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Portfolio choice under local industry and country factors

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  • Carlos Castro

Abstract

This article extends the parametric portfolio policy approach to optimizing portfolios with a large numbers of assets (Brandt et al. 2009 ). The proposed approach incorporates unobserved effects into the portfolio policy function. These effects measure the importance of unobserved heterogeneity for exploiting the difference between groups of assets. The source of the heterogeneity is local priced factors, such as industry or country. The statistical model allows testing the importance of such local factors in portfolio optimization. The results suggest that local effects or return heterogeneity associated with economic sectors or geographic factors is not as straightforward to exploit financially or as relevant as suggested by the extensive multivariate factor literature on the subject. Furthermore, trying to exploit industry effects rarely provides a gain over simple benchmarks, neither in-sample nor more importantly, out-of-sample. On the other hand, exploiting country effects does provide gains over the benchmark. However, these gains may be offset by the increasing cost of and risk inherent in such strategies. Finally, exploiting size, momentum, and liquidity anomalies in the cross-section of stocks provides strictly greater returns than the industry and country effects. Copyright Swiss Society for Financial Market Research 2010

Suggested Citation

  • Carlos Castro, 2010. "Portfolio choice under local industry and country factors," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 24(4), pages 353-393, December.
  • Handle: RePEc:kap:fmktpm:v:24:y:2010:i:4:p:353-393
    DOI: 10.1007/s11408-010-0143-9
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    References listed on IDEAS

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    1. John Y. Campbell & Luis M. Viceira, 1999. "Consumption and Portfolio Decisions when Expected Returns are Time Varying," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 114(2), pages 433-495.
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    3. Michael W. Brandt & Amit Goyal & Pedro Santa-Clara & Jonathan R. Stroud, 2005. "A Simulation Approach to Dynamic Portfolio Choice with an Application to Learning About Return Predictability," The Review of Financial Studies, Society for Financial Studies, vol. 18(3), pages 831-873.
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    8. Yacine AÏT‐SAHALI & Michael W. Brandt, 2001. "Variable Selection for Portfolio Choice," Journal of Finance, American Finance Association, vol. 56(4), pages 1297-1351, August.
    9. Hoevenaars, Roy P.M.M. & Molenaar, Roderick D.J. & Schotman, Peter C. & Steenkamp, Tom B.M., 2008. "Strategic asset allocation with liabilities: Beyond stocks and bonds," Journal of Economic Dynamics and Control, Elsevier, vol. 32(9), pages 2939-2970, September.
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    1. Nandkumar Nayar & Ajai Singh & Wen Yu, 2011. "Unraveling a puzzle: the case of value line timeliness rank upgrades," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 25(4), pages 379-409, December.

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    More about this item

    Keywords

    Portfolio choice; Multifactor asset pricing models; Industry and country factors; G11; G12; G15;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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