IDEAS home Printed from https://ideas.repec.org/a/inm/ormnsc/v18y1971i2pb1-b13.html
   My bibliography  Save this article

Mean-Absolute-Deviation Characteristic Lines for Securities and Portfolios

Author

Listed:
  • William F. Sharpe

    (Stanford University)

Abstract

The characteristic line of a security or portfolio relates its rate of return to that of a "market portfolio." Several investigators have suggested the desirability of obtaining such a line by minimizing the sum of the absolute deviations rather than the sum of the squared deviations around the line. This paper presents a new algorithm for such a regression problem. The procedure has at least two virtues: it is simple, and it produces useful information as a byproduct of the solution process. Empirical evidence is also presented on the differences in the values obtained with the two regression methods (i.e., mean-absolute-deviation and least-squares). The differences appear to be relatively slight, at least for well-diversified portfolios.

Suggested Citation

  • William F. Sharpe, 1971. "Mean-Absolute-Deviation Characteristic Lines for Securities and Portfolios," Management Science, INFORMS, vol. 18(2), pages 1-13, October.
    • Handle: RePEc:inm:ormnsc:v:18:y:1971:i:2:p:b1-b13
    DOI: 10.1287/mnsc.18.2.B1
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/mnsc.18.2.B1
    Download Restriction: no
    File URL: https://libkey.io/10.1287/mnsc.18.2.B1?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
    ---><---

    Citations

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


    Cited by:

    1. Joe Hirschberg & Jenny Lye, 2021. "Estimating risk premiums for regulated firms when accounting for reference-day variation and high-order moments of return volatility," Environment Systems and Decisions, Springer, vol. 41(3), pages 455-467, September.
    2. Fima Klebaner & Zinoviy Landsman & Udi Makov & Jing Yao, 2017. "Optimal portfolios with downside risk," Quantitative Finance, Taylor & Francis Journals, vol. 17(3), pages 315-325, March.
    3. Wojtek Michalowski & Włodzimierz Ogryczak, 2001. "Extending the MAD portfolio optimization model to incorporate downside risk aversion," Naval Research Logistics (NRL), John Wiley & Sons, vol. 48(3), pages 185-200, April.
    4. Giloni, Avi & Simonoff, Jeffrey S. & Sengupta, Bhaskar, 2006. "Robust weighted LAD regression," Computational Statistics & Data Analysis, Elsevier, vol. 50(11), pages 3124-3140, July.
    5. Richard W. Cottle, 2017. "On “Pre-historic” Linear Programming and the Figure of the Earth," Journal of Optimization Theory and Applications, Springer, vol. 175(1), pages 255-277, October.
    6. Trzpiot Grażyna, 2012. "Selected Robust Methods for Camp Model Estimation," Folia Oeconomica Stetinensia, Sciendo, vol. 12(2), pages 58-71, December.
    7. Sehgal, Ruchika & Sharma, Amita & Mansini, Renata, 2023. "Worst-case analysis of Omega-VaR ratio optimization model," Omega, Elsevier, vol. 114(C).
    8. Renata Mansini & Włodzimierz Ogryczak & M. Speranza, 2007. "Conditional value at risk and related linear programming models for portfolio optimization," Annals of Operations Research, Springer, vol. 152(1), pages 227-256, July.
    9. R. Douglas Martin & Daniel Z. Xia, 2022. "Efficient bias robust regression for time series factor models," Journal of Asset Management, Palgrave Macmillan, vol. 23(3), pages 215-234, May.
    10. Pan, Yubin & Hong, Rongjing & Chen, Jie & Wu, Weiwei, 2020. "A hybrid DBN-SOM-PF-based prognostic approach of remaining useful life for wind turbine gearbox," Renewable Energy, Elsevier, vol. 152(C), pages 138-154.
    11. Mansini, Renata & Ogryczak, Wlodzimierz & Speranza, M. Grazia, 2014. "Twenty years of linear programming based portfolio optimization," European Journal of Operational Research, Elsevier, vol. 234(2), pages 518-535.
    12. Juan Carlos Gutierrez Betancur, 2017. "Robust Estimation of beta and the hedging ratio in Stock Index Futures In the Integrated Latin American Market," Revista Ecos de Economía, Universidad EAFIT, vol. 21(44), pages 37-71, June.
    13. Garud Iyengar & Alfred Ma, 2013. "Fast gradient descent method for Mean-CVaR optimization," Annals of Operations Research, Springer, vol. 205(1), pages 203-212, May.

    More about this item

    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:inm:ormnsc:v:18:y:1971:i:2:p:b1-b13. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    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.