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Contribution Details
| Type | Master's Thesis |
| Scope | Discipline-based scholarship |
| Title | Stock market volatility: Identification of risk drivers and forecasting using random forest |
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| Institution | University of Zurich |
| Faculty | Faculty of Business, Economics and Informatics |
| Number of Pages | 43 |
| Date | 2017 |
| Abstract Text | Random forest is a machine learning method which can be used for regression and classification. Due to its ability to handle large data setswith highly nonlinear dependencies, random forest is a powerful prediction tool. Furthermore, despite being a non-parametric approach, random forest allows for inference regarding the importance of input variables. |
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