IDEAS home Printed from https://ideas.repec.org/a/imx/journl/v20y2025i2a6.html

Evaluación de la consistencia de las betas en el modelo de CAPM mediante un análisis de bootstraps con memoria

Author

Listed:
  • Josué Alan Cantú Esquivel

    (Instituto Politécnico Nacional, México)

  • Salvador Cruz Aké

    (Instituto Politécnico Nacional, México)

  • Ana Lorena Jiménez Preciado

    (Instituto Politécnico Nacional, México)

Abstract

Esta investigación evalúa la estabilidad de la beta del CAPM en diez activos financieros mediante metodos de series de tiempo complementando el análisis con técnicas de bootstrapping, proponiendo incorporar un método basado en percentiles para un cálculo más realista de la sensibilidad de las acciones a oscilaciones sistemáticas del mercado. Se destaca la importancia de considerar las inconsistencias de la beta a lo largo del tiempo para evitar errores en la toma de decisiones y la gestión de riesgos. Los activos analizados son DVN, OXY, ON, FSLR, MRO, ENPH, APA, COP, STLD y MPC. Los resultados proporcionan evidencia empírica de la dinámica cambiante en la relación riesgo-rendimiento y su influencia en las estrategias de inversión. Finalmente, se propone una metodología de valoración alternativa que captura mejor la presencia de valores extremos en el mercado financiero.

Suggested Citation

  • Josué Alan Cantú Esquivel & Salvador Cruz Aké & Ana Lorena Jiménez Preciado, 2025. "Evaluación de la consistencia de las betas en el modelo de CAPM mediante un análisis de bootstraps con memoria," Remef - Revista Mexicana de Economía y Finanzas Nueva Época REMEF (The Mexican Journal of Economics and Finance), Instituto Mexicano de Ejecutivos de Finanzas, IMEF, vol. 20(2), pages 1-21, Abril - J.
    • Handle: RePEc:imx:journl:v:20:y:2025:i:2:a:6
    as

    Download full text from publisher

    File URL: https://www.remef.org.mx/index.php/remef/article/view/1192
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Bali, Turan G. & Demirtas, K. Ozgur & Levy, Haim, 2009. "Is There an Intertemporal Relation between Downside Risk and Expected Returns?," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 44(4), pages 883-909, August.
    2. Malcolm Baker & Brendan Bradley & Jeffrey Wurgler, 2011. "Benchmarks as Limits to Arbitrage: Understanding the Low-Volatility Anomaly," Financial Analysts Journal, Taylor & Francis Journals, vol. 67(1), pages 40-54, January.
    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. Chiang, Thomas C., 2019. "Empirical analysis of intertemporal relations between downside risks and expected returns—Evidence from Asian markets," Research in International Business and Finance, Elsevier, vol. 47(C), pages 264-278.
    2. Chen, Jian & Jiang, Fuwei & Liu, Yangshu & Tu, Jun, 2017. "International volatility risk and Chinese stock return predictability," Journal of International Money and Finance, Elsevier, vol. 70(C), pages 183-203.
    3. Chan, Kalok & Yang, Jian & Zhou, Yinggang, 2018. "Conditional co-skewness and safe-haven currencies: A regime switching approach," Journal of Empirical Finance, Elsevier, vol. 48(C), pages 58-80.
    4. Arısoy, Yakup Eser & Altay-Salih, Aslıhan & Akdeniz, Levent, 2015. "Aggregate volatility expectations and threshold CAPM," The North American Journal of Economics and Finance, Elsevier, vol. 34(C), pages 231-253.
    5. Yuming Li, 2017. "Risks and rewards for momentum and reversal portfolios," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 31(3), pages 289-315, August.
    6. Long, Huaigang & Zhu, Yanjian & Chen, Lifang & Jiang, Yuexiang, 2019. "Tail risk and expected stock returns around the world," Pacific-Basin Finance Journal, Elsevier, vol. 56(C), pages 162-178.
    7. Dai, Yingtong & Harris, Richard D.F., 2023. "Average tail risk and aggregate stock returns," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 82(C).
    8. Yao, Haixiang & Huang, Jinbo & Li, Yong & Humphrey, Jacquelyn E., 2021. "A general approach to smooth and convex portfolio optimization using lower partial moments," Journal of Banking & Finance, Elsevier, vol. 129(C).
    9. Malakhov, Alexey & Riley, Timothy B. & Yan, Qing, 2024. "Do hedge funds bet against beta?," International Review of Economics & Finance, Elsevier, vol. 93(PA), pages 1507-1525.
    10. Shiyang Huang & Xin Liu & Dong Lou & Christopher Polk, 2024. "The Booms and Busts of Beta Arbitrage," Management Science, INFORMS, vol. 70(8), pages 5367-5385, August.
    11. Wu, Shue-Jen, 2023. "The role of the past long-run oil price changes in stock market," International Review of Economics & Finance, Elsevier, vol. 84(C), pages 274-291.
    12. Maik Dierkes & Sebastian Schroen, 2023. "Betting against sentiment? Seemingly unrelated anomalies and the low‐risk effect," Review of Financial Economics, John Wiley & Sons, vol. 41(2), pages 152-176, April.
    13. Agbeyegbe, Terence D., 2015. "An inverted U-shaped crude oil price return-implied volatility relationship," Review of Financial Economics, Elsevier, vol. 27(C), pages 28-45.
    14. Nektarios Aslanidis & Charlotte Christiansen & Christos S. Savva, 2021. "Quantile Risk–Return Trade-Off," JRFM, MDPI, vol. 14(6), pages 1-14, June.
    15. Bradrania, Reza & Veron, Jose Francisco & Wu, Winston, 2026. "Investor behavior and the beta anomaly: Who benefits from betting against beta?," Economics Letters, Elsevier, vol. 258(C).
    16. Sun, Yufei & Aw, Grace & Teo, Kok Lay & Zhu, Yanjian & Wang, Xiangyu, 2016. "Multi-period portfolio optimization under probabilistic risk measure," Finance Research Letters, Elsevier, vol. 18(C), pages 60-66.
    17. Ahmed, Walid M.A., 2021. "Stock market reactions to upside and downside volatility of Bitcoin: A quantile analysis," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
    18. Xu, Xia, 2025. "Market neutrality and beta crashes," Journal of Empirical Finance, Elsevier, vol. 80(C).
    19. Shim Jeungbo & Lee Seung-Hwan, 2017. "Dependency between Risks and the Insurer’s Economic Capital: A Copula-based GARCH Model," Asia-Pacific Journal of Risk and Insurance, De Gruyter, vol. 11(1), pages 1-29, January.
    20. Pantisa Pavabutr & Bin Zhao, 2024. "Do retail investors gamble more during lockdown?," International Review of Finance, International Review of Finance Ltd., vol. 24(4), pages 572-603, December.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    JEL classification:

    • C16 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Econometric and Statistical Methods; Specific Distributions
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation: Models and Applications
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

    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:imx:journl:v:20:y:2025:i:2:a:6. 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: Ricardo Mendoza (email available below). General contact details of provider: https://www.remef.org.mx/index.php/remef/index .

    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.