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Minimal concave cost rebalance of a portfolio to the efficient frontier

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Abstract.

One usually constructs a portfolio on the efficient frontier, but it may not be efficient after, say three months since the efficient frontier will shift as the elapse of time. We then have to rebalance the portfolio if the deviation is no longer acceptable. The method to be proposed in this paper is to find a portfolio on the new efficient frontier such that the total transaction cost required for this rebalancing is minimal. This problem results in a nonconvex minimization problem, if we use mean-variance model. In this paper we will formulate this problem by using absolute deviation as the measure of risk and solve the resulting linearly constrained concave minimization problem by a branch and bound algorithm successfully applied to portfolio optimization problem under concave transaction costs. It will be demonstrated that this method is efficient and that it leads to a significant reduction of transaction costs.

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References

  1. Falk, J.E., Soland, R.M.: An algorithm for separable nonconvex programming problems. Management Science 15, 550–569 (1969)

    Google Scholar 

  2. Gotoh, J., Konno, H.: Third degree slochastic dominance and mean-risk analysis. Management Science 46, 289–301 (2000)

    Google Scholar 

  3. Konno, H., Yamazaki, H.: Mean-absolute deviation portfolio optimization model and its application to tokyo stock market. Management Science 37, 519–531 (1991)

    Google Scholar 

  4. Konno, H., Wijayanayake, A.: Mean-Absolute Deviation Portfolio Optimization Model under Transaction Costs. J. Oper. Res. Society of Japan 42, 422–435 (1999)

    Google Scholar 

  5. Konno, H., Wijayanayake, A.: Portfolio optimization problems with concave transaction costs and minimal transaction unit constraints. Math. Program. 89, 233–250 (2001)

    Google Scholar 

  6. Markowitz, H.: Portfolio Selection: Efficient Diversification of Investments. John Wiley & Sons, 1959

  7. Mulvey, J.M., Ziemba, W.T.: Asset and Liability Allocation in Global Environment. In: Finance (Jarrow al, R. ed), North Holland, 1995

  8. Ogryczak, W., Ruszczynski, A.: From stochastic dominance to mean-risk model: semideviation as the risk measures. Eurapean J. of Operational Research 116, 33–50 (1999)

    Google Scholar 

  9. Ogryczak, W., Ruszczynski, A.: On consistency of stochastic dominance and mean-semideviation models. Math. Program. 89, 217–232 (2001)

    Google Scholar 

  10. Perold, A.: Large scale prtofolio optimization. Management Science 30, 1143–1160 (1984)

    Google Scholar 

  11. Phong, T.Q., An, L.T.H., Tao, P.D.: On globally solving linearly constrained indefinite quadratic minimization problems by decomposition branch and bound method. Operations Research Letters, 17, 215–220 (1995)

    Google Scholar 

  12. Tuy, H.: Convex Analysis and Global Optimization. (Kluwer Academic Publishers, 1998)

  13. Yamamoto, Y.: Optimization over the Efficient Set: Overview. J. of Global Optimization 22, 285–317 (2002)

    Google Scholar 

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Correspondence to Hiroshi Konno.

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Key words. portfolio optimization – rebalance – mean-absolute deviation model – concave cost minimization – optimization over the efficient set – global optimization

Mathematics Subject Classification (1991): 20E28, 20G40, 20C20

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Konno, H., Yamamoto, R. Minimal concave cost rebalance of a portfolio to the efficient frontier. Math. Program., Ser. B 97, 571–585 (2003). https://doi.org/10.1007/s10107-003-0428-0

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  • DOI: https://doi.org/10.1007/s10107-003-0428-0

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