2020年全球爆發COVID-19，重創世界經濟與金融市場，至2022年全球染疫死亡人數超過600萬人。為避免因疫情對經濟造成二次傷害，美國率先實施量化寬鬆政策發放大量補助，各國央行紛紛跟進釋放大量貨幣。本研究欲透過時間序列等研究方法探討在疫情爆發的2020年至2021年間，美元指數期貨價格、比特幣兌美元價格、恐慌指數、黃金期貨價格、銅期貨價格間是否有彼此互相影響關係或長期穩定關係與短期之變化。結果發現，本研究之變數間與銅期貨價格具有共整關係，因此採用向量誤差正模型分析之。結果顯示，在長期共整合下美元指數與比特幣價格兩者之間有格蘭傑因果的回饋關係。同時數據顯示，比特幣兌美元價格的漲跌與銅期貨價格有同步的狀況。後續追蹤10個月後的數據預測變化，僅有一個月出現與結果不符合的狀況。

The global outbreak of the COVID-19 pandemic in 2020 has severely hit the world economy and financial markets. By 2022, the global death toll from the epidemic will exceed 6 million. To avoid secondary damage to the economy caused by the epidemic, the United States took the lead in implementing the quantitative easing policy to issue large amounts of subsidies, and central banks around the world followed suit and released large amounts of money. This study intends to use time series and other research methods to explore whether there is a causal relationship or a long-term stable relationship and short-term changes between the US dollar index futures price, bitcoin to the US dollar exchange rate, VIX, gold futures price, and copper futures prices during the period from 2020 to 2021 when the epidemic broke out. It is empirically found that the variables in this study have a co-integration relationship with the gold futures price, so the VECM is used to analyze it.

The results show that there is a Granger causal feedback relationship between the US dollar index and Bitcoin price under long-term co-integration. At the same time, the data shows that the rise and fall of the price of Bitcoin against the US dollar is synchronized with the price of copper futures. The data forecast changes after 10 months of follow-up were followed, and only one month appeared inconsistent with the results.

Adekoya, O. B., Oliyide, J. A., & Oduyemi, G. O. (2021). How COVID-19 upturns the hedging potentials of gold against oil and stock markets risks: Nonlinear evidences through threshold regression and markov-regime switching models. Resources Policy, 70, 101926.
Ahmad, W., Hernandez, J. A., Saini, S., & Mishra, R. K. (2021). The US equity sectors, implied volatilities, and COVID-19: What does the spillover analysis reveal? Resources Policy, 72, 102102.
Akhtaruzzaman, M., Boubaker, S., Lucey, B. M., & Sensoy, A. (2021). Is gold a hedge or a safe-haven asset in the COVID–19 crisis? Economic Modelling, 102, 105588.
Al-Awadhi, A. M., Alsaifi, K., Al-Awadhi, A., & Alhammadi, S. (2020). Death and contagious infectious diseases: Impact of the COVID-19 virus on stock market returns. Journal of behavioral and experimental finance, 27, 100326.
Baek, C., & Elbeck, M. (2015). Bitcoins as an investment or speculative vehicle? A first look. Applied Economics Letters, 22(1), 30-34.
Baker, S. R., Bloom, N., Davis, S. J., Kost, K., Sammon, M., & Viratyosin, T. (2020). The unprecedented stock market reaction to COVID-19. The review of asset pricing studies, 10(4), 742-758.
Basher, S. A., & Sadorsky, P. (2016). Hedging emerging market stock prices with oil, gold, VIX, and bonds: A comparison between DCC, ADCC and GO-GARCH. Energy Economics, 54, 235-247.
Baur, D. G., & Lucey, B. M. (2010). Is gold a hedge or a safe haven? An analysis of stocks, bonds and gold. Financial Review, 45(2), 217-229.
Bhuyan, R., Lin, E. C., & Ricci, P. F. (2010). Asian stock markets and the Severe Acute Respiratory Syndrome (SARS) epidemic: implications for health risk management. International journal of environment and health, 4(1), 40-56.
Bouri, E., Cepni, O., Gabauer, D., & Gupta, R. (2021). Return connectedness across asset classes around the COVID-19 outbreak. International Review of Financial Analysis, 73, 101646.
Briere, M., Oosterlinck, K., & Szafarz, A. (2015). Virtual currency, tangible return: Portfolio diversification with bitcoin. Journal of Asset Management, 16(6), 365-373.
Carr, P., & Wu, L. (2006). A tale of two indices. The Journal of Derivatives, 13(3), 13-29.
Chen, C., Liu, L., & Zhao, N. (2020). Fear sentiment, uncertainty, and bitcoin price dynamics: The case of COVID-19. Emerging Markets Finance and Trade, 56(10), 2298-2309.
Ciaian, P., Rajcaniova, M., & Kancs, D. A. (2016). The economics of BitCoin price formation. Applied economics, 48(19), 1799-1815.
Corbet, S., Larkin, C., & Lucey, B. (2020). The contagion effects of the COVID-19 pandemic: Evidence from gold and cryptocurrencies. Finance Research Letters, 35, 101554.
Dickey, D. A., & Fuller, W. A. (1979). Distribution of the estimators for autoregressive time series with a unit root. Journal of the American statistical association, 74(366a), 427-431.
Elshkaki, A., Graedel, T. E., Ciacci, L., & Reck, B. K. (2016). Copper demand, supply, and associated energy use to 2050. Global environmental change, 39, 305-315.
Engle, R. F., & Granger, C. W. (1987). Co-integration and error correction: representation, estimation, and testing. Econometrica: journal of the Econometric Society, 251-276.
Grobys, K. (2021). When Bitcoin has the flu: On Bitcoin’s performance to hedge equity risk in the early wake of the COVID-19 outbreak. Applied Economics Letters, 28(10), 860-865.
Kapetanios, G., Mumtaz, H., Stevens, I., & Theodoridis, K. (2012). Assessing the economy‐wide effects of quantitative easing. The Economic Journal, 122(564), F316-F347.
Konstantinidi, E., & Skiadopoulos, G. (2011). Are VIX futures prices predictable? An empirical investigation. International Journal of Forecasting, 27(2), 543-560.
Konstantinidi, E., & Skiadopoulos, G. (2011). Are VIX futures prices predictable? An empirical investigation. International Journal of Forecasting, 27(2), 543-560.
Kurka, J. (2019). Do cryptocurrencies and traditional asset classes influence each other? Finance Research Letters, 31, 38-46.
Lawrence, C. (2003). Why is gold different from other assets? An empirical investigation. London, UK: The World Gold Council.
Lee, J., & Yue, C. (2017). Impacts of the US dollar (USD) exchange rate on economic growth and the environment in the United States. Energy Economics, 64, 170-176.
Marfatia, H. A. (2020). Investors’ risk perceptions in the US and global stock market integration. Research in International Business and Finance, 52, 101169.
Meinusch, A., & Tillmann, P. (2016). The macroeconomic impact of unconventional monetary policy shocks. Journal of Macroeconomics, 47, 58-67.
Mokni, K., & Ajmi, A. N. (2021). Cryptocurrencies vs. US dollar: Evidence from causality in quantiles analysis. Economic Analysis and Policy, 69, 238-252.
Nelson, C. R., & Plosser, C. R. (1982). Trends and random walks in macroeconmic time series: some evidence and implications. Journal of monetary economics, 10(2), 139-162.
Ouandlous, A., Barkoulas, J. T., & Alhaj-Yaseen, Y. (2018). Persistence and discontinuity in the VIX dynamics. Chaos, Solitons & Fractals, 113, 333-344.
Phillips, P. C., & Perron, P. (1988). Testing for a unit root in time series regression. Biometrika, 75(2), 335-346.
Ramelli, S., & Wagner, A. F. (2020). Feverish stock price reactions to COVID-19. The Review of Corporate Finance Studies, 9(3), 622-655.
Said, S. E., & Dickey, D. A. (1984). Testing for unit roots in autoregressive-moving average models of unknown order. Biometrika, 71(3), 599-607.
Sarwar, G. (2012). Is VIX an investor fear gauge in BRIC equity markets? Journal of Multinational Financial Management, 22(3), 55-65.
Sims, C. A. (1980). Macroeconomics and reality. Econometrica: journal of the Econometric Society, 1-48.
Tully, E., & Lucey, B. M. (2007). A power GARCH examination of the gold market. Research in International Business and Finance, 21(2), 316-325.
Yousfi, M., Zaied, Y. B., Cheikh, N. B., Lahouel, B. B., & Bouzgarrou, H. (2021). Effects of the COVID-19 pandemic on the US stock market and uncertainty: A comparative assessment between the first and second waves. Technological Forecasting and Social Change, 167, 120710.
Zhang, D., Hu, M., & Ji, Q. (2020). Financial markets under the global pandemic of COVID-19. Finance research letters, 36, 101528.