IDEAS home Printed from https://ideas.repec.org/a/gam/jjrfmx/v16y2023i8p369-d1215353.html
   My bibliography  Save this article

Tensors Associated with Mean Quadratic Differences Explaining the Riskiness of Portfolios of Financial Assets

Author

Listed:
  • Pierpaolo Angelini

    (Dipartimento di Scienze Statistiche, Università La Sapienza, 00185 Rome, Italy)

  • Fabrizio Maturo

    (Faculty of Economics, Universitas Mercatorum, 00186 Rome, Italy)

Abstract

Bound choices such as portfolio choices are studied in an aggregate fashion using an extension of the notion of barycenter of masses. This paper answers the question of whether such an extension is a natural fashion of studying bound choices or not. Given n risky assets, the question of why it is appropriate to treat only two risky assets at a time inside the budget set of the decision-maker is handled in this paper. Two risky assets are two goods. They are two marginal goods. The question of why they always give rise to a joint good inside the budget set of the decision-maker is addressed by this research work. A single risky asset is viewed as a double one using four nonparametric joint distributions of probability. The variability of a joint distribution of probability always depends on the state of information and knowledge associated with a given decision-maker. For this reason, two variability tensors are defined to identify the riskiness of the same risky asset. A multilinear version of the Sharpe ratio is shown. It is based on tensors. After computing the expected return on an n -risky asset portfolio, its riskiness is obtained using mean quadratic differences developed through tensors.

Suggested Citation

  • Pierpaolo Angelini & Fabrizio Maturo, 2023. "Tensors Associated with Mean Quadratic Differences Explaining the Riskiness of Portfolios of Financial Assets," JRFM, MDPI, vol. 16(8), pages 1-25, August.
  • Handle: RePEc:gam:jjrfmx:v:16:y:2023:i:8:p:369-:d:1215353
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1911-8074/16/8/369/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1911-8074/16/8/369/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Mohammed Abdellaoui & Han Bleichrodt & Olivier l'Haridon & Corina Paraschiv, 2013. "Is There One Unifying Concept of Utility?An Experimental Comparison of Utility Under Risk and Utility Over Time," Management Science, INFORMS, vol. 59(9), pages 2153-2169, September.
    2. Yoram Halevy & Dotan Persitz & Lanny Zrill, 2018. "Parametric Recoverability of Preferences," Journal of Political Economy, University of Chicago Press, vol. 126(4), pages 1558-1593.
    3. Federico Echenique, 2020. "New Developments in Revealed Preference Theory: Decisions Under Risk, Uncertainty, and Intertemporal Choice," Annual Review of Economics, Annual Reviews, vol. 12(1), pages 299-316, August.
    4. Carina Gerstenberger & Daniel Vogel, 2015. "On the efficiency of Gini’s mean difference," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 24(4), pages 569-596, November.
    5. R. Rockafellar & Stan Uryasev & Michael Zabarankin, 2006. "Generalized deviations in risk analysis," Finance and Stochastics, Springer, vol. 10(1), pages 51-74, January.
    6. Haim Shalit & Shlomo Yitzhaki, 2005. "The Mean‐Gini Efficient Portfolio Frontier," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 28(1), pages 59-75, March.
    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. Pierpaolo Angelini, 2023. "Probability Spaces Identifying Ordinal and Cardinal Utilities in Problems of an Economic Nature: New Issues and Perspectives," Mathematics, MDPI, vol. 11(20), pages 1-22, October.

    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. Pierpaolo Angelini & Fabrizio Maturo, 2022. "The consumer’s demand functions defined to study contingent consumption plans," Quality & Quantity: International Journal of Methodology, Springer, vol. 56(3), pages 1159-1175, June.
    2. Pawe{l} Dziewulski & Joshua Lanier & John K. -H. Quah, 2024. "Revealed preference and revealed preference cycles: a survey," Papers 2405.08459, arXiv.org.
    3. Maria-Teresa Bosch-Badia & Joan Montllor-Serrats & Maria-Antonia Tarrazon-Rodon, 2017. "Analysing assets’ performance inside a portfolio: From crossed beta to the net risk premium ratio," Cogent Economics & Finance, Taylor & Francis Journals, vol. 5(1), pages 1270251-127, January.
    4. Pierpaolo Angelini, 2024. "Invariance of the Mathematical Expectation of a Random Quantity and Its Consequences," Risks, MDPI, vol. 12(1), pages 1-17, January.
    5. Fabrizio Maturo & Pierpaolo Angelini, 2023. "Aggregate Bound Choices about Random and Nonrandom Goods Studied via a Nonlinear Analysis," Mathematics, MDPI, vol. 11(11), pages 1-30, May.
    6. Pierpaolo Angelini & Fabrizio Maturo, 2020. "Non-Parametric Probability Distributions Embedded Inside of a Linear Space Provided with a Quadratic Metric," Mathematics, MDPI, vol. 8(11), pages 1-17, October.
    7. Stephen L. Cheung & Agnieszka Tymula & Xueting Wang, 2022. "Present bias for monetary and dietary rewards," Experimental Economics, Springer;Economic Science Association, vol. 25(4), pages 1202-1233, September.
    8. Dimitrios G. Konstantinides & Georgios C. Zachos, 2019. "Exhibiting Abnormal Returns Under a Risk Averse Strategy," Methodology and Computing in Applied Probability, Springer, vol. 21(2), pages 551-566, June.
    9. Björn Häckel, 2010. "Risikoadjustierte Wertbeiträge zur ex ante Entscheidungsunterstützung: Ein axiomatischer Ansatz," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 21(1), pages 81-108, June.
    10. Migliavacca, Milena & Goodell, John W. & Paltrinieri, Andrea, 2023. "A bibliometric review of portfolio diversification literature," International Review of Financial Analysis, Elsevier, vol. 90(C).
    11. Jun-ya Gotoh & Michael Jong Kim & Andrew E. B. Lim, 2020. "Worst-case sensitivity," Papers 2010.10794, arXiv.org.
    12. Thai Chuong, 2013. "Newton-like methods for efficient solutions in vector optimization," Computational Optimization and Applications, Springer, vol. 54(3), pages 495-516, April.
    13. Johannes König & Carsten Schröder, 2018. "Inequality-minimization with a given public budget," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 16(4), pages 607-629, December.
    14. Paolo Giovanni Piacquadio, 2017. "A Fairness Justification of Utilitarianism," Econometrica, Econometric Society, vol. 85, pages 1261-1276, July.
    15. Balbás, Alejandro & Balbás, Beatriz & Heras, Antonio, 2011. "Stable solutions for optimal reinsurance problems involving risk measures," European Journal of Operational Research, Elsevier, vol. 214(3), pages 796-804, November.
    16. Pierpaolo Angelini, 2024. "Financial Decisions Based on Zero-Sum Games: New Conceptual and Mathematical Outcomes," IJFS, MDPI, vol. 12(2), pages 1-28, June.
    17. Patrick Krieger & Carsten Lausberg, 2021. "Entscheidungen, Entscheidungsfindung und Entscheidungsunterstützung in der Immobilienwirtschaft: Eine systematische Literaturübersicht [Decisions, decision-making and decisions support systems in r," Zeitschrift für Immobilienökonomie (German Journal of Real Estate Research), Springer;Gesellschaft für Immobilienwirtschaftliche Forschung e. V., vol. 7(1), pages 1-33, April.
    18. Christopher P. Chambers & Georgios Gerasimou, 2023. "Non-diversified portfolios with subjective expected utility," Papers 2304.08059, arXiv.org, revised Oct 2024.
    19. Jose Apesteguia & Miguel A. Ballester, 2015. "A Measure of Rationality and Welfare," Journal of Political Economy, University of Chicago Press, vol. 123(6), pages 1278-1310.
    20. Branda, Martin, 2013. "Diversification-consistent data envelopment analysis with general deviation measures," European Journal of Operational Research, Elsevier, vol. 226(3), pages 626-635.

    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:jjrfmx:v:16:y:2023:i:8:p:369-:d:1215353. 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.