This paper evaluates the time-varying volatility forecasting performance of a range of macroeconomic theory-based models, explains the exchange rates in the US and UK, and non-theory-based models using univariate GARCH and bivariate GARCH models. This paper uses a traditional statistical criterion and a more practical Value at Risk (VaR) approach to judge these models’ performance, using out-of-sample data and one-step-ahead forecasts. The results are mixed: some models perform well in terms of one criterion but badly in terms of another. The best model considering both criteria is the model based on the efficient market hypothesis (EMH), but it does not outperform the other models significantly, especially in terms of the VaR method, which gives the EMH model the same performance as GARCH (1,1).

Congrui Yin. QLIKE and VaR evaluation approaches for volatility forecasts of exchange rates using structural models in US and UK. Academic Journal of Business & Management (2024) Vol. 6, Issue 10: 161-175. https://doi.org/10.25236/AJBM.2024.061025.

[1] Baillie, R. T., & Bollerslev, T. (1989). The Message in Daily Exchange Rates: A Conditional-Variance Tale. Journal of Business & Economic Statistics, 7(3), 297. https://doi.org/10.2307/1391527

[2] Baillie, R. T., & Bollerslev, T. (1991). Intra-Day and Inter-Market Volatility in Foreign Exchange Rates. The Review of Economic Studies, 58(3), 565. https://doi.org/10.2307/2298012

[3] Bank of England. (n.d.). Statistics. Www.bankofengland.co.uk. https://www.bankofengland. co.uk/statistics

[4] Boffelli, S., & Urga, G. (2016). Financial econometrics using stata. College Station, Texas (Estados Unidos) Stata Press.

[5] Bollerslev, T. (1986). Generalized autoregressive conditional heteroskedasticity. Journal of Econometrics, 31(3), 307–327.

[6] Bollerslev, T. (1990). Modelling the Coherence in Short-Run Nominal Exchange Rates: a Multivariate Generalized Arch Model. The Review of Economics and Statistics, 72(3), 498. https://doi.org/10.2307/2109358

[7] Clarida, R. H., & Taylor, M. P. (1997). The Term Structure of Forward Exchange Premiums and the Forecastability of Spot Exchange Rates: Correcting the Errors. Review of Economics and Statistics, 79(3), 353–361. https://doi.org/10.1162/003465397556827

[8] Christoffersen, P. F. (1998). Evaluating Interval Forecasts. International Economic Review, 39(4), 841. https://doi.org/10.2307/2527341

[9] Diebold, F. X., & Nerlove, M. (1989). The dynamics of exchange rate volatility: A multivariate latent factor ARCH model. Journal of Applied Econometrics, 4(1), 1–21. https://doi.org/ 10.1002/jae. 3950040102

[10] Federal Reserve Bank of St. Louis. (2024). FRED Economic Data. Stlouisfed.org; Federal Reserve Bank of St. Louis. https://fred.stlouisfed.org/

[11] Frenkel, J. A. (1976). A Monetary Approach to the Exchange Rate: Doctrinal Aspects and Empirical Evidence. The Scandinavian Journal of Economics, 78(2), 200. https://doi.org/10.2307/3439924

[12] Garratt, A., & Lee, K. (2010). Investing under model uncertainty: Decision based evaluation of exchange rate forecasts in the US, UK and Japan. Journal of International Money and Finance, 29(3), 403–422. https://doi.org/10.1016/j.jimonfin.2009.07.002

[13] Garratt, A., Lee, K., M. Hashem Pesaran, & Shin, Y. (2006). Global and National Macroeconometric Modelling. In Oxford University PressOxford eBooks. Oxford University Press. https://doi.org/10.1093/0199296855.001.0001

[14] Geurts, M., Box, G. E. P., & Jenkins, G. M. (1977). Time Series Analysis: Forecasting and Control. Journal of Marketing Research, 14(2), 269. https://doi.org/10.2307/3150485

[15] International Financial Statistics. (2019). Imf.org. https://data.imf.org/?sk=4C514D48-B6BA-49ED-8AB9-52B0C1A0179B

[16] Mittnik, S., & Paolella, M. S. (2000). Conditional density and value-at-risk prediction of Asian currency exchange rates. Journal of Forecasting, 19(4), 313–333. https://doi.org/10.1002/1099-131x(200007)19:4%3C313::aid-for776%3E3.0.co;2-e

[17] Patton, A. J. (2011). Volatility forecast comparison using imperfect volatility proxies. Journal of Econometrics, 160(1), 246–256. https://doi.org/10.1016/j.jeconom.2010.03.034

[18] Pilbeam, K., & Langeland, K. N. (2014). Forecasting exchange rate volatility: GARCH models versus implied volatility forecasts. International Economics and Economic Policy, 12(1), 127–142. https://doi.org/10.1007/s10368-014-0289-4

[19] Vilasuso, J. (2002). Forecasting exchange rate volatility. Economics Letters, 76(1), 59–64. https://doi.org/10.1016/s0165-1765(02)00036-8

[20] West, K. D., Edison, H. J., & Cho, D. (1993). A utility-based comparison of some models of exchange rate volatility. Journal of International Economics, 35(1-2), 23–45. https://doi.org/ 10.1016/0022-1996(93)90003-g