The rapid development of globalization and financial markets has continuously expanded the potential impact range of systemic financial risks, and systemic financial risks have become a highly concerned focus for governments and financial institutions around the world. Time series analysis and machine learning techniques provide new methods and tools for predicting systemic financial risks.  This article will explore and analyze how machine learning models can achieve nonlinear modeling in systematic financial risk warning based on time series, and analyze the effectiveness of these models in practical applications.

Ke Ma. Research on Nonlinear Modeling of Machine Learning Models Based on Time Series Analysis in Systematic Financial Risk Warning. International Journal of Business Management and Economics and Trade (2024), Vol. 6, Issue 1: 73-81. https://doi.org/10.38007/IJBMET.2025.060108.

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