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Portfolio Optimization Using Forward-Looking Information

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  • Alexander Kempf
  • Olaf Korn
  • Sven Saßning

Abstract

We develop a new family of estimators of the covariance matrix that relies solely on forward-looking information. It uses only current prices of plain-vanilla options. In an out-of-sample study, we show that a minimum variance strategy based on these fully-implied estimators outperforms several benchmark strategies, including various strategies based on historical estimates, index investing, and 1/N investing. The outperformance originates in crisis periods when information flow and information asymmetry are high. Although the historical benchmark strategies improve when more recent data are used, they never outperform fully-implied strategies. Thus, our results suggest that investors are better off relying on forward-looking information.

Suggested Citation

  • Alexander Kempf & Olaf Korn & Sven Saßning, 2015. "Portfolio Optimization Using Forward-Looking Information," Review of Finance, European Finance Association, vol. 19(1), pages 467-490.
    • Handle: RePEc:oup:revfin:v:19:y:2015:i:1:p:467-490.
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    Cited by:

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    3. Wolfgang Schadner, 2021. "Feasible Implied Correlation Matrices from Factor Structures," Papers 2107.00427, arXiv.org.
    4. Gkionis, Konstantinos & Kostakis, Alexandros & Skiadopoulos, George & Stilger, Przemyslaw S., 2021. "Positive stock information in out-of-the-money option prices," Journal of Banking & Finance, Elsevier, vol. 128(C).
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    6. Rui Fan & Stephen J. Taylor & Matteo Sandri, 2018. "Density forecast comparisons for stock prices, obtained from high‐frequency returns and daily option prices," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(1), pages 83-103, January.
    7. Rainer Baule & Olaf Korn & Sven Saßning, 2016. "Which Beta Is Best? On the Information Content of Option†implied Betas," European Financial Management, European Financial Management Association, vol. 22(3), pages 450-483, June.
    8. Yi Huang & Wei Zhu & Duan Li & Shushang Zhu & Shikun Wang, 2023. "Integrating Different Informations for Portfolio Selection," Papers 2305.17881, arXiv.org.
    9. Wolfgang Schadner & Joshua Traut, 2022. "Estimating Forward-Looking Stock Correlations from Risk Factors," Mathematics, MDPI, vol. 10(10), pages 1-19, May.
    10. Gagnon, Marie-Hélène & Power, Gabriel J. & Toupin, Dominique, 2016. "International stock market cointegration under the risk-neutral measure," International Review of Financial Analysis, Elsevier, vol. 47(C), pages 243-255.
    11. Schadner, Wolfgang, 2021. "Ex-Ante Risk Factors and Required Structures of the Implied Correlation Matrix," Finance Research Letters, Elsevier, vol. 41(C).
    12. Yuta Hibiki & Takuya Kiriu & Norio Hibiki, 2024. "Optimal Currency Portfolio with Implied Return Distribution in the Mean-Variance Approach," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 31(2), pages 251-283, June.
    13. Mohrschladt, Hannes & Schneider, Judith C., 2021. "Option-implied skewness: Insights from ITM-options," Journal of Economic Dynamics and Control, Elsevier, vol. 131(C).
    14. Fabian Hollstein & Marcel Prokopczuk & Chardin Wese Simen, 2019. "The term structure of systematic and idiosyncratic risk," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(4), pages 435-460, April.
    15. Guidolin, Massimo & Wang, Kai, 2023. "The empirical performance of option implied volatility surface-driven optimal portfolios," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 618(C).
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    17. Przemysław S. Stilger & Alexandros Kostakis & Ser-Huang Poon, 2017. "What Does Risk-Neutral Skewness Tell Us About Future Stock Returns?," Management Science, INFORMS, vol. 63(6), pages 1814-1834, June.

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