本文研究了過去在討論時較少被提及、但在近年來卻隨著新興市場的崛起以及地緣政治的發展而顯得愈發重要的澳大利亞股市以及澳幣匯率與經濟綜合領先指標對當地盛產並同時對世界經濟有重大影響之黃金、銅和近年來最備受期待能徹底改變人們生活樣貌的鋰金屬價格在遭遇市場動盪前後彼此間的互動關係，藉由將過去數年內對人類社會造成極大影響的COVID疫情做為區隔，分別針對市場正常時期(2014/01-2019/12)以及市場動盪時期(2020/1-2023/10)兩個時期下之時間序列進行分析。透過使用ADF單根檢定、Johansen共整合檢定、VAR模型、VECM模型、Granger因果關係檢驗、衝擊反應分析、預測誤差變異數分解等多樣計量方法來進行實證研究。
透過Granger因果關係檢驗與預測誤差變異數分解的結果，本研究發現在市場正常時期下，澳幣匯率變動能在短期下對澳股變化做出指引，同時黃金價格、銅價格的變動在長短期下皆能對澳洲股市的變動具有一定之解釋能力；此外澳股變動、澳幣匯率變動、黃金價格變動也對鋰價格的變動在長短期下皆具有領先關係。後續的衝擊反應分析中可以看到澳股、澳幣對鋰價格產生負向衝擊，同時黃金價格、銅價格則對澳股具有正向之衝擊。而澳幣匯率對澳股為負向衝擊、黃金價格對鋰價格為負向衝擊等。
而在市場動盪時期下則出現了截然不同的結果，上述之領先落後關係皆不復存在，取而代之的是澳股、澳幣匯率以及綜合經濟領先指標能對黃金價格在長短期下做出指引以及澳股、鋰價、黃金變動皆領先於綜合領先指標變動，特別關注到的是澳股在此期間對黃金產生的衝擊為正向，顯現黃金做為傳統避險資產的性質似乎出現了動搖，同時綜合領先指標相比正常時期而產生了更多的回饋關係等，使投資者能夠藉由此類相關之資訊以調整投資組合來符合個人之投資偏好。

This study investigates the relationships among six variables—Australian stock market, Australian dollar exchange rate, OECD Australia's Composite Leading Indicator, gold, copper, and lithium—during two distinct periods defined by the COVID-19 pandemic: the normal market period (January 2014 - December 2019) and the turbulent market period (January 2020 - October 2023). Using methods such as the Granger causality test and impulse response analysis, the study finds the following:
1. During the normal market period, the Australian stock market and the Australian dollar exhibit a negative Granger causality with lithium prices. Additionally, gold and copper prices show a positive causality with the Australian stock market. Further analysis reveals a negative causality from the Australian dollar exchange rate to the Australian stock market and from gold prices to lithium prices.
2. In contrast, during the turbulent market period, the previously mentioned lead-lag relationships disappear. Instead, the Australian stock market shows a positive Granger causality with gold prices. The Composite Leading Indicator has a negative causality with gold prices, and the relationship between the Australian dollar and gold prices varies in the short and long term. Moreover, the Australian stock market and lithium prices positively lead the Composite Leading Indicator, while gold prices negatively lead the Australian dollar.

1. Akaike, H. (1974). A new look at the statistical model identification. IEEE Transactions on Automatic Control, 19(6), 716-723.
2. Akram, Q. F. (2009). Commodity prices, interest rates and the dollar. Energy Economics, 31(6), 838-851.
3. Ayres, J., Hevia, C., & Nicolini, J. P. (2020). Real exchange rates and primary commodity prices. Journal of International Economics, 122, Article 103261.
4. Bakas, D., & Triantafyllou, A. (2018). The impact of uncertainty shocks on the volatility of commodity prices. Journal of International Money and Finance, 87, 96-111.
5. Baur, D. G., & McDermott, T. K. (2010). Is gold a safe haven? International evidence. Journal of Banking & Finance, 34(8), 1886-1898.
6. Beckmann, J., Belke, A., & Czudaj, R. (2014). Does global liquidity drive commodity prices? Journal of Banking & Finance, 48, 224-234.
7. Ben Zeev, N., Pappa, E., & Vicondoa, A. (2017). Emerging economies business cycles: The role of commodity terms of trade news. Journal of International Economics, 108, 368-376.
8. Berger, T., Grabert, S., & Kempa, B. (2017). Global macroeconomic uncertainty. Journal of Macroeconomics, 53, 42-56.
9. Black, A. J., Klinkowska, O., McMillan, D. G., & McMillan, F. J. (2014). Forecasting Stock Returns: Do Commodity Prices Help? Journal of Forecasting, 33(8), 627-639.
10. Bodart, V., Candelon, B., & Carpantier, J. F. (2012). Real exchanges rates in commodity producing countries: A reappraisal. Journal of International Money and Finance, 31(6), 1482-1502.
11. Bodart, V., Candelon, B., & Carpantier, J. F. (2015). Real exchanges rates, commodity prices and structural factors in developing countries. Journal of International Money and Finance, 51, 264-284.
12. Caporale, G. M., Spagnolo, F., & Spagnolo, N. (2017). Macro News and Commodity Returns. International Journal of Finance & Economics, 22(1), 68-80.
13. Chan, K. F., Treepongkaruna, S., Brooks, R., & Gray, S. (2011). Asset market linkages: Evidence from financial, commodity and real estate assets. Journal of Banking & Finance, 35(6), 1415-1426.
14. Chen, Y. C., Rogoff, K. S., & Rossi, B. (2010). Can Exchange Rates Forecast Commodity Prices? Quarterly Journal of Economics, 125(3), 1145-1194.
15. Cologni, A., & Manera, M. (2008). Oil prices, inflation and interest rates in a structural cointegrated VAR model for the G-7 countries. Energy Economics, 30(3), 856-888.
16. Coudert, V., Couharde, C., & Mignon, V. (2015). On the impact of volatility on the real exchange rate - terms of trade nexus: Revisiting commodity currencies. Journal of International Money and Finance, 58, 110-127.
17. Creti, A., Joëts, M., & Mignon, V. (2013). On the links between stock and commodity markets' volatility. Energy Economics, 37, 16-28.
18. Delatte, A. L., & Lopez, C. (2013). Commodity and equity markets: Some stylized facts from a copula approach. Journal of Banking & Finance, 37(12), 5346-5356.
19. 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(366), 427-431.
20. Drechsel, T., & Tenreyro, S. (2018). Commodity booms and busts in emerging economies. Journal of International Economics, 112, 200-218.
21. Engle, R.F., & Granger, C.W.J. (1987). Co-Integration and error correction: representation, estimation, and testing. Journal of The Econometric Society, 55(2), 251-276.
22. Elder, J., Miao, H., & Ramchander, S. (2012). Impact of macroeconomic news on metal futures. Journal of Banking & Finance, 36(1), 51-65.
23. Fernández, A., González, A., & Rodríguez, D. (2018). Sharing a ride on the commodities roller coaster: Common factors in business cycles of emerging economies. Journal of International Economics, 111, 99-121.
24. Ferraro, D., Rogoff, K., & Rossi, B. (2015). Can oil prices forecast exchange rates? An empirical analysis of the relationship between commodity prices and exchange rates. Journal of International Money and Finance, 54, 116-141.
25. Gargano, A., & Timmermann, A. (2014). Forecasting commodity price indexes using macroeconomic and financial predictors. International Journal of Forecasting, 30(3), 825-843.
26. Glick, R., & Leduc, S. (2012). Central bank announcements of asset purchases and the impact on global financial and commodity markets. Journal of International Money and Finance, 31(8), 2078-2101.
27. Gorton, G., & Rouwenhorst, K. G. (2006). Facts and fantasies about commodity futures. Financial Analysts Journal, 62(2), 47-68.
28. Granger, C.W.J. (1969). Investigating causal relations by econometric models and cross-spectral methods. Journal of The Econometric Society, 37(3), 424-438.
29. Granger, C.W.J., & Newbold, P. (1974). Spurious regression in econometrics. Journal of The Econometrics, 2(2), 111-120.
30. Granger, C. W. J. (1981). Some properties of time-series data and their use in economic-model specification. Journal of Econometrics, 16(1), 121-130.
31. Hamilton, J. D. (1983). Oil and thee macroeconomy since WORLD-WAR-II. Journal of Political Economy, 91(2), 228-248.
32. Hammoudeh, S., Nguyen, D. K., & Sousa, R. M. (2015). US monetary policy and sectoral commodity prices. Journal of International Money and Finance, 57, 61-85.
33. Hess, D., Huang, H. & Niessen, A. (2008). How do commodity futures respond to macroeconomic news? Financ Mark Portfolio Manag, 22, 127-146.
34. Hollstein, F., Prokopczuk, M., Tharann, B., & Simen, C. W. (2021). Predictability in commodity markets: Evidence from more than a century. Journal of Commodity Markets, 24, Article 100171.
35. Iyke, B. N., & Ho, S. Y. (2021). Stock return predictability over four centuries: The role of commodity returns. Finance Research Letters, 40, Article 101711.
36. Johansen, S. (1988). Statistical analysis of cointegration vectors. Journal of Economic Dynamics and Control, 12, 231-254.
37. Junttila, J., Pesonen, J., & Raatikainen, J. (2018). Commodity market-based hedging against stock market risk in times of financial crisis: The case of crude oil and gold. Journal of International Financial Markets Institutions & Money, 56, 255-280.
38. Kocaarslan, B., Sari, R., Gormus, A., & Soytas, U. (2017). Dynamic correlations between BRIC and U.S. stock markets: The asymmetric impact of volatility expectations in oil, gold and financial markets. Journal of Commodity Markets, 7, 41-56.
39. Nelson, C.R. & Plosser, C.R. (1982). Trends and random walks in macroeconomic time series: Some evidence and implications. Journal of Monetary Economics, 10(2), 139-162.
40. Pukthuanthong, K., & Roll, R. (2011). Gold and the Dollar (and the Euro, Pound, and Yen). Journal of Banking & Finance, 35(8), 2070-2083.
41. Ratti, R. A., & Vespignani, J. L. (2015). Commodity prices and BRIC and G3 liquidity: A SFAVEC approach. Journal of Banking & Finance, 53, 18-33.
42. Rossi, B. (2012). The Changing Relationship Between Commodity Prices and Equity Prices in Commodity Exporting Countries. Imf Economic Review, 60(4), 533-569.
43. Said, S. E., & Dickey, D. A. (1984). Testing for unit roots in autoregressive-moving average models of unknown order. Biometrika, 71(3), 599-607.
44. Schwarz, G. (1978). Estimating the dimension of a model. The Annals of Statistics, 6(2), 461-464.
45. Silvennoinen, A., & Thorp, S. (2013), Financialization, crisis and commodity correlation dynamics, Journal of International Financial Markets, Institutions and Money, 24, 42-65.
46. Sims, C.A. (1980). Macroeconomics and Reality. Journal of The Econometric Society, 48(1), 1-48.
47. Sjaastad, A.L., & Scacciavillani, F. (1996). The price of gold and the exchange rate, Journal of International Money and Finance,15(6), 879-897.
48. Wang, W. H., & Cheung, Y. W. (2023). Commodity price effects on currencies. Journal of International Money and Finance, 130, Article 102745.