Uso de variables de mercado en la predicción de dificultades financieras para las empresas que cotizan en Vietnam
Resumen
Este artículo tiene como objetivo investigar el poder de clasificación de las variables del mercado como factores predictivos en el modelo de predicción de dificultades financieras para las empresas que cotizan en bolsa en un mercado fronterizo como el mercado de valores de Vietnam. Los datos se recopilan de 70 compañías con dificultades financieras que sufrieron una pérdida en 3 años consecutivos y 156 empresas sin dificultades financieras en Vietnam desde 2010 a 2017. Se han construido cuatro modelos diferentes utilizando regresión Logit y la técnica de análisis de SVM para hacer una predicción en 1 a 3 años por delante. Los resultados del análisis muestran que la combinación de ratios contables con variables de mercado como la volatilidad de los precios y el P / E puede mejorar la capacidad de clasificación del modelo ex ante. Además, a diferencia de los resultados de investigaciones anteriores relacionadas en mercados emergentes, en este estudio, los modelos Logit superan a los modelos SVM. Por lo tanto, para futuras investigaciones, se deben investigar los modelos que aplican otros clasificadores de aprendizaje automático, como el Árbol de decisiones (DT) o la Red neuronal (NN).
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