神经网络与多元货币预测

Proceedings of 1995 Conference on Computational Intelligence for Financial Engineering (CIFEr) Pub Date : 1995-04-09 DOI:10.1109/CIFER.1995.495259

N. Kahhwa, Gan Woon Seng

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引用次数: 1

摘要

提出了一种多元货币预测的神经网络方法。该模型的性能与主要货币瑞士法郎的单变量货币模型进行了比较;德国马克和日元。在单步和多步预测中，多元货币模型对所有三种货币的预测优于单变量模型。

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Neural networks and multivariate currency forecasting

A neural network approach to multivariate currency forecasting is presented. The performance of this model is compared with a univariate currency model for the major currencies, the Swiss Franc; Deutschemark and the Yen. The multivariate currency model outperforms the univariate model in prediction for all three currencies for single-step and multi-step forecasting.

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Proceedings of 1995 Conference on Computational Intelligence for Financial Engineering (CIFEr)

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