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...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.展开更多
文摘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.
