Unit-Root Tests and Excess Returns
When introducing students to the modem theory of financial markets, it is common to characterize the behavior of the log of asset prices as martingales, and their excess returns as being serially uncorrelated or even unpredictable. This is consistent with Fama’s (1970) characterization of weak, semi-strong, and strong market efficiency. To be sure, there is an extensive literature documenting the deviations of asset prices from this characterization. Despite this, most would accept the proposition that asset prices contain a unit root in their time-series representation and that excess returns do not. Put another way, the stylized fact is that asset prices are integrated of order one (I(1)) and excess returns are integrated of order zero (I(0)). However, a small number of prominent recent papers have presented evidence that appears to reject this characterization in a surprising way. They show that, according to some tests, some excess returns appear to contain a unit root.
Unable to display preview. Download preview PDF.
- Baillie, R. T. and T. Bollerslev (1989). “Common Stochastic Trends in a System of Exchange Rates,” Journal of Monetary Economics, 44, 167–181.Google Scholar
- Campbell, J. and P. Perron (1991). “Pitfalls and Opportunities: What Macroeconomists Should Know About Unit Roots,” in O. Blanchard and S. Fischer (eds.) NBER Macroeconomics Annual. Cambridge: MIT Press.Google Scholar
- Durlauf, S. (1989). “Output Persistence, Economic Structure and the Choice of Stabilization Policy,” Brookings Papers on Economic Activity, 69–137.Google Scholar
- Edison, H. J., E. Gagnon, and W. R. Melick (1994). “Understanding the Empirical Literature on Purchasing Power Parity: the Post-Bretton Woods Era,” Board of Governors of the Federal Reserve System International Finance Discussion Papers No. 465.Google Scholar
- Evans, M. D. D. and K. Lewis (1992). “Trends in Excess Returns in Currency and Bond Markets,” NBER working paper No. 4116.Google Scholar
- Godbout, M. and S. van Norden (1997). “Reconsidering Cointegration in International Finance: Three Case Studies of Size Distortion in Finite Samples,” working paper No. 97-1, Bank of Canada.Google Scholar
- Gonzalo, J. and J. Pitarakis (1994). “Comovements in Large Systems,” discussion paper No. 9465, CORE.Google Scholar
- Gregory, A. (1994). “Testing for Cointegrating in Linear Quadratic Models,” Journal of Business and Economic Statistics, 12, 347–360.Google Scholar
- Hendry, S. (1995). “Long-Run Demand for Ml,” working paper No. 95-11, Bank of Canada.Google Scholar
- Reinsel, G. C. and S. H. Ahn (1988). “Asymptotic Distribution of the Likelihood Ratio Test for Cointegration in the Nonstationary Vector AR Case,” technical report, Department of Statistics, University of Wisconsin.Google Scholar
- Watson, M. W. (1995). “Vector Autoregressions and Cointegration,” in Engle, R.F. and D. McFadden (eds.), Handbook of Econometrics, Vol. 4. New York: North Holland.Google Scholar