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Learfield Communications, LLC Credit Rating & Financial Statements Analysis

BOSTON (AI Credit Rating Terminal) Tue Jun 15 2021 01:30:02 GMT+0000 (Coordinated Universal Time) AI Credit Ratings today took the rating actions below:

Financial Statements Overview & Credit Rating Rationales


We rerated Learfield Communications, LLC because of covenant, legal, tax, regulatory, or other characteristics of the group structure (for example, minority interests) are not a significant constraint on the flow of loss-absorbing capital among group members. (We use econometric methods for period (n+1) simulate with Rate of Change (ROC) Linear Regression). For companies in more volatile sectors, we assess the resiliency of liquidity through a cycle. If we do not believe the resulting descriptor reflects sustainable liquidity characteristics, we could adjust our liquidity assessment downward. For example, we could lower our liquidity assessment on a volatile company to strong from exceptional if we believe key quantitative measures typical of exceptional liquidity are not sustainable over the forecast period. This could especially be true if we believe there is a higher prospect of ratios weakening from the peak of an economic cycle. 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 Learfield Communications, LLC as of 15 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 Learfield Communications, LLC as below:

Credit Ratings for Learfield Communications, LLC as of 15 Jun 2021


Credit Rating Short-Term Long-Term Senior
AI Rating Class*Ba3Ba2
Semantic Signals7582
Financial Signals8064
Risk Signals8468
Substantial Risks3866
Speculative Signals3857

*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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