caa a22 4500 477072879 CHVBK 20180405111431.0 cr unu---uuuuu 170330e19960901xx s 000 0 eng 10.1007/BF01414877 doi (NATIONALLICENCE)springer-10.1007/BF01414877 Predicting returns on Canadian exchange rates with artificial neural networks and EGARCH-M models [Elektronische Daten] [Athanasios Episcopos, Jefferson Davis] This paper investigates the problem of predicting daily returns based on five Canadian exchange rates using artificial neural networks and EGARCH-M models. First, the statistical properties of five daily exchange rate series (US Dollar, German Mark, French Franc, Japanese Yen and British Pound) are analysed. EGARCH-M models on the Generalised Error Distribution (GED) are fitted to the return series, and serve as comparison standards, along with random walk models. Second, backpropagation networks (BPN) using lagged returns as inputs are trained and tested. Estimated volatilities from the EGARCH-M models are used also as inputs to see if performance is affected. The question of spillovers in interrelated markets is investigated with networks of multiple inputs and outputs. In addition, Elman-type recurrent networks are also trained and tested. Comparison of the various methods suggests that, despite their simplicity, neural networks are similar to the EGARCH-M class of nonlinear models, but superior to random walk models, in terms of insample fit and out-of-sample prediction performance. Springer-Verlag London Limited, 1996 Backpropagation nationallicence EGARCH-M nationallicence Elman nationallicence Exchange rates nationallicence Neural networks nationallicence Episcopos Athanasios Department of Economics & Finance, Clarkson University, 13699-5785, Potsdam, NY, USA aut Davis Jefferson Department of Accounting & Law, Clarkson University, Potsdam, New York, USA aut Neural Computing & Applications Springer-Verlag 4/3(1996-09-01), 168-174 0941-0643 4:3<168 1996 4 521 https://doi.org/10.1007/BF01414877 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/BF01414877 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Episcopos Athanasios Department of Economics & Finance, Clarkson University, 13699-5785, Potsdam, NY, USA aut NATIONALLICENCE 700 1- Davis Jefferson Department of Accounting & Law, Clarkson University, Potsdam, New York, USA aut NATIONALLICENCE 773 0- Neural Computing & Applications Springer-Verlag 4/3(1996-09-01), 168-174 0941-0643 4:3<168 1996 4 521 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer