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Improved Estimates of Correlation Coefficients and their Impact on Optimum Portfolios

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  • Edwin J. Elton
  • Martin J. Gruber
  • Jonathan Spitzer

Abstract

To implement mean variance analysis one needs a technique for forecasting correlation coefficients. In this article we investigate the ability of several techniques to forecast correlation coefficients between securities. We find that separately forecasting the average level of pair‐wise correlations and individual pair‐wise differences from the average improves forecasting accuracy. Furthermore, forming homogenous groups of firms on the basis of industry membership or firm attributes (e.g. size) improves forecast accuracy. Accuracy is evaluated in two ways: First, in terms of the error in estimating future correlation coefficients. Second, in the characteristics of portfolios formed on the basis of each forecasting technique. The ranking of forecasting techniques is robust across both methods of evaluation and the better techniques outperform prior suggestions in the literature of financial economics.

Suggested Citation

  • Edwin J. Elton & Martin J. Gruber & Jonathan Spitzer, 2006. "Improved Estimates of Correlation Coefficients and their Impact on Optimum Portfolios," European Financial Management, European Financial Management Association, vol. 12(3), pages 303-318, June.
  • Handle: RePEc:bla:eufman:v:12:y:2006:i:3:p:303-318
    DOI: 10.1111/j.1354-7798.2006.00322.x
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    2. 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.
    3. Lavko, Matus & Klein, Tony & Walther, Thomas, 2023. "Reinforcement Learning and Portfolio Allocation: Challenging Traditional Allocation Methods," QBS Working Paper Series 2023/01, Queen's University Belfast, Queen's Business School.
    4. Kwan, Clarence C.Y., 2008. "Estimation error in the average correlation of security returns and shrinkage estimation of covariance and correlation matrices," Finance Research Letters, Elsevier, vol. 5(4), pages 236-244, December.
    5. Le, Trung H., 2021. "International portfolio allocation: The role of conditional higher moments," International Review of Economics & Finance, Elsevier, vol. 74(C), pages 33-57.
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    7. Olivier Ledoit & Michael Wolf, 2018. "Robust performance hypothesis testing with smooth functions of population moments," ECON - Working Papers 305, Department of Economics - University of Zurich.
    8. Colm Kearney & Valerio Potì, 2008. "Have European Stocks become More Volatile? An Empirical Investigation of Idiosyncratic and Market Risk in the Euro Area," European Financial Management, European Financial Management Association, vol. 14(3), pages 419-444, June.
    9. Dai, Zhifeng & Wen, Fenghua, 2018. "Some improved sparse and stable portfolio optimization problems," Finance Research Letters, Elsevier, vol. 27(C), pages 46-52.
    10. Justo Puerto & Federica Ricca & Mois'es Rodr'iguez-Madrena & Andrea Scozzari, 2021. "A combinatorial optimization approach to scenario filtering in portfolio selection," Papers 2103.01123, arXiv.org.
    11. Zhang, Xi & Li, Jian, 2018. "Credit and market risks measurement in carbon financing for Chinese banks," Energy Economics, Elsevier, vol. 76(C), pages 549-557.
    12. Eom, Cheoljun, 2017. "Two-faced property of a market factor in asset pricing and diversification effect," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 471(C), pages 190-199.
    13. Francesco Cesarone & Fabio Tardella, 2017. "Equal Risk Bounding is better than Risk Parity for portfolio selection," Journal of Global Optimization, Springer, vol. 68(2), pages 439-461, June.
    14. To, W.M., 2014. "Association between energy use and poor visibility in Hong Kong SAR, China," Energy, Elsevier, vol. 68(C), pages 12-20.
    15. Kempf, Alexander & Korn, Olaf & Saßning, Sven, 2014. "Portfolio optimization using forward-looking information," CFR Working Papers 11-10 [rev.], University of Cologne, Centre for Financial Research (CFR).
    16. Justo Puerto & Moises Rodr'iguez-Madrena & Andrea Scozzari, 2019. "Location and portfolio selection problems: A unified framework," Papers 1907.07101, arXiv.org.
    17. Lan Liu & Hao Lin, 2010. "Covariance estimation: do new methods outperform old ones?," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 34(2), pages 187-195, April.
    18. Isaac T. Tabner, 2012. "In Defence of Capitalisation Weights: Evidence from the FTSE 100 and S&P 500 Indices," European Financial Management, European Financial Management Association, vol. 18(1), pages 142-161, January.
    19. Jing-zhi Huang & Zhaodong Zhong, 2013. "Time Variation in Diversification Benefits of Commodity, REITs, and TIPS," The Journal of Real Estate Finance and Economics, Springer, vol. 46(1), pages 152-192, January.
    20. Francesco Cesarone & Rosella Giacometti & Manuel Luis Martino & Fabio Tardella, 2023. "A return-diversification approach to portfolio selection," Papers 2312.09707, arXiv.org.

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