Applying Portfolio Change and Conditional Performance Measures: The Case of Industry Rotation via the Dynamic Investment Model

Applying Portfolio Change and Conditional Performance Measures: The Case of Industry Rotation via... This paper applies portfolio change and conditional performance measures to assess the performance of the dynamic investment model in various industry-rotation settings spanning the 1934–1995 period. The dynamic investment model employs the empirical probability assessment approach in raw form. In addition, it incorporates three adjustments for estimation error: James–Stein, Bayes–Stein, and CAPM-based corrections. The tests are unanimous in their conclusion that the excess returns attained by the (unadjusted) historic, the Bayes–Stein, and the James–Stein estimators are (sometimes highly) statistically significant over the 1966–1995 and 1966–1981 sub-periods. This lends support to the idea that the joint empirical probability assessment approach based on the recent past, with and without Stein-based corrections for estimation error, contains information that can be profitably exploited. The relationship of these findings to the extant literature on momentum and contrarian strategies is addressed. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Review of Quantitative Finance and Accounting Springer Journals

Applying Portfolio Change and Conditional Performance Measures: The Case of Industry Rotation via the Dynamic Investment Model

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Publisher
Kluwer Academic Publishers
Copyright
Copyright © 2001 by Kluwer Academic Publishers
Subject
Finance; Corporate Finance; Accounting/Auditing; Econometrics; Operation Research/Decision Theory
ISSN
0924-865X
eISSN
1573-7179
D.O.I.
10.1023/A:1012240609470
Publisher site
See Article on Publisher Site

Abstract

This paper applies portfolio change and conditional performance measures to assess the performance of the dynamic investment model in various industry-rotation settings spanning the 1934–1995 period. The dynamic investment model employs the empirical probability assessment approach in raw form. In addition, it incorporates three adjustments for estimation error: James–Stein, Bayes–Stein, and CAPM-based corrections. The tests are unanimous in their conclusion that the excess returns attained by the (unadjusted) historic, the Bayes–Stein, and the James–Stein estimators are (sometimes highly) statistically significant over the 1966–1995 and 1966–1981 sub-periods. This lends support to the idea that the joint empirical probability assessment approach based on the recent past, with and without Stein-based corrections for estimation error, contains information that can be profitably exploited. The relationship of these findings to the extant literature on momentum and contrarian strategies is addressed.

Journal

Review of Quantitative Finance and AccountingSpringer Journals

Published: Oct 3, 2004

References

  • Transaction Costs and Predictability: Some Utility Cost Calculations
    Balduzzi, P.; Lynch, A. W.
  • Portfolio Performance Measurement: Theory and Applications
    Chen, Z.; Knez, P.
  • Does the Stock Market Overreact?
    DeBondt, W. F. M.; Thaler, R.
  • Further Evidence on Investor Overreaction and Stock Market Seasonality
    DeBondt, W. F. M.; Thaler, R.
  • Further Ambiguity When Performance is Measured by the Security Market Line
    Grauer, R. R.
  • Gains from Diversifying into Real Estate: Three Decades of Portfolio Returns Based on the Dynamic Investment Model
    Grauer, R. R.; Hakansson, N. H.
  • Market Timing Ability and Volatility Implied in Investment Newsletter Asset Allocation Recommendations
    Harvey, C.; Graham, J.
  • Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency
    Jagadeesh, N.; Titman, S.

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