本研究係以中國股票市場之上證綜合股價指數及其所屬的五個分類指數與中國總體經濟指標為研究對象,研究期間2005年8月至2009年8月之月調整後收盤股價及經濟指標數據做作為研究標的。資料來源取自於教育部AREMOS 資料庫,運用灰色預測模型原理與向量自我迴歸模型(VAR)運用在中國股市與經濟體系中,嘗試將灰色預測模型GM(1,1)導入VAR模型中,目的在於了解中國股票指數與總體經濟指標間之互動結構。 研究實證結果發現:消費者物價指數、進口值、出口值及M0和股價指數間存在「因果關係」;依據AIC準則決定自我迴歸落後期數,實證發現股價指數領先經濟指標2個月;利用Granger因果關係檢定、預測變異數分解及衝擊反應分析了解中國股價指數和總體經濟指標間存在「互動結構」,實證發現中國的經濟指標與股價指數有密切的互動結構,符合中國經濟結構現況。
The subjects of this study are the SSE Stock Index and the five categorized indices from China stocks market, and China macro-economic indices. The monthly closing stock indices and macro-economic indices are sampled during the period starting August 2005, and ending August 2009, the data of which were obtained from the census and statistics department; the Government of the Advanced Retrieval Modeling System, AREMOS. I applied GM(1,1) on VAR in to a GVAR with the purpose of realizing the dynamic structure between Economic Indices and China Stock Market Indices. The empirical results indicate that CPI ,Import, and Export have a Granger causality relationship with stock market indices respectively. In accordance with AIC rule, stock market indices are a leading index to economic indices by two months. With decomposition variance and the impulse response analysis by the way of Granger causality, we realize the existence of the dynamic structure between economic indices and stock market indices in China. And we discovered the fact that there is a close interaction between Chinese Economic Indices and stock market indices, which matches the current state of Chinese economy.