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The Accuracy Of Exchange Rate Forecasts In Romania

Author

Listed:
  • Mihaela SIMIONESCU

    (Institute for Economic Forecasting of the Romanian Academy)

Abstract

The main aim of this research is to predict the average exchange rate RON/USD in Romania using various quantitative methods. Recent researches have confirmed the prediction power of neural networks, but in this article econometric models and exponential smoothing techniques have been employed. For predicting the average RON/USD exchange rate using neural networks the following variables have been used: the real growth of monetary supply M2, the real interest rate, index of production prices and real exchange rate. For predictions based on multiplicative Holt-Winters model on 2011-2013, we obtained a recognised superiority in terms of accuracy, outperforming other predictions based on neural networks (perceptron multilayer and radial basis function) and econometric models (autoregressive model and vector-autoregressive model).

Suggested Citation

  • Mihaela SIMIONESCU, 2015. "The Accuracy Of Exchange Rate Forecasts In Romania," Journal of Social and Economic Statistics, Bucharest University of Economic Studies, vol. 4(1), pages 54-64, JULY.
    • Handle: RePEc:aes:jsesro:v:4:y:2015:i:1:p:54-64
    as

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    File URL: http://www.jses.ase.ro/downloads/Vol4NO1/Simionescu.pdf
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    References listed on IDEAS

    as
    1. Wong, W.K. & Xia, Min & Chu, W.C., 2010. "Adaptive neural network model for time-series forecasting," European Journal of Operational Research, Elsevier, vol. 207(2), pages 807-816, December.
    2. Proietti, Tommaso & Lütkepohl, Helmut, 2013. "Does the Box–Cox transformation help in forecasting macroeconomic time series?," International Journal of Forecasting, Elsevier, vol. 29(1), pages 88-99.
    3. Chih-Chung Yang & Yungho Leu & Chien-Pang Lee, 2014. "A Dynamic Weighted Distancedbased Fuzzy Time Series Neural Network with Bootstrap Model for Option Price Forecasting," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 115-129, June.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    exchange rate; forecasts; neural network; econometric model; accuracy;
    All these keywords.

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

    Statistics

    Access and download statistics

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