Application of Machine Learning Algorithm in Risk Prediction of Financial Markets

It is of great practical value to establish an accurate financial forecasting model for financial product management and risk control. In view of the characteristics of short launch cycle of financial products and less modeling data in the new era, a grey linear regression combination financial forecasting model with less data modeling is constructed. Grey linear regression is a technique for financial forecasting, which is used to estimate the future value of variables at different time points. It is also known as the method of “combining” two models or datasets to predict the future value of a variable from the past and current values of other variables. if we know the relationship between two variables, we can use it to predict the value of another variable according to its relationship with the two variables. Simply put, grey linear regression combines two models (or datasets) and predicts one variable. Finally, the paper empirically analyzes the effectiveness of the grey linear combination financial forecasting model for the few data modeling, and the empirical results show that the combination financial forecasting model has a high prediction accuracy.