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Mimicking Portfolios with Conditioning Information

Author

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  • Ferson, Wayne
  • Siegel, Andrew F.
  • Xu, Pisun (Tracy)

Abstract

Mimicking portfolios have long been useful in asset pricing research. In most empirical applications, the portfolio weights are assumed to be fixed over time, while in theory they may be functions of the economic state. This paper derives and characterizes mimicking portfolios in the presence of predetermined state variables, or conditioning information. The results generalize and integrate multifactor minimum variance efficiency (Fama (1996)) with conditional and unconditional mean-variance efficiency (Hansen and Richard (1987), Ferson and Siegel (2001)). Empirical examples illustrate the potential importance of time-varying mimicking portfolio weights and highlight challenges in their application.

Suggested Citation

  • Ferson, Wayne & Siegel, Andrew F. & Xu, Pisun (Tracy), 2006. "Mimicking Portfolios with Conditioning Information," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 41(3), pages 607-635, September.
    • Handle: RePEc:cup:jfinqa:v:41:y:2006:i:03:p:607-635_00
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    Cited by:

    1. Zhang, Xiang & Liu, Yangyi & Wu, Kun & Maillet, Bertrand, 2021. "Tradable or nontradable factors—what does the Hansen–Jagannathan distance tell us?," International Review of Economics & Finance, Elsevier, vol. 71(C), pages 853-879.
    2. Asgharian, Hossein, 2011. "A conditional asset-pricing model with the optimal orthogonal portfolio," Journal of Banking & Finance, Elsevier, vol. 35(5), pages 1027-1040, May.
    3. Cooper, Ilan & Priestley, Richard, 2011. "Real investment and risk dynamics," Journal of Financial Economics, Elsevier, vol. 101(1), pages 182-205, July.
    4. Chiang, I-Hsuan Ethan, 2015. "Modern portfolio management with conditioning information," Journal of Empirical Finance, Elsevier, vol. 33(C), pages 114-134.
    5. Yang Zhao & Charalampos Stasinakis & Georgios Sermpinis & Filipa Da Silva Fernandes, 2019. "Revisiting Fama–French factors' predictability with Bayesian modelling and copula‐based portfolio optimization," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 24(4), pages 1443-1463, October.
    6. Francesco Chincoli & Massimo Guidolin, 2017. "Linear and nonlinear predictability in investment style factors: multivariate evidence," Journal of Asset Management, Palgrave Macmillan, vol. 18(6), pages 476-509, October.
    7. Francisco Peñaranda, 2009. "Understanding Portfolio Efficiency with Conditioning Information," FMG Discussion Papers dp626, Financial Markets Group.
    8. Cao, Min & Conlon, Thomas, 2023. "Composite jet fuel cross-hedging," Journal of Commodity Markets, Elsevier, vol. 30(C).
    9. Ferruz Agudo, Luis & Vargas Magallón, María & Nievas López, J., 2008. "¿Utilizan los gestores españoles de fondos de inversión información privada en sus labores de gestión?," Estudios de Economia Aplicada, Estudios de Economia Aplicada, vol. 26, pages 257-278, Septiembr.
    10. Kroencke, Tim A. & Schindler, Felix & Sebastian, Steffen & Theissen, Erik, 2013. "GDP mimicking portfolios and the cross-section of stock returns," ZEW Discussion Papers 13-026, ZEW - Leibniz Centre for European Economic Research.
    11. Eriksen, Jonas N., 2019. "Cross-sectional return dispersion and currency momentum," Journal of Empirical Finance, Elsevier, vol. 53(C), pages 91-108.
    12. Barras, Laurent, 2007. "International conditional asset allocation under specification uncertainty," Journal of Empirical Finance, Elsevier, vol. 14(4), pages 443-464, September.
    13. Peñaranda, Francisco, 2009. "Understanding portfolio efficiency with conditioning information," LSE Research Online Documents on Economics 24415, London School of Economics and Political Science, LSE Library.

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