摘要
上海的私家车牌照采用拍卖的形式,竞争激烈,千金难求,因此研究拍卖价格的变动趋势对沪牌价格预测具有较高的现实意义。车牌拍卖价格序列符合时间序列的性质,ARIMA模型根据历史信息和变动趋势对未来信息进行预测,能较好地把握时间序列的动态规律。因此,首先通过ARIMA模型拟合沪牌往期拍卖价格,得出沪牌价格的变动趋势。此外,沪牌拍卖价格不仅与历史信息有关,还受到外部回归量的影响,在ARIMA模型的基础上,首次加入两个外部回归量,即中标率和警示价,从而得到基于外部回归量的ARIMA模型。通过对预测结果的对比分析,利用历史数据对沪牌价格进行拟合,预测结果和实际值十分接近,能够有效地预测沪牌价格,且相对于传统ARIMA模型,基于外部回归量的ARIMA模型的预测效果更好。
Private car licenses in Shanghai are sold in the form of auctions,which are fiercely competitive and difficult to win.Therefore,it is of great practical significance to study the trend of auction’s price and predict it.The series of auction’s price conforms to the nature of time series.The ARIMA model predicts future information based on historical information and changing trends,and can better grasp the dynamic laws of time series.In this article,we firstly use the ARIMA model to fit the previous auction price of the Shanghai brand to obtain the trend of the Shanghai brand price.However,the Shanghai car license’s price is not only related to historical information,but also affected by external regressors.Therefore,two external regressors are added:the bid winning rate and the warning price.Then we get the improved ARIMA model based on external regressors.Using historical data to fit the Shanghai brand price,it is found that the prediction result is very close to the actual value,which can effectively predict the Shanghai brand price.
作者
彭宜洛
钟世恒
林红梅
PENG Yi-luo;ZHONG Shi-heng;LIN Hong-mei(School of Statistics and Information,Shanghai University of International Business and Economics,Shanghai 201600,China)
出处
《经济研究导刊》
2021年第10期86-90,共5页
Economic Research Guide
关键词
ARIMA模型
外部回归量
中标率
警示价
沪牌
价格预测
ARIMA model
external regressors
bid winning rate
the warning price
Shanghai brand
price forecast
