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| Title: | 各國股市與台灣股市之間外溢效果之研究
The Study of Spillover Effects of Stock Markets among Countries |
| Authors: | 石佳煌
SHIH, CHIA-HUANG |
| Contributors: | 黃仁德
蕭明福
HUANG, REN-DE
XIAO, MING-FU
石佳煌
SHIH, CHIA-HUANG |
| Keywords: | 外溢效果
向量自我迴歸模型
總外溢效果
動態外溢效果
Spillover Effect
Vector Autoregressive Model
Total Spillover Effect
Dynamic Spillover Effect |
| Date: | 2024 |
| Issue Date: | 2024-09-04 14:38:48 (UTC+8) |
| Abstract: | 隨著全球化的加速，國際間的經濟和金融活動日益緊密，市場的連動性明顯增強，在這樣的時空背景下，深入研究各國股市之間的互動關係，特別是對特定國家或區域的影響機制，將有助於更好地理解全球金融體系的運作規律。本文運用向量自我迴歸模型及Diebold 與 Yilmaz（2012）提出的外溢指標，並採用2004年4月至2023年12月的週報酬率與波動率數據，分析美國四大指數與台股加權指數間的關聯性，並進一步探討台灣、美國、日本、中國、香港、日本、英國、德國、及法國等國家股價指數之間的相互影響程度與方向。
本文實證結果，得到以下的結論：各國指數報酬率間具有高度連動性；恆生指數報酬率對台股指數報酬率造成的外溢效果最大；淨外溢效果顯示，台股指數報酬率在市場中主要為被其他指數影響者；淨成對外溢效果亦顯示，台股指數報酬率為被其他指數影響者；各國指數波動度間亦有高度連動性；恆生指數波動度對台股指數波動度造成的外溢效果最大；淨外溢效果顯示，台股指數波動度在市場中主要為被其他指數影響者；淨成對外溢效果亦顯示，台股指數波動度為被其他指數影響者；及金融危機時期，各國指數間的連動性升高。
With the acceleration of globalization, international economic and financial activities have become increasingly intertwined, significantly enhancing market interconnectivity. In this context, an in-depth study of the interactions between stock markets, particularly the impact mechanisms on specific countries or regions, will contribute to a better understanding of the operational patterns of the global financial system.
This paper employs the vector autoregression (VAR) model and the spillover index proposed by Diebold and Yilmaz (2012), using weekly return and volatility data from April 2004 to December 2023, to analyze the relationship between the four major U.S. indices and the Taiwan weighted index. Furthermore, it explores the degree and direction of mutual influence among the stock indices of Taiwan, the United States, Japan, China, Hong Kong, Japan, the United Kingdom, Germany, and France.
According to the research results, the following conclusions were obtained: there is a high degree of interconnectivity among the returns of various indices; the Hang Seng Index returns have the greatest spillover effect on the Taiwan Index returns; the net spillover effect shows that the Taiwan Index returns are primarily influenced by other indices in the market; the net pairwise spillover effect also indicates that the Taiwan Index returns are influenced by other indices; there is a high degree of interconnectivity among the volatilities of various indices; the Hang Seng Index volatility has the greatest spillover effect on the Taiwan Index volatility; the net spillover effect shows that the Taiwan Index volatility is primarily influenced by other indices in the market; the net pairwise spillover effect also indicates that the Taiwan Index volatility is influenced by other indices; and during the financial crisis period, the interconnectivity among various indices increased. |
| Reference: | 王朝仕、黃嘉興(2003)，〈台股指數對美國三大主要指數理性預期關係之探討〉，國立高雄第一科技大學金融營運系碩士論文。
朱正修(2004)，〈台灣股市與國際股市連動性之研究〉，國立成功大學統計學研究所碩士論文。
康文姿(2008)，〈美股指數波動對台股指數之影響—探究2008年電子與金融類股〉，國立屏東教育大學應用數學系碩士論文。
張瑛淑(2010)，〈台股指數、美股指數的預測及兩者關連性之分析〉，國立屏東教育大學應用數學系碩士論文。
郭維裕、李淯靖、陳致綱、林建秀(2015)，〈台灣產業指數的外溢效果〉，《經濟論文叢刊》，43:4，頁407-442。
Cheol, S. E. and S. Shim (1989), “International Transmission of Stock Market Movements,” Journal of Financial and Quantitative Analysis, 24:2, pp. 241-256.
Diebold, F. X. and K. Yilmaz (2012), “Better to Give than to Receive: Predictive Directional Measurement of Volatility Spillover,” International Journal of Forecasting, 28:1, pp. 57–66.
Diebold, F. X. and K. Yilmaz (2009), “Measuring Financial Asset Return and Volatility Spillovers, with Application to Global Equity,” Economic Journal, 119:534, pp. 158–171.
Darrat, A. F. and O. M. Benkato (2003), “Interdependence and Volatility Spillovers under Market Liberalization: The Case of Istanbul Stock Exchange,” Journal of Business Finance and Accounting, 30:2, pp. 1089–1114.
Engle, R. (2002), “Dynamic Conditional Correlation: A Simple Class of Multivariate Generalized Autoregressive Conditional Heteroskedasticity Models,” Journal of Business and Economic Statistics, 20:3, pp. 339-350.
Kim, H. L. (2015). “Volatility Spillover Dynamics and Relationship across G7 Financial Markets,” North American Journal of Economics and Finance, 33:4, pp. 328-365.
Koop, G., M. H. Pesaran, and S. M. Potter (1996) “Impulse Response Analysis in Non-Linear Multivariate Models,” Journal of Econometrics, 74:1, pp. 119-147.
Nikolaos, A., C. Floros, and R. Kizys (2016) “Dynamic Spillover Effects in Futures Markets: UK and US Evidence,” International Review of Financial Analysis, 48:3, pp. 406-418.
Nikolaos, A. and R. Kizys (2015). “Dynamic Spillovers between Commodity and Currency Markets,” International Review of Financial Analysis, 41:3, pp. 303-319.
Pesaran, H. H. and Y. Shin (1998), “Generalized Impulse Response Analysis in Linear Multivariate Models,” Economics Letters, 58:1, pp. 17–29.
Yilmaz, K. (2010), “Return and Volatility Spillovers among the East Asian Equity Markets,” Journal of Asian Economics, 21:3, pp. 304–313. |
| Description: | 碩士
國立政治大學
經濟學系
111258021 |
| Source URI: | http://thesis.lib.nccu.edu.tw/record/#G0111258021 |
| Data Type: | thesis |
| Appears in Collections: | [經濟學系] 學位論文
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