亞洲主要股市報酬波動的潛在鏈結程度衡量

Abstract

本研究根據 Diebold and Yilmaz (2014, Journal of Econometrics) 所延伸網絡拓 樸 (network topology) 的概念與分析架構, 利用向量自我迴歸模型 (vector autoregression, VAR) 之廣義預測誤差變異數分解 (generalized forecast error variance decomposition) 的估計結果, 在 「控制歐美主要股市影響」 下, 建立了亞洲各股市 報酬率及波動率對應的潛在鏈結 (connectedness) 關係網絡。 我們發現 (1) 亞洲各 股市之間的鏈結有越趨緊密的態勢 ; (2) 鏈結指數在金融危機與外生衝擊事件發生 時具有較高的數值, 此反映危機發生時各股市間更為緊密的依存現象 ; (3) 亞洲股 市的金融傳導網絡主要以香港和新加坡為中心, 而中國與俄羅斯股市則與其餘亞 洲股市無顯著的鏈結。

According to the network topology and the framework proposed by Diebold and Yilmaz (2014), this paper measures the potential connectedness of returns and volatilities among Asian stock markets while controlling for the effects of European and U.S. stock markets. The main findings are (i) the connectedness among Asian stock markets is getting closer in general; (ii) the larger values of the connectedness index are usually observed in the periods of financial crises; (iii) Hong Kong and Singapore play the major roles as far as spillover effects on Asian stock markets are concerned, whereas China and Russia play only minor roles.