Forecasting daily and monthly exchange rates with machine learning techniques
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- Vasilios Plakandaras & Theophilos Papadimitriou & Periklis Gogas, 2015. "Forecasting Daily and Monthly Exchange Rates with Machine Learning Techniques," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 34(7), pages 560-573, November.
References listed on IDEAS
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CitationsCitations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
- Vasilios Plakandaras & Theophilos Papadimitriou & Periklis Gogas & Konstantinos Diamantaras, 2014. "Market Sentiment and Exchange Rate Directional Forecasting," Working Paper series 37_14, Rimini Centre for Economic Analysis.
- Rangan Gupta & Tahir Suleman & Mark E. Wohar, 2017. "Exchange Rate Returns and Volatility: The Role of Time-Varying Rare Disaster Risks," Working Papers 201767, University of Pretoria, Department of Economics.
- Vasilios Plakandaras & Periklis Gogas & Theophilos Papadimitriou & Rangan Gupta, 2016. "The Term Premium as a Leading Macroeconomic Indicator," Working Papers 201613, University of Pretoria, Department of Economics.
- Plakandaras, Vasilios & Gupta, Rangan & Wohar, Mark E., 2017.
"The depreciation of the pound post-Brexit: Could it have been predicted?,"
Finance Research Letters,
Elsevier, vol. 21(C), pages 206-213.
- Vasilios Plakandaras & Rangan Gupta & Mark E. Wohar, 2016. "The Depreciation of the Pound Post-Brexit: Could it have been Predicted?," Working Papers 201670, University of Pretoria, Department of Economics.
More about this item
KeywordsExchange rate forecasting; Support Vector Regression; local learning; feature selection; Ensemble Empirical Mode Decomposition; time series; trend;
- G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
NEP fieldsThis paper has been announced in the following NEP Reports:
- NEP-ALL-2013-03-23 (All new papers)
- NEP-EEC-2013-03-23 (European Economics)
- NEP-FOR-2013-03-23 (Forecasting)
- NEP-ORE-2013-03-23 (Operations Research)
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