Construction of Financial Economic Cycle Early Warning System based on DE-Jaya Hybrid Optimization Algorithm

The financial economic cycle early warning system is an effective tool for monitoring the operating status of the financial economy. To a certain extent, it can help financial management departments predict and evaluate the operating status of the financial economy. At present, many scholars have conducted relevant research on this, but the financial economic cycle early warning method based on the DE-Jaya algorithm has not yet been reported. To this end, this article uses past market data as samples and financial economic operating indicators as output indicators, using the DE-Jaya algorithm to provide early warning for financial economic cycles. This article will improve the DE-Jaya algorithm from three aspects: model structure, data structure and parameter optimization, and use the improved algorithm to provide early warning for the macroeconomic operating status. Empirical results show that the improved method can effectively realize early warning and assessment of macroeconomic operating status, and the improved accuracy can reach up to 97.7%.