应用马尔科夫链模型预测短期房价——以南宁市为例  

Application of Markov Chain Model to Predict Short-Term Housing Prices—A Case Study of Nanning City

作　　者：谭元元[1] 涂火年[1] 

机构地区：[1]广西财经学院中国–东盟统计学院,广西 南宁

出　　处：《统计学与应用》2024年第4期1592-1600,共9页Statistical and Application

摘　　要：本文阐述了马尔科夫预测模型的特点,并通过选取南宁市2019年3月至2022年2月商品房住宅价格的月度统计数据,构建马尔科夫预测模型,借助EViews软件对该数据进行分析,最终得出的预测结果显示,未来一段时间内,南宁市房价处于平稳状态的可能性最大。研究结果和实际情况相符,说明了利用马尔科夫预测模型对房价短期走势的预测是比较精准可靠的。This paper describes the characteristics of the Markov prediction model and constructs the Markov prediction model by selecting the monthly statistical data of residential commodity house prices in Nanning City from March 2019 to February 2022. By analyzing the data with the help of EViews software, the final prediction result shows that the housing prices in Nanning City are most likely to be in a stable state in the future. The results of the study are consistent with the actual situation, which shows that the Markov prediction model is more accurate and reliable in predicting the short-term trend of housing prices.

关 键 词：马尔科夫链 状态转移 转移概率 

分 类 号：F42[经济管理—产业经济]