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Forecasting Daily Foreign Exchange Rate In India With Artificial Neural Network

Author

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  • CHAKRADHARA PANDA

    (Department of Economics, University of Hyderabad, India)

  • V. NARASIMHAN

    (Department of Economics, University of Hyderabad, India)

Abstract

This study compares the efficiency of a non-linear model called artificial neural network with linear autoregressive and random walk models in the one-step-ahead prediction of daily Indian rupee/US dollar exchange rate. We find that neural network and linear autoregressive models outperform random walk model in in-sample and out-of-sample forecasts. The in-sample forecasting of neural network is found to be better than that of linear autoregressive model. As far as out-of-sample forecasting is concerned, the results are mixed and we do not find a "winner" model between neural network and linear autoregressive model. However, neural network is able to improve upon the linear autoregressive model in terms of sign predictions. In addition to this, we also find that the number of input nodes has greater impact on neural network's performance than the number of hidden nodes.

Suggested Citation

  • Chakradhara Panda & V. Narasimhan, 2003. "Forecasting Daily Foreign Exchange Rate In India With Artificial Neural Network," The Singapore Economic Review (SER), World Scientific Publishing Co. Pte. Ltd., vol. 48(02), pages 181-199.
    • Handle: RePEc:wsi:serxxx:v:48:y:2003:i:02:n:s0217590803000712
    DOI: 10.1142/S0217590803000712
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    References listed on IDEAS

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    1. Engel, Charles, 1994. "Can the Markov switching model forecast exchange rates?," Journal of International Economics, Elsevier, vol. 36(1-2), pages 151-165, February.
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    Cited by:

    1. Manish KUMAR, 2009. "Exploiting The Information Of Stock Market To Forecast Exchange Rate Movements," Analele Stiintifice ale Universitatii "Alexandru Ioan Cuza" din Iasi - Stiinte Economice (1954-2015), Alexandru Ioan Cuza University, Faculty of Economics and Business Administration, vol. 56, pages 563-575, November.
    2. Panda, Chakradhara & Narasimhan, V., 2007. "Forecasting exchange rate better with artificial neural network," Journal of Policy Modeling, Elsevier, vol. 29(2), pages 227-236.

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