首页|New Machine Learning Study Findings Have Been Reported by Investigators at Unive rsity of Quebec Montreal (A Machine Learning Approach In Stress Testing Us Bank Holding Companies)
New Machine Learning Study Findings Have Been Reported by Investigators at Unive rsity of Quebec Montreal (A Machine Learning Approach In Stress Testing Us Bank Holding Companies)
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Investigators publish new report on Ma chine Learning. According to news originating from Montreal, Canada, by NewsRx e ditors, the research stated, "This paper assesses the utility of machine learnin g (ML) techniques combined with comprehensive macroeconomic and microeconomic da tasets in enhancing risk analysis during stress tests. The analysis unfolds in t wo stages." Financial supporters for this research include Fonds de recherche sur la societe et la culture (Quebec), Canadian chair in Macroeconomy and Forecasting (UQAM). Our news journalists obtained a quote from the research from the University of Q uebec Montreal, "I initially benchmark ML's efficacy in forecasting two pivotal banking variables, net charge-off (NCO) and pre-provision net revenue (PPNR), ag ainst traditional linear models. Results underscore the superiority of Random Fo rest and Adaptive Lasso models in this context. Subsequently, I use these models to project PPNR and NCO for selected bank holding companies under adverse stres s scenarios. This exercise feeds into the Tier 1 common equity capital (T1CR) de nsities simulation. T1CR is the equity capital ratio corrected by some regulator y adjustments to risk-weighted assets. Crucially, findings reveal a pronounced l eft skew in the T1CR distribution for globally systemically important banks vis- & agrave;-vis linear models."
MontrealCanadaNorth and Central Amer icaCyborgsEmerging TechnologiesInvestment and FinanceMachine LearningU niversity of Quebec Montreal
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