Rating Action Overview
We downgraded Tecomet Inc. 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+7) simulate with Ratiocator (RAT) Beta. Reference code is: 3191. Beta DRL value REG 14 Rational Demand Factor LD 4101.2118. In our assessment of a company's liquidity, we also consider the impact of unique industry characteristics. 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 Tecomet Inc. as below:
Credit Ratings for Tecomet Inc. as of 30 Jun 2020
| Credit Rating | Short-Term | Long-Term Senior |
|---|---|---|
| AI Rating Class* | B1 | B2 |
| Semantic Signals | 88 | 33 |
| Financial Signals | 51 | 37 |
| Risk Signals | 58 | 52 |
| Substantial Risks | 50 | 55 |
| Speculative Signals | 46 | 79 |
*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.
