ROTORK PLC Credit Rating & Financial Statements Analysis

BOSTON (AI Credit Rating Terminal) Sat Jun 05 2021 05:30:02 GMT+0000 (Coordinated Universal Time) AI Credit Ratings today took the rating actions below:

Financial Statements Overview & Credit Rating Rationales


We rerated ROTORK PLC 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+30) simulate with Gunn Oscillator Lasso Regression). We do not assume future debt refinancing or the rolling over of CP, regardless of the company's perceived credit strength or issuer credit rating. For instance, even for investment-grade issuers, we do not assume future debt maturities are refinanced with potential uncommitted capital raises. We could, however, consider a shorter time horizon. 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.

Risk Heat Map for ROTORK PLC as of 05 Jun 2021


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 ROTORK PLC as below:

Credit Ratings for ROTORK PLC as of 05 Jun 2021


Credit Rating Short-Term Long-Term Senior
AI Rating Class*Ba3B3
Semantic Signals4551
Financial Signals7147
Risk Signals8442
Substantial Risks4445
Speculative Signals8847

*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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Disclaimers: AC Investment Inc. currently does not act as an equities executing broker, credit rating agency or route orders containing equities securities. In our Machine Learning experiment, we focus on an approach known as Decision making using game theory. We apply principles from game theory to model the relationships between rating actions, news, market signals and decision making.The rating information provided is for informational, non-commercial purposes only, does not constitute investment advice and is subject to conditions available in our Legal Disclaimer. Usage as a credit rating or as a benchmark is not permitted.

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