In this paper a long-term portfolio optimization model is developed, through the use of economic indicators (CLI and BCI). In this way, an investment portfolio will adjust to the movements of the business cycle, mitigating its risk in the event of possible downturns. The proposed model was tested in Mexico between 1998-2021. The active strategy makes investments in fixed income (Certificados de la Tesorería, CETES) and the market index (Índice de Precios y Cotizaciones, IPC), through operations of 25 % of the capital in monthly decisions. The dynamic investment strategy outperforms market index by 4.3 % in the period analyzed (differences in annual geometric return). In that period, only 5 % of the annual returns of the active strategy were negative, compared to 25.8 % in the market index.
Celebi, K., & Hönig,M. (2019). The impact of Macroeconomic Factors on the German Stock Market: Evidence for the Crisis, Pre-and Post-Crisis Periods. International Journal of Financial Studies, 7(2), 1-13. https://doi.org/10.3390/ijfs7020018
Cervantes, M., Montoya, M.A., & Bernal-Ponce, L.A. (2016). Effect of the Business Cycle on Investment Strategies: Evidence from Mexico. Revista Mexicana de Economía y Finanzas (REMEF), nueva época, 11(2), 39-49. https://doi.org/10.21919/remef.v11i2.85
Dzikevičius, A., & Vetrov, J. (2013). Investment portfolio management using the business cycle approach. Business: Theory and Practice, 14(1), 57-63. https://doi.org/10.3846/btp.2013.07
Dzikevičius, A., & Vetrov, J. (2012a). Analysis of asset classes through the business cycle. Business, Management and Education, 10(1), 1-10. https://doi.org/10.3846/bme.2012.01
Dzikevičius, A., & Vetrov, J. (2012b). Stock market analysis through business cycle approach. Business: Theory and Practice, 13(1), 36-42. https://doi.org/10.3846/btp.2012.04
Han, L., Li, Z., & Yin, L. (2018). Investor Attention and Stock Returns: International Evidence. Emerging Markets Finance and Trade, 54(14), 3168-3188. https://doi.org/10.1080/1540496X.2017.1413980
Gajewski, P. (2014). Nowcasting Quarterly GDP Dynamics In The Euro Area – The Role Of Sentiment Indicators. Comparative Economic Research, 17(2), 5-23. https://doi.org/10.2478/cer-2014-0011
Markowitz, H. (1952). Portfolio Selection. The Journal of Finance, 7(1), 77-91. https://doi.org/10.1111/j.1540-6261.1952.tb01525.x
OECD (2019a). (2019, October 30). Composite leading indicator (CLI). https://doi.org/10.1787/4a174487
OECD (2019b). Business confidence index (BCI). OECD System of Composite Leading Indicators. Paris, France. https://doi.org/10.1787/3092dc4f
Palley, T. (2012). The Rise and Fall of Export-led Growth. Investigación Económica, 70(276), 125-162. http://dx.doi.org/10.22201/fe.01851667p.2012.280.37339
Peláez, R. F. (2015). Market-timing the business cycle. Review of Financial Economics, 26, 55-64. https://doi.org/10.1016/j.rfe.2015.03.003
Tkacova, A., Gavurova, B., & Behun, M. (2017). The composite leading indicator for German business cycle. Journal of Competitiveness, 9(4), 114-133. https://doi.org/10.7441/joc.2017.04.08
Vraná, L. (2018). On Extending Composite Leading Indicators by International Economic Series. Statistika-Statistics and economy Journal, 98(2), 113-134.
Wong, S. S. L., Chin-Hong, P. U. A. H., Mansor, S. A., & Liew, V. K. S. (2014, March). Measuring business cycle fluctuations: An alternative precursor to economic crises. In ACRN Proceedings in Finance and Risk Series ‘13: Proceedings of the 13th FRAP Conference in Cambridge (vol. 2, p. 33). ACRN Publishing House.
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Copyright (c) 2022 Nova Scientia