Market Efficiency of Euro Exchange Rates and Trading Strategies
Abstract
This paper tests the hypothesis on market efficiency for returns on the euro against fifteen currencies while assuming predictability of returns, dependent on the sign and magnitude of endogenous shocks. Considering the properties of exchange rate returns, the quantile autoregression approach was selected in empirical analysis. Based on the research data sample, consisting of daily exchange rates between January first, 1999, and April thirty, 2020, the paper suggests profitable trading strategies depending on a currency pair. In the case of six out of fifteen currency pairs, exchange rate returns were found non- predictable or almost non-predictable. In the case of nine considered currency pairs, there was a significant linkage between current and past exchange rate returns, found as dependent on the sign and magnitude of endogenous shocks in exchange rate returns. Finally, the paper considered possible factors of inefficiency and suggested further research of the topic.
Downloads
References
Baur, D. G. (2013). The structure and degree of dependence: a quantile regression approach. Journal of Banking & Finance, 37(3), 786-798. https://doi.org/10.1016/j.jbankfin.2012.10.015
Belbute, J. M., Delgado, J. A., Monteiro, S. C., & Pascoa, T. (2014). Measuring persistence in nominal exchange rate: Implications for Angola’s entrepreneurship and business development. International Journal of Latest Trends in Finance and Economic Sciences, 6(3), 1180-1193.
Bošnjak, M., Novak, I., & Bašić, M. (2019). Persistence of shocks in CDS returns on Croatian bonds: Quantile autoregression approach. Zbornik radova Ekonomskog fakulteta u Rijeci: časopis za ekonomsku teoriju i praksu, 37(2), 759-775. https://doi.org/10.18045/zbefri.2019.2.759
Brunnermeier, M. K., Nagel, S., & Pedersen, L. H. (2008). Carry trades and currency crashes. NBER macroeconomics annual, 23(1), 313-348. https://doi.org/10.1086/593088
Ca’Zorzi, M., Kolasa, M., & Rubaszek, M. (2017). Exchange rate forecasting with DSGE models. Journal of International Economics, 107, 127-146. https://doi.org/10.1016/j.jinteco.2017.03.011
Cheung, Y. W., Chinn, M. D., Pascual, A. G., & Zhang, Y. (2018). Exchange rate prediction redux: new models, new data, new currencies. Journal of International Money and Finance. (advanced online publication: https://doi.org/10.1016/j.jimonfin.2018.03.010)
Cook, D., & Devereux, M. B. (2016). Exchange rate flexibility under the zero-lower bound. Journal of International Economics, 101, 52-69. https://doi.org/10.1016/j.jinteco.2016.03.011
Della Corte, P., Ramadorai, T., & Sarno, L. (2016). Volatility risk premia and exchange rate predictability. Journal of Financial Economics, 120(1), 21-40. https://doi.org/10.1016/j.jfineco.2016.02.015
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. https://doi.org/10.1080/01621459.1979.10482531
Eichenbaum, M., Johannsen, B. K., & Rebelo, S. (2017). Monetary policy and the predictability of nominal exchange rates (No. w23158). National Bureau of Economic Research. doi: 10.3386/w23158
Elliott, G. Rothenberg, T. J. & Stock, J. H. (1992). Efficient Tests for an Autoregressive Unit Root. Econometrica, 64(4), 813-836. doi: 10.3386/ t0130
Engel, C., & Wu, S. P. Y. (2018). Liquidity and Exchange Rates: An Empirical Investigation (No. w25397). National Bureau of Economic Research. doi: 10.3386/w25397
Engel, C., Lee, D., Liu, C., Liu, C., & Wu, S. P. Y. (2018). The uncovered interest parity puzzle, exchange rate forecasting, and Taylor rules. Journal of International Money and Finance. https://doi.org/10.1016/j.jimonfin.2018.03.008
Fama, E. F. (1965). The behavior of stock-market prices. The journal of Business, 38(1), 34-105.https://www.jstor.org/stable/2350752
Hsu, P. H., Taylor, M. P., & Wang, Z. (2016). Technical trading: Is it still beating the foreign exchange market? Journal of International Economics, 102, 188-208. https://doi.org/10.1016/j.jinteco.2016.03.012
Juselius, K. (2017). Using a theory consistent CVAR scenario to test an exchange rate model based on imperfect knowledge. Econometrics, 5(3), 30. https://doi.org/10.3390/econometrics5030030
Juselius, K., & Assenmacher, K. (2017). Real exchange rate persistence and the excess return puzzle: The case of Switzerland versus the US. Journal of Applied Econometrics, 32(6), 1145-1155. https://doi.org/10.1002/jae.2562
Juselius, K., & Stillwagon, J. R. (2018). Are outcomes driving expectations or the other way around? An I (2) CVAR analyzis of interest rate expectations in the dollar/pound market. Journal of International Money and Finance, 83, 93-105. https://doi.org/10.1016/j.jimonfin.2018.02.003
Kang, M. W. (2019). Currency Market Efficiency Revisited: Evidence from Korea. International Journal of Financial Studies, 7(3), 52. https://doi.org/10.3390/ijfs7030052
Katusiime, L., Shamsuddin, A., & Agbola, F. W. (2015). Foreign exchange market efficiency and profitability of trading rules: Evidence from a developing country. International Review of Economics & Finance, 35, 315-332. https://doi.org/10.1016/j.iref.2014.10.003
Kim, Y. S., Lee, J., Mittnik, S., & Park, J. (2015). Quanto option pricing in the presence of fat tails and asymmetric dependence. Journal of Econometrics, 187(2), 512-520. https://doi.org/10.1016/j.jeconom.2015.02.035
Koenker, R., and Xiao, Z. (2004). Unit root quantile autoregression inference. Journal of the American Statistical Association, 99(467), 775-787. https://doi.org/10.1198/016214504000001114
Koenker, R., & Xiao, Z. (2006). Quantile autoregression. Journal of the American Statistical Association, 101(475), 980-990. https://doi.org/10.1198/016214506000000672
Kuck, K., & Maderitsch, R. (2019). Intra-day dynamics of exchange rates: New evidence from quantile regression. The Quarterly Review of Economics and Finance, 71, 247-257. https://doi.org/10.1016/j.qref.2018.09.001
Kuck, K., Maderitsch, R., & Schweikert, K. (2015). Asymmetric over-and undershooting of major exchange rates: evidence from quantileregressions. Economics Letters, 126, 114-118. https://doi.org/10.1016/j.econlet.2014.11.028
Kwiatkowski, D., Phillips, P., Schmidt, P., & Shin, Y.; (1992). Testing the Null Hypothesis of Stationarity Against the Alternatives of a Unit Root: How Sure Are We That Economic Time Series Have a Unit Root? Journal of Econometrics, 54, 159-178.
Levich, R., Conlon, T., & Potì, V. (2019). Measuring excess-predictability of asset returns and market efficiency over time. Economics Letters, 175, 92-96. https://doi.org/10.1016/j.econlet.2018.12.022
Li, J., Lu, X., & Zhou, Y. (2016). Cross-correlations between crude oil and exchange markets for selected oil rich economies. Physica A: Statistical Mechanics and its Applications, 453, 131-143. https://doi.org/10.1016/j.physa.2016.02.039
Phillips, P.C.B., & Perron, P. (1988). Testing for a unit root in time series regression. Biometrika, 75, 335-346. https://doi.org/10.1093/biomet/75.2.335
Salazar,L. (2017). Modeling Real Exchange Rate Persistence in Chile.Econometrics,5(3),29. https://doi.org/10.3390/econometrics5030029
Sensoy, A., & Tabak, B. M. (2016). Dynamic efficiency of stock markets and exchange rates. International Review of Financial Analyzis, 47,353-371. https://doi.org/10.1016/j.irfa.2016.06.001