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The Power of Dynamic Asset Allocation

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Abstract

This article re-assesses the evidence and practical relevance of asset returns’ long-horizon predictability, investigating whether practitioners can profitably exploit predictability patterns by using relatively simple, dynamic asset allocation strategies. The analysis shows forward-looking models that rely on steady-state equations for equities and initial yields to maturity for bonds are far better predictors of markets’ long-run direction than is the industry’s conventional approach, which involves extrapolating from historical averages. Using a long-term U.S. sample from 1926 to 2010, the authors find that predictability translates into significantly better risk-adjusted performance from dynamic asset allocation strategies that rely on forward-looking inputs.

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  • Mirko Cardinale & Marco Navone & Andrzej Pioch, 2014. "The Power of Dynamic Asset Allocation," Published Paper Series 2014-2, Finance Discipline Group, UTS Business School, University of Technology, Sydney.
    • Handle: RePEc:uts:ppaper:2014-2
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    Cited by:

    1. Giulia Dal Pra & Massimo Guidolin & Manuela Pedio & Fabiola Vasile, 2016. "Do Regimes in Excess Stock Return Predictability Create Economic Value? An Out-of-Sample Portfolio Analysis," BAFFI CAREFIN Working Papers 1637, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.

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