基于条件异方差模型的上证地产指数外推预测

对于金融时间序列,常会出现观测值在某个时间段波动大,但在另一个时间段波动比较小的聚类性现象。本文运用ARCH模型和GARCH模型建立上证地产指数的条件异方差模型,即利用加入条件标准差的GARCH-M模型进行外推一期预测,结果表明,外推一期的结果可以有效地预测上证地产指数收盘价。

Extrapolation Forecast of Shanghai Real Estate Index Based on Conditional Heteroscedasticity Model

In financial time series, more volatile observed value always exists in certain period, while tess vola-tile observed value exists in other period, that phenomenon is called clustering. This paper uses ARCH modeland GARCH model to develop a Shanghai real estate index Conditional Heteroskedasticity model which meansusing the added conditional standard deviation for one cycle of extrapolation forecast. It turns out that the resultcan effectively forecast the closing price of Shanghai real estate index.