Ocean Bio-Chem, Inc. Credit Rating

BOSTON (AI Credit Rating Terminal) Sat Aug 01 2020 12:19:02 GMT+0000 (Coordinated Universal Time) AI Credit Ratings today took the rating actions below:

Rating Action Overview


We downgraded Ocean Bio-Chem, Inc. because the liabilities' resolution-driven default is unlikely because of all of the following: The type of liability is earmarked in the resolution framework for potential exclusion from bail-in at the discretion of the national regulator, other creditors in our view are unlikely to legally challenge such an exclusion. We use econometric methods for period (n+7) simulate with Armstrong Oscillator Ridge Regression. Reference code is: 4701. Beta DRL value REG 42 Rational Demand Factor LD 4359.9024. 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 Ocean Bio-Chem, Inc. as below:

Credit Ratings for Ocean Bio-Chem, Inc. as of 01 Aug 2020


Credit Rating Short-Term Long-Term Senior
AI Rating Class*Ba2B1
Semantic Signals7034
Financial Signals5956
Risk Signals8081
Substantial Risks4232
Speculative Signals8882

*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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