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Long-Term Strategic Asset Allocation: An Out-of-Sample Evaluation

Author

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  • Bart Diris

    (Econometric Institute, Erasmus School of Economics, Erasmus University Rotterdam, 3000 DR, Rotterdam, The Netherlands)

  • Franz Palm

    (Quantitative Economics Department, Maastricht University, 6200 MD, Maastricht, The Netherlands)

  • Peter Schotman

    (Finance Department, Maastricht University, 6200 MD, Maastricht, The Netherlands)

Abstract

We evaluate the out-of-sample performance of a long-term investor who follows an optimized dynamic trading strategy. Although the dynamic strategy is able to benefit from predictability out-of-sample, a short-term investor using a single-period market timing strategy would have realized an almost identical performance. The value of intertemporal hedge demands in strategic asset allocation appears negligible. The result is caused by the estimation error in predicting the predictors. A myopic investor only needs to predict one-period-ahead expected returns, but hedge demands also require accurate predictions of the predictor variables. To reduce the problem of errors in optimized portfolio weights, we consider Bayesian procedures. Myopic and dynamic portfolios are similarly affected by such modifications, and differences in performance become even smaller.Data, as supplemental material, are available at http://dx.doi.org/10.1287/mnsc.2014.1924 . This paper was accepted by Brad Barber, finance.

Suggested Citation

  • Bart Diris & Franz Palm & Peter Schotman, 2015. "Long-Term Strategic Asset Allocation: An Out-of-Sample Evaluation," Management Science, INFORMS, vol. 61(9), pages 2185-2202, September.
  • Handle: RePEc:inm:ormnsc:v:61:y:2015:i:9:p:2185-2202
    DOI: 10.1287/mnsc.2014.1924
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    2. Platanakis, Emmanouil & Sakkas, Athanasios & Sutcliffe, Charles, 2019. "Harmful diversification: Evidence from alternative investments," The British Accounting Review, Elsevier, vol. 51(1), pages 1-23.
    3. Rongju Zhang & Nicolas Langren'e & Yu Tian & Zili Zhu & Fima Klebaner & Kais Hamza, 2018. "Local Control Regression: Improving the Least Squares Monte Carlo Method for Portfolio Optimization," Papers 1803.11467, arXiv.org, revised Sep 2018.
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    5. Emmanouil Platanakis & Athanasios Sakkas & Charles Sutcliffe, 2017. "Should Portfolio Model Inputs Be Estimated Using One or Two Economic Regimes?," ICMA Centre Discussion Papers in Finance icma-dp2017-07, Henley Business School, University of Reading.

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