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The Fundamental Review of the Trading Book (FRTB) is a set of regulations by the Basel committee, which is expected to be implemented by banks by 2022. The regulation targets market risk management in banking industry. According to FRTB, banks need to post extra capital against non-modellable risk factors, which could account for 30% of total market risk capital requirement. Reducing the weight of non-modellable risk factors can greatly reduce the required capital and thus increase banks’ profitability. In this research, we will first examine three ways for the purpose of reducing non-modellable risk factors: simple rule-based proxies, statistical modelling approach and machine learning. We will also study another machine learning method based on Gaussian process regression. This method requires fewer parameters for calibration and hence less complex. Since the method is based on well-known probability distribution, it can be understood easily.
Matthew Davison;Marcos Escobar Anel
Zhenxian Gong;Junhe Chen
CIBC
Statistics / Actuarial sciences
Finance, insurance and business
Western University
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