Modelling the Behaviour of Currency Exchange Rates with Singular Spectrum Analysis and Artificial Neural Networks
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- Golyandina, Nina & Korobeynikov, Anton & Shlemov, Alex & Usevich, Konstantin, 2015. "Multivariate and 2D Extensions of Singular Spectrum Analysis with the Rssa Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 67(i02).
- Sulandari, Winita & Subanar, & Lee, Muhammad Hisyam & Rodrigues, Paulo Canas, 2020. "Indonesian electricity load forecasting using singular spectrum analysis, fuzzy systems and neural networks," Energy, Elsevier, vol. 190(C).
- Ca’ Zorzi, Michele & Kolasa, Marcin & Rubaszek, Michał, 2017.
"Exchange rate forecasting with DSGE models,"
Journal of International Economics, Elsevier, vol. 107(C), pages 127-146.
- Ca' Zorzi, Michele & Kolasa, Marcin & Rubaszek, Michał, 2016. "Exchange rate forecasting with DSGE models," Working Paper Series 1905, European Central Bank.
- Marcin Kolasa & Michał Rubaszek & Michele Ca' Zorzi, 2017. "Exchange rate forecasting with DSGE models," NBP Working Papers 260, Narodowy Bank Polski.
- Hyndman, Rob J. & Khandakar, Yeasmin, 2008.
"Automatic Time Series Forecasting: The forecast Package for R,"
Journal of Statistical Software, Foundation for Open Access Statistics, vol. 27(i03).
- Rob J. Hyndman & Yeasmin Khandakar, 2007. "Automatic time series forecasting: the forecast package for R," Monash Econometrics and Business Statistics Working Papers 6/07, Monash University, Department of Econometrics and Business Statistics.
- Adam Stokes & Ahmed S. Abou-Zaid, 2012. "Forecasting foreign exchange rates using artificial neural networks: a trader's approach," International Journal of Monetary Economics and Finance, Inderscience Enterprises Ltd, vol. 5(4), pages 370-394.
- Hassani, Hossein & Heravi, Saeed & Zhigljavsky, Anatoly, 2009. "Forecasting European industrial production with singular spectrum analysis," International Journal of Forecasting, Elsevier, vol. 25(1), pages 103-118.
- Jordi Galí & Tommaso Monacelli, 2005.
"Monetary Policy and Exchange Rate Volatility in a Small Open Economy,"
The Review of Economic Studies, Review of Economic Studies Ltd, vol. 72(3), pages 707-734.
- GalÃ, Jordi & Monacelli, Tommas, 2002. "Monetary Policy and Exchange Rate Volatility in a Small Open Economy," CEPR Discussion Papers 3346, C.E.P.R. Discussion Papers.
- Jordi Gali & Tommaso Monacelli, 2002. "Monetary Policy and Exchange Rate Volatility in a Small Open Economy," NBER Working Papers 8905, National Bureau of Economic Research, Inc.
- Jordi Galí & Tommaso Monacelli, 2004. "Monetary policy and exchange rate volatility in a small open economy," Economics Working Papers 835, Department of Economics and Business, Universitat Pompeu Fabra.
- Jordi Galí & Tommaso Monacelli, 2003. "Monetary Policy and Exchange Rate Volatility in a Small Open Economy," Working Papers 11, Barcelona School of Economics.
- Rahim Mahmoudvand & Dimitrios Konstantinides & Paulo Canas Rodrigues, 2017. "Forecasting mortality rate by multivariate singular spectrum analysis," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 33(6), pages 717-732, November.
- de Carvalho, Miguel & Rodrigues, Paulo C. & Rua, António, 2012.
"Tracking the US business cycle with a singular spectrum analysis,"
Economics Letters, Elsevier, vol. 114(1), pages 32-35.
- António Rua & Miguel de Carvalho, 2010. "Tracking the US Business Cycle With a Singular Spectrum Analysis," Working Papers w201009, Banco de Portugal, Economics and Research Department.
- Sebastian Edwards & Miguel A. Savastano, 1999. "Exchange Rates in Emerging Economies: What Do We Know? What Do We Need to Know?," NBER Working Papers 7228, National Bureau of Economic Research, Inc.
- de Carvalho, Miguel & Rua, António, 2017.
"Real-time nowcasting the US output gap: Singular spectrum analysis at work,"
International Journal of Forecasting, Elsevier, vol. 33(1), pages 185-198.
- António Rua & Miguel de Carvalho, 2014. "Real-time nowcasting the US output gap: Singular spectrum analysis at work," Working Papers w201416, Banco de Portugal, Economics and Research Department.
- Nag, Ashok K & Mitra, Amit, 2002. "Forecasting Daily Foreign Exchange Rates Using Genetically Optimized Neural Networks," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 21(7), pages 501-511, November.
- Rahim Mahmoudvand & Paulo Canas Rodrigues, 2018. "A new parsimonious recurrent forecasting model in singular spectrum analysis," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 37(2), pages 191-200, March.
- Makridakis, Spyros & Spiliotis, Evangelos & Assimakopoulos, Vassilios, 2020. "The M4 Competition: 100,000 time series and 61 forecasting methods," International Journal of Forecasting, Elsevier, vol. 36(1), pages 54-74.
- von Hagen, Jurgen & Zhou, Jizhong, 2007. "The choice of exchange rate regimes in developing countries: A multinomial panel analysis," Journal of International Money and Finance, Elsevier, vol. 26(7), pages 1071-1094, November.
- Paul Alagidede & Muazu Ibrahim, 2017. "On the Causes and Effects of Exchange Rate Volatility on Economic Growth: Evidence from Ghana," Journal of African Business, Taylor & Francis Journals, vol. 18(2), pages 169-193, April.
- Makridakis, Spyros & Spiliotis, Evangelos & Assimakopoulos, Vassilios, 2018. "The M4 Competition: Results, findings, conclusion and way forward," International Journal of Forecasting, Elsevier, vol. 34(4), pages 802-808.
- Hassani, Hossein, 2007. "Singular Spectrum Analysis: Methodology and Comparison," MPRA Paper 4991, University Library of Munich, Germany.
- Andreas Groth & Michael Ghil, 2017. "Synchronization of world economic activity," Post-Print hal-01701086, HAL.
- Montero, Pablo & Vilar, José A., 2014. "TSclust: An R Package for Time Series Clustering," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 62(i01).
- Olushina Olawale Awe & Luis Alberiko Gil-Alana, 2019. "Time series analysis of economic growth rate series in Nigeria: structural breaks, non-linearities and reasons behind the recent recession," Applied Economics, Taylor & Francis Journals, vol. 51(50), pages 5482-5489, October.
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- Awe, Olushina Olawale & Dias, Ronaldo, 2022. "Comparative Analysis of ARIMA and Artificial Neural Network Techniques for Forecasting Non-Stationary Agricultural Output Time Series," AGRIS on-line Papers in Economics and Informatics, Czech University of Life Sciences Prague, Faculty of Economics and Management, vol. 14(4), December.
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Keywords
singular spectrum analysis; multivariate singular spectrum analysis; time series forecasting; artificial neural networks; currency exchange rates;All these keywords.
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