Time Series Analysis and Forecasting: Application of Financial Crisis Early Warning

Affected by the new crown pneumonia epidemic around the world, many companies have experienced financial crises and even gone bankrupt. Business managers, investors and creditors have all suffered considerable economic losses. Based on the time series forecasting method, this study chooses ARIMA model and exponential smoothing model to build financial early warning models respectively. By comparing the data of the two forecasting models, it is shown that the forecasting error rates of ARIMA model and exponential smoothing forecasting model are both in a reasonable range, and they are both suitable for enterprise financial early warning research. In contrast, the prediction accuracy of exponential smoothing model is higher. In the future, when an enterprise establishes a financial crisis early warning system, it can use the above two models to make financial forecast, so as to judge the financial situation of the enterprise.