RBC applies ‘deep hedging’ to stress scenarios
Risk USA: machine learning model generates more realistic estimates of trading losses
RBC Capital Markets is testing a form of machine learning called deep hedging to estimate trading losses during a global market shock, a component of the US Federal Reserve’s annual supervisory Comprehensive Capital Analysis and Review (CCAR) for large banks.
The bank found that deep hedging produces more accurate estimates of the trading losses that would be incurred in a stress scenario when compared with traditional modelling techniques.
“Machine learning can help increase accuracy of
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