摘要
城市房价的稳定关系到国计民生,其涨跌受到多种因素的影响.本文选取柳州市2015年5月—2018年4月商品房销售价格的月统计数据,将其视为马尔科夫过程.利用R软件分别画出原始房价数据和房价一阶差分数据的时序图及其自相关系数图,并根据ADF检验进行平稳性分析,选定房价变化为马尔科夫链的状态.并依据我国房贷基础利率4.9%,将房价变化分为下降、稳定、上升但上升幅度不高于贷款利率、上升且上升幅度高于贷款利率4个状态.通过数理统计方法得到马尔科夫链的状态转移矩阵,以此对柳州市房价走势进行预测,从而指导消费者,特别是需要商业贷款的消费者购买商品房.
The urban housing price is influenced by various factors. In this paper, we take the monthly statistics of the urban housing sales prices from May 2015 to April 2018 in Liuzhou as a Markov process. R software is used to draw the sequence diagram and autocorrelation coefficient chart of prices of the original and the first difference respectively, and then the changes of the price are regarded as the status of Markov chains based on the stability analysis of ADF test. And according to the basic interest rate of mortgage of China 4.9%, the price changes are divided into decline, stability and increase （ with the increase not higher than the loan interest rate and that higher than the loan interest rate） . State transition matrix of Markov chain is obtained by mathematical statistics method and used to forecast the price trend of Liuzhou city, so as to guide the consumers, especially those who need commercial loan.
作者
胡振寰
王智文
唐博文
HU Zhenhuan;WANG Zhiwen;TANG Bowen(School of Electric and Information Engineering,Guangxi University of Science and Technology;School of Computer Science and Communication Engineering,Guangxi University of Science and Technology,545006,China)
出处
《广西科技大学学报》
2018年第4期79-83,共5页
Journal of Guangxi University of Science and Technology
基金
国家自然科学基金项目(61462008
61751213
61365009)
广西自然科学基金项目(2014GXNSFAA118368)
广西科技大学创新团队项目(gxkjdxcxtd201504)
广西科技大学创新项目(GKYC201708)资助
柳州市科学研究与技术开发计划项目(2016C050205)
关键词
马尔科夫链
平稳性分析
状态转移矩阵
房贷基础利率
价格预测
Markov chain
stationarity analysis
state transition matrix
base rate of mortgage
price forecasting
