Portfolio optimization in hedge funds by OGARCH and Markov Switching Model

نویسندگان

  • Cuicui Luo
  • Luis Seco
  • Lin-Liang Bill Wu
چکیده

This paper investigates and compares the performances of the optimal portfolio selected by using the Orthogonal GARCH (OGARCH) Model, Markov Switching Model and the Exponentially Weighted Moving Average (EWMA) Model in a fund of hedge funds. These models are used to calibrate the returns of four HFRX indices from which the optimal portfolio is constructed using the Mean-Variance method. The performance of each optimal portfolio is compared in an out-of-sample period and it is observed that overall, OGARCH gives the best-performed optimal portfolio with the highest Sharpe ratio and the lowest risk. Moreover, a sensitivity analysis for the parameters of OGARCH is performed and it shows that the asset weights in the optimal portfolios selected by OGARCH are very sensitive to slight changes in the input parameters. & 2015 Elsevier Ltd. All rights reserved.

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تاریخ انتشار 2015