Residential Rent in Wuhan Based on Geometric Brownian Motion Model Fluctuation Fitting and Prediction

This paper makes an analysis of the fitting and prediction of residential rent fluctuation in Wuhan by using the advantages of big data. Frequent fluctuations in rental residential prices and market trends urgently need to strengthen the analysis of residential rental market price monitoring data. This paper attempts to fit and analyze the trend of random fluctuation behavior of residential rent based on scientific methods. Based on the geometric Brownian motion, the geometric Brownian motion model is established for the 24-month residential rental price fluctuation behavior of 7 districts in Wuhan, and the Monte Carlo method is used to simulate the residential rental price. By comparing the correlation coefficient between the fitted value and the actual price, the residual sum of squares and the residual analysis diagram test the goodness of fit of the simulation results to explore the differences in the fitting application of different districts to the model, and use the selected optimal fitting results to analyze the future price trend and establish the price monitoring and early warning model mechanism. Through empirical research, it provides a new method for the government to accurately grasp the dynamic fluctuation law of residential rental price.