Dynamic correlation between Crude Oil Price and Exchange rate: The Case of ASEAN-5
Keywords:DCC GARCH, Exchange rate, Gold price
This study examines the relationship between exchange rate and crude oil price of five Southeast Asia countries including Indonesia, Malaysia, Philippines, Thailand and Singapore from January 1979 to January 2022 using monthly data. Augmented Dickey-Fuller test is used to examine the stationarity of the data. DCC-GARCH model is used to investigate the correlation between oil price and exchange rate. The result shows that skewness, kurtosis, autocorrelation and ARCH effects were found in both oil price and exchange rate. Results suggested that both short run persistence (α) and long run persistence(β) are found to be highly significant for oil price and exchange rate of all countries except Indonesia. Furthermore, the correlation coefficients vary over times for all the countries studied. Negative relationship was found between oil price and exchange rate over most of the periods studied in all countries studied.
 Reuters. (2022, March 6). Closure of Libya's El Feel and Sharara oilfields caused loss of 330,000 bpd - NOC. Retrieved from Reuters: https://www.reuters.com/world/middle-east/libyas-noc-says-closure-el-feel-sharara-oilfields-resulted-loss-330000-bpd-2022-03-06/
 Jain, A., & Biswal, P. (2016). Dynamic linkages among oil price, gold price, exchange rate, and stock market in India. Resources Policy. 179-185.
 Devlin, W., Woods, S., & Coates, B. (2012). Commodity price volatility. Economic Roundup , 1.
 Hecht, A. (2022, March 24). Why Are Commodities More Volatile Than Other Assets? Retrieved from The Balance: https://www.thebalance.com/why-commodities-are-volatile-assets-4126754#:~:text=While%20equity%2C%20bond%2C%20and%20currency,to%20natural%20disasters%2C%20and%20geopolitics.
 Engle, R. (1982). Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation. Econometrica. 987-1007.
 Bollerslev, T. (1986). Generalized autoregressive conditional heteroskedasticity. Journal of Econometrics. 307-327.
 Gokcan, S. (2000). Forecasting volatility of emerging stock markets: Linear versus non-linear GARCH models. Journal of Forecasting. 19(6), 499-504.
 Su, W., & Huang, Y. (2010). Comparison of Multivariate GARCH Models with Application to Zero-Coupon Bond Volatility. LUP Student Papers. 1619618.
 Raji, J., Abdulkadir, R., & Badru, B. (2018). Dynamic Relationship between Nigeria-US Exchange Rate and Crude Oil Price. African Journal of Economic and Management Studie. 9(2), 1-31.
 Guo, J., & Tanaka, T. (2020). Examining the determinants of global and local price passthrough in cereal markets: evidence from DCC-GJR-GARCH and panel analyses. Agricultural and Food Economics. 1-22.
 Kiatmanaroch, T., & Sriboonchitta, S. (2014). Relationship between Exchange Rates, Palm Oil Prices, and Crude Oil Prices: A Vine Copula Based GARCH Approach. Modeling Dependence in Econometrics. 399-413.
 Singhal, S., Choudhary, S., & Biswal, P. (2019). Return and volatility linkages among International crude oil price, gold. Resources Policy. 255-261.
 Narayan, P., Narayan, S., & Prasad, A. (2008). Understanding the oil price-exchange rate nexus for the Fiji islands. Energy Economics. 2686-2696.
 Tian, M., Li, W., & Wen, F. (2021). The dynamic impact of oil price shocks on the stock market and the USD/RMB exchange rate: Evidence from implied volatility indices. North American Journal of Economics and Finance. 1-21.
 Chen, S.-S., & Chen, H.-C. (2007). Oil Prices and Real Exchange Rate. Energy Economics, 390-404.
 Habib, M., & Kalamova, M. (2007). Are there oil currencies? The real exchange rate of oil exporting countries. European Central Bank Working Paper Series. 1-38.
 Tiwari, A., Mutascu, M., & Albulescu, C. (2013). The influence of the international oil prices on the real effective exchange rate in Romania in a wavelet transform framework. Energy Economics. 714-733.
 Adam, P., Rosnawintang, Saidi, L., Tondi, L., & Sani, L. (2018). The Causal Relationship between Crude Oil Price, Exchange Rate and Rice Price. INternational Journal of Energy Economics and Policy. 90-94.
 Pusparani, I. (2019, January 16). Southeast Asia Tops Global Rankings for Investment Destination, Is Your Country on the List? Retrieved from Good News From Southeast Asia: https://seasia.co/2019/01/16/southeast-asia-tops-global-rankings-for-investment-destination-is-your-country-on-the-list
 Berument, M., Ceylan, N., & Dogan, N. (2010). The Impact of Oil Price Shocks on the Economic Growth of Selected MENA Countries. The Energy Journal. 31, 149-176.
 EIA. (2014, October 28). Benchmarks play an important role in pricing crude oil. Retrieved from U.S. Energy Information Administration: https://www.eia.gov/todayinenergy/detail.php?id=18571#:~:text=The%20most%20widely%20used%20benchmarks,market%20development%3B%20and%2For%20delivery
 Ajmi, A., Hammoudeh, S., & Mokni, K. (2021, October). Detection of bubbles in WTI, Brent, and Dubai oil prices: A novel double recursive algorithm. Resources Policy. 101956. Retrieved from DAILYFX.
 Altman, D., & Bland, J. (2009). Parametric v non-parametric methods for data analysis. British Medical Journal. doi:doi.org/10.1136/bmj.a3167
 Omay, T., Corakci, A., & Hasdemir, E. (2021). High Persistence and Nonlinear Behaviour in Financial Variables: A More Powerful Unit Root Testing in the ESTAR Framework. Mathematics. 9, 2534.
 Dickey, D., & Fuller, W. (1981). Autoregressive Time Series with a Unit Root. Econometric. 49(4), 1057-1072.
 Gregoriou, G., & Pascalau, R. (2011). Nonlinear Financial Econometrics: Forecasting Models, Computational and Bayesian Models. UK: Palgrave Macmillan.
 Ardia, D., Bluteau, K., Boudt, K., & Leopoldo, C. (2018). Forecasting risk with Markov-switching GARCH models:A large-scale performance study. International Journal of Forecasting. 34(4), 733-747.
 Efimova, O., & Serletis, A. (2014). Energy Markets Volatility Modelling using GARCH. Energy Economics. 43, 264-273.
 Engle, R. (2002). Dynamic Conditional Correlation: A Simple Class of Multivariate Generalized Autoregressive Conditional Heteroskedasticity Models. Journal of Business & Economic Statistics. 339-350.
 Bollerslev, T. (1990). Modelling the Coherence in Short-run Nominal Exchange Rates: A Multivariate Generalized ARCH Model. The Review of Economics and Statistics. 498-505.
 Kebalo, L. (2016). What DCC-GARCH model tell us about the effect of the gold price’s volatility on south African exchange rate? MPRA Paper 72584. Retrieved from :https://mpra.ub.uni-muenchen.de/72584/
 Aziz, M., & Hakim, J. (2013). Oil price and exchange rate relationship for ASEAN-5 countries: A panel study approach. World Applied Sciences Journal. 27-31.
 OEC. (2022, March 25). Crude Petroleum. Retrieved from Observatory of Economic Complexity: https://oec.world/en/profile/bilateral-product/crude-petroleum/reporters/
 Saidu, M., Naseem, N., Law, S., & Yasmin, B. (2021). Exploring the asymmetric effect of oil price on exchange rate: Evidence from the top six African net oil importers. Energy Reports. 8238-8257.
 Gjika, D., & Horvath, R. (2013). Stock market comovements in Central Europe: Evidence from the asymmetric DCC model. Economic Modelling. 55-64.
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