Analysis Related Influence Factors And Forecast Chongqing Commercial Real Estate Price

In recent years,the price of commercial housing in Chongqing city is growing rapidly.The problem caused by high housing price have aroused extensive concerns among different social sectors and the term "mortgage slave" has been appearing frequently in people's social networks and daily lives.This thesis conducts a corresponding analysis over the problem of Chongqing commercial housing price and makes a prediction about Chongqing commercial housing price in the short-term.This research aims at being more comprehensively,objectively and correctly in understanding related influential factors on Chongqing's commercial housing price and in providing corresponding referential opinions for participants in Chongqing housing market.Firstly,based on relevant economic theories and exiting fruits of relevant scientific research,this article makes qualitative and quantitative analysis on demand factor,supply factor,inflation and other factors which influence the price of commercial housing in Chongqing city.Demand factors include population,per capita GDP,per capita savings deposit balance,urban per capita disposable income.Supply factors include land-transferring fees,number of employees at the end of the year,real estate industry investments,market monopoly power of real estate developers,completed commercial housing areas.Inflation factor includes housing sales price index,consumer price index.And other factors include loan interest rate from three to five years and real estate tax.Secondly,using related data from 2000 to 2015 and principal component analysis to reduce the dimension of the original variables,we first establish multiple linear regression model and BP neural network model which is based on principal component analysis.Then we compare the accuracy of the two models in fitting Chongqing commercial housing prices and find that the BP neural network based on the principal component analysis model performs better.Finally,based on the principal component analysis of BP neural network model,we predict that the average price of commercial housing in Chongqing city is 5440.8 yuan / square meter in 2016 and 5823.6 yuan / square meter in 2017.The main innovation of this paper lies in using multiple linear regression and BP neural network combined with principal component analysis to predict Chongqing commercial housing prices,effectively solving the previous overfitting problem and improving the original models' poor ability in generalization caused by excessive housing price-influential factors.Finally,after the analysis of previous results,this thesis also gives corresponding suggestions to participants in the commercial housing market in Chongqing city.