Chaturvedi, Priya and Kumar, Kuldeep (2022): Econometric modelling of exchange rate volatility using mixed-frequency data.
Preview |
PDF
MPRA_paper_115222.pdf Download (721kB) | Preview |
Abstract
In the paper, we use generalized autoregressive conditional heteroskedasticity-mixed data sampling (GARCH-MIDAS) to study the impact of Australia’s commodity price index, Global economic conditions indicator, Global Economic Policy Uncertainty Index, monthly realised volatility of S&P/ASX 200 index and monthly realised volatility of money supply on the volatility of the Australian dollar during the period from 1999 to 2021. The results indicate that exchange rate volatility rises with a rise in fluctuations in S&P/ASX 200 index, money supply volatility, commodity price index and falls with a rise in global economic activity. For the GEPU index, the slope coefficient is positive and significant only in the 3- years lag and not significant in the 1- and 2-years lags. This means that a rise in economic turmoil leads to a rise in exchange rate volatility. We also find strong evidence for asymmetry in the short-term volatility component. The results obtained in the study show that there is co-movement of volatility across various financial markets.
Item Type: | MPRA Paper |
---|---|
Original Title: | Econometric modelling of exchange rate volatility using mixed-frequency data |
Language: | English |
Keywords: | exchange rate volatility; GARCH-MIDAS; macroeconomic and financial variables; asymmetry |
Subjects: | C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C58 - Financial Econometrics |
Item ID: | 115222 |
Depositing User: | Ms. Priya Chaturvedi |
Date Deposited: | 01 Nov 2022 14:32 |
Last Modified: | 07 Nov 2022 14:27 |
References: | Aghion P, Bacchetta P, Ranciere R, Rogoff K (2009) Exchange rate volatility and productivity growth: The role of financial development. J Monet Econ 56(4): 494-513. Asgharian H, Hou AJ, Javed (2013) The importance of the macroeconomic variables in forecasting stock return variance: A GARCH‐MIDAS approach. J of Forecast 32(7): 600-612. Bagella M, Becchetti L, Hasan I (2006) Real effective exchange rate volatility and growth: A framework to measure advantages of flexibility vs. costs of volatility. J Bank Financ 30(4): 1149-1169. Bailey G, Steeley, JM (2019) Forecasting the volatility of the Australian dollar using high‐frequency data: Does estimator accuracy improve forecast evaluation? Int J Financ Econ 24(3): 355-1389. Baillie RT, Bollerslev T (1991) Intra-day and inter-market volatility in foreign exchange rates. Rev Econ Stud 58(3): 565-585. Baum CF, Caglayan M (2010) On the sensitivity of the volume and volatility of bilateral trade flows to exchange rate uncertainty. J Int Money Financ 29(1): 79-93. Baum CF, Caglayan M, Ozkan N (2004) Nonlinear effects of exchange rate volatility on the volume of bilateral exports. J Appl Economet 19(1): 1-23. Baumeister C, Korobilis D, Lee TK (2022) Energy markets and global economic conditions. Rev Econ Stat 104(4): 828-844. Belke A (2005) Exchange Rate Movements and Unemployment in the EU Accession Countries—A Panel Analysis. Rev Dev Econ 9(2): 249-263. Braun M, Larrain B (2005) Finance and the business cycle: international, inter‐industry evidence. J Financ 60(3): 1097-1128. Bush G, Noria, GL (2021) Uncertainty and exchange rate volatility: Evidence from Mexico. Int Rev Econ Fin 75: 704-722. Chen L, Du Z, Hu Z (2020) Impact of economic policy uncertainty on exchange rate volatility of China. Fin Res Lett 32: 101266. Chen YC, Rogoff K (2003) Commodity currencies. J Int Econ 60(1): 133-160. Christou C, Gupta R, Hassapis C, Suleman T (2018) The role of economic uncertainty in forecasting exchange rate returns and realized volatility: Evidence from quantile predictive regressions. J Forecast, 37(7): 705-719. Conrad C, Custovic A, Ghysels E (2018) Long-and short-term cryptocurrency volatility components: A GARCH-MIDAS analysis. J Risk Financ Manag 11(2): 23. Conrad C, Kleen O (2020) Two are better than one: Volatility forecasting using multiplicative component GARCH‐MIDAS models. J Appl Economet 35(1): 19-45. Conrad C, Loch K (2015). Anticipating long‐term stock market volatility. J Appl Economet 30(7): 1090-1114. Conrad C, Loch K, Rittler D (2014) On the macroeconomic determinants of long-term volatilities and correlations in US stock and crude oil markets. J Emp Financ 29: 26-40. Davis, S J (2016) An index of global economic policy uncertainty (No. w22740). National Bureau of Economic Research. Engle RF, Ghysels E, Sohn B (2013) Stock market volatility and macroeconomic fundamentals. Rev Econ Stat 95(3): 776-797. Fang L, Yu H, Xiao W (2018) Forecasting gold futures market volatility using macroeconomic variables in the United States. Econ Model 72: 249-259. Feldmann H (2011) The unemployment effect of exchange rate volatility in industrial countries. Econ Lett 111(3): 268-271. 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. J Int Money Finance, 54, 116-141. Ferrara L, Metelli L, Natoli F, Siena D (2021) Questioning the puzzle: fiscal policy, real exchange rate and inflation. J Int Econ 133: 103524. Girardin E, Joyeux R (2013) Macro fundamentals as a source of stock market volatility in China: A GARCH-MIDAS approach. Econ Model 34: 59-68. Grier R, Grier KB (2006) On the real effects of inflation and inflation uncertainty in Mexico. J Dev Econ 80(2): 478-500. Grossmann A, Orlov AG (2014) A panel‐regressions investigation of exchange rate volatility. Int J Financ Econ 19(4): 303-326. Hamilton JD (2021) Measuring global economic activity. J Appl Economet 36(3): 293-303. Inoue A, Rossi B (2019) The effects of conventional and unconventional monetary policy on exchange rates. J Int Econ 118: 419-447. Kanas A (2002) Is exchange rate volatility influenced by stock return volatility? Evidence from the US, the UK and Japan. App Econ Lett 9(8): 501-503. Kim S, Roubini N (2008) Twin deficit or twin divergence? Fiscal policy, current account, and real exchange rate in the US. J Int Econ 74(2), 362-383. Koosakul J, Shim I (2021) The effects of asset price volatility on market participation: Evidence from the Thai foreign exchange market. J Bank Financ 124: 106036. Li T, Ma F, Zhang X, Zhang, Y (2020) Economic policy uncertainty and the Chinese stock market volatility: Novel evidence. Econ Model 87: 24-33. Moraghen W, Seetanah B, Sookia NUH (2020) The impact of exchange rate and exchange rate volatility on Mauritius foreign direct investment: A sector‐wise analysis. Intl J Financ Econ. Morana C (2009) On the macroeconomic causes of exchange rate volatility. Int J Forecast 25(2): 328-350. Nguyen DK, Walther T (2020) Modeling and forecasting commodity market volatility with long‐term economic and financial variables. J Forecast 39(2): 126-142. Olayeni OR, Tiwari AK, Wohar ME (2020) Global economic activity, crude oil price and production, stock market behaviour and the Nigeria-US exchange rate. Energy Econ 92: 104938. Schwert GW (1989) Why does stock market volatility change over time? J Financ 44(5): 1115-1153. Su Z, Fang T, Yin L (2017) The role of news-based implied volatility among US financial markets. Econ Lett 157: 24-27. Su Z, Fang T, Yin L (2019) Understanding stock market volatility: What is the role of US uncertainty? North Am J Econ Financ 48: 582-590. Wang L, Ma F, Liu J, Yang L (2020) Forecasting stock price volatility: New evidence from the GARCH-MIDAS model. Int J Forecast 36(2): 684-694. You Y, Liu X (2020) Forecasting short-run exchange rate volatility with monetary fundamentals: A GARCH-MIDAS approach. J Bank Financ 116: 105849. Zhang HJ, Dufour JM, Galbraith JW (2016) Exchange rates and commodity prices: Measuring causality at multiple horizons. J Emp Financ 36: 100-120. Zhou Z, Fu Z, Jiang Y, Zeng X, Lin L (2020). Can economic policy uncertainty predict exchange rate volatility? New evidence from the GARCH-MIDAS model. Financ Res Lett 34: 101258. |
URI: | https://mpra.ub.uni-muenchen.de/id/eprint/115222 |