本文探討2018/3中美貿易戰前後美國對石油、黃金與中港台金融市場的影響。首先以已實現波動度GARCH模型(Realized Volatility GARCH model) 探討美國股市對中港台三地股市訊息傳遞效應的變化，接著採用下三角對角化GARCH模型(Diagonal Vech GARCH model)，研究美元指數與石油和黃金價格、中國、台灣和香港匯率的互動，藉以將探討範圍拓展至美國政策的不確定性對全球景氣、避險情緒與國際資本移動的互動變化作為穩健性檢定。實證結果顯示，在貿易戰之前，美國金融市場對黃金、石油、中港台三地股市與匯率市場的報酬與波動度都有顯著性的影響。在貿易戰之後，美國股市對中國、台灣和香港股市的影響僅存在於開盤時。此外，實證得知，中國是美國波動外溢的最大接受國。再者，美元報酬率波動度與石油、黃金與中國匯率報酬波動度存在雙邊互動，且互動幅度於貿易戰之後變大。整體而言，中美貿易戰之後，美國失去了部分對台灣和香港金融市場的影響力。由全球性商品市場的角度來看，中美貿易戰開始之後，美國對全球性金融市場方向性的影響力可能降低了。

This paper studies the information transmission effects from the US to China, Taiwan, Hong Kong, and commodities in the mean and variance of prices in terms of the impact of the US-China trade-war in March 2018. We construct a two-factor structure in a realized GARCH, adopt intraday realized volatility as an exogenous variable to improve volatility estimation, and divide the daily close-to-close returns into overnight returns (previous close-to-open) and daytime returns (open-to-close) to examine the impact of the US stock market on the three Asian stock markets before and after the trade war induced by the Trump administration. Additionally, this study adopts bivariate GARCH model with diagonal vech parameterization to investigate the bilateral relationships between the US dollar index and the global commodities prices, China, Taiwan, and Hong Kong exchange rates as the robustness. The empirical results suggest that the effects from the US stock market decrease in the post-trade war period, its influence only exists in the Taiwan and Hong Kong market opening time spans, and China is the largest recipient of US volatility spillovers. As to the macroeconomic forecasting and hedging demand, oil and gold prices volatility have bilateral interactions with US dollar, the representing of the uncertainty from the US. After the policy uncertainty initiating, the US may lost the guidance stance to the global financial markets.

CONTENTS
1.Introduction …………………………………………………………………………………………………………………1
2.Data and Methodology ……………………………………………………………………………………………8
2.1 Data Description …………………………………………………………………………………………………8
2.2 Methodology ……………………………………………………………………………………………………………18
3. Empirical Results and Analysis………………………………………………………………23
4.Robust test …………………………………………………………………………………………………………………31
4.1 Data Description…………………………………………………………………………………………………31
4.2 Methodology………………………………………………………………………………………………………………42
4.3 Empirical Results and Analysis……………………………………………………………46
5.Conclusion ……………………………………………………………………………………………………………………50
References……………………………………………………………………………………………………………………………53

LIST OF TABLES
Table 1 Descriptive statistics (pre-trade war period)…………12
Table 2 Descriptive statistics (post-trade war period)………14
Table 3 Empirical results of bivariate realized GARCH (1,1) model for pre-trade war period (2007/1/2–2018/3/22)………………29
Table 4 Empirical results of bivariate realized GARCH (1,1) model for post-trade war period (2018/3/23–2019/6/30)…………30
Table 5 Descriptive statistics (pre-trade war period)…………36
Table 6 Descriptive statistics (post-trade war period)………37
Table 7 Empirical results of diagonal vech GARCH (1,1) model for pre-trade war period (2011/1/4–2018/3/22)………………………………49
Table 8 Empirical results of diagonal vech GARCH (1,1) model for post-trade war period (2018/3/23–2020/9/30)…………………………50

LIST OF FIGRUES
Figure 1 Stock Prices of S&P 500 (SP), Shanghai Composite Index (SSEC), Taiwan Capitalization Weighted Stock Index (TAIEX), and Hang Seng Index (HSI).…………………………………………………………16
Figure 2 Realized Volatilities of SP, SSEC, TAIFEX, and HSI………………………………………………………………………………………………………………………………………………18
Figure 3 US Dollar Index Spot price (DXY), Brent crude oil spot price (OIL), Gold spot price (GOLD), US Dollar (USD) to China Renminbi (CNY) exchange rate (USDCNY), US Dollar (USD) to Taiwan Dollar (TWD) exchange rate (USDTWD), and US Dollar (USD) to Hong Kong Dollar (HKD) exchange rate (USDHKD)………39
Figure 4 Realized Volatilities of DXY, OIL, GOLD, USDCNY, USDTWD, and USDHKD ……………………………………………………………………………………………………41

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