Shanghai Electric Group Company Limited Credit Rating

BOSTON (AI Credit Rating Terminal) Fri Jul 31 2020 00:19:03 GMT+0000 (Coordinated Universal Time) AI Credit Ratings today took the rating actions below:

Rating Action Overview


We downgraded Shanghai Electric Group Company Limited because of the firm's business is modestly more concentrated than average for peers, and the concentration represents modest incremental risk above what is captured in the anchor, but it is not a key credit weakness. We use econometric methods for period (n+7) simulate with Running Moving Average (RMA) Lasso Regression. Reference code is: 4519. Beta DRL value REG 42 Rational Demand Factor LD 4502.463. Larger, investment-grade issuers that have access to both public and private debt markets have greater flexibility than companies that depend solely on private bank loans. In addition, we consider whether a company can borrow on an unsecured basis, has access to the commercial paper markets, and issues debt in multiple geographies. It is more costly to raise debt in the public bond markets and often requires a company to establish a track record among investors. These costs and information asymmetry issues sometimes make it impractical for smaller, speculative-grade issuers to raise small amounts of debt in public markets. Credit Rating AI Process rely on primary sources of information: Sec Filings, Financial Statements, Credit Ratings, Semantic Signals. Take a look at Machine Learning section for Financial Deep Reinforcement Learning.Oscillators are used for generating credit risk signals by using the semantic and financial signals. The value of the oscillators indicate the strength of trend. Using the correlation matrices, the credit rating risk map for Shanghai Electric Group Company Limited as below:

Credit Ratings for Shanghai Electric Group Company Limited as of 31 Jul 2020


Credit Rating Short-Term Long-Term Senior
AI Rating Class*B3B2
Semantic Signals7755
Financial Signals6541
Risk Signals3643
Substantial Risks3372
Speculative Signals4734

*Machine Learning utilizes multiple learning algorithms to obtain better predictive powers. In our research, we utilize machine learning to combine the results from the Neural Network and Support Vector Machines.
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