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Optimal Dynamic Portfolio Selection with Earnings-at-Risk

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Abstract

In this paper we investigate a continuous-time portfolio selection problem. Instead of using the classical variance as usual, we use earnings-at-risk (EaR) of terminal wealth as a measure of risk. In the settings of Black-Scholes type financial markets and constantly-rebalanced portfolio (CRP) investment strategies, we obtain closed-form expressions for the best CRP investment strategy and the efficient frontier of the mean-EaR problem, and compare our mean-EaR analysis to the classical mean-variance analysis and to the mean-CaR (capital-at-risk) analysis. We also examine some economic implications arising from using the mean-EaR model.

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Authors and Affiliations

  1. Lingnan College, Sun Yat-Sen University, Guangzhou, People’s Republic of China

    Z. F. Li

  2. Department of Statistics and Actuarial Science, The University of Hong Kong, Hong Kong, Hong Kong

    H. Yang

  3. Department of Computer Science, City University of Hong Kong, Kowloon, Hong Kong

    X. T. Deng

Authors
  1. Z. F. Li
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  2. H. Yang
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  3. X. T. Deng
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Corresponding author

Correspondence to Z. F. Li.

Additional information

Communicated by P.M. Pardalos.

The authors thank the referees for careful reading of the paper and helpful suggestions. They are indebted to Panos Pardalos for support and suggestions.

The research of Z.F. Li was supported in part by FANEDD (Grant 200267), NSFC (Grants 70471018 and 70518001), and NCET (Grant NCET-04-0798).

The research of H. Yang was supported in part by the Hong Kong Research Grant Council (Grant HKU 7239/04H), and a Research Grant of the University of Hong Kong.

The research of X.T. Deng was supported in part by the NSFC Major Research Program (Grant 60496327), and the Hong Kong Research Grant Council (Grant CityU 1156/04E).

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Li, Z.F., Yang, H. & Deng, X.T. Optimal Dynamic Portfolio Selection with Earnings-at-Risk. J Optim Theory Appl 132, 459–473 (2007). https://doi.org/10.1007/s10957-007-9184-2

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  • DOI: https://doi.org/10.1007/s10957-007-9184-2

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