Optimización ponderada por appraisal del índice Dow Jones industrial average mediante el modelo Treynor-Black
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https://doi.org/10.18381/eq.v23i2.7400Resumen
Objetivo: Evaluar si el desempeño histórico a]g permite optimizar la ponderación dinámica de los componentes del Dow Jones Industrial Average (DJIA)mediante el modelo Treynor-Black y mejorar el desempeño frente al índice.Metodología: Para los activos que integran el DJIA en cada periodo, se estima α con CAPM y modelos multifactoriales para construir un portafolio activo ponderado por el ratio appraisal (a/varianza idiosincrática) mediante ventanas móviles retrospectivas y sin apalancamiento. Se incorpora una validación temporal cronológica 80%-20% y un alpha de Jensen progresivo con ventana móvil de 252 días.Resultados: El modelo basado en CAPM alcanza un rendimiento promedio anual cercano al 13.8% frente a 7.8% del índice, con una probabilidad aproximada de 66.9% de superarlo y mejor relación riESGo-rendimiento. La validación temporal 80%-20% mantiene la ventaja fuera de muestra: en el bloque OOS, el portafolio registra una media de 13.7% frente a 10.3% del DJIA y un alpha de Jensen progresivo promedio de 0.0470.Limitaciones: Los resultados dependen de la estabilidad de a de cambios en régimen de mercado y de la sensibilidad en la estimación del riESGo específico.Originalidad: Integra la asignación por desempeño (appraisal), preservando comparabilidad temporal con el DJIA.Conclusiones: La ponderación basada por desempeño (appraisal) mejora el desempeño relativo cuando las señales son estadísticamente robustas.Descargas
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Ali, F., Khurram, M. U., and Jiang, Y. (2021). The five-factor asset pricing model tests and profitability and investment premiums: evidence from Pakistan. Emerging Markets Finance and Trade, 57(9), 2651-2673. DOI: https://doi.org/10.1080/1540496X.2019.1650738
Amenc, N., and Le Sourd, V. (2005). Portfolio theory and performance analysis. New York: Wiley.
Arisena, A., Noviyanti, L., and Achmad Zanbar, S. (2018). Portfolio return using Black Litterman single view model with ARMA GARCH and Treynor-Black model. Journal of Physics: Conference Series, 974(1), 012023. DOI: https://doi.org/10.1088/1742-6596/974/1/012023
Benhamou, E., and Guez, B. (2021). Computation of the marginal contribution of Sharpe ratio and other performance ratios [Preprint]. hal-03189299v2
Berg, F., Lo, A. W., Rigobon, R., Singh, M., and Zhang, R. (2023). Quantifying the returns of ESG investing: an empirical analysis with six ESG metrics. MIT Sloan Research Paper (6930-23). DOI: https://doi.org/10.2139/ssrn.4367367
Brands, S., Brown, S. J., and Gallagher, D. R. (2005). Portfolio concentration and investment manager performance. International Review of Finance, 5(3-4), 149-174. DOI: https://doi.org/10.1111/j.1468-2443.2006.00054.x
Busse, J. A., and Irvine, P. J. (2006). Bayesian alphas and mutual fund persistence. The Journal of Finance, 61(5), 2251-2288. DOI: https://doi.org/10.1111/j.1540-6261.2006.01057.x
Campbell, R. (2021). noTBoxPlot (Versión 1.3.1) [Software de computación]. GitHub. https://github.com/raacampbell/noTBoxPlot
Ceballos Bejarano, F. E., Hihuaña Hallasi, J. C., and Viza Huayllaso, J. C. (2025). Optimización de carteras de inversión mediante programación cuadrática: un enfoque desde el modelo de Markowitz. Revista Minerva, 6(esp), 7-11. DOI: https://doi.org/10.47460/minerva.v6isp.200
Cuthbertson, K., Nitzsche, D., and O’Sullivan, N. (2010). Mutual fund performance: measurement and evidence Financial Markets, Institutions & Instruments, 19(2), 95-187. DOI: https://doi.org/10.1111/j.1468-0416.2010.00156.x
De Roon, F. A., Nijman, T. E., & Ter Horst, J. R. (2000). Evaluating style analysis [Working paper]. Tilburg University. https://repository.tilburguniversity.edu/bitstreams/6c849ff3-085d-43a6-a976-827334eb7e41/download
Fama, E. F., and French, K. R. (2015). A five-factor asset pricing model. Journal of Financial Economics, 116(1), 1-22. DOI: https://doi.org/10.1016/j.jfineco.2014.10.010
French, C. W. (2003). The Treynor capital asset pricing model. Journal of Investment Management, 1(2), 60-72. https://finance.martinsewell.com/capm/French2003.pdf
Harvey, C. R., and Liu, Y. (2021). Lucky factors. Journal of Financial Economics, 141(2), 413-435. DOI: https://doi.org/10.1016/j.jfineco.2021.04.014
He, Z. (2007). Incorporating alpha uncertainty into portfolio decisions: a Bayesian revisit of the Treynor-Black model. Journal of Asset Management, 8(3), 161-175. DOI: https://doi.org/10.1057/palgrave.jam.2250071
Heinrich, L., Shivarova, A., and Zurek, M. (2021). Factor investing: alpha concentration versus diversification. Journal of Asset Management, 22(6), 464-487. DOI: https://doi.org/10.1057/s41260-021-00226-0
Hunter, D., Kandel, E., Kandel, S., and Wermers, R. (2013). Mutual fund performance evaluation with active peer benchmarks Journal of Financial Economics, 112(1), 1-29. DOI: https://doi.org/10.1016/j.jfineco.2013.12.006
Infanger, G. (2006). Dynamic asset allocation strategies using a stochastic dynamic programming approach. En S. A. Zenios and W. T. Ziemba (Eds.). Handbook of asset and liability management (v. 1, pp. 199-251). Amsterdam: Elsevier.
Jarvis, S., Lawrence, A., and Miao, S. (2009). Dynamic asset allocation techniques. British Actuarial Journal, 15(3), 573-655. DOI: 10.1017/S1357321700005742
Jones, C. S., and Shanken, J. (2005). Mutual fund performance with learning across funds. Journal of Financial Economics, 78(3), 507-552. DOI: https://doi.org/10.1016/j.jfineco.2004.08.009
Kurtti, M. (2020). How many stocks make a diversified portfolio in a continuoustime world? (MS Thesis). University of Oulu, Finland. https://oulurepo.oulu.fi/handle/10024/16938
Lo, A. W. (2008). Where do alphas come from? A new measure of the value of active investment management. Journal of Investment Management, 6(3), 1-39. https://ssrn.com/abstract=1279690
Manap, A., Glorya, R., Rievay, G. S., and Zahra, Y. A. (2024). Evaluating financial performance of investment companies using the Treynor- Black method: an analysis of risk-adjusted returns and portfolio optimization. Journal on Economics, Management and Business Technology, 3(1), 33-40. DOI: https://doi.org/10.35335/jembut.v3i1.244
Nuorlahti, M. (2021). Performance of smart beta exchange traded funds during 2006 2019: evidence from the United States stock markets (Tesis de maestría). Lappeenranta Lahti University of Technology, Finland. https://lutpub.lut.fi/bitstream/handle/10024/162752/Progradu_Nuorlahti_Maiju.pdf?sequence=1&isAllowed=y
Pannu, G. S. (2021). Hedge fund performance with the Treynor-Black model (Honors Thesis No. 330). University of Dayton, Dayton, OH. https://ecommons.udayton.edu/uhp_theses/330
Perold, A. F., and Sharpe, W. F. (1988). Dynamic strategies for asset allocation. Financial Analysts Journal, 44(1), 16-27. DOI: https://doi.org/10.2469/faj.v44.n1.16
Reuss, A., Olivares, P., Seco, L., and Zagst, R. (2016). Risk management and portfolio selection using α-stable regime switching models. Applied Mathematical Sciences, 10(12), 549-582. DOI: https://doi.org/10.12988/ams.2016.512722
Rezaei, M., and Nezamabadi-Pour, H. (2025). A taxonomy of literature reviews and experimental study of deep reinforcement learning in portfolio management. Artificial Intelligence Review, 58(3), 94. DOI: https://doi.org/10.1007/s10462-024-11066-w
Ross, L. (2021). Are characteristic interactions important to the cross-section of expected returns? Social Science Research Network. DOI: https://doi.org/10.2139/ssrn.3862847
Salardini, F., Abdoh Tabrizi, H., Cheetsazan, H., & Abbasian, E. (2020). Performance evaluation of actively managed mutual funds and the puzzle of their acceptance by investors. Journal of Financial Management Perspective, 31, 103–127. http://doi.org/10.52547/jfmp.10.31.103
Singh, A. B., and Tandon, P. (2021). Association between fund’s attributes and fund’s performance: A panel data approach. Benchmarking: An International Journal, 29(1), 285-304. DOI: https://doi.org/10.1108/BIJ-10-2020-0545
Ter Horst, J. R., Nijman, T. E., and de Roon, F. A. (2004). Evaluating style analysis Journal of Empirical Finance, 11(1), 29-53. DOI: https://doi.org/10.1016/j.jempfin.2002.12.003
Treynor, J. L., and Black, F. (1973). How to use security analysis to improve portfolio selection. The Journal of Business, 46(1), 66-86. https://www.jstor.org/stable/2351280
Vargas Sánchez, A. (2012). Gestión activa de portafolios mediante la aplicación del modelo Treynor-Black. Investigación y Desarrollo, 1(12), 17-32. DOI: https://doi.org/10.23881/idupbo.012.1-2e
Venturato, G. (2018). Bayesian state space modelling of factor investing: a quantitative equity strategy based on Kalman filter (Master’s Thesis). Copenhagen Business School, Denmark. https://research.cbs.dk/files/65697661/Giovanni_Venturato.pdf
Zurek, M., and Heinrich, L. (2020). Bottom up versus top-down factor investing: an alpha forecasting perspective. Journal of Asset Management, 22(1), 11-29. DOI: https://doi.org/10.1057/s41260-020-00188-9
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Derechos de autor 2026 Ángel Samaniego Alcántar

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