Forecasting of IQD/USD Exchange Rate by Using some Machine Learning Methods with Time-Varying Volatility
| المصدر: | مجلة القادسية للعلوم الإدارية والاقتصادية |
|---|---|
| الناشر: | جامعة القادسية - كلية الادارة والاقتصاد |
| المؤلف الرئيسي: | Dikheel, Tahir R. (Author) |
| مؤلفين آخرين: | Sami, Sura H. (Co-Author) |
| المجلد/العدد: | مج23, ع2 |
| محكمة: | نعم |
| الدولة: |
العراق |
| التاريخ الميلادي: |
2021
|
| الصفحات: | 133 - 137 |
| ISSN: |
1816-9171 |
| رقم MD: | 1235014 |
| نوع المحتوى: | بحوث ومقالات |
| اللغة: | الإنجليزية |
| قواعد المعلومات: | EcoLink |
| مواضيع: | |
| كلمات المؤلف المفتاحية: |
Machine Learning | Random Forests | Regression Trees | Exchange Rate | GARCH Model
|
| رابط المحتوى: |
الناشر لهذه المادة لم يسمح بإتاحتها. |
| المستخلص: |
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 is 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. |
|---|---|
| ISSN: |
1816-9171 |
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