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研究生:黄詩芸
研究生(外文):Shih-yun Huang
論文名稱:總經不確定性,不同金融市場間的相關係數與三種資產的資產配置策略之探討
論文名稱(外文):Macroeconomic Uncertainty, Correlations between Different Financial Markets, and Three-Asset Allocation Strategies
指導教授:張光第張光第引用關係
指導教授(外文):Guang-di Chang
口試委員:張光第
口試委員(外文):Guang-di Chang
口試日期:2013-04-11
學位類別:碩士
校院名稱:國立臺灣科技大學
系所名稱:財務金融研究所
學門:商業及管理學門
學類:財務金融學類
論文種類:學術論文
論文出版年:2013
畢業學年度:101
語文別:英文
論文頁數:33
中文關鍵詞:總經不確定性相關係數資產配置策略
外文關鍵詞:macroeconomic uncertaintycorrelationsasset allocation strategy
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本研究探討總經不確定性與不同金融市場間的相關係數之關聯,並且提供三種資產的資產配置策略。採用物價指數、工業生產指數與恐慌指數的月資料來做為總經變數。樣本選取2004年到2011年G7和新興亞洲等國的資料。此外,選取VECM模型來檢定總經不確定性對G7和新興亞洲等國指數的影響。
研究結果顯示有六個投資組合的結果是顯著的。在已開發國家中,相關係數和工業生產指數的變動成正相關。然而,在全球股市中,新興市場物價指數的變動、已開發市場和新興市場工業生產指數的變動與恐慌指數的變動對已開發市場新興市場間的相關係數的影響也是顯著的。因此,當總經不確定性改變時,投資人和基金經理人可以透過重新調整投資組合內各資產的比例而獲利。
This study is aimed to investigate whether there is a relationship between correlations in different financial markets and macroeconomic uncertainty factors, regarding three-asset allocation strategies. We apply the monthly data of inflation, industrial production and the VIX Index to be the proxies of the macroeconomic uncertainties. Our data samples include the G7 and emerging Asian countries from 2004 to 2011. Furthermore, the vector error correction model (VECM) is used to examine the effects of uncertainty in macroeconomic variables on correlations between the G7 and emerging Asia indices.
Our results show that correlations of six portfolios are significantly affected by different macroeconomic variables. In summary, in developed countries, changes in the correlations are positively related to changes in industrial production uncertainty; and for World Stock Portfolio, changes in emerging markets inflation uncertainty, changes in industrial production uncertainty of developed and emerging markets and changes in the VIX Index are significantly associated with correlations between developed and emerging Asia stocks markets. We conclude that investors and asset managers can benefit from diversifying into different financial markets and asset classes.
Abstract 1
I. Introduction 3
II. Literature review 4
III. Data and methodology 5
1. Data and Summary Statistics 5
2. Empirical Method 11
IV. Results 18
V. Conclusions 29
Reference 32
Beber, A. and M. W. Brandt, 2009, “Resolving macroeconomic uncertainty in stock and bond markets,” Review of Finance, 13 (1), 1-45.
Baum, C. F. and C. Wan, 2010, “Macroeconomic uncertainty and credit default swap spreads,” Applied Financial Economics, 20, 1163-1171.
Bredin, D. and S. Fountas, 2009, “Macroeconomic uncertainty and performance in the European Union,” Journal of International Money and Finance, 28, 972-986.
Chang, G.D. and W.H. Chen, 2011, “Macroeconomic uncertainty, correlations between global financial markets, and portfolio strategies,” submitted to the International Review of Economics and Finance.
Hope, Ole-Kristian and T. Kang, 2005, “The association between macroeconomic uncertainty and analysts’ forecast accuracy,” Journal of International Accounting Research, 1, 23-38.
Gilmore, C.G. and G.M. McManus, 2002, “International portfolio diversification: US and Central European equity markets,” Emerging Markets Review, 3, 69-83.
Granger, C.W.J. and P. Newbold, 1974, “Spurious regression in econometrics,” Journal of Econometrics, 2, 111-120.
Flavin, T.J. and Wickens M.R, 2003, “Macroeconomic influences on optimal asset allocation,” Review of Financial Economics, Volume 12, Issue 2, 207
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