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Modeling Stock Prices without Knowing How to Induce Stationarity

Published online by Cambridge University Press:  11 February 2009

David N. DeJong
Affiliation:
University of Pittsburgh
Charles H. Whiteman
Affiliation:
University of Iowa

Abstract

Bayesian procedures for evaluating linear restrictions imposed by economic theory on dynamic econometric models are applied to a simple class of presentvalue models of stock prices. The procedures generate inferences that are not conditional on ancillary assumptions regarding the nature of the nonstationarity that characterizes the data. Inferences are influenced by prior views concerning nonstationarity, but these views are formally incorporated into the analysis, and alternative views are easily adopted. Viewed in light of relatively tight prior distributions that have proved useful in forecasting, the present-value model seems at odds with the data. Researchers less certain of the interaction between dividends and prices would find little reason to look beyond the present-value model.

Type
Articles
Copyright
Copyright © Cambridge University Press 1994

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References

1.Akaike, H. Information theory and an extension of the maximum likelihood principle. In Petrov, B.N. & Csaki, F. (eds.), Second International Symposium on Information Theory, pp. 267281. Akademiai Kiado: Budapest, 1973.Google Scholar
2.Campbell, J. & Shiller, R.J.. Cointegration and tests of present value models. Journal of Political Economy 95 (1987): 10621088.CrossRefGoogle Scholar
3.Campbell, J. & Shiller, R.J.. Stock prices, earnings, and expected dividends. Journal of Finance 43 (1988): 661676.CrossRefGoogle Scholar
4.Campbell, J. & Shiller, R.J.. The dividend-price ratio and expectations of future dividends and discount factors. Review of Financial Studies 1 (1989): 195228.CrossRefGoogle Scholar
5.Cowles, A.Common-Stock Indexes, 2nd ed. Bloomington, IN: Principia, 1939.Google Scholar
6.DeJong, D.N.Co-integration and trend-stationarity in macroeconomic time series. Journal of Econometrics 52 (1992): 347370.CrossRefGoogle Scholar
7.DeJong, D.N., Nankervis, J., Savin, N.E. & Whiteman, C.H.. Integration versus trendstationarity in time series. Econometrica 60 (1992): 423433.CrossRefGoogle Scholar
8.DeJong, D.N., Nankervis, J., Savin, N.E. & Whiteman, C.H.. The power problems of unit root tests in time series with autoregressive errors. Journal of Econometrics 53 (1992): 323343.CrossRefGoogle Scholar
9.DeJong, D.N., Nankervis, J., Savin, N.E. & Whiteman, C.H.. Testing for Unit Roots: A User's Guide, with Applications. University of Pittsburgh, 1992.Google Scholar
10.DeJong, D.N. & Whiteman, C.H.. The temporal stability of dividends and stock prices: evidence from the likelihood function. American Economic Review 81 (1991): 600617.Google Scholar
11.DeJong, D.N. & Whiteman, C.H.. More unsettling evidence on the perfect markets hypothesis: Trend-stationarity revisited. Federal Reserve Bank of Atlanta Economic Review 77 (1992): 113.Google Scholar
12.Doan, T.RATS 3.11 User's Manual. Evanston, IL: VAR Econometrics, 1990.Google Scholar
13.Doan, T., Litterman, R. & Sims, C.. Forecasting and conditional projection using realistic prior distributions. Econometric Reviews 3 (1984): 1100.CrossRefGoogle Scholar
14.Durlauf, S.N. & Phillips, P.C.B.. Trends versus random walks in time series analysis. Econometrica 56 (1988): 13331354.CrossRefGoogle Scholar
15.Engle, R.F. & Granger, C.W.J.. Co-integration and error correction: Representation, estimation, and testing. Econometrica 55 (1987): 251276.CrossRefGoogle Scholar
16.Fama, E.F.Efficient capital markets: A review of theory and empirical work. Journal of Finance 25 (1970): 383417.CrossRefGoogle Scholar
17.Grossman, S.J. & Shiller, R.J.. The determinants of the variability of stock market prices. American Economic Review 71 (1981): 222227.Google Scholar
18.Kleidon, A.W.Variance bounds tests and stock price valuation methods. Journal of Political Economy 94 (1986): 9531001.CrossRefGoogle Scholar
19.LeRoy, S.F. & Porter, R.D.. The present value relation: Tests based on implied variance bounds. Econometrica 49 (1981): 555574.CrossRefGoogle Scholar
20.Mankiw, N.G., Romer, D. & Shapiro, M.D.. An unbiased reexamination of stock market volatility. Journal of Finance 40 (1985): 677687.CrossRefGoogle Scholar
21.McCulloch, R. & Rossi, P.. A Bayesian approach to testing the arbitrage pricing theory. Journal of Econometrics 49 (1991): 141168.CrossRefGoogle Scholar
22.Marsh, T.A. & Merton, R.C.. Dividend variability and variance bounds tests for the rationality of stock market prices. American Economic Review 76 (1986): 483498.Google Scholar
23.Merton, R.C. On the current state of the stock market rationality hypothesis. In Dornbusch, R., Fischer, S.F. & Bossuns, J. (eds.), Macroeconomics and Finance: Essays in Honor of Franco Modigliani, pp. 93124. Cambridge: MIT Press, 1987.Google Scholar
24.Phillips, P.C.B.To criticize the critics: An objective Bayesian analysis of stochastic trends. Journal of Applied Econometrics 6 (1991): 333364.CrossRefGoogle Scholar
25.Schwarz, G.Estimating the dimension of a model. Annals of Statistics 6 (1978): 461464.CrossRefGoogle Scholar
26.Shiller, R.J.Do stock prices move too much to be justified by subsequent changes in dividends? American Economic Review 71 (1981): 421436.Google Scholar
27.Shiller, R.J.The use of volatility measures in assessing market efficiency. Journal of Finance 36 (1981): 291304.Google Scholar
28.Uhlig, H.BVARTEC–Bayesian Vector Autoregressions with Time-Varying Error Covariances. Princeton University, 1992.Google Scholar
29.West, K.D.Dividend innovations and stock price volatility. Econometrica 56 (1988): 3761.CrossRefGoogle Scholar
30.Zellner, A.An Introduction to Bayesian Inference in Econometrics. New York: Wiley, 1971.Google Scholar
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