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Differential equations are important tools to portray dynamic problems, andare widely used in finance, engineering and biology. Here, multiple dynamicdifferential models were built innovatively, and discretized with theRunge-Kutta method. The the model parameters were estimated. The models wereaveraged using the Optimal weight selection method, and the consistency of suchparameter estimation was verified. Numerical simulations were also conducted,and the simulated results outperformed ordinary linear models. Finally, thedifferential averaging model built here was used to empirically analyze theShanghai Index 300. This method integrated the fluctuation features of multipleShanghai Composite Index fitting models, and yielded good analytical results.This study provides a methodological reference for analysis of stock marketsituations, and offers research clues for the parameter estimation ofdifferential equations.

Parameter Estimation of Differential Equation Model based on Optimal Weight Choice Method