首页|Study Data from Technical University Munich (TU Munich) Update Understanding of Artificial Intelligence (Analyzing Credit Spread Changes Using Explainable Artif icial Intelligence)
Study Data from Technical University Munich (TU Munich) Update Understanding of Artificial Intelligence (Analyzing Credit Spread Changes Using Explainable Artif icial Intelligence)
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Fresh data on Artificial Intelligence are presented in a new report. According to news reporting from Garching, German y, by NewsRx journalists, research stated, “We compare linear regression, local polynomial regression and selected machine learning methods for modeling credit spread changes. Using partial dependence plots (PDPs) and H-statistic, we find t hat the outperformance of machine learning models compared to regression ones is mostly attributable to complex non-linearities and not to interactions.” The news correspondents obtained a quote from the research from Technical Univer sity Munich (TU Munich), “The PDPs are additionally used to perform a factor hed ging. For the first time, credit spread changes are decomposed by applying SHapl ey Additive exPlanation (SHAP) values. The proposed frame-work is applied to US a nd Euro Area corporate and covered bond credit spread changes of different matur ities to quantify the influence of several macroeconomic and financial variables .”
GarchingGermanyEuropeArtificial In telligenceCyborgsEmerging TechnologiesMachine LearningTechnical Universi ty Munich (TU Munich)
NETL
NSTL
