Exchange Rate Forecasting using Recurrent Self-Organizing Maps

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BAYAT NEDA

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Journal: Journal of New Economy and Trade Year:2019 | Volume:13 | Issue:4 Page(s): 55-84

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Title

Exchange Rate Forecasting using Recurrent Self-Organizing Maps

Author(s)

BAYAT NEDA | Issue Writer Certificate

Keywords

Exchange RateQ2

ForecastingQ1

Recurrent Self-Organizing MapsQ1

Self-Organizing MapsQ2

sanction effects.JEL Classification:F31Q1

Y91Q1

F51Q1

Abstract

Exchange Rate is one of the most important variables in economics, which impacts many other macroeconomic variables in an economy. Such changes are more important in developing countries, which are often exporters of raw materials. Exchange Rate fluctuations in Iran is also critical since the country is highly dependent on foreign exchange earnings from oil exports and also subject to the severs sanctions imposed by the US in recent years. In this paper, we propose a Forecasting model using Recurrent Self-Organizing Maps to forecast the Exchange Rates considering the factors affecting the Exchange Rate markets. In total, 12 selected variables are used in modeling the Exchange Rate, which includes the effective macro variables and the price index of competing markets, such as gold, stock exchange and housing. We also control for the effect of sanctions. The results show that the model produces relatively accurate forecasts of the Exchange Rates with a less than 3% error.

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APA: Copy

BAYAT, NEDA. (2019). Exchange Rate Forecasting using Recurrent Self-Organizing Maps. JOURNAL OF NEW ECONOMY & COMMERCE, 13(4 ), 55-84. SID. https://sid.ir/paper/381271/en

Vancouver: Copy

BAYAT NEDA. Exchange Rate Forecasting using Recurrent Self-Organizing Maps. JOURNAL OF NEW ECONOMY & COMMERCE[Internet]. 2019;13(4 ):55-84. Available from: https://sid.ir/paper/381271/en

IEEE: Copy

NEDA BAYAT, “Exchange Rate Forecasting using Recurrent Self-Organizing Maps,” JOURNAL OF NEW ECONOMY & COMMERCE, vol. 13, no. 4 , pp. 55–84, 2019, [Online]. Available: https://sid.ir/paper/381271/en

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