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Modern portfolio management with conditioning information

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  • Chiang, I-Hsuan Ethan

Abstract

This paper studies models in which active portfolio managers utilize conditioning information unavailable to their clients to optimize performance relative to a benchmark. We derive explicit solutions for the optimal strategies with multiple risky assets, with or without a risk-free asset, and consider various constraints on portfolio risks or weights. The optimal strategies feature a mean–variance efficient component (to minimize portfolio variance), and a hedging demand for the benchmark portfolio (to maximize correlation with the benchmark). A currency portfolio example shows that the optimal strategies improve the measured performance by 53% out of sample, compared with portfolios ignoring conditioning information.

Suggested Citation

  • Chiang, I-Hsuan Ethan, 2015. "Modern portfolio management with conditioning information," Journal of Empirical Finance, Elsevier, vol. 33(C), pages 114-134.
    • Handle: RePEc:eee:empfin:v:33:y:2015:i:c:p:114-134
    DOI: 10.1016/j.jempfin.2015.05.003
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    Cited by:

    1. Marc Boissaux & Jang Schiltz, 2010. "An Optimal Control Approach to Portfolio Optimisation with Conditioning Information," LSF Research Working Paper Series 10-09, Luxembourg School of Finance, University of Luxembourg.
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    3. Fletcher, Jonathan & Basu, Devraj, 2016. "An examination of the benefits of dynamic trading strategies in U.K. closed-end funds," International Review of Financial Analysis, Elsevier, vol. 47(C), pages 109-118.

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    More about this item

    Keywords

    Portfolio management; Conditioning information; Benchmark; Tracking error; Foreign exchange;
    All these keywords.

    JEL classification:

    • C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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