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Analyzing Investments Whose Histories Differ in Length

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  • Robert F. Stambaugh

Abstract

This study explores multivariate methods for investment analysis based on a sample of return histories that differ in length across assets. The longer histories provide greater information about moments of returns, not only for the longer-history assets, but for the shorter-history assets as well. To account for the remaining parameter uncertainty, or estimation risk,' portfolio opportunities are characterized by a Bayesian predictive distribution. Examples involving emerging markets demonstrate the value of using the combined sample of histories and accounting for estimation risk, as compared to truncating the sample to produce equal-length histories or ignoring estimation risk by using maximum-likelihood estimates.

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Bibliographic Info

Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 5918.

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Date of creation: Feb 1997
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Handle: RePEc:nbr:nberwo:5918

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  1. Goetzmann, William N. & Jorion, Philippe, 1999. "Re-Emerging Markets," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 34(01), pages 1-32, March.
  2. Robert R. Grauer & Nils H. Hakansson, 1993. "On the Use of Mean-Variance and Quadratic Approximations in Implementing Dynamic Investment Strategies: A Comparison of Returns and Investment Policies," Management Science, INFORMS, vol. 39(7), pages 856-871, July.
  3. Klein, Roger W. & Bawa, Vijay S., 1977. "Abstract: The Effect of Limited Information and Estimation Risk on Optimal Portfolio Diversification," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 12(04), pages 669-669, November.
  4. Gibbons, Michael R & Ross, Stephen A & Shanken, Jay, 1989. "A Test of the Efficiency of a Given Portfolio," Econometrica, Econometric Society, vol. 57(5), pages 1121-52, September.
  5. Frost, Peter A. & Savarino, James E., 1986. "An Empirical Bayes Approach to Efficient Portfolio Selection," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 21(03), pages 293-305, September.
  6. Kandel, S. & McCulloch, R. & Stambaugh, R.F., 1991. "Bayesian Inference and Portfolio Efficiency," Weiss Center Working Papers 8-91, Wharton School - Weiss Center for International Financial Research.
  7. Brown, Stephen J & Goetzmann, William N & Ross, Stephen A, 1995. " Survival," Journal of Finance, American Finance Association, vol. 50(3), pages 853-73, July.
  8. Harvey, Campbell R, 1995. "Predictable Risk and Returns in Emerging Markets," Review of Financial Studies, Society for Financial Studies, vol. 8(3), pages 773-816.
  9. Barry, Christopher B. & Brown, Stephen J., 1985. "Differential Information and Security Market Equilibrium," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 20(04), pages 407-422, December.
  10. Harvey, Campbell R. & Zhou, Guofu, 1990. "Bayesian inference in asset pricing tests," Journal of Financial Economics, Elsevier, vol. 26(2), pages 221-254, August.
  11. Jorion, Philippe, 1986. "Bayes-Stein Estimation for Portfolio Analysis," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 21(03), pages 279-292, September.
  12. Klein, Roger W. & Bawa, Vijay S., 1977. "The effect of limited information and estimation risk on optimal portfolio diversification," Journal of Financial Economics, Elsevier, vol. 5(1), pages 89-111, August.
  13. Shanken, Jay, 1987. "A Bayesian approach to testing portfolio efficiency," Journal of Financial Economics, Elsevier, vol. 19(2), pages 195-215, December.
  14. Klein, Roger W. & Bawa, Vijay S., 1976. "The effect of estimation risk on optimal portfolio choice," Journal of Financial Economics, Elsevier, vol. 3(3), pages 215-231, June.
  15. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-54, July.
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