Análisis de portafolios de inversión mediante simulación de Monte Carlo en Python: Evaluación del riesgo y rendimiento con acciones mexicanas
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Este estudio utiliza la simulación de Monte Carlo para analizar portafolios de inversión, evaluando el riesgo y rendimiento de diez acciones mexicanas seleccionadas de diversas industrias. Generando 1000 combinaciones aleatorias de ponderaciones. La simulación mostró una amplia gama de escenarios de desempeño para las carteras. Los resultados destacaron la importancia del índice de Sharpe para identificar portafolios óptimos, revelando que mayores rendimientos suelen implicar mayor volatilidad, mientras que las carteras estables ofrecen un mejor balance riesgo-retorno. La frontera eficiente visualizó esta relación. Este análisis demuestra el valor de la simulación Monte Carlo para optimizar asignaciones de activos y apoyar decisiones informadas.
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