Fukoku Co Ltd Credit Rating & Financial Statements Analysis

BOSTON (AI Credit Rating Terminal) Fri Jun 04 2021 11:00:02 GMT+0000 (Coordinated Universal Time) AI Credit Ratings today took the rating actions below:

Financial Statements Overview & Credit Rating Rationales


We rerated Fukoku Co Ltd because market risk charges capture the risk of loss on trading portfolio at a one-year horizon and a 99.9% confidence level. (We use econometric methods for period (n+1) simulate with Keltner Channels Linear Regression). In addition, a speculative-grade company's access to the credit markets during times of stress, such as the financial crisis, is often a function of the capital market's appetite for risk. Accordingly, it would be rare that we would characterize a speculative-grade company as having a generally high standing in the credit markets, and even low-investment-grade companies may not have access to a diversity of funding sources required for this assessment. 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 Fukoku Co Ltd as of 04 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 Fukoku Co Ltd as below:

Credit Ratings for Fukoku Co Ltd as of 04 Jun 2021


Credit Rating Short-Term Long-Term Senior
AI Rating Class*B1Ba3
Semantic Signals7474
Financial Signals3665
Risk Signals7081
Substantial Risks5681
Speculative Signals7431

*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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