Economic Crisis Early Warning of Real Estate Companies Based on PSO-Optimized SVM

Abstract

For the possible economic crisis of real estate companies, by analyzing the shortcomings of support vector machine (SVM) model, after optimization with particle swarm optimization (PSO), the PSO-SVM model was established by changing economic condition parameters and using data to warn the real estate economic crisis. Then, this model is used to warn the economic capacity of four real estate companies in Beijing. The results show that this model can further predict and analyze the solvency index, operating ability index, development ability index, profitability index, cash flow index, and comprehensive financial index of real estate companies and come to the conclusion that profitability index is the most important, and higher profitability can resist the harm brought by economic crisis. Finally, it analyzes the economic crisis that real estate companies may encounter and puts forward specific suggestions.