首页|Central South University Reports Findings in Machine Learning (Do green finance and green innovation affect corporate credit rating performance? Evidence from m achine learning approach)
Central South University Reports Findings in Machine Learning (Do green finance and green innovation affect corporate credit rating performance? Evidence from m achine learning approach)
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 – New research on Machine Learning is th e subject of a report. According to news originating from Changsha, People’s Rep ublic of China, by NewsRx correspondents, research stated, “This study investiga tes the impact of green finance (GF) and green innovation (GI) on corporate cred it rating (CR) performance in Chinese A-share listed firms from 2018 to 2021. Th e least absolute shrinkage and selection operators (LASSOs) machine learning alg orithms are first used to select the critical drivers of corporate credit perfor mance.” Our news journalists obtained a quote from the research from Central South Unive rsity, “Then, we applied partialing-out LASSO linear regression (POLR) and doubl e selection LASSO linear regression (DSLR) machine learning techniques to check the impact of GF and GI on CR. The main results reveal that a 1% i ncrease in GF diminishes CR by 0.26%, whereas GI promotes CR perfor mance by 0.15%. Moreover, the heterogeneity analysis reveals a more significant negative effect of GF on the CR performance of heavily polluting fi rms, non-state-owned enterprises, and firms in the Western region.”
ChangshaPeople’s Republic of ChinaAs iaCyborgsEmerging TechnologiesMachine Learning
NETL
NSTL
