基于Holt-Winters滤波模型的上海新房价格的预测

Prediction of Shanghai New House Price Based on Holt-Winters Filtering Model

摘要: 时间序列分析是用来描述历史数据随时间变化的规律，并用于预测变量趋势的重要工具之一。在房地产市场中常常利用时间序列对房地产价格趋势进行预测，为投资者在房地产市场中提供决策依据。本文基于2005年1月~2015年12月的中房上海新房住宅指数132组月度数据，借助R软件进行分析，通过建立Holt-Winters滤波模型对中房上海新房住宅指数进行数据拟合，最后经过比较选择了Holt-Winters滤波模型加法模型，并运用该模型对未来三年的中房上海住宅指数进行预测。

Abstract: Time series analysis is one of the most important tools to describe the change of historical data over time and to predict the trend of variables. In the real estate market, time series are often used to forecast the trend of real estate prices, which provides the basis for investors to make decisions in the real estate market. There are 132 groups Shanghai housing index of residential houses monthly data from January 2005 to December 2015, analyzed by R, through the establishment of Holt-Winters filtering model of data fitting in the Shanghai new residential index, finally chose the Holt-Winters filter model of the additive model, and uses this model to predict the future three years of Shanghai residential housing index.