronto, 1981.

Academic Appointments

J. Paul Sticht Professor of International Business, Fuqua School of Business, Duke University, [joined Duke University in 1986].

Research Associate, National Bureau of Economic Research, appointed in 1993.

Visiting Scholar, Board of Governors of the Federal Reserve Bank, Summer 1994.

Visiting Professor of Finance, Swedish School of Economics and Business Administration, Helsinki, Summer 1996.

Visiting Professor of Finance, Handelshogskogskolan I Stockholm-(Stockholm School of Economics), Summer 1993.

Visiting Associate Professor of Finance, Graduate School of Business, University of Chicago, September 1990 - August 1991.

Visiting Lecturer in Finance, Helsingin Kauppakorkeakoulu - (Helsinki School of Economics), Summer 1990.

Publications

Working Papers

Work in Progress

Books, Chapters, Monographs

Reviews

Published Discussions

Policy

Executive Education Materials

Value and Risk Management Through Derivatives (PM1)

Lessons in Risk Management (PM2)

Option Valuation in Corporate Fiance (PM3)

Value Creation (PM4)

Active Investment in Developed and Emerging Markets (PM5)

Time-varing International Correlations: Implications for Global Diversification (PM6)

Predictable Returns in Developed and Emerging Markets (PM7)

Return Prediction for Dynamic Trading Strategies (PM8)

Mathematics for Finance (PM9)

Emerging Markets: Opportunities and Risks (PM10)

An Introduction to Conditional Asset Allocation (PM11)

The Implications of Predictable Returns in Asset Markets (PM12)

Global Financial Management and Country Risk (PM13)

Stock Market Predictability and Active Asset Allocation in Emerging and Mature Markets ( PM14

Towards a Truly Global Portfolio Strategy: New Directions in Dynamically Forecasting and Comparing the Risk and Returns of Worldwide Stocks (PM15)

Outperforming in Emerging Markets: Using Quantitative Methods ( PM16)

Active Asset Allocation: Does it Work? (PM17)

What Matters for Emerging Markets Investments (PM18)

I. Recent Advances in Cost of Capital Measurement; II. Global Financial Management and Shareholder Value (PM19)

An Introduction to Dynamic Global Financial Management (PM20)

Emerging Markets: Unsolved Puzzles (PM21)

Emerging Market Debt: A Global Perspective (PM22)

Cross-Sectional Prediction in Dynamic Trading Strategies(PM23)

Stock Selection in Emerging Markets (PM24)

Conditioning Variables and the Cross-Section of Stock Returns(PM25)

Editorial Appointments

Honors

Teaching MBA/Ph.D

Grants

External Work

Professor Harvey has wide-ranging consulting experience. He currently holds two directorships and is a consultant to some of the world's leading asset management firms. Harvey specializes in the construction of global equity and fixed income allocation models. Additional details are available on request.

Public Relations

Overview of Research

1. Unifying theme

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.

2. Term structure models

My research began with a study of the consumption-based asset pricing model. The framework of Robert Lucas (1978) implied a general time-variation in asset returns and risks. This framework was empirically tested by Lars Hansen and Kenneth Singleton (1982). These two papers along with class lectures of Lucas, Hansen and Sanford Grossman suggested a starting point for my research. I wrote down the linearized version of the Lucas model and noticed that there was potential information in the real term structure of interest rates that was relevant for forecasting the future path of consumption. My dissertation work (which was subsequently published as ``The Real Term Structure and Consumption Growth'' JFE88) explored the implications of this model. I subsequently published a number of papers exploring the information in the term structure of interest rates in both the U.S. and other countries. In this research area, my work has had impact on the practice of management. Many companies use forecasting models based on this work to track expected economic growth.

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 ``Seasonality and Consumption-Based Asset Pricing'' 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.

3. Asset Pricing Frameworks

3.1 Domestic
My JFE89, ``Time-Varying Conditional Covariances in Asset Pricing Tests'' draws heavily from my joint work with Ferson. In trying to salvage a linear consumption model, we tried many different formulations of the risk function. In my JFE89, I apply some of these formulations (and develop new ones) to versions of the Sharpe-Lintner asset pricing model as well as alternative multifactor models. The advantage of the formulation is that it provides for general covariance dynamics without explicitly parameterizing these dynamics. As such, the instrumental variables approach provided an alternative to other approaches (in particular to the GARCH family of models).

Ferson and I jointly studied an approach that incorporated time-varying risk and returns in our ``The Variation of Economic Risk Premiums'' JPE91. The genesis of this paper was the controversy regarding the attribution of predictability in asset returns: Was it due to rational asset pricing implications or was it due to market imperfections and/or irrational behavior on the part of investors? We noted that most of the asset pricing tests had been conducted within the paradigm of constant expected returns and risks. Our contribution was to study a multifactor model that allowed for general time-variation in asset returns and risk. We detailed an economic interpretation of the changes in economic risk premiums through the business cycle. We measured the ``statistical predictability'' of asset returns (i.e., from projecting asset returns on some, perhaps data-mined, set of predictors) and compared this predictability with that implied by asset pricing specification. We found that 85% of the predictability could be attributed to the asset pricing dynamics. While we could not eliminate the possibility of market imperfections causing some predictability, I think that the strength of our results tilted the balance of opinion toward rational asset pricing interpretations.

My final examination of domestic asset pricing question incorporates investigators' prior beliefs into the problem (``Bayesian Inference in Asset Pricing Tests'' 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) is 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.

3.2 International
I used the framework of my JFE89 to study expected international returns and risk in ``The World Price of Covariance Risk,'' published in JF91. I was very nervous about my initial submission to the JF because the framework of the paper appeared too similar to my JFE89. However, this paper was one of the first attempts to study international asset prices in a conditional (time-varying returns and risk) framework. Using data through mid 1989, I found that a single factor model did a reasonable job of accounting for the time-series and cross-section of expected returns with the exception of one country - Japan. In that country, the expected returns were too high given the risk (implying share prices were too high).

Ferson and I provided a comprehensive examination of expected international returns in our ``The Risk and Predictability of International Equity Returns'' 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 ``Time-Varying World Market Integration'' JF95. 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 ``Emerging Equity Market Volatility'' (JFE97), 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.

4. Other markets

My research theme has been extended to other markets as well. In my work with Roger Huang, we study time-varying ``Volatility in the Foreign Currency Futures Market'' RFS91. We also have a working paper which studies the volatility impact of the size and type of Federal Reserve open market operation (see W3) . In my work with Robert Whaley in ``Market Volatility Prediction and the Efficiency of the S&P 100 Index Option Market'' JFE92 and ``S&P 100 Index Option Volatility'' JF91, we study the implications of time-varying volatility in the options market. We present a model which forecasts implied volatility of the S&P 100 index option and develop trading strategies to assess whether the predictability leads to arbitrage profits.

5. Recent Research 1997-1998

I have a number new projects. The first is with Ferson, ``Country Risk and Asset Pricing.'' The goal of this paper is to provide a unified framework for assessing risk and asset selection in a global context. We provide a new framework for evaluating country risk. Our results also provide a possible interpretation to the recent domestic evidence that fundamental variables (like price-to-book ratios) impact the cross-section of expected returns. Our framework provides a theoretically consistent way for fundamental information to affect expected returns through the risk function. This paper was recently accepted at the JBF.

The second project is with John Graham. In ``Market Timing Ability and Volatility Implied in Investment Newsletters' Asset Allocation Recommendations,'' 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. This paper was recently published in the JFE (1996).

The third project is with Ravi Bansal, ``Dynamic Trading Strategies''. 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, ``Forecasting Foreign Exchange Market Returns via Entropy Coding.'' 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.

6. On the horizon

I have an exciting new initiative with Bekaert, ``Foreign Speculators and Emerging Equity Markets.'' In this work, we examine the impact of regulatory changes, ADRs and Country Funds on the cost of capital, volatility and correlations in 20 emerging market. We also investigate new data on capital flows. I also have an exciting project in the early stages with Bernard Dumas. We look at the economic linkages between countries, for example, the correlations between real economic growth. We use an economic model to predict what the equity correlations between countries should be. Our is the first attempt to try to explain the patterns of correlations across countries.

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.

Additional details available on request.

Updated July 1997