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Hedge Funds: Risk And Performance

Author

Listed:
  • SANGHEON SHIN

    (Department of Accounting & Finance, Percy J. Vaughn, Jr. College of Business Administration, Alabama State University, 915 S. Jackson St., Montgomery, AL 36117, USA)

  • JAN SMOLARSKI

    (Department of Accounting and Finance, William G. Rohrer College of Business, Rowan University, 201 Mullica Road, Glassboro, NJ 08028, USA)

  • GÖKÇE SOYDEMIR

    (Department of Accounting & Finance, College of Business Administration, California State University, Stanislaus, One University Circle, Turlock CA, 95382, USA)

Abstract

This paper models hedge fund exposure to risk factors and examines time-varying performance of hedge funds. From existing models such as asset-based style (ABS)-factor model, standard asset class (SAC)-factor model, and four-factor model, we extract the best six factors for each hedge fund portfolio by investment strategy. Then, we find combinations of risk factors that explain most of the variance in performance of each hedge fund portfolio based on investment strategy. The results show instability of coefficients in the performance attribution regression. Incorporating a time-varying factor exposure feature would be the best way to measure hedge fund performance. Furthermore, the optimal models with fewer factors exhibit greater explanatory power than existing models. Using rolling regressions, our customized investment strategy model shows how hedge funds are sensitive to risk factors according to market conditions.

Suggested Citation

  • Sangheon Shin & Jan Smolarski & Gökçe Soydemir, 2018. "Hedge Funds: Risk And Performance," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 6(01), pages 1-43, June.
    • Handle: RePEc:wsi:ijmpcx:v:30:y:2018:i:12:n:s2591768418500034
    DOI: 10.1142/S2591768418500034
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