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Forecasting the BDT/USD Exchange Rate: An Accuracy Comparison of Artificial Neural Network Models and Different Time Series Models |
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PP: 131-138 |
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doi:10.18576/jsapl/040304
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Author(s) |
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Md. Shahajada Mia,
Md. Siddikur Rahman,
Sukanta Das,
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Abstract |
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| Exchange rate is the price of one currency in terms of another currency. Exchange rates play an important role in controlling dynamics of the foreign exchange market. Predicting exchange rates has become one of the most challenging applications of financial time series forecasting due to its unpredictability and volatility. We selected to forecast the BDT against US Dollar because United States is the top trading partner of Bangladesh. This research study is to develop and compare the accuracy of different models; autoregressive Integrated Moving Average (ARIMA), Exponential smoothing models as the time series models and Feedforward neural network with the Backpropagation algorithm as the Artificial Neural Network (ANN) model for predicting monthly currency exchange rate of Bangladeshi Taka against US Dollar (BDT/USD). According to the performance of different models, it can be concluded that the ANN based model performs better when compared with the ARIMA model to predict the exchange rate of BDT/USD. |
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