本文以中國ETF市場為證，採用馬可夫轉換模型（Markov-switching model）進行實證，觀察在國際間不同的貨幣政策下，資金流通快速的移動，是否會增加中國ETF市場風險結構，並同時劃分為緊縮與寬鬆兩個子樣本進行觀察，捕捉真實的報酬與風險的行徑。最後，本研究也加入油市來分析外溢效果。
    本文重點關注與滬深300指數相關的ETF，並取其收盤價與成交量的資料變數定義代表債市。中國與台灣的股市分別以滬深300指數和台灣加權指數作為代表，而油市以西德州原油作為代表，並用聯邦基準利率、一個月期國庫券固定期限利率和十年期公債固定期限利率來計算利差。資料使用期間為2012年7月18日至2018年9月28日。
本研究發現了油市對股市的外溢效果，研究結果顯示油價與FFR呈負向關係。因此可以預期當油價下跌時，FFR開始上升，則可進一步推知利差上升，而利差的增加使違約風險上升，由於市場處於貨幣緊縮政策下，市場資金逐漸從市場抽離，使流動性風險上升，股價開始下跌。相反的，在貨幣寬鬆政策下，熱錢開始湧入市場，使股票流動性上升，股價開始上升。另外，本研究也發現在緊縮的貨幣政策下對股票市場帶來的影響要大於在寬鬆的貨幣政策下。

This paper mainly studies China's economic market that under the different international monetary policies, the rapid movement of capital circulation will increase the risk structure of China's ETF market or not. In addition, this paper uses the Markov-switching model to investigate the spot and ETFs market with the most representative ETF of the CSI 300 Index from Jul. 18, 2012 to Sep. 28, 2018 and is simultaneously divided into two subsamples of tight and expansionary for observation to effectively capture the real returns and the path of risks. Finally, this paper also joined the oil market to analyse the spillover effect. 
  The results of this paper show that the oil market's volatility spillover effect on the stock market, oil price and FFR are negatively related. So it can be expected that when the oil price falls, FFR starts to rise, it can further infer that the spread spreads, and the increase in spreads makes the default risk As the market is in a monetary tightening policy, market funds are gradually withdrawing from the market, causing liquidity risks to rise, and stock prices begin to fall. In addition, this paper also finds that the impact on the stock market in the state of tight monetary policy is greater than loose monetary policy.

[CONTENTS]
CHAPTER I Introduction	1
1.1 The Development of the ETFs Market	1
1.2 Monetary Environment and Capital Market	4
1.2.1 The implementation of the US monetary policy	4
1.2.2 The rise of the Chinese market and the bilateral exchange rate	7
1.3 Purpose of this paper	11
1.4 Chart of How to Research	13
CHAPTER II Literature Review	14
2.1 The Effects of Monetary Policies on the Financial Commodities	14
2.2 The Relationship between the ETFs Market and the Stock Market	16
2.3 Market Efficiency and Hedging Benefits	20
2.4 Spillover Effects on Financial Markets	24
2.4.1 Spillover Effects between Stock and Oil Markets	24
2.4.2 Spillover Effects on International Financial Markets	26
CHAPTER III Methodology	29
3.1 Definitions of Variables	29
3.2 Methodology	30
3.2.1 Unit Root Test	30
3.2.1.1 Augmented Dickey-Fuller Test (ADF Test) 	30
3.2.1.2 Phillips-Perron Test (PP Test)	32
3.2.2 GARCH Model	32
3.2.3 Markov-switching Model	33
CHAPTER IV Data Source and Treatment	37
4.1 Source and Processing	37
4.2 Basic Statistics	38
CHAPTER V Empirical Results	42
5.1 Empirical Results from the Unit Root Test	42
5.2 Empirical Results from GARCH Model	44
5.3 Empirical Results from the Markov-switching Model	44
CHAPTER VI Conclusions	48
Refrerences  	 49

[Lists of Figures]
Figure 1 architecture diagram of the research	13
Figure 2 the trend of close and volume in each market	41
Figure 3 the trend of FFR and WTI	41
Figure 4 the smoothing probability of China and Taiwan under the regime of down-market and up-market	47

[Lists of Tables]
Table 1 basic statistic	40
Table 2 empirical results from the unit root test	42
Table 3 empirical results from GARCH model of the oil market	44
Table 4 empirical results from the Markov-switching model	46

1.	Alam, N., 2013, “A Comparative Performance Analysis of Conventional and Islamic Exchange-Traded Funds”, Journal of Asset Management, Vol. 14, No. 1, pp. 27-36.
2.	Alikhanov, A., 2013, “To What Extent are Stock Returns Driven by Mean and Volatility Spillover Effects? - Evidence from Eight European Stock Markets”, Review of Economic Perspectives; Brno, Vol. 13, No. 1, pp. 3.
3.	Anonymous, 2012-2013, “Foreign commodity exporters to China seek RMB settlement after US fiscal cliff fears”, FX Week, FX Invest, London, pp. 33.
4.	Anonymous, 2014, “RMB Private Bank - Company Capsule”, Wealth Insight, London.
5.	Anonymous, 2015, “An opportunity in RMB bonds”, AsianInvestor, Hong Kong.
6.	Antonakakis, N., Cunado, J., Filis, G., Gabauer, D., Perez de Gracia, F., 2018, “Oil Volatility, Oil and Gas Firms and Portfolio Diversification”, Energy Economics, Vol. 70, pp. 499-515.
7.	Bertone, S., Paeglis, I., Ravi, R.,2015, “(How) Has the Market Become More Efficient?”, Journal of Banking and Finance, Vol. 54, pp. 72-86.
8.	Bhuyan, R., Robbani, M., Talukdar, B., Jain, A., 2016, “Information Transmission and Dynamics of Stock Price Movements: An Empirical Analysis of BRICS and US Stock Markets”, International Review of Economics and Finance, Vol. 46, pp. 180-195.
9.	Boubaker, H., Raza, S.A., 2017, “A Wavelet Analysis of Mean and Volatility Spillovers between Oil and BRICS Stock Markets”, Energy Economics, Vol. 64, pp. 105-117.
10.	Bouri, E., 2015, “A Broadened Causality in Variance Approach to Assess the Risk Dynamics between Crude Oil Prices and the Jordanian Stock Market”, Energy Policy, Vol. 85, pp.271-279.
11.	Chacko, G., Das, S., Fan, R., 2016, “An Index-Based Measure of Liquidity”, Journal of Banking and Finance, Vol. 68, pp. 162-178.
12.	Chu, P.K., 2011, “Study on the Tracking Errors and Their Determinants: Evidence from Hong Kong Exchange Traded Funds”, Applied Financial Economics, Vol. 21, No. 4-6, pp. 309-315.
13.	De Jong, J.J., Rhee, S.G., 2008, “Abnormal Returns with Momentum/Contrarian Strategies Using Exchange-Traded Funds”, Journal of Asset Management, Vol. 9, No. 4, pp. 289-299.
14.	DiLellio, J.A., Hesse, R., Stanley, D.J., 2014, “Portfolio Performance with Inverse and Leveraged ETFs”, Financial Services Review, Vol. 23, No. 2, pp. 123-149.
15.	Du, L., He, Y., 2015, “Extreme Risk Spillovers between Crude Oil and Stock Markets”, Energy Economics, Vol. 51, pp. 455-465.
16.	Elton, E.J., 2002, “Spiders: Where Are the Bugs? ”, Journal of Business, Vol. 75, No. 3, pp. 453-472.
17.	Estrada, J., Vargas, M., 2012, “Black Swans, Beta, Risk, and Return”, Journal of Applied Finance, Vol. 22, No. 2, pp. 77-89.
18.	Gastineau, G.L., 2008, “The Short Side of 130/30 Investing for the Conservative Portfolio Manager”, Journal of Portfolio Management, Vol. 34, No. 2, pp. 39-52.
19.	Ge, F., Fan, Y., 2013, “Quantifying the Risk to Crude Oil Imports in China: An Improved Portfolio Approach”, Energy Economics, Vol. 40, pp. 72-80.
20.	Goldstein, M., Nicholas, L., 2006, “China's Exchange Rate Policy Dilemma”, American Economic Review, Vol. 96, pp. 422-426.
21.	Gomes, M., Chaibi, A., 2014, “Volatility Spillovers Between Oil Prices And Stock Returns: A Focus On Frontier Markets”, Journal of Applied Business Research; Laramie, Vol. 30, No. 2.
22.	Harper, J.T., Madura, J., Schnusenberg, O., 2006, “Performance Comparison between Exchange-Traded Funds and Closed-End Country Funds”, Journal of International Financial Markets, Institutions and Money, Vol. 16, No. 2, pp. 104-122.
23.	Hlawitschka, W., Tucker, M., 2008, “Utility Comparison between Security Selectors, Asset Allocators and Equally Weighted Portfolios within a Selected ETF Universe”, Journal of Asset Management, Vol. 9, No. 1, pp. 67-72.
24.	Ho, T.K., 2014, “Dilemma of the Silver Standard Economies: The Case of China”, Southern Economic Journal, Vol. 81, No. 2, pp. 519-534.
25.	Hoesli, M., Oikarinen, E., 2016, “Are Public and Private Asset Returns and Risks the Same? Evidence from Real Estate Data”, Journal of Real Estate Portfolio Management, Vol. 22, No. 2, pp. 179-198.
26.	Hu, J., 2014, “An Empirical Approach on Regulating China's Pension Investment”, European Journal of Law and Economics ,Vol. 37, No. 3, pp. 495-516.
27.	I, T., 2015, “Study on Return and Volatility Spillover Effects among Stock, CDS, and Foreign Exchange Markets in Korea”, Journal of East Asian Economic Integration, Vol. 19, No. 3, pp. 275-322.
28.	Jin, C.,Grissom, T.V., Ziobrowski, A.J., 2007, “The Mixed Asset Portfolio for Asia-Pacific Markets”, Journal of Real Estate Portfolio Management, Boston, Vol. 13, No. 3, pp. 249-256.
29.	Jouini, J., 2013, “Return and Volatility Interaction between Oil Prices and Stock Markets in Saudi Arabia”, Journal of Policy Modeling, Vol. 35, No. 6, pp. 1124-1144.
30.	Jouini, J., Harrathi, N., 2014, “Revisiting the Shock and Volatility Transmissions among GCC Stock and Oil Markets: A Further Investigation”, Economic Modelling, Vol. 38, pp. 486-494.
31.	Jung, H.Y., Wu, W.X., Xi, B.L., 2014, “Spillover Effects in Different Time Zones: Evidence from China, Korea and USA”, Actual Problems of Economics, Vol. 154, No. 4, pp. 428-437.
32.	Lin, B., Wesseh, P.J., Appiah, M.O., 2014, “Oil Price Fluctuation, Volatility Spillover and the Ghanaian Equity Market: Implication for Portfolio Management and Hedging Effectiveness”, Energy Economics, Vol. 42, pp. 172-182.
33.	Kadapakkam, P.R., Krause, T., Tse, Y., 2015, “Exchange Traded Funds, Size-Based Portfolios, and Market Efficiency”, Review of Quantitative Finance and Accounting, Vol. 45, No. 1, pp. 89-110.
34.	Karolyi, G.A., Lee, K.H., van Dijk, M., 2012, “Understanding Commonality in Liquidity around the World”, A.Journal of Financial Economics, Vol. 105, No. 1, pp. 82-112.
35.	Kuo, W., Li, Y.C., Chen, J.G., Lin, C.H., 2015, “Industrial Spillover Effects in the Taiwan Stock Market.”, Taiwan Economic Review, Vol. 43, No. 4, pp. 407-442.
36.	Kvamvold, J., Lindset, S., 2017, “Index Trading and Portfolio Risk”, Journal of Economics and Finance, Vol. 41, No. 1, pp. 78-99.
37.	Lee, J., 2014, “Cross-margining is key for the RMB futures market - SGX”, FX Week, London, Vol. 25, No. 31, pp. 6.
38.	Lingaraja, K., Selvam, M., Vasanth, V., Ramkumar, R.R., 2015, “Long-Run Overseas Portfolio Diversification Benefits and Opportunities of Asian Emerging Stock Markets and Developed Markets”, International Journal of Economics and Financial Issues, Vol. 5, No. 2, pp. 324-333.
39.	Liu, B.J., Wang, Y., Wang, J., Wu, X., Zhang, S., 2015, “Is China the Price Taker in Soybean Futures?”, China Agricultural Economic Review, Vol. 7, No. 3, pp. 389-404.
40.	McKinnon, R., Schnabl, G., 2009, “The Case for Stabilizing China's Exchange Rate: Setting the Stage for Fiscal Expansion”, China and World Economy, Vol. 17, No. 1, pp. 1-32.
41.	Moon, G.H., 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, Vol. 39, No. 2, pp. 129-149.
42.	Oskooe, P., Ali, S., 2012, “Oil Price Shocks and Stock Market in an Oil-Exporting Countries: Evidence from Iran Stock Market”, OPEC Energy Review, Vol. 36, No. 4, pp. 396-412.
43.	Peng, C., Zhu, H., Jia, X., You, W., 2017, “Stock Price Synchronicity to Oil Shocks across Quantiles: Evidence from Chinese Oil Firms”, Economic Modelling, Vol. 61, pp. 248-259.
44.	Pope, P.F., Yadav, P.K., 1994, “Discovering Errors in Tracking Error”, Journal of Portfolio Management, Vol. 20, No. 2, pp. 27-32.
45.	Roll, R., 1992, “A Mean/Variance Analysis of Tracking Error”, Journal of Portfolio Management, Vol. 18, No. 4, pp. 13-22.
46.	Safdar, R., Yan, C., 2016, “Information Risk, Stock Returns, and the Cost of Capital in China”, China Finance Review International ,Vol. 6, No. 1, pp. 77-95.
47.	Schlusche, B., 2009, “Price Formation in Spot and Futures Markets: Exchange Traded Funds vs. Index Futures”, Journal of Derivatives, Vol. 17, No. 2, pp. 26-40.
48.	Schubert, L., 2011, “Hedge Ratios for Short and Leveraged ETFs”, Atlantic Review of Economics/Revista Atlantica de Economia.
49.	Shin, S., Soydemir, G., 2010, “Exchange-Traded Funds, Persistence in Tracking Errors and Information Dissemination”, Journal of Multinational Financial Management, Vol. 20, No. 4-5, pp. 214-234.
50.	Takeda, A., Niranjan, M., Gotoh, J., and Kawahara, Y., 2013, “Simultaneous Pursuit of Out-of-Sample Performance and Sparsity in Index Tracking Portfolios”, Computational Management Science, Vol. 10, No. 1,  pp. 21-49.
51.	Tang, H., Xu, X.E., 2016, “Tracking Performance of Leveraged Energy Exchange-Traded Funds”, Journal of Derivatives, Vol. 23, No. 3, pp. 37-60.
52.	Tian, L., 2007, “Modeling Risk and Return in China's Stock Market”, University of California, Los Angeles, ProQuest Dissertations Publishing.
53.	Tsai, I.C., 2014, “Spillover of Fear: Evidence from the Stock Markets of Five Developed Countries”, International Review of Financial Analysis, Vol. 33, pp. 281-288.
54.	Tseng, Y.C., Lee, W.C., 2016, “Investor Sentiment and ETF Liquidity - Evidence from Asia Markets”, Advances in Management and Applied Economics, Vol. 6, No. 1, pp. 89-111.
55.	Wang, C., Chen, Y., Jin, X., 2018, “Research on the Effect of International Oil Prices Pass-through on China's New Energy Market”, Journal of Quantitative and Technical Economics, Vol. 35, No. 4, pp. 131-146.
56.	Wang, Y., 2010, “The internal and external equilibrium exchange rate of RMB: 1982-2010”, Frontiers of Economics in China, Beijing, Vol. 5, No. 2, pp. 210-231.
57.	Zhang, B., Li, X., 2010, “Currency appreciation and stock market performance: Evidence from China”, Frontiers of Economics in China, Beijing, Vol. 5, No. 3, pp. 393-411.
58.	Zhao, J., 2008, “Three essays dealing with open economy models based on the portfolio balance tradition”, University of Ottawa (Canada), ProQuest Dissertations Publishing.