Research on a Financial Crisis Early Warning Model Based on a Stochastic Forest Algorithm

Abstract

To solve the problem of low accuracy of the traditional financial crisis early warning model, this study proposes a financial crisis early warning model based on the random forest algorithm. First, according to the formation mechanism of the financial crisis, from the aspects of operation ability, development ability, profitability, solvency, cash flow, ratio structure and so on, this paper selects the early warning and detection indicators of the financial crisis. Then, the random forest algorithm is used to screen the early warning detection indicators and calculate the weight of financial crisis indicators. Through the comparison of financial crisis detection results and early warning thresholds, financial crisis early warnings are realized. The experimental results show that compared with the traditional model, the false positive rate and false negative rate of this model are lower, and the values of the two indicators are always lower than 5%, indicating that this model has good performance in early warning accuracy.