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020 |z0-662-29766-0
022 |a1192-5434
040 |aCaOODSP|beng
043 |an-cn---
0861 |aFB3-2/100-23E
1102 |aBank of Canada.
24514|aThe application of artificial neural networks to exchange rate forecasting : |bthe role of market microstructure variables / |cby Nikola Gradojevic and Jing Yang.
260 |aOttawa - Ontario : |bBank of Canada |c2000.
300 |av, 27p. : |bfigs., graphs, tables ; |c28 cm.
4901 |aWorking paper|x1192-5434|v100-23
500 |a"Artificial neural networks (ANN) are employed for high-frequency Canada/U.S. dollar exchange rate forecasting."--Abstract. "This paper examines whether introducing a market microstructure variable (that is, order flow) into a set of daily observations of macroeconomic variables (interest rate, crude oil price) together with an ANN technique can explain Canada/U.S. dollar exchange rate movement better than linear and random walk models. Two statistics are used to compare models: root-mean squared error (RMSE) and the percentage of correctly predicted exchange rate changes (PERC)."--Introduction.
504 |aBibliography.
5203 |aArtificial neural networks (ANN) are employed for high-frequency Canada/U.S. dollar exchange rate forecasting.--Abstract This paper examines whether introducing a market microstructure variable (that is, order flow) into a set of daily observations of macroeconomic variables (interest rate, crude oil price) together with an ANN technique can explain Canada/U.S. dollar exchange rate movement better than linear and random walk models. Two statistics are used to compare models: root-mean squared error (RMSE) and the percentage of correctly predicted exchange rate changes (PERC).--Introduction
546 |aRésumés en français
563 |aSoftcover
590 |a01-01|b2001-01-05
69007|aExchange rates|2gcpds
69007|aCurrency|2gcpds
7201 |aGradojevic, Nikola
7201 |aYang, Jing
7760#|tThe application of artificial neural networks to exchange rate forecasting : |w(CaOODSP)9.571563
830#0|aWorking paper,|x1192-5434|v100-23|w(CaOODSP)9.514622