IDEAS home Printed from https://ideas.repec.org/a/gam/jrisks/v12y2024i6p88-d1401095.html
   My bibliography  Save this article

Some Results on Bivariate Squared Maximum Sharpe Ratio

Author

Listed:
  • Samane Al-sadat Mousavi

    (Department of Statistics, College of Mathematics, Yazd University, Yazd P.O. Box 89195-741, Iran)

  • Ali Dolati

    (Department of Statistics, College of Mathematics, Yazd University, Yazd P.O. Box 89195-741, Iran)

  • Ali Dastbaravarde

    (Department of Statistics, College of Mathematics, Yazd University, Yazd P.O. Box 89195-741, Iran)

Abstract

The Sharpe ratio is a widely used tool for assessing investment strategy performance. An essential part of investing involves creating an appropriate portfolio by determining the optimal weights for desired assets. Before constructing a portfolio, selecting a set of investment opportunities is crucial. In the absence of a risk-free asset, investment opportunities can be identified based on the Sharpe ratios of risky assets and their correlation. The maximum squared Sharpe ratio serves as a useful metric that summarizes the performance of an investment opportunity in a single value, considering the Sharpe ratios of assets and their correlation coefficients. However, the assumption of a normal distribution in asset returns, as implied by the Sharpe ratio and related metrics, may not always hold in practice. Non-normal returns with a non-linear dependence structure can result in an overestimation or underestimation of these metrics. Copula functions are commonly utilized to address non-normal dependence structures. This study examines the impact of asset dependence on the squared maximum Sharpe ratio using copulas and proposes a copula-based approach to tackle the estimation issue. The performance of the proposed estimator is illustrated through simulation and real-data analysis.

Suggested Citation

  • Samane Al-sadat Mousavi & Ali Dolati & Ali Dastbaravarde, 2024. "Some Results on Bivariate Squared Maximum Sharpe Ratio," Risks, MDPI, vol. 12(6), pages 1-17, May.
  • Handle: RePEc:gam:jrisks:v:12:y:2024:i:6:p:88-:d:1401095
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-9091/12/6/88/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2227-9091/12/6/88/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Barillas, Francisco & Kan, Raymond & Robotti, Cesare & Shanken, Jay, 2020. "Model Comparison with Sharpe Ratios," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 55(6), pages 1840-1874, September.
    2. Genest, Christian & Rémillard, Bruno & Beaudoin, David, 2009. "Goodness-of-fit tests for copulas: A review and a power study," Insurance: Mathematics and Economics, Elsevier, vol. 44(2), pages 199-213, April.
    3. Dowd, Kevin, 2000. "Adjusting for risk:: An improved Sharpe ratio," International Review of Economics & Finance, Elsevier, vol. 9(3), pages 209-222, July.
    Full references (including those not matched with items on IDEAS)

    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. Jie Huang & Haiming Zhou & Nader Ebrahimi, 2022. "Bayesian Bivariate Cure Rate Models Using Copula Functions," International Journal of Statistics and Probability, Canadian Center of Science and Education, vol. 11(3), pages 1-9, May.
    2. Daniel Puig & Oswaldo Morales-Nápoles & Fatemeh Bakhtiari & Gissela Landa, 2017. "The accountability imperative for quantifiying the uncertainty of emission forecasts : evidence from Mexico," Working Papers hal-03389325, HAL.
    3. Richard C. Bradley & Richard A. Davis & Dimitris N. Politis, 2021. "Preface to the Murray Rosenblatt memorial special issue of JTSA," Journal of Time Series Analysis, Wiley Blackwell, vol. 42(5-6), pages 495-498, September.
    4. Bedoui, Rihab & Braiek, Sana & Guesmi, Khaled & Chevallier, Julien, 2019. "On the conditional dependence structure between oil, gold and USD exchange rates: Nested copula based GJR-GARCH model," Energy Economics, Elsevier, vol. 80(C), pages 876-889.
    5. Gaißer, Sandra & Schmid, Friedrich, 2010. "On testing equality of pairwise rank correlations in a multivariate random vector," Journal of Multivariate Analysis, Elsevier, vol. 101(10), pages 2598-2615, November.
    6. Ali, Fahad & Ülkü, Numan, 2021. "Quest for a parsimonious factor model in the wake of quality-minus-junk, misvaluation and Fama-French-six factors," Finance Research Letters, Elsevier, vol. 41(C).
    7. Jesse M. Keenan & Anurag Gumber, 2019. "California climate adaptation trust fund: exploring the leveraging of cap-and-trade proceeds," Environment Systems and Decisions, Springer, vol. 39(4), pages 454-465, December.
    8. Righi, Marcelo Brutti & Ceretta, Paulo Sergio, 2013. "Estimating non-linear serial and cross-interdependence between financial assets," Journal of Banking & Finance, Elsevier, vol. 37(3), pages 837-846.
    9. Okhrin, Ostap & Ristig, Alexander, 2014. "Hierarchical Archimedean Copulae: The HAC Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 58(i04).
    10. Wu, Shaomin, 2014. "Construction of asymmetric copulas and its application in two-dimensional reliability modelling," European Journal of Operational Research, Elsevier, vol. 238(2), pages 476-485.
    11. Katarzyna Baran-Gurgul, 2022. "The Risk of Extreme Streamflow Drought in the Polish Carpathians—A Two-Dimensional Approach," IJERPH, MDPI, vol. 19(21), pages 1-27, October.
    12. Massimiliano Caporin & Grégory M. Jannin & Francesco Lisi & Bertrand B. Maillet, 2014. "A Survey On The Four Families Of Performance Measures," Journal of Economic Surveys, Wiley Blackwell, vol. 28(5), pages 917-942, December.
    13. Luca Riccetti, 2013. "A copula–GARCH model for macro asset allocation of a portfolio with commodities," Empirical Economics, Springer, vol. 44(3), pages 1315-1336, June.
    14. Daniel Puig & Oswaldo Morales-Nápoles & Fatemeh Bakhtiari & Gissela Landa, 2017. "The accountability imperative for quantifiying the uncertainty of emission forecasts : evidence from Mexico," SciencePo Working papers Main hal-03389325, HAL.
    15. Michał Adam & Piotr Bańbuła & Michał Markun, 2013. "Dependence and contagion between asset prices in Poland and abroad. A copula approach," NBP Working Papers 169, Narodowy Bank Polski.
    16. Marc Gronwald & Janina Ketterer & Stefan Trück, 2011. "The Dependence Structure between Carbon Emission Allowances and Financial Markets - A Copula Analysis," CESifo Working Paper Series 3418, CESifo.
    17. Ahmed, Osama & Serra, Teresa, 2015. "Evaluate the economic consequences of revenue insurance programs in Spain using copula models. The case of orange and apple," 2015 Conference, August 9-14, 2015, Milan, Italy 212522, International Association of Agricultural Economists.
    18. Dominik Paprotny, 2021. "Convergence Between Developed and Developing Countries: A Centennial Perspective," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 153(1), pages 193-225, January.
    19. Wanling Huang & Artem Prokhorov, 2014. "A Goodness-of-fit Test for Copulas," Econometric Reviews, Taylor & Francis Journals, vol. 33(7), pages 751-771, October.
    20. Adam Zaremba & Jacob Koby Shemer, 2018. "Price-Based Investment Strategies," Springer Books, Springer, number 978-3-319-91530-2, October.

    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:gam:jrisks:v:12:y:2024:i:6:p:88-:d:1401095. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.