Forecasting Of IQD/USD Exchange Rate By Using Some Machine
Leaening Methods With Time-Varying Volatility
Tahir R. Dikhee, Sura H. Sami
University of Al-Qadisiyah/College of Administration and Economics
| Corresponding Author: Sura H. Sami surahassan154@gmail.com |
| Abstract : Abstract: The machine learning technique such as random forests and regression trees, are nonparametric methods that it recently used for regression estimation. In these methods, the variance of random errors needs to be constant, but that’s not true always, especially, in the financial data. Unfortunately, the financial time series suffer from the volatility that happens during different periods where the researchers were an effort to solve this problem by combining the random forest and the regression trees with the GARCH model. In this paper, we use these methods to estimate the conditional variance of the GARCH model to forecast the exchange rate of IQD/USD. KEYWORDS :Machine learning; random forests; regression trees; exchange rate; GARCH model |
