IDEAS home Printed from https://ideas.repec.org/a/eee/finlet/v19y2016icp241-246.html
   My bibliography  Save this article

On the weight sign of the global minimum variance portfolio

Author

Listed:
  • Chiu, Wan-Yi
  • Jiang, Ching-Hai

Abstract

We investigate the one-to-one mapping between the global minimum variance portfolio and regression hedge coefficients. The analysis demonstrates that assets with a superior (inferior) regression hedged effect in terms of marginal return create a negative (positive) weight. The asset has a weight of zero when both the asset and regression hedge enjoy the same marginal return. In addition, we develop a modified information ratio to compare the magnitudes of two arbitrary weights of the global minimum variance portfolio. From the perspective of hedging, we determine that the asset with a higher modified information ratio yields a larger weight.

Suggested Citation

  • Chiu, Wan-Yi & Jiang, Ching-Hai, 2016. "On the weight sign of the global minimum variance portfolio," Finance Research Letters, Elsevier, vol. 19(C), pages 241-246.
  • Handle: RePEc:eee:finlet:v:19:y:2016:i:c:p:241-246
    DOI: 10.1016/j.frl.2016.08.008
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S154461231630143X
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.frl.2016.08.008?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Victor DeMiguel & Lorenzo Garlappi & Raman Uppal, 2009. "Optimal Versus Naive Diversification: How Inefficient is the 1-N Portfolio Strategy?," Review of Financial Studies, Society for Financial Studies, vol. 22(5), pages 1915-1953, May.
    2. Kim, Jang Ho & Kim, Woo Chang & Fabozzi, Frank J., 2013. "Composition of robust equity portfolios," Finance Research Letters, Elsevier, vol. 10(2), pages 72-81.
    3. Guy V. G. Stevens, 1998. "On the Inverse of the Covariance Matrix in Portfolio Analysis," Journal of Finance, American Finance Association, vol. 53(5), pages 1821-1827, October.
    4. Maillet, Bertrand & Tokpavi, Sessi & Vaucher, Benoit, 2015. "Global minimum variance portfolio optimisation under some model risk: A robust regression-based approach," European Journal of Operational Research, Elsevier, vol. 244(1), pages 289-299.
    5. Kim, Jang Ho & Kim, Woo Chang & Fabozzi, Frank J., 2016. "Portfolio selection with conservative short-selling," Finance Research Letters, Elsevier, vol. 18(C), pages 363-369.
    6. repec:dau:papers:123456789/14735 is not listed on IDEAS
    7. Gabriel Frahm, 2010. "Linear statistical inference for global and local minimum variance portfolios," Statistical Papers, Springer, vol. 51(4), pages 789-812, December.
    8. Das, Sanjiv & Markowitz, Harry & Scheid, Jonathan & Statman, Meir, 2010. "Portfolio Optimization with Mental Accounts," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 45(2), pages 311-334, April.
    9. Fu, Chengbo & Jacoby, Gady & Wang, Yan, 2015. "Investor sentiment and portfolio selection," Finance Research Letters, Elsevier, vol. 15(C), pages 266-273.
    10. Anderson, Ronald W & Danthine, Jean-Pierre, 1981. "Cross Hedging," Journal of Political Economy, University of Chicago Press, vol. 89(6), pages 1182-1196, December.
    11. Alexander Kempf & Christoph Memmel, 2006. "Estimating the global Minimum Variance Portfolio," Schmalenbach Business Review (sbr), LMU Munich School of Management, vol. 58(4), pages 332-348, October.
    12. Bertrand Maillet & Sessi Tokpavi & Benoît Vaucher, 2015. "Global minimum variance portfolio optimisation under some model risk : A robust regression-based approach," Post-Print hal-02312329, HAL.
    13. Scherer, Bernd, 2011. "A note on the returns from minimum variance investing," Journal of Empirical Finance, Elsevier, vol. 18(4), pages 652-660, September.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Dai, Zhifeng & Wen, Fenghua, 2018. "Some improved sparse and stable portfolio optimization problems," Finance Research Letters, Elsevier, vol. 27(C), pages 46-52.
    2. Bednarek, Ziemowit & Patel, Pratish, 2018. "Understanding the outperformance of the minimum variance portfolio," Finance Research Letters, Elsevier, vol. 24(C), pages 175-178.
    3. Chiu, Wan-Yi, 2022. "Stepwise expanding the frontier one asset at a time," Finance Research Letters, Elsevier, vol. 46(PA).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ruili Sun & Tiefeng Ma & Shuangzhe Liu & Milind Sathye, 2019. "Improved Covariance Matrix Estimation for Portfolio Risk Measurement: A Review," JRFM, MDPI, vol. 12(1), pages 1-34, March.
    2. Philippe Bertrand & Vincent Lapointe, 2018. "Risk-based strategies: the social responsibility of investment universes does matter," Annals of Operations Research, Springer, vol. 262(2), pages 413-429, March.
    3. Fabrizio Cipollini & Giampiero Gallo & Alessandro Palandri, 2020. "A Dynamic Conditional Approach to Portfolio Weights Forecasting," Econometrics Working Papers Archive 2020_06, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    4. Alireza Ghahtarani & Ahmed Saif & Alireza Ghasemi, 2022. "Robust portfolio selection problems: a comprehensive review," Operational Research, Springer, vol. 22(4), pages 3203-3264, September.
    5. Sandra Caçador & Joana Matos Dias & Pedro Godinho, 2020. "Global minimum variance portfolios under uncertainty: a robust optimization approach," Journal of Global Optimization, Springer, vol. 76(2), pages 267-293, February.
    6. Alireza Ghahtarani & Ahmed Saif & Alireza Ghasemi, 2021. "Robust Portfolio Selection Problems: A Comprehensive Review," Papers 2103.13806, arXiv.org, revised Jan 2022.
    7. Bonaccolto, Giovanni & Caporin, Massimiliano & Maillet, Bertrand B., 2022. "Dynamic large financial networks via conditional expected shortfalls," European Journal of Operational Research, Elsevier, vol. 298(1), pages 322-336.
    8. Xidonas, Panos & Hassapis, Christis & Soulis, John & Samitas, Aristeidis, 2017. "Robust minimum variance portfolio optimization modelling under scenario uncertainty," Economic Modelling, Elsevier, vol. 64(C), pages 60-71.
    9. Thomas Conlon & John Cotter & Iason Kynigakis, 2021. "Machine Learning and Factor-Based Portfolio Optimization," Papers 2107.13866, arXiv.org.
    10. Mazin A.M. Al Janabi, 2021. "Is optimum always optimal? A revisit of the mean‐variance method under nonlinear measures of dependence and non‐normal liquidity constraints," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(3), pages 387-415, April.
    11. Al Janabi, Mazin A.M. & Arreola Hernandez, Jose & Berger, Theo & Nguyen, Duc Khuong, 2017. "Multivariate dependence and portfolio optimization algorithms under illiquid market scenarios," European Journal of Operational Research, Elsevier, vol. 259(3), pages 1121-1131.
    12. Panos Xidonas & Ralph Steuer & Christis Hassapis, 2020. "Robust portfolio optimization: a categorized bibliographic review," Annals of Operations Research, Springer, vol. 292(1), pages 533-552, September.
    13. Theo Berger & Ramazan Gençay, 2020. "Short‐run wavelet‐based covariance regimes for applied portfolio management," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(4), pages 642-660, July.
    14. Carroll, Rachael & Conlon, Thomas & Cotter, John & Salvador, Enrique, 2017. "Asset allocation with correlation: A composite trade-off," European Journal of Operational Research, Elsevier, vol. 262(3), pages 1164-1180.
    15. Frahm, Gabriel & Wiechers, Christof, 2011. "On the diversification of portfolios of risky assets," Discussion Papers in Econometrics and Statistics 2/11, University of Cologne, Institute of Econometrics and Statistics.
    16. Francisco Fernández-Navarro & Luisa Martínez-Nieto & Mariano Carbonero-Ruz & Teresa Montero-Romero, 2021. "Mean Squared Variance Portfolio: A Mixed-Integer Linear Programming Formulation," Mathematics, MDPI, vol. 9(3), pages 1-13, January.
    17. Hongxin Zhao & Lingchen Kong & Hou-Duo Qi, 2021. "Optimal portfolio selections via $$\ell _{1, 2}$$ ℓ 1 , 2 -norm regularization," Computational Optimization and Applications, Springer, vol. 80(3), pages 853-881, December.
    18. Ding, Wenliang & Shu, Lianjie & Gu, Xinhua, 2023. "A robust Glasso approach to portfolio selection in high dimensions," Journal of Empirical Finance, Elsevier, vol. 70(C), pages 22-37.
    19. Chiu, Wan-Yi, 2022. "Another look at portfolio optimization with mental accounts," Applied Mathematics and Computation, Elsevier, vol. 419(C).
    20. Bodnar, Taras & Parolya, Nestor & Schmid, Wolfgang, 2018. "Estimation of the global minimum variance portfolio in high dimensions," European Journal of Operational Research, Elsevier, vol. 266(1), pages 371-390.

    More about this item

    Keywords

    Global minimum variance portfolio; Inverse covariance matrix; Regression hedge; Modified information ratio;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:finlet:v:19:y:2016:i:c:p:241-246. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/frl .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.