The stock price realization for NSE:UGARSUGAR is a decision making process between multiple investors each of which controls a subset of design variables and seeks to minimize its cost function subject to future forecast constraints. That is, investors act like players in a game; they cooperate to achieve a set of overall goals. 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 with Triple Exponential Moving Average (TRIX) and Paired T-Test. Machine Learning based stock forecast (n+30) for UGARSUGAR The Ugar Sugar Works Limited as below: UGARSUGAR The Ugar Sugar Works Limited Stock Forecast (Buy or Sell) as of 31 Oct 2021 for (n+30) How Does Forecast Model Work? x axis:Likelihood % y axis:Potential Impact % z axis:Color (yellow to green) Technical Analysis % Stock Forecast Rationales & Estimation Model Time series to forecast n: 31 Oc

BOSTON (AC Invest Credit Rating Terminal) Sun Oct 31 2021 10:55:02 GMT+0000 (Coordinated Universal Time) AI Credit Ratings today took the rating actions below: Credit Rating Rationales & Model For new issuers, while our ratings are prospective, we will not include proposed financing as a source in our liquidity calculations until the financing has been obtained or is fully underwritten. Similarly, we would not include rights issues as a source of liquidity for a company, unless the rights issue is irrevocably guaranteed (for example, an underwriter agrees to buy any securities not taken up by existing holders). Rating Model for Huntington Ingalls Industries, Inc. Common Stock: We estimate the credit risk parameters by Running Moving Average (RMA) and Wilcoxon Sign-Rank Test Credit Ratings for Huntington Ingalls Industries, Inc. Common Stock as of 31 Oct 2021 Credit Rating Short-Term Long-Term Senior AI Rating Class* Ba3 B1 Semantic Signals 69 49 Financial

The stock price realization for NASDAQ:EQ is a decision making process between multiple investors each of which controls a subset of design variables and seeks to minimize its cost function subject to future forecast constraints. That is, investors act like players in a game; they cooperate to achieve a set of overall goals. 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 with Average True Range (ATR) and Linear Regression. Machine Learning based stock forecast (n+30) for EQ Equillium as below: EQ Equillium Stock Forecast (Buy or Sell) as of 31 Oct 2021 for (n+30) How Does Forecast Model Work? x axis:Likelihood % y axis:Potential Impact % z axis:Color (yellow to green) Technical Analysis % Stock Forecast Rationales & Estimation Model Time series to forecast n: 31 Oct 2021 for (n+30) If a company has a credit put that causes debt acc

BOSTON (AC Invest Credit Rating Terminal) Sun Oct 31 2021 10:25:02 GMT+0000 (Coordinated Universal Time) AI Credit Ratings today took the rating actions below: Credit Rating Rationales & Model Our liquidity uses include dividends and share repurchases that we expect under a stress scenario. Unlike other potential uses of liquidity, such as debt maturities or maintenance capital spending, we view dividends and share repurchases as more discretionary, although more so for the latter. For this reason, when evaluating a company's liquidity position, we may use a lower estimate of dividends and shareholder repurchases than in our base-case forecast based on our views of management and the company's track record in terms of shareholder returns and maintaining a certain minimum level of liquidity. Rating Model for Golub Capital BDC, Inc.: We estimate the credit risk parameters by EMR and ANOVA Credit Ratings for Golub Capital BDC, Inc. as of 31 Oct 2021 Credit Ratin

The stock price realization for NASDAQ:PFBI is a decision making process between multiple investors each of which controls a subset of design variables and seeks to minimize its cost function subject to future forecast constraints. That is, investors act like players in a game; they cooperate to achieve a set of overall goals. 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 with Price and ANOVA. Machine Learning based stock forecast (n+1y) for PFBI Premier Financial Bancorp as below: PFBI Premier Financial Bancorp Stock Forecast (Buy or Sell) as of 31 Oct 2021 for (n+1y) How Does Forecast Model Work? x axis:Likelihood % y axis:Potential Impact % z axis:Color (yellow to green) Technical Analysis % Stock Forecast Rationales & Estimation Model Time series to forecast n: 31 Oct 2021 for (n+1y) While we only include contractual acquisiti

BOSTON (AC Invest Credit Rating Terminal) Sun Oct 31 2021 09:55:02 GMT+0000 (Coordinated Universal Time) AI Credit Ratings today took the rating actions below: Credit Rating Rationales & Model We do not include potential future debt issuances as a source of liquidity because of the uncertainty of a company's ability to access debt markets in times of financial stress, even for investment-grade issuers. For instance, in the case of a proposed financing, with the intended use of proceeds to repay existing debt, we will assess a company's liquidity excluding the proposed financing until it's obtained or fully underwritten. Rating Model for KKR Financial Holdings LLC Pfd Ser A Llc: We estimate the credit risk parameters by Profit and Beta Credit Ratings for KKR Financial Holdings LLC Pfd Ser A Llc as of 31 Oct 2021 Credit Rating Short-Term Long-Term Senior AI Rating Class* B1 Ba3 Semantic Signals 65 79 Financial Signals 45 65 Risk Signals 73 70

The stock price realization for NYSE:ENS is a decision making process between multiple investors each of which controls a subset of design variables and seeks to minimize its cost function subject to future forecast constraints. That is, investors act like players in a game; they cooperate to achieve a set of overall goals. 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 with Voltage Controlled Oscillator and Beta. Machine Learning based stock forecast (n+15) for ENS Enersys as below: ENS Enersys Stock Forecast (Buy or Sell) as of 31 Oct 2021 for (n+15) How Does Forecast Model Work? x axis:Likelihood % y axis:Potential Impact % z axis:Color (yellow to green) Technical Analysis % Stock Forecast Rationales & Estimation Model Time series to forecast n: 31 Oct 2021 for (n+15) In these cases, the level of capital expenditures will be low

BOSTON (AC Invest Credit Rating Terminal) Sun Oct 31 2021 09:25:02 GMT+0000 (Coordinated Universal Time) AI Credit Ratings today took the rating actions below: Credit Rating Rationales & Model 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. Rating Model for Kimco Realty Corporation DEPOSITARY SH REPSTG 1/1000TH PFD SER I: We estimate the credit risk parameters by Gunn Oscillator and Sign Test Credit Ratings for Kimco Realty Corporation DEPOSITARY SH REPSTG 1/1000TH PFD SER I as of 31 Oct 2021 Credit Rating Short-Term Long-Term Senior AI Rating Class* B1 B2 Semantic Signals 78 68 Financial Signals 57 38 Risk Signals 75 55 Substantial Risks 30 62 Speculative

The stock price realization for NSE:KUANTUM is a decision making process between multiple investors each of which controls a subset of design variables and seeks to minimize its cost function subject to future forecast constraints. That is, investors act like players in a game; they cooperate to achieve a set of overall goals. 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 with Multi-Wave Oscillators and Sign Test. Machine Learning based stock forecast (n+30) for KUANTUM Kuantum Papers Limited as below: KUANTUM Kuantum Papers Limited Stock Forecast (Buy or Sell) as of 31 Oct 2021 for (n+30) How Does Forecast Model Work? x axis:Likelihood % y axis:Potential Impact % z axis:Color (yellow to green) Technical Analysis % Stock Forecast Rationales & Estimation Model Time series to forecast n: 31 Oct 2021 for (n+30) If a company has a cre

BOSTON (AC Invest Credit Rating Terminal) Sun Oct 31 2021 08:55:02 GMT+0000 (Coordinated Universal Time) AI Credit Ratings today took the rating actions below: Credit Rating Rationales & Model Investments should be able to be quickly liquidated without requiring deep discounts to their carrying value. This does not preclude long-term investments from being included. It does, however, exclude large stakes in non-liquid equity investments. Rating Model for Apple REIT Seven, Inc.: We estimate the credit risk parameters by Gunn Oscillator and Chi-Square Credit Ratings for Apple REIT Seven, Inc. as of 31 Oct 2021 Credit Rating Short-Term Long-Term Senior AI Rating Class* Baa2 Ba3 Semantic Signals 68 59 Financial Signals 88 61 Risk Signals 88 59 Substantial Risks 65 82 Speculative Signals 69 50 *Machine Learning utilizes multiple learning algorithms to obtain better predictive powers. In our research, we utilize machine learning to combine the results from

The stock price realization for NASDAQ:CASS is a decision making process between multiple investors each of which controls a subset of design variables and seeks to minimize its cost function subject to future forecast constraints. That is, investors act like players in a game; they cooperate to achieve a set of overall goals. 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 with Profit and Factor. Machine Learning based stock forecast (n+7) for CASS Cass Information Systems as below: CASS Cass Information Systems Stock Forecast (Buy or Sell) as of 31 Oct 2021 for (n+7) How Does Forecast Model Work? x axis:Likelihood % y axis:Potential Impact % z axis:Color (yellow to green) Technical Analysis % Stock Forecast Rationales & Estimation Model Time series to forecast n: 31 Oct 2021 for (n+7) Our liquidity uses include dividends and share

BOSTON (AC Invest Credit Rating Terminal) Sun Oct 31 2021 08:25:02 GMT+0000 (Coordinated Universal Time) AI Credit Ratings today took the rating actions below: Credit Rating Rationales & Model For new issuers, while our ratings are prospective, we will not include proposed financing as a source in our liquidity calculations until the financing has been obtained or is fully underwritten. Similarly, we would not include rights issues as a source of liquidity for a company, unless the rights issue is irrevocably guaranteed (for example, an underwriter agrees to buy any securities not taken up by existing holders). Rating Model for WEBAC HOLDING AG: We estimate the credit risk parameters by Rating and ANOVA Credit Ratings for WEBAC HOLDING AG as of 31 Oct 2021 Credit Rating Short-Term Long-Term Senior AI Rating Class* B1 B2 Semantic Signals 89 50 Financial Signals 32 67 Risk Signals 34 45 Substantial Risks 78 56 Speculative Signals 73 34 *Machine Learnin

The stock price realization for NYSE:CCL is a decision making process between multiple investors each of which controls a subset of design variables and seeks to minimize its cost function subject to future forecast constraints. That is, investors act like players in a game; they cooperate to achieve a set of overall goals. 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 with Money Flow Index (MFI) and Polynomial Regression. Machine Learning based stock forecast (n+30) for CCL Carnival Corporation as below: CCL Carnival Corporation Stock Forecast (Buy or Sell) as of 31 Oct 2021 for (n+30) How Does Forecast Model Work? x axis:Likelihood % y axis:Potential Impact % z axis:Color (yellow to green) Technical Analysis % Stock Forecast Rationales & Estimation Model Time series to forecast n: 31 Oct 2021 for (n+30) We do not exclude cash th

BOSTON (AC Invest Credit Rating Terminal) Sun Oct 31 2021 07:55:02 GMT+0000 (Coordinated Universal Time) AI Credit Ratings today took the rating actions below: Credit Rating Rationales & Model For new issuers, while our ratings are prospective, we will not include proposed financing as a source in our liquidity calculations until the financing has been obtained or is fully underwritten. Similarly, we would not include rights issues as a source of liquidity for a company, unless the rights issue is irrevocably guaranteed (for example, an underwriter agrees to buy any securities not taken up by existing holders). Rating Model for IRC Retail Centers LLC: We estimate the credit risk parameters by RC Phase Shift Oscillator and Linear Regression Credit Ratings for IRC Retail Centers LLC as of 31 Oct 2021 Credit Rating Short-Term Long-Term Senior AI Rating Class* Baa2 B2 Semantic Signals 90 33 Financial Signals 46 63 Risk Signals 88 78 Substantial Risks 79 32

The stock price realization for NASDAQ:PRDO is a decision making process between multiple investors each of which controls a subset of design variables and seeks to minimize its cost function subject to future forecast constraints. That is, investors act like players in a game; they cooperate to achieve a set of overall goals. 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 with Running Moving Average (RMA) and Paired T-Test. Machine Learning based stock forecast (n+1y) for PRDO Perdoceo Education Corporation as below: PRDO Perdoceo Education Corporation Stock Forecast (Buy or Sell) as of 31 Oct 2021 for (n+1y) How Does Forecast Model Work? x axis:Likelihood % y axis:Potential Impact % z axis:Color (yellow to green) Technical Analysis % Stock Forecast Rationales & Estimation Model Time series to forecast n: 31 Oct 2021 for (n+1y) To

BOSTON (AC Invest Credit Rating Terminal) Sun Oct 31 2021 07:25:03 GMT+0000 (Coordinated Universal Time) AI Credit Ratings today took the rating actions below: Credit Rating Rationales & Model To assess forecasted working capital outflows for companies with material intra-year working capital requirements (for example, companies in seasonal businesses), we use forecasted peak working capital outflows, per paragraph 32 of the liquidity criteria. For seasonal businesses, in many cases the annual projection might indicate a working capital inflow or neutral working capital, even though there could be material intra-quarter or inter-quarter outflows throughout the year. Rating Model for Hongda High-Tech Holding Co Ltd: We estimate the credit risk parameters by Rating and Wilcoxon Rank-Sum Test Credit Ratings for Hongda High-Tech Holding Co Ltd as of 31 Oct 2021 Credit Rating Short-Term Long-Term Senior AI Rating Class* B2 B2 Semantic Signals 88 43 Financial S

The stock price realization for NSE:PIONEEREMB is a decision making process between multiple investors each of which controls a subset of design variables and seeks to minimize its cost function subject to future forecast constraints. That is, investors act like players in a game; they cooperate to achieve a set of overall goals. 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 with Relative Strength Index (RSI) and Wilcoxon Rank-Sum Test. Machine Learning based stock forecast (n+15) for PIONEEREMB Pioneer Embroideries Limited as below: PIONEEREMB Pioneer Embroideries Limited Stock Forecast (Buy or Sell) as of 31 Oct 2021 for (n+15) How Does Forecast Model Work? x axis:Likelihood % y axis:Potential Impact % z axis:Color (yellow to green) Technical Analysis % Stock Forecast Rationales & Estimation Model Time series to forecast n: 31 O

BOSTON (AC Invest Credit Rating Terminal) Sun Oct 31 2021 06:55:03 GMT+0000 (Coordinated Universal Time) AI Credit Ratings today took the rating actions below: Credit Rating Rationales & Model Other factors we consider include a company's frequency of debt issuance and market access, especially during times of company-specific stress or credit market turbulence. Rating Model for China Television Media, Ltd: We estimate the credit risk parameters by Demand and Wilcoxon Rank-Sum Test Credit Ratings for China Television Media, Ltd as of 31 Oct 2021 Credit Rating Short-Term Long-Term Senior AI Rating Class* Ba2 B2 Semantic Signals 57 44 Financial Signals 82 67 Risk Signals 86 48 Substantial Risks 76 34 Speculative Signals 48 76 *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.

The stock price realization for NASDAQ:SEDG is a decision making process between multiple investors each of which controls a subset of design variables and seeks to minimize its cost function subject to future forecast constraints. That is, investors act like players in a game; they cooperate to achieve a set of overall goals. 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 with RRS and Spearman Correlation. Machine Learning based stock forecast (n+6m) for SEDG SolarEdge Technologies as below: SEDG SolarEdge Technologies Stock Forecast (Buy or Sell) as of 31 Oct 2021 for (n+6m) How Does Forecast Model Work? x axis:Likelihood % y axis:Potential Impact % z axis:Color (yellow to green) Technical Analysis % Stock Forecast Rationales & Estimation Model Time series to forecast n: 31 Oct 2021 for (n+6m) We believe that when a company is vi

BOSTON (AC Invest Credit Rating Terminal) Sun Oct 31 2021 06:25:02 GMT+0000 (Coordinated Universal Time) AI Credit Ratings today took the rating actions below: Credit Rating Rationales & Model Given the earnings volatility companies experience, we have specified for these issuers a more stringent decline in EBITDA percentage for each liquidity category to the extent our cash flow forecasts are not already assuming a downside scenario. Rating Model for Medius Holdings Co Ltd: We estimate the credit risk parameters by Expectation and Sign Test Credit Ratings for Medius Holdings Co Ltd as of 31 Oct 2021 Credit Rating Short-Term Long-Term Senior AI Rating Class* B3 B3 Semantic Signals 75 34 Financial Signals 36 53 Risk Signals 41 38 Substantial Risks 40 37 Speculative Signals 38 58 *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

The stock price realization for NYSE:NWE is a decision making process between multiple investors each of which controls a subset of design variables and seeks to minimize its cost function subject to future forecast constraints. That is, investors act like players in a game; they cooperate to achieve a set of overall goals. 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 with Crystal Oscillators and Wilcoxon Rank-Sum Test. Machine Learning based stock forecast (n+6m) for NWE NorthWestern Corporation as below: NWE NorthWestern Corporation Stock Forecast (Buy or Sell) as of 31 Oct 2021 for (n+6m) How Does Forecast Model Work? x axis:Likelihood % y axis:Potential Impact % z axis:Color (yellow to green) Technical Analysis % Stock Forecast Rationales & Estimation Model Time series to forecast n: 31 Oct 2021 for (n+6m) Our liquidity uses

BOSTON (AC Invest Credit Rating Terminal) Sun Oct 31 2021 05:55:02 GMT+0000 (Coordinated Universal Time) AI Credit Ratings today took the rating actions below: Credit Rating Rationales & Model Given the earnings volatility companies experience, we have specified for these issuers a more stringent decline in EBITDA percentage for each liquidity category to the extent our cash flow forecasts are not already assuming a downside scenario. Rating Model for Xin Point Holdings Ltd: We estimate the credit risk parameters by Ring Oscillators and Simple Regression Credit Ratings for Xin Point Holdings Ltd as of 31 Oct 2021 Credit Rating Short-Term Long-Term Senior AI Rating Class* B1 B3 Semantic Signals 48 41 Financial Signals 71 42 Risk Signals 34 38 Substantial Risks 88 42 Speculative Signals 58 52 *Machine Learning utilizes multiple learning algorithms to obtain better predictive powers. In our research, we utilize machine learning to combine the results fr

The stock price realization for NASDAQ:LSXMB is a decision making process between multiple investors each of which controls a subset of design variables and seeks to minimize its cost function subject to future forecast constraints. That is, investors act like players in a game; they cooperate to achieve a set of overall goals. 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 with OCL and ANOVA. Machine Learning based stock forecast (n+7) for LSXMB Liberty Media Corporation as below: LSXMB Liberty Media Corporation Stock Forecast (Buy or Sell) as of 31 Oct 2021 for (n+7) How Does Forecast Model Work? x axis:Likelihood % y axis:Potential Impact % z axis:Color (yellow to green) Technical Analysis % Stock Forecast Rationales & Estimation Model Time series to forecast n: 31 Oct 2021 for (n+7) If we believe a company would use cash trappe

BOSTON (AC Invest Credit Rating Terminal) Sun Oct 31 2021 05:25:02 GMT+0000 (Coordinated Universal Time) AI Credit Ratings today took the rating actions below: Credit Rating Rationales & Model When assessing strong or exceptional liquidity, we include all forecasted capital expenditures over the next 24 months, including discretionary growth capital spending. Rating Model for H. PAT HENSON COMPANY, THE: We estimate the credit risk parameters by Price Oscillator (PPO) and Sign Test Credit Ratings for H. PAT HENSON COMPANY, THE as of 31 Oct 2021 Credit Rating Short-Term Long-Term Senior AI Rating Class* B2 Ba3 Semantic Signals 50 48 Financial Signals 78 51 Risk Signals 41 64 Substantial Risks 74 68 Speculative Signals 43 78 *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.

The stock price realization for NSE:VENKEYS is a decision making process between multiple investors each of which controls a subset of design variables and seeks to minimize its cost function subject to future forecast constraints. That is, investors act like players in a game; they cooperate to achieve a set of overall goals. 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 with Rate of Change (ROC) and Linear Regression. Machine Learning based stock forecast (n+6m) for VENKEYS Venky's (India) Limited as below: VENKEYS Venky's (India) Limited Stock Forecast (Buy or Sell) as of 31 Oct 2021 for (n+6m) How Does Forecast Model Work? x axis:Likelihood % y axis:Potential Impact % z axis:Color (yellow to green) Technical Analysis % Stock Forecast Rationales & Estimation Model Time series to forecast n: 31 Oct 2021 for (n+6m) While

BOSTON (AC Invest Credit Rating Terminal) Sun Oct 31 2021 04:55:02 GMT+0000 (Coordinated Universal Time) AI Credit Ratings today took the rating actions below: Credit Rating Rationales & Model For new issuers, while our ratings are prospective, we will not include proposed financing as a source in our liquidity calculations until the financing has been obtained or is fully underwritten. Similarly, we would not include rights issues as a source of liquidity for a company, unless the rights issue is irrevocably guaranteed (for example, an underwriter agrees to buy any securities not taken up by existing holders). Rating Model for Retech Technology Co Ltd: We estimate the credit risk parameters by Sustainability and Ridge Regression Credit Ratings for Retech Technology Co Ltd as of 31 Oct 2021 Credit Rating Short-Term Long-Term Senior AI Rating Class* B1 Caa1 Semantic Signals 81 44 Financial Signals 46 42 Risk Signals 42 37 Substantial Risks 68 34 Specula

The stock price realization for NYSE:GWB is a decision making process between multiple investors each of which controls a subset of design variables and seeks to minimize its cost function subject to future forecast constraints. That is, investors act like players in a game; they cooperate to achieve a set of overall goals. 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 with Voltage Controlled Oscillator and Sign Test. Machine Learning based stock forecast (n+6m) for GWB Great Western Bancorp as below: GWB Great Western Bancorp Stock Forecast (Buy or Sell) as of 31 Oct 2021 for (n+6m) How Does Forecast Model Work? x axis:Likelihood % y axis:Potential Impact % z axis:Color (yellow to green) Technical Analysis % Stock Forecast Rationales & Estimation Model Time series to forecast n: 31 Oct 2021 for (n+6m) To assess an issuer's st

BOSTON (AC Invest Credit Rating Terminal) Sun Oct 31 2021 04:25:02 GMT+0000 (Coordinated Universal Time) AI Credit Ratings today took the rating actions below: Credit Rating Rationales & Model We do not include potential future debt issuances as a source of liquidity because of the uncertainty of a company's ability to access debt markets in times of financial stress, even for investment-grade issuers. For instance, in the case of a proposed financing, with the intended use of proceeds to repay existing debt, we will assess a company's liquidity excluding the proposed financing until it's obtained or fully underwritten. Rating Model for WELLNET CORPORATION: We estimate the credit risk parameters by Pearson-Anson Oscillators and Sign Test Credit Ratings for WELLNET CORPORATION as of 31 Oct 2021 Credit Rating Short-Term Long-Term Senior AI Rating Class* B2 Ba3 Semantic Signals 74 72 Financial Signals 34 70 Risk Signals 45 33 Substantial Risks

The stock price realization for NASDAQ:MEET is a decision making process between multiple investors each of which controls a subset of design variables and seeks to minimize its cost function subject to future forecast constraints. That is, investors act like players in a game; they cooperate to achieve a set of overall goals. 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 with Running Moving Average (RMA) and Spearman Correlation. Machine Learning based stock forecast (n+7) for MEET The Meet Group as below: MEET The Meet Group Stock Forecast (Buy or Sell) as of 31 Oct 2021 for (n+7) How Does Forecast Model Work? x axis:Likelihood % y axis:Potential Impact % z axis:Color (yellow to green) Technical Analysis % Stock Forecast Rationales & Estimation Model Time series to forecast n: 31 Oct 2021 for (n+7) Under times of stress, such ac

BOSTON (AC Invest Credit Rating Terminal) Sun Oct 31 2021 03:55:02 GMT+0000 (Coordinated Universal Time) AI Credit Ratings today took the rating actions below: Credit Rating Rationales & Model When calculating sources of liquidity, we only include the undrawn, available portion of committed bank lines maturing beyond the specified time horizon for each liquidity descriptor. For example, when assessing liquidity as adequate, we only include a committed revolving credit facility as a source if it matured beyond the next 12 months. Similarly, given that our liquidity assessment looks out over two years when assessing liquidity as strong or exceptional, we only include a facility maturing beyond 24 months as a source of liquidity. Rating Model for Shenzhen CDL Precision Technology Co Ltd: We estimate the credit risk parameters by Moving Average Convergence Divergence (MACD) and Lasso Regression Credit Ratings for Shenzhen CDL Precision Technology Co Ltd as of 31 Oct 2021

The stock price realization for NASDAQ:COHR is a decision making process between multiple investors each of which controls a subset of design variables and seeks to minimize its cost function subject to future forecast constraints. That is, investors act like players in a game; they cooperate to achieve a set of overall goals. 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 with Chaikin Oscillator and Lasso Regression. Machine Learning based stock forecast (n+7) for COHR Coherent as below: COHR Coherent Stock Forecast (Buy or Sell) as of 31 Oct 2021 for (n+7) How Does Forecast Model Work? x axis:Likelihood % y axis:Potential Impact % z axis:Color (yellow to green) Technical Analysis % Stock Forecast Rationales & Estimation Model Time series to forecast n: 31 Oct 2021 for (n+7) Asset divestitures. We do not include asset sales as a

BOSTON (AC Invest Credit Rating Terminal) Sun Oct 31 2021 03:25:02 GMT+0000 (Coordinated Universal Time) AI Credit Ratings today took the rating actions below: Credit Rating Rationales & Model Shared facilities with captive finance entities. When an issuer has a shared revolving credit facility with a captive finance entity, for purposes of calculating the issuer's liquidity sources, we net outstanding commercial paper at the captive from the revolver's borrowing availability. In these cases, we generally use an estimate of peak CP borrowings at the captive to avoid potentially overstating sources available to the issuer over a 12- to 24-month period. Rating Model for Nacogdoches Commercial Bancshares: We estimate the credit risk parameters by Dynatron Oscillators and ANOVA Credit Ratings for Nacogdoches Commercial Bancshares as of 31 Oct 2021 Credit Rating Short-Term Long-Term Senior AI Rating Class* B2 B3 Semantic Signals 52 45 Financial Signal

The stock price realization for NASDAQ:FAAR is a decision making process between multiple investors each of which controls a subset of design variables and seeks to minimize its cost function subject to future forecast constraints. That is, investors act like players in a game; they cooperate to achieve a set of overall goals. 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 with Volume + Moving Average and ElasticNet Regression. Machine Learning based stock forecast (n+6m) for FAAR First Trust Alternative Absolute Return Strategy ETF as below: FAAR First Trust Alternative Absolute Return Strategy ETF Stock Forecast (Buy or Sell) as of 31 Oct 2021 for (n+6m) How Does Forecast Model Work? x axis:Likelihood % y axis:Potential Impact % z axis:Color (yellow to green) Technical Analysis % Stock Forecast Rationales & Estimation Model Time

BOSTON (AC Invest Credit Rating Terminal) Sun Oct 31 2021 02:55:02 GMT+0000 (Coordinated Universal Time) AI Credit Ratings today took the rating actions below: Credit Rating Rationales & Model Other factors we consider include a company's frequency of debt issuance and market access, especially during times of company-specific stress or credit market turbulence. Rating Model for Oculina Bank: We estimate the credit risk parameters by Pearson-Anson Oscillators and Stepwise Regression Credit Ratings for Oculina Bank as of 31 Oct 2021 Credit Rating Short-Term Long-Term Senior AI Rating Class* B1 Ba3 Semantic Signals 53 59 Financial Signals 71 81 Risk Signals 69 68 Substantial Risks 40 54 Speculative Signals 75 50 *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.

The stock price realization for LON:RIO is a decision making process between multiple investors each of which controls a subset of design variables and seeks to minimize its cost function subject to future forecast constraints. That is, investors act like players in a game; they cooperate to achieve a set of overall goals. 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 with Aroon and Stepwise Regression. Machine Learning based stock forecast (n+1y) for RIO RIO TINTO PLC as below: RIO RIO TINTO PLC Stock Forecast (Buy or Sell) as of 31 Oct 2021 for (n+1y) How Does Forecast Model Work? x axis:Likelihood % y axis:Potential Impact % z axis:Color (yellow to green) Technical Analysis % Stock Forecast Rationales & Estimation Model Time series to forecast n: 31 Oct 2021 for (n+1y) If a company has a credit put that causes debt acceleration

BOSTON (AC Invest Credit Rating Terminal) Sun Oct 31 2021 02:25:02 GMT+0000 (Coordinated Universal Time) AI Credit Ratings today took the rating actions below: Credit Rating Rationales & Model For example, if a company incurred a large working capital inflow in the fourth quarter, which more than offset working capital outflows during the first three quarters, we would use the peak working capital outflows within our A/B and A-B calculation. However, we avoid double-counting when the working capital outflow is already captured through our assumption of peak CP amount. Rating Model for Kentucky First Federal Bancorp: We estimate the credit risk parameters by Keltner Channels and Linear Regression Credit Ratings for Kentucky First Federal Bancorp as of 31 Oct 2021 Credit Rating Short-Term Long-Term Senior AI Rating Class* B2 B1 Semantic Signals 38 83 Financial Signals 38 77 Risk Signals 75 48 Substantial Risks 55 30 Speculative Signals 64 59 *Machine L

The stock price realization for LON:RICO is a decision making process between multiple investors each of which controls a subset of design variables and seeks to minimize its cost function subject to future forecast constraints. That is, investors act like players in a game; they cooperate to achieve a set of overall goals. 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 with Parabolic SAR (PSAR) and Stepwise Regression. Machine Learning based stock forecast (n+7) for RICO RICOH CO LTD as below: RICO RICOH CO LTD Stock Forecast (Buy or Sell) as of 31 Oct 2021 for (n+7) How Does Forecast Model Work? x axis:Likelihood % y axis:Potential Impact % z axis:Color (yellow to green) Technical Analysis % Stock Forecast Rationales & Estimation Model Time series to forecast n: 31 Oct 2021 for (n+7) Given the earnings volatility companies experi

BOSTON (AC Invest Credit Rating Terminal) Sun Oct 31 2021 01:55:02 GMT+0000 (Coordinated Universal Time) AI Credit Ratings today took the rating actions below: Credit Rating Rationales & Model The EBITDA declines companies would have to withstand and still have defined sources cover defined uses are as follows for each liquidity descriptor: Adequate: Positive A-B, even if forecasted EBITDA declines by 30%.Weak: A/B or A-B reflecting a material deficit over the next 12 months. Rating Model for Original Engineering Consultants Co Ltd: We estimate the credit risk parameters by Ring Oscillators and Spearman Correlation Credit Ratings for Original Engineering Consultants Co Ltd as of 31 Oct 2021 Credit Rating Short-Term Long-Term Senior AI Rating Class* Caa2 B2 Semantic Signals 35 34 Financial Signals 67 35 Risk Signals 39 58 Substantial Risks 43 58 Speculative Signals 35 58 *Machine Learning utilizes multiple learning algorithms to obtain better predicti

The stock price realization for NYSE:V is a decision making process between multiple investors each of which controls a subset of design variables and seeks to minimize its cost function subject to future forecast constraints. That is, investors act like players in a game; they cooperate to achieve a set of overall goals. 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 with Ratiocator (RAT) and Chi-Square. Machine Learning based stock forecast (n+1y) for V Visa Inc. as below: V Visa Inc. Stock Forecast (Buy or Sell) as of 31 Oct 2021 for (n+1y) How Does Forecast Model Work? x axis:Likelihood % y axis:Potential Impact % z axis:Color (yellow to green) Technical Analysis % Stock Forecast Rationales & Estimation Model Time series to forecast n: 31 Oct 2021 for (n+1y) To assess forecasted working capital outflows for companies with mater

BOSTON (AC Invest Credit Rating Terminal) Sun Oct 31 2021 01:25:02 GMT+0000 (Coordinated Universal Time) AI Credit Ratings today took the rating actions below: Credit Rating Rationales & Model We do not exclude cash that the company needs to maintain to run the business and meet potential working capital requirements. Since working capital outflows are included under uses (B) of liquidity, system-related cash needed to run the business should be included in sources, along with items such as customer advances. Rating Model for Guangzheng Group Co Ltd: We estimate the credit risk parameters by Rating and Beta Credit Ratings for Guangzheng Group Co Ltd as of 31 Oct 2021 Credit Rating Short-Term Long-Term Senior AI Rating Class* Baa2 Baa2 Semantic Signals 73 80 Financial Signals 82 78 Risk Signals 67 68 Substantial Risks 76 81 Speculative Signals 66 65 *Machine Learning utilizes multiple learning algorithms to obtain better predictive powers. In our rese

The stock price realization for NYSE:BP is a decision making process between multiple investors each of which controls a subset of design variables and seeks to minimize its cost function subject to future forecast constraints. That is, investors act like players in a game; they cooperate to achieve a set of overall goals. 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 with Expectation and Wilcoxon Rank-Sum Test. Machine Learning based stock forecast (n+30) for BP BP p.l.c. as below: BP BP p.l.c. Stock Forecast (Buy or Sell) as of 31 Oct 2021 for (n+30) How Does Forecast Model Work? x axis:Likelihood % y axis:Potential Impact % z axis:Color (yellow to green) Technical Analysis % Stock Forecast Rationales & Estimation Model Time series to forecast n: 31 Oct 2021 for (n+30) For companies in more volatile sectors, we assess the resili

BOSTON (AC Invest Credit Rating Terminal) Sun Oct 31 2021 00:55:02 GMT+0000 (Coordinated Universal Time) AI Credit Ratings today took the rating actions below: Credit Rating Rationales & Model Under times of stress, such actions could include dividend cuts, suspension of share repurchases, or maintenance of minimum cash balances. This is particularly relevant for exceptional and strong assessments, where issuers are required to carry higher levels of excess liquidity even during times of stress. For example, when assessing liquidity, we would generally expect companies to be able to cover the full amount of dividends and share repurchases included in our base-case forecast, while still maintaining excess liquidity and achieving the required A/B and A-B measures under a stress case. Rating Model for Allied Capital Corporation Allied Capital Corporation 6.875% Notes due April 15, 2047: We estimate the credit risk parameters by Relative Strength Index (RSI) and Wilcoxon Sign-Rank

The stock price realization for NSE:PRAKASH is a decision making process between multiple investors each of which controls a subset of design variables and seeks to minimize its cost function subject to future forecast constraints. That is, investors act like players in a game; they cooperate to achieve a set of overall goals. 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 with Simple Moving Average (SMA) and ElasticNet Regression. Machine Learning based stock forecast (n+6m) for PRAKASH Prakash Industries Limited as below: PRAKASH Prakash Industries Limited Stock Forecast (Buy or Sell) as of 31 Oct 2021 for (n+6m) How Does Forecast Model Work? x axis:Likelihood % y axis:Potential Impact % z axis:Color (yellow to green) Technical Analysis % Stock Forecast Rationales & Estimation Model Time series to forecast n: 31 Oct 2021 for (n+6

BOSTON (AC Invest Credit Rating Terminal) Sun Oct 31 2021 00:25:02 GMT+0000 (Coordinated Universal Time) AI Credit Ratings today took the rating actions below: Credit Rating Rationales & Model When evaluating uses of liquidity, we include all debt maturities over the liquidity horizon that are either recourse to the company, or nonrecourse that we believe the company will support even in times of stress. In cases where the debt includes a put option held by debtholders, we will consider the date of the put option the effective debt maturity--i.e., we will assume the debt will need to be repaid/refinanced on the day the put can be first exercised. Rating Model for WUESTENROT+WUERTT.AG O.N.: We estimate the credit risk parameters by Accumulation Distribution Line and Linear Regression Credit Ratings for WUESTENROT+WUERTT.AG O.N. as of 31 Oct 2021 Credit Rating Short-Term Long-Term Senior AI Rating Class* B2 B3 Semantic Signals 44 34 Financial Signals 36 69

The stock price realization for NSE:PKTEA is a decision making process between multiple investors each of which controls a subset of design variables and seeks to minimize its cost function subject to future forecast constraints. That is, investors act like players in a game; they cooperate to achieve a set of overall goals. 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 with Moving Average Convergence Divergence (MACD) and Stepwise Regression. Machine Learning based stock forecast (n+1y) for PKTEA The Peria Karamalai Tea & Produce Company Limited as below: PKTEA The Peria Karamalai Tea & Produce Company Limited Stock Forecast (Buy or Sell) as of 30 Oct 2021 for (n+1y) How Does Forecast Model Work? x axis:Likelihood % y axis:Potential Impact % z axis:Color (yellow to green) Technical Analysis % Stock Forecast Rationales & Est

BOSTON (AC Invest Credit Rating Terminal) Sat Oct 30 2021 23:55:02 GMT+0000 (Coordinated Universal Time) AI Credit Ratings today took the rating actions below: Credit Rating Rationales & Model Given that it can be difficult to identify outstanding CP at any point in time, when considering coverage, we may include our expectations for peak outstanding CP during the year as opposed to CP balances as of the last filing date, especially if we believe reported balances are not reflective of typical borrowing patterns. Rating Model for SECURITY STATE BANK: We estimate the credit risk parameters by Parabolic SAR (PSAR) and ANOVA Credit Ratings for SECURITY STATE BANK as of 30 Oct 2021 Credit Rating Short-Term Long-Term Senior AI Rating Class* Ba3 Ba2 Semantic Signals 67 76 Financial Signals 80 49 Risk Signals 86 54 Substantial Risks 37 86 Speculative Signals 65 69 *Machine Learning utilizes multiple learning algorithms to obtain better predictive powers. In

The stock price realization for NSE:SHYAMTEL is a decision making process between multiple investors each of which controls a subset of design variables and seeks to minimize its cost function subject to future forecast constraints. That is, investors act like players in a game; they cooperate to achieve a set of overall goals. 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 with Wien Bridge Oscillator and Wilcoxon Sign-Rank Test. Machine Learning based stock forecast (n+7) for SHYAMTEL Shyam Telecom Limited as below: SHYAMTEL Shyam Telecom Limited Stock Forecast (Buy or Sell) as of 30 Oct 2021 for (n+7) How Does Forecast Model Work? x axis:Likelihood % y axis:Potential Impact % z axis:Color (yellow to green) Technical Analysis % Stock Forecast Rationales & Estimation Model Time series to forecast n: 30 Oct 2021 for (n+7) Larger, in