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The ever-evolving regulation surrounding banks and market risk, coupled with increased computing power, make for favourable conditions in employing machine learning techniques to estimate and forecast market risk metrics such as value at risk (VaR) and expected shortfall (ES). This study consists of...
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| Format: | Thesis |
| Language: | English English |
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Department of Finance and Tax
2025
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