臺灣人文及社會科學引文索引資料庫系統

:::

詳目顯示

回上一頁
第 1 筆 / 總合 1 筆   第一頁 上一頁 下一頁 最後一頁
/1頁
題名：國際金融市場之實證研究
作者：許碧純
作者(外文)：Pi-Chun Hsu
校院名稱：臺灣大學
系所名稱：國際企業學研究所
指導教授：陳思寬
學位類別：博士
出版日期：2011
主題關鍵詞：外溢效果；貨幣政策；報酬率；新興工業經濟體；多變量一般條件變異數異質模型；馬可夫鍊一般條件變異數異質模型；Spillover effect；monetary policy；stock returns；emerging stock markets；multivariate GARCH-M mode；Markov-switching GARCH-M model
原始連結：連回原系統網址new window
相關次數：
  • 被引用次數被引用次數:期刊(0) 博士論文(0) 專書(0) 專書論文(0)
  • 排除自我引用排除自我引用:0
  • 共同引用共同引用:0
  • 點閱點閱:28
隨著世界扁平化, 經濟發展與合作的國際化, 以及網路資訊快速傳遞的進展, 各國間股票市場相互影響及依賴的程度日益加深。因此, 本論文遂以國際間股票市場中相互依賴關係的實證研究為主軸, 特別著重於亞洲的新興工業化經濟體之股票市場為主要研究對象, 進行實證資料與應用計量模型的分析。首先, 我們以探討韓國股票市場與世界第一大, 美國股市, 與世界第二大, 日本股市之相互影響的資訊傳遞領先與落後的關係;
其後, 將研究的範疇由韓國擴及至亞洲的台灣、香港、新加坡等, 探討相互依賴以及他們對於美國貨幣政策改變的影響效果。
首章緒論之後, 在第二章的部分, 我們分別以 (一) 單變數自我相關的一般條件變異數異質模型, (二) 以兩階段方法, 加入所估計的其他國家股市一階與二階動差之單變數自我相關的一般條件變異數異質模型, 以及 (三) 多變量自我相關的一般條件變異數異質模型, 做為實證研究的計量方法, 以探討韓國股票市場與美國股市、日本股市之相互影響的資訊在平均報酬與波動性的傳遞領先與落後關係。以1980年至2010年, 三十年間股票市場的交易日資料, 作為研究樣本。實證的結果發現, 對韓國股票市場而言, 日本股票市場不論是平均報酬率與或波動性的傳遞效果上,
都具有雙向的Granger因果關係, 而且, 波動性更呈現負向相關。美國股票市場對於日本和韓國市場, 均呈現單向的Granger因果關係, 顯示韓國與日本對於美國股票市場並無回饋效果。因此, 由透過國際投資組合以分散風險的角度而言, 考慮有高度產業競爭性的日本和韓國股票市場的組合, 相較於做為全球消費國特色的美國股市和韓國股票市場的組合, 可能是較佳的資產配置。
在第三章的部分, 我們將研究的範圍擴及到亞洲新興工業體, 亦即傳統所謂的亞洲四小龍: 台灣、香港、新加坡和韓國。以馬可夫鍊二狀態轉換的一般化設定之指數型一般條件變異數異質模型, 分析這四個相對於其他亞洲國家而言, 發展較健全、開放的股票市場對於美國貨幣政策改變的反應。由1985年至2010年的股市交易週資料, 四個亞洲新興工業體的銀行間三個月隔夜拆款利率與美國聯邦基金利率, 做為各自的貨幣政策指標。研究的結果發現, 美國的貨幣政策改變時, 對於亞洲股市相對於美國股市的影響, 其不對稱性的效果更為顯著, 尤其是當美國調降利率, 而亞洲股市又趨於牛市之時。此外, 亞洲新興工業體的貨幣政策與美國貨幣政策在同時間的相關性並不顯著, 顯示美國貨幣政策傳遞到亞洲的效果, 遠不及貨幣政策改變直接對於亞洲股票市場的衝擊。
因此, 在發展較健全、開放的亞洲股票市場, 對於美國貨幣政策的改變,
呈現其市場有訊息揭露效率性的特色, 但其波動性的過度不對稱性又呈現其相對可能不理性的程度或是對於借貸市場之管制。
總結而言, 本論文採用當前廣泛使用的計量研究方法, 以分析股票市場之跨國相互依賴的情況, 以及美國貨幣政策所產生的跨國傳遞之股票市場外溢效果。在分析股票市場之跨國相互依賴的研究中, 我們採取韓國與日本產業競爭的觀點, 作為跨國投資組合的建議, 後續的研究, 可以切割樣本, 分析此三十年來, 在不同特定金融事件中, 韓國股市對於來自日本與美國的衝擊反應, 相信在投資組合的建議上, 將更有其實用參考價值。在分析美國貨幣政策的外溢傳遞效果時, 我們討論亞洲新興工業體的貨幣政策不若股票市場對於美國貨幣政策的反應, 而此股票市場之波動性不對稱反應更勝於美國國內股票市場的效果, 因此觀察到這些發展較為開放的亞洲新興工業體, 所呈現的資訊傳遞效率性與投資人可能不理性的程度或是這些市場對於借貸市場之管制。
後續的研究, 可以結合其他貨幣政策外溢效果的分析比較, 例如歐元區、日本甚至是中國的貨幣政策對於當前亞洲新興工業體的股票市場的影響, 相信更能廣泛觀察亞洲新興工業體股票市場的相互依賴與市場效率性。
The current dissertation consists of two topics of interdependence and monetary policy transmission for the Asian emerging stock markets and both adopt the time series econometrics method.
The first subject empirically examines the interdependence of returns and volatility among the South Korean, Japanese and the US stock markets by focusing specifically on the spillover effects from the world first and second largest financial markets to the emerging market such as South Korea. We use (1) the univariate generalized autoregressive conditional heteroskedasticity in mean (GARCH-M) model, (2) the univariate GARCH-M with interdependent effects model, and (3) the multivariate GARCH-M models to assess the magnitude of the time-varying cross-market interdependence. Based on the results from the estimation of returns by these three models, we find stronger positive impacts on South Korea arising from Japan than from the US. Moreover, from the estimation of conditional volatility, we find significant bidirectional Granger causality between South Korea and Japan, especially from negative spillover volatility clustering effects. The results in this chapter indicate that Japan is an industrial competitor to South Korea and the US is a global consumer to them both. The different roles played by these countries and in the stock market, may suggest that potential portfolio benefits exist from diversifying and acquiring the competitor rather than the consumer.
To take a broad prospect, the second subject is a examination of assessing the effects of US monetary policy on the Asian stock markets. We study the external effects of changes in US monetary policy to the Asian emerging stock markets, i.e. Hong Kong, Singapore, South Korea, and Taiwan. Using exponential GARCH (EGARCH) with dummy variable models and Markov-switching EGARCH models, the empirical evidence form weekly data indicate that changes in the US monetary policy measure as Fed fund rate has larger asymmetric effects on Asian stock returns during their bull markets relative to their impact over US stock markets. In addition, it is shown that expansive US monetary policy is contrary to simultaneously in Asian local monetary policy changes and associated with higher probability of switching to the bull-market regime for Asian stock markets while which effect insignificantly over the US stock market herself. Therefore, the transmission of changes in US monetary policy not only is asymmetry to Asian stock markets volatility but also be asymmetric comparing the impact across US and Asian stock markets.
In brief, this dissertation adopts currently practical econometrics methods to study the international stock markets. The first study contributes to the financial research with the idea of industrial competition between countries, while the second study contributes to the international financial research with the local stock market regime switching affected by the US monetary policy change. It is worth for further research in expanding the methodology to link the examination of interaction among monetary policy, stock market and industrial competition.
[1]Abd. Majid, M. S., Meera, A. K. and Omar, M. A. (2007), “Interdependence of ASEAN-5 Stock Markets from the US and Japan,” 20th Australasian Finance and Banking Conference 2007 Paper, Available at SSRN: http://ssrn.com/abstract=1005287.
[2]Amsden, A. H. and Singh, A. (1994), “The Optimal Degree of Competition and Dynamic Efficiency in Japan and Korea,” European Economic Review, 38, p. 941-951.
[3]Basistha, A. and Kurov, A. (2008), “Macroeconomic Cycles and the Stock Market''s Reaction to Monetary Policy,” Journal of Banking and Finance, 32, p. 2606-2616.
[4]Baur, D. and Jung, R. C. (2006), “Return and Volatility Linkages between the US and the German Stock Market,” Journal of International Money and Finance, 25, p. 598-613.
[5]Bauwens, L., Laurent, S. and Rombouts, J. V. K., (2006), “Multivariate GARCH Models: A Survey,” Journal of Applied Econometrics, 21, p. 79-109.
[6]Bernanke, B. S. and Kuttner, K. (2005), “What Explains the Stock Market''s Reaction to Federal Reserve Policy?” Journal of Finance, 60, p. 1221-1257.
[7]Bohl, M. T., Siklos, P. L. and Sondermann, D. (2007) “Shocking markets: European stock markets and the ECB''s monetary policy surprises. Available at SSRN: http://ssrn.com/abstract=1091133.
[8]Bollerslev, T., Chou, R. Y. and Kroner, K. F. (1992), “ARCH Modeling in Finance: A Selective Review of the Theory and Empirical Evidence,” Journal of Econometrics, 52, p. 5-59.
[9]Chen, G. M., Firth, M. and Rui, O. M. (2002), “Stock Market Linkages: Evidence from Latin America,” Journal of Banking and Finance, 26, p. 1113-1141.
[10]Chen, S. S. (2007) “Does Monetary Policy Have Asymmetric Effects on Stock Returns?” Journal of Money, Credit and Banking, 39, p. 667-88.
[11]Cheung, Y. W. and Ng, L. K. (1996), “A Causality-in-Variance Test and Its Application to Financial Market Prices,” Journal of Econometrics, 72, p. 33-48.
[12]Conover, C. M., Jensen, G. R. and Johnson, R. R. (1999) “Monetary Policies and International Stock Returns,” Journal of Banking and Finance, 9, p. 1357-1381.
[13]Crowder, W. J. (2006) “The Interaction of Monetary Policy and Stock Returns,” Journal of Financial Research, 29, p. 523-35.
[14]Davig, T. and J. R. Gerlach (2006) “State-Dependent Stock Market Reactions to Monetary Policy,” International Journal of Central Banking, 4, p. 65-83.
[15]Ehrmann, M. and Fratzscher, M. (2004) “Taking stock: monetary policy transmission to equity markets,” Working Paper Series, 354, European Central Bank.
[16]Engle, R. F., Lilien, D. M. and Robins, R. P. (1987), “Estimating Time-Varying Risk Premia in the Term Structure: the ARCH-M Model,” Econometrica, 55, p. 391-408.
[17]Engle, R. F. and Kroner, K. F. (1995), “Multivariate Simultaneous Generalized ARCH,” Econometric Theory, 11, p. 122-150.
[18]Erb, C. B., Harvey, C. R. and Viskanta, T.E. (1996), “Expected Returns and Volatility in 135 Countries,” Journal of Portfolio Management, 22, p. 46-58.
[19]French, K. R., Schwert G. W. and Stambaugh R. E. (1987), “Expected Stock Returns and Volatility,” Journal of Financial Economics, 19, p. 3-29.
[20]Glosten, L. R., R. Jagannathan, and D. E. Runkle (1993), “On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks,” Journal of Finance, 48, p. 1779-1801.
[21]Granger, C. W. J. (1969), “Investigating Causal Relations by Econometric Models and Cross-Spectral Methods,” Econometrica, 37, p.424-438.
[22]Gray, S.F. (1996), “Modeling the Conditional Distribution of Interest Rates as a Regime-Switching Process,” Journal of Financial Economics, 42, p.27-62.
[23]Henry, Q. T. (2009), “Regime Switching in the Relationship Between Equity Returns and Short-Term Interest in the UK,” Journal of Banking and Finance, 33, p.405-414.
[24]Hirayama, K., and Tsutsui, Y. (1998), “Threshold Effect in International Linkage of Stock Price,” Japan and the World Economy, 10, p. 441-453.
[25]Ioannidis, C. and Kontonikas, A. (2008), “The Impact of Monetary Policy on Stock Prices,” Journal of Policy Modeling, 30, p. 33-53.
[26]Jeon, B.N., and von Furstenberg, G. M. (1990), “Growing International Co-Movement in Stock Indices,” Quarterly Review of Economics and Finance, 30, p. 15-30.
[27]Jensen, G. R., and Johnson, R. R. (1995), “Discount Rate Changes and Security Returns in the U.S., 1962-1991,” Journal of Banking and Finance, 19, p. 79-95.
[28]Karolyi, G. A. (1995),“A Multivariate GARCH Model of International Transmissions of Stock Returns and Volatility: The Case of the United States and Canada,” Journal of Business and Economic Statistics, 13, p. 11-25.
[29]Kearney, C. and Patton, A. J. (2000), “Multivariate GARCH Modeling of Exchange Rate Volatility Transmission in the European Monetary System,” The Financial Review, 35, p. 29-48.
[30]Kim, A. (2009),“An Empirical Analysis of Korea''s Trade Imbalances with the US and Japan,” Journal of the Asia Pacific Economy, 14, p. 211-226.
[31]Kim, S. J. (2005), “Information Leadership in the Advanced Asia-Pacific Stock Markets: Return, Volatility and Volume Information Spillovers from the US and Japan,” Journal of the Japanese and International Economies, 19, p. 338-365.
[32]Kim, S. W. and Lee, B. S. (2008), “Stock Return, Asymmetric Volatility, Risk Aversion, and Business Cycle: Some New Evidence,” Economic Inquiry, 46, p. 131-148.
[33]Konstantin, K., Montagnoli, A., Napolitano, O., and Siliverstovs, B. (2009), “Assessing the Impact of the ECB''s Monetary Policy on the Stock Markets: A Sectoral View,” Economics Letters, 105, p. 211-213.
[34]Lunde A. and Timmermann, A. (2004), “Duration Dependence in Stock Prices: An Analysis of Bull and Bear Markets,” Journal of Business and Economic Statistics, 22, p. 253-273.
[35]Maheu, J. M., and McCurdy, T. H. (2000), “Identifying Bull and Bear Markets in Stock Returns,” Journal of Business and Economic Statistics, 18, p. 100-112.
[36]Martens, M. and Poon, S. H. (2001), “Returns Synchronization and Daily Correlation Dynamics between International Stock Markets,” Journal of Banking and Finance, 25, p. 1805-1827.
[37]Masih, R. and Masih, A. M. (2001) , “Long and Short Term Dynamic Causal Transmission Amongst International Stock Markets, ”Journal of International Money and Finance, 20, p. 563-587.
[38]Merton, R. C. (1980), “On Estimating the Expected Return on the Market: An Exploratory Investigation,” Journal of Financial Economics, 8, p. 323-361.
[39]Moon, G. H. and Yu, W. C. (2010), “Volatility Spillovers between the US and China Stock Markets: Structural Break Test with Symmetric and Asymmetric GARCH Approaches,” Global Economic Review, 39, p. 129-149.
[40]Moon, H. C. and Jung, J. S. (2010), “Northeast Asian Cluster through Business and Cultural Cooperation,” Journal of Korea Trade, 14, p. 29-53.
[41]Neri, S. and Nobili, A. (2010), “The Transmission of US Monetary Policy to the Euro Area,” International Finance, 13, p. 55-78.
[42]Nelson, D. B. (1991), “Conditional Heteroskedasticity in Asset Return: A New Approach,” Econometrica, 2, p. 347--370.
[43]Patelis, A. D. (1997), “Stock Return Predictability and the Role of Monetary Policy,” Journal of Finance, 52, p. 1951-72.
[44]Pagan A. R. and Sossounov, K. A. (2003), “A Simple Framework for Analyzing Bull and Bear markets,” Journal of Applied Econometrics, 18, p. 23-46.
[45]Peek, J. and Rosengren, E. S. (1997), “The International Transmission of Financial Shocks: The Case of Japan,” American Economic Review, 87, p. 495-505.
[46]Phylaktis, K. and Xia, L. C. (2009), “Equity Market Comovement and Contagion: A Sectoral Perspective,” Financial Management, 38, p. 381-409.
[47]Rigobon, R. and Sack, B. (2003), “Measuring the Reaction of Monetary Policy to the Stock Market,” Quarterly Journal of Economics, 118, p. 639-669.
[48]Thorbecke, W. (1997), “On the Stock Market Returns and Monetary Policy,” Journal of Finance, 52, p. 635-654.
[49]Wongswan, J. (2006), “Transmission of Information across International Equity Markets,” Review of Financial Studies, 19, p. 1157-1189.
[50]Worthington, A. and Higgs, H. (2004), “Transmission of Equity Returns and Volatility in Asian Developed and Emerging Markets: A Multivariate GARCH Analysis,” International Journal of Finance and Economics, 9, p. 71-80.


 
 
 
 
第一頁 上一頁 下一頁 最後一頁 top
QR Code
QRCODE

臺灣人文及社會科學引文索引資料庫

目前上線人數：682（臺灣：654，外國：28） ／ 本年度總使用人次：2241491 ／ 訪客人次（自102年09月）：68034655
國家圖書館著作權聲明 Copyright © 2013 All rights reserved.
本館地址: 100201臺北市中山南路20號． 本館地圖及交通資訊．
總機：(02)23619132．最佳瀏覽解析度為1024x768以上