臺灣博碩士論文加值系統

本文研究的目的在於探討3種經濟不確定性對於股票和商品間動態相關性之影響，樣本資料包含美國3大股票指數及8種能源及金屬商品，樣本期間為2000年1月至2021年12月，共264筆月資料。首先使用Engle(2002)提出的 DCC-GARCH 模型來估算股價和商品價格的動態相關係數，接著再以線性 OLS 模型檢驗不確定性對商品和股票報酬相關性之影響。本文同時使用波動率指數VIX為對照組，比較分析不確定指數與VIX的差異性。本文的實證結果顯示，不論是以標普500、道瓊和納斯達克指數三者與商品價格相關性來分析時，經濟不確定性對動態相關性的影響多強勢於VIX指數，當經濟不確定性上升時，股票和商品之相關性也會提高；VIX指數上升時，股票和商品之相關性會降低。

The purpose of this study is to explore the impact of three types of economic uncertainty on the dynamic correlation between stocks and commodities. The sample data includes the three major stock indices in the United States and eight energy and metal commodities. The sample period is from January 2000 to December 2021. Month, a total of 264 monthly records. First, the DCC-GARCH model proposed by Engle (2002) is used to estimate the dynamic correlation coefficients between stock prices and commodity prices, and then the linear OLS model is used to test the impact of uncertainty on the correlation between commodity and stock returns. This article also uses the volatility index VIX as the control group to compare and analyze the difference between the uncertainty index and VIX. The empirical results of this paper show that, regardless of the correlation between the S&P 500, the Dow Jones and the Nasdaq index and commodity prices, the impact of economic uncertainty on the dynamic correlation is stronger than that of the VIX index. When economic uncertainty rises, the correlation between stocks and commodities will also increase; when the VIX index rises, the correlation between stocks and commodities will decrease.

目錄 III
表目錄 V
表1各變數之敘述統計量 20
表2 標普 500 指數及商品相關性的 OLS 迴歸估計結果 28
表3 納茲達克指數及商品相關性的 OLS 迴歸估計結果 30
表4 道瓊指數及商品相關性的 OLS 迴歸估計結果 31
表5 經濟政策不確定性指數(EPU)統整三種美股指數和商品OLS 估計結果 32
表6 總體經濟不確定性(MU)統整三種美股指數和商品OLS 估計結果 33
表7 金融不確定性(FU)統整三種美股指數和商品OLS 估計結果 33
表8波動率指數(VIX)統整三種美股指數和商品OLS 估計結果 34
圖目錄 VI
圖1 研究流程圖 6
圖2 經濟政策不確定性指數(EPU)之趨勢圖 21
圖3 總體經濟不確定性指數(MU)之趨勢圖 21
圖4 金融不確定性指數(FU)之趨勢圖 22
圖5 波動率指數(VIX)之趨勢圖 23
圖6 標普 500 指數及商品相關性的DCC-GARCH 模型之估計結果圖 24
圖7 納茲達克指數及商品相關性的DCC-GARCH 模型之估計結果圖 25
圖8 道瓊指數及商品相關性的DCC-GARCH 模型之估計結果圖 26
第一章緒論 1
第一節研究動機與目的 1
第二節研究架構與流程 5
第二章文獻探討 7
第一節政策不確定性指標 7
第二節不確定性對金融市場的影響 10
第三章研究方法 15
第一節 DCC-GARCH模型 15
第二節模型設定 17
第四章實證結果 19
第五章結論 35
參考文獻 37

呂瑞秋和陳淑華，(2012)，黃金價格與股價指數、石油價格及波動率指數關係之研究，臺灣銀行季刊，第63卷第2期。
林青宜，（2021），經濟不確定性對股票與商品之動態關連性之影響。國立高雄科技大學金融資訊系碩士論文。
Atems, Bebonchu, Devin Kapper, & Eddery Lam. (2015). “Do exchange rates respond asymmetrically to shocks in the crude oil market?” Energy Economicsvol. 49, pp.227-238.
Arouri, M., Estay, C., Rault, C., & Roubaud, D. (2016). “Economic policy uncertainty and stock markets: Long-run evidence from the US.” Finance Research Letters. 18,pp.136-141.
Bollerslev, T. (1986). “Generalized autoregressive conditional heteroskedasticity.” Journal of Econometrics. 31, pp.307-327.
Bloom N., (2009), “The impact of uncertainty shock” Econometrica, 77,pp.623-685.
Brunnermeier, M.K. & L.H. Pedersen (2009),“Market liquidity and funding liquidity,”Review of Financial Studies. 22, pp.2201-2238.
Bekaert,G.,Hoerova,M. (2014) “The VIX, the variance premium and stock market volatility.” Journal of Econometrics. 183, pp.181–192
Bordo, M. D., Duca, J. V. & Koch, C, (2016),“Economic policy uncertainty and the credit channel: Aggregate and bank level U.S. evidence over several decades” Journal of Financial Stability. 26 , pp. 90-106.
Bakas, D., &Triantafyllou, A. (2019).“Volatility forecasting in commodity markets using macro uncertainty.” Energy Economics. 81, pp.79-94
Copeland, M., & T. Copeland (1999),“Market Timing: Style and Size Rotation Using the VIX,” Financial Analysts Journal. 55, pp.73-81
Claycomb, C., Droge, C. & Germain, R. (2001).“Applied process knowledge and market performance: The moderating effect of environmental uncertainty.” Journal of Knowledge Management. 5, pp. 264–277.
Engle, R. F. (1982).“Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation.” Econometrica. 50, pp.987-1007.
Engle, R. (2002).“Dynamic conditional correlation: A simple class of multivariate generalized autoregressive conditional heteroskedasticity models.” Journal of Business & Economic Statistics. 20, pp.339-350.
French K., Schwert W., Stambaugh R. (1987) “Expected stock returns and volatility” Journal of Financial Economics. 19, pp.3-29.
Fang, L., Chen, B., Yu, H., &Xiong, C. (2018).“The effect of economic policy uncertainty on the long-run correlation between crude oil and the US stock markets.” Finance Research Letters. 24, pp.56-63.
Gulen H., & Ion M. (2016).“Editor’s choice: Policy uncertainty and corporate investment.” Review of Financial Studies. 29, pp.523-564.
Ihsan Badshah, Riza Demirer, Muhammad Tahir Sulemanc (2019).“The effect of economic policy uncertainty on stock-commodity correlations and its implications on optimal hedging” Energy economics. 84, pp.1-10.
Jurado, K., Ludvigson, S. C., & Ng, S. (2015).“Measuring uncertainty.” American Economic Review. 105, pp.1177-1216.
Korajczyk, R.A.& R. Sadka (2008),“Pricing the Commonality across Alternative Measures of Liquidity,”Journal of Financial Economics. 87,pp.45-72.
Moore, T., & Wang, P. (2014).“Dynamic linkage between real exchange rates and stock prices: Evidence from developed and emerging Asian markets.” International Review of Economics & Finance. 29, pp.1-11.
Pastor, L. & R. Stambaugh (2003),“Liquidity Risk and Expected Stock Returns, Journal of Political Economy. 111, pp.642–685.
Phan, D. H. B., Iyke, B. N., Sharma, S. S., & Affandi, Y. (2021).“Economic policy uncertainty and financial stability–Is there a relation?.” Economic Modelling. 94, pp.1018-1029.
Qadan, M., & Yagil, J. (2012). “Fear sentiments and price: testing causality in-mean and in-variance. Applied Economics Letters. 19, pp.363-366
Sari, R., Soytas, U.,& Hacihasanoglu, E. (2011).Do global rick perceptions influence world oil prices？Energy Economics. 33, pp.515-524.
Segal, G., Shaliastovich, I., & Yaron, A. (2015).“Good and bad uncertainty: Macroeconomic and financial market implications.” Journal of Financial Economics. 117, pp.369-397.
Tang K., & Xiong W. (2012).“Index investment and the financialization of commodities.” Financial Analysts Journal. 68, pp.54-74.
Whaley, R.E (1993), “Derivatives on Market Volatility: Hedging Tools Long Overdue.” Journal of Derivatives. 1, pp.71-84
Wang S. L., & McPhail L. (2014).“Impacts of energy shocks on US agricultural productivity growth and commodity prices-A structural VAR analysis.” Energy Economics. 46, pp.435-444.