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Factor-based portfolio optimization

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  • Auh, Jun Kyung
  • Cho, Wonho

Abstract

A parsimonious factor model mitigates idiosyncratic noise in historical data for portfolio optimization. We use market predictors and machine learning to incorporate forward-looking information into expected returns. The combination of the factor model and forward-looking returns improves out-of-sample performance, conforming to the theoretical assumption that the mean and variance correspond to future returns.

Suggested Citation

  • Auh, Jun Kyung & Cho, Wonho, 2023. "Factor-based portfolio optimization," Economics Letters, Elsevier, vol. 228(C).
    • Handle: RePEc:eee:ecolet:v:228:y:2023:i:c:s0165176523001623
    DOI: 10.1016/j.econlet.2023.111137
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    References listed on IDEAS

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    1. William F. Sharpe, 1963. "A Simplified Model for Portfolio Analysis," Management Science, INFORMS, vol. 9(2), pages 277-293, January.
    2. Hjalmarsson, Erik & Manchev, Petar, 2012. "Characteristic-based mean-variance portfolio choice," Journal of Banking & Finance, Elsevier, vol. 36(5), pages 1392-1401.
    3. Olivier Ledoit & Michael Wolf, 2017. "Nonlinear Shrinkage of the Covariance Matrix for Portfolio Selection: Markowitz Meets Goldilocks," Review of Financial Studies, Society for Financial Studies, vol. 30(12), pages 4349-4388.
    4. Ravi Jagannathan & Tongshu Ma, 2003. "Risk Reduction in Large Portfolios: Why Imposing the Wrong Constraints Helps," Journal of Finance, American Finance Association, vol. 58(4), pages 1651-1683, August.
    5. John H. Cochrane, 2011. "Presidential Address: Discount Rates," Journal of Finance, American Finance Association, vol. 66(4), pages 1047-1108, August.
    6. Michael W. Brandt & Pedro Santa-Clara & Rossen Valkanov, 2009. "Parametric Portfolio Policies: Exploiting Characteristics in the Cross-Section of Equity Returns," Review of Financial Studies, Society for Financial Studies, vol. 22(9), pages 3411-3447, September.
    7. Pastor, Lubos & Stambaugh, Robert F., 2000. "Comparing asset pricing models: an investment perspective," Journal of Financial Economics, Elsevier, vol. 56(3), pages 335-381, June.
    8. Richard J. McGee & Jose Olmo, 2022. "Optimal characteristic portfolios," Quantitative Finance, Taylor & Francis Journals, vol. 22(10), pages 1853-1870, October.
    9. Green, Richard C & Hollifield, Burton, 1992. "When Will Mean-Variance Efficient Portfolios Be Well Diversified?," Journal of Finance, American Finance Association, vol. 47(5), pages 1785-1809, December.
    10. Best, Michael J & Grauer, Robert R, 1991. "On the Sensitivity of Mean-Variance-Efficient Portfolios to Changes in Asset Means: Some Analytical and Computational Results," Review of Financial Studies, Society for Financial Studies, vol. 4(2), pages 315-342.
    11. Sanford J. Grossman & Zhongquan Zhou, 1993. "Optimal Investment Strategies For Controlling Drawdowns," Mathematical Finance, Wiley Blackwell, vol. 3(3), pages 241-276, July.
    12. T. Law & J. Shawe-Taylor, 2017. "Practical Bayesian support vector regression for financial time series prediction and market condition change detection," Quantitative Finance, Taylor & Francis Journals, vol. 17(9), pages 1403-1416, September.
    13. Gaoxun Zhang & Gaoxiu Qiao, 2021. "Out-of-sample realized volatility forecasting: does the support vector regression compete combination methods," Applied Economics, Taylor & Francis Journals, vol. 53(19), pages 2192-2205, April.
    14. Turan G. Bali & Robert F. Engle & Yi Tang, 2017. "Dynamic Conditional Beta Is Alive and Well in the Cross Section of Daily Stock Returns," Management Science, INFORMS, vol. 63(11), pages 3760-3779, November.
    15. Eugene F. Fama & Kenneth R. French, 2004. "The Capital Asset Pricing Model: Theory and Evidence," Journal of Economic Perspectives, American Economic Association, vol. 18(3), pages 25-46, Summer.
    16. Ravi Jagannathan & Tongshu Ma, 2003. "Risk Reduction in Large Portfolios: Why Imposing the Wrong Constraints Helps," Journal of Finance, American Finance Association, vol. 58(4), pages 1651-1684, August.
    17. Merton, Robert C., 1980. "On estimating the expected return on the market : An exploratory investigation," Journal of Financial Economics, Elsevier, vol. 8(4), pages 323-361, December.
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    More about this item

    Keywords

    Portfolio optimization; Factor model; Algorithmic trading; Machine learning;
    All these keywords.

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G24 - Financial Economics - - Financial Institutions and Services - - - Investment Banking; Venture Capital; Brokerage

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