The stock price realization for NYSE:FNB 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 EMR and Paired T-Test. Machine Learning based stock forecast (n+15) for FNB F.N.B. Corporation as below: FNB F.N.B. Corporation Stock Forecast (Buy or Sell) as of 18 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: 18 Oct 2021 for (n+15) Under times of stress, such actions could include divide

BOSTON (AC Invest Credit Rating Terminal) Mon Oct 18 2021 10:55:02 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 Barclays PLC: We estimate the credit risk parameters by Meissner Oscillators and Polynomial Regression Credit Ratings for Barclays PLC as of 18 Oct 2021 Credit Rating Short-Term Long-Term Senior AI Rating Class* Ba2 B2 Semantic Signals 63 72 Financial Signals 69 32 Risk Signals 89 59 Substantial Risks 40 43 Speculative Signals 80 60 *Machine Learning utilizes multiple learning algorithms to obtain better predictive powers. In our research, we utilize machine learning to combine the results from the N

The stock price realization for LON:SMS 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 Rank Correlation Index (RCI) and Ridge Regression. Machine Learning based stock forecast (n+30) for SMS SMART METERING SYSTEMS PLC as below: SMS SMART METERING SYSTEMS PLC Stock Forecast (Buy or Sell) as of 18 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: 18 Oct 2021 for (n+30) Given the ear

BOSTON (AC Invest Credit Rating Terminal) Mon Oct 18 2021 10:25:02 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 APCO Holdings, LLC: We estimate the credit risk parameters by Meissner Oscillators and Polynomial Regression Credit Ratings for APCO Holdings, LLC as of 18 Oct 2021 Credit Rating Short-Term Long-Term Senior AI Rating Class* B2 B1 Semantic Signals 47 51 Financial Signals 43 49 Risk Signals 63 86 Substantial Risks 43 47 Speculativ

The stock price realization for NASDAQ:EVOK 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 Pearson-Anson Oscillators and Paired T-Test. Machine Learning based stock forecast (n+6m) for EVOK Evoke Pharma as below: EVOK Evoke Pharma Stock Forecast (Buy or Sell) as of 18 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: 18 Oct 2021 for (n+6m) We do not include potential future debt i

BOSTON (AC Invest Credit Rating Terminal) Mon Oct 18 2021 09:55:03 GMT+0000 (Coordinated Universal Time) AI Credit Ratings today took the rating actions below: Credit Rating Rationales & Model If we believe a company would use cash trapped at a foreign subsidiary to meet debt maturities or other liquidity uses at that foreign subsidiary, we would include this cash as a source of liquidity up to the amount of the corresponding use. We generally haircut the cash to be included under sources when a material proportion of a group's cash is held in a different part of the structure than where the debt is located, and we believe the cash may not be fully fungible within the group. Rating Model for Shimizu Corporation: We estimate the credit risk parameters by Trend and Beta Credit Ratings for Shimizu Corporation as of 18 Oct 2021 Credit Rating Short-Term Long-Term Senior AI Rating Class* Ba3 Ba3 Semantic Signals 90 41 Financial Signals 52 61 Risk Signals 8

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 Penetration and Logistic Regression. Machine Learning based stock forecast (n+1y) for GWB Great Western Bancorp as below: GWB Great Western Bancorp Stock Forecast (Buy or Sell) as of 18 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: 18 Oct 2021 for (n+1y) For example, if a company incurred a

BOSTON (AC Invest Credit Rating Terminal) Mon Oct 18 2021 09:25:02 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 Shen Zhen Shengxunda Technology Co Ltd: We estimate the credit risk parameters by Stochastic Oscillator and Paired T-Test Credit Ratings for Shen Zhen Shengxunda Technology Co Ltd as of 18 Oct 2021 Credit Rating Short-Term Long-Term Senior AI Rating Class* Ba3 Ba3 Semantic Signals 86 32 Financial Signals 71 48 Risk Signals 79 73 Substantial Risks 45 69 Speculative Signals 51 90 *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 M

The stock price realization for NASDAQ:ALBO 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 Logistic Regression. Machine Learning based stock forecast (n+1y) for ALBO Albireo Pharma as below: ALBO Albireo Pharma Stock Forecast (Buy or Sell) as of 18 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: 18 Oct 2021 for (n+1y) In addition, a speculative-gr

BOSTON (AC Invest Credit Rating Terminal) Mon Oct 18 2021 08:55:02 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 Hainan Airlines Holding Co Ltd: We estimate the credit risk parameters by Penetration and Polynomial Regression Credit Ratings for Hainan Airlines Holding Co Ltd as of 18 Oct 2021 Credit Rating Short-Term Long-Term Senior AI Rating Class* B2 Baa2 Semantic Signals 38 66 Financial Signals 33 90 Risk Signals 49 77 Substantial Risks 88 82 Speculative Signals 64 70 *Machine Learning utilizes multiple learning algorithms to obtain better predictive powers. In our research, we utilize machine learning to combi

The stock price realization for NSE:HEROMOTOCO 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 Beta. Machine Learning based stock forecast (n+6m) for HEROMOTOCO Hero MotoCorp Limited as below: HEROMOTOCO Hero MotoCorp Limited Stock Forecast (Buy or Sell) as of 18 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: 18 Oct 2021 for (n+6m

BOSTON (AC Invest Credit Rating Terminal) Mon Oct 18 2021 08:25:02 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 United Insurance Co. of America: We estimate the credit risk parameters by Robinson Oscillators and ElasticNet Regression Credit Ratings for United Insurance Co. of America as of 18 Oct 2021 Credit Rating Short-Term Long-Term Senior AI Rating Class* B3 B2 Semantic Signals 57 60 Financial Signals 40 32 Risk Signals 57 51 Substantial Risks 40 63 Speculative Signals 61 57 *Machine Learning utilizes multi

The stock price realization for NASDAQ:JJSF 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 Robinson Oscillators and Chi-Square. Machine Learning based stock forecast (n+15) for JJSF J & J Snack Foods Corp. as below: JJSF J & J Snack Foods Corp. Stock Forecast (Buy or Sell) as of 18 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: 18 Oct 2021 for (n+15) When evaluating use

BOSTON (AC Invest Credit Rating Terminal) Mon Oct 18 2021 07:55:02 GMT+0000 (Coordinated Universal Time) AI Credit Ratings today took the rating actions below: Credit Rating Rationales & Model For these reasons, although the criteria establish no rating threshold for liquidity, we typically expect: Instances of 'B+' and below rated issuers achieving liquidity descriptors higher than adequate to be rare and Few companies to qualify for the exceptional category, and these entities to typically have issuer credit ratings of 'BBB-' or above. Rating Model for Medical Net Inc: We estimate the credit risk parameters by RRS and Spearman Correlation Credit Ratings for Medical Net Inc as of 18 Oct 2021 Credit Rating Short-Term Long-Term Senior AI Rating Class* Caa2 B2 Semantic Signals 69 44 Financial Signals 49 86 Risk Signals 39 30 Substantial Risks 39 37 Speculative Signals 30 46 *Machine Learning utilizes multiple learning algorithms to ob

The stock price realization for NASDAQ:PPH 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 Williams %R and Beta. Machine Learning based stock forecast (n+1y) for PPH VanEck Vectors Pharmaceutical ETF as below: PPH VanEck Vectors Pharmaceutical ETF Stock Forecast (Buy or Sell) as of 18 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: 18 Oct 2021 for (n+1y) Our liquidity uses includ

BOSTON (AC Invest Credit Rating Terminal) Mon Oct 18 2021 07:25:03 GMT+0000 (Coordinated Universal Time) AI Credit Ratings today took the rating actions below: Credit Rating Rationales & Model If a company has a credit put that causes debt acceleration or collateral posting due to a downgrade of three notches or less, we would include these requirements under uses of liquidity, per paragraph 30 of the liquidity criteria. For example, if a 'BBB' rated company had a credit put that was triggered with a downgrade to speculative grade, we would include the corresponding cash requirement under uses of liquidity. This is because the criteria evaluate a company's liquidity position during times of stress, when potential downgrades are more likely. Rating Model for FIRST NATIONAL BANK IN TIGERTON: We estimate the credit risk parameters by Cross-Coupled Oscillators and Sign Test Credit Ratings for FIRST NATIONAL BANK IN TIGERTON as of 18 Oct 2021 Credit Rating

The stock price realization for NSE:KALYANIFRG 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 Pierce Oscillators and Beta. Machine Learning based stock forecast (n+15) for KALYANIFRG Kalyani Forge Limited as below: KALYANIFRG Kalyani Forge Limited Stock Forecast (Buy or Sell) as of 18 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: 18 Oct 2021 for (n+15) For these reasons, altho

BOSTON (AC Invest Credit Rating Terminal) Mon Oct 18 2021 06:55:26 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 interspace co., ltd: We estimate the credit risk parameters by Tri-tet Oscillators and Beta Credit Ratings for interspace co., ltd as of 18 Oct 2021 Credit Rating Short-Term Long-Term Senior AI Rating Class* Ba3 Ba3 Semantic Signals 70 73 Financial Signals 84 45 Risk Signals 46 57 Substantial Risks 64 56 Speculative Signals 71 80 *Machine Learning utilizes multiple learning algorithms to obtain better predictive powers. In o

The stock price realization for NSE:SEAMECLTD 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 Oscillator (PPO) and Ridge Regression. Machine Learning based stock forecast (n+6m) for SEAMECLTD Seamec Limited as below: SEAMECLTD Seamec Limited Stock Forecast (Buy or Sell) as of 18 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: 18 Oct 2021 for (n+6m) Our liquidity uses includ

BOSTON (AC Invest Credit Rating Terminal) Mon Oct 18 2021 06:25:18 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 Eversource Energy: We estimate the credit risk parameters by Envelope (ENV) and ElasticNet Regression Credit Ratings for Eversource Energy as of 18 Oct 2021

The stock price realization for NASDAQ:VGSH 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 Rating and Independent T-Test. Machine Learning based stock forecast (n+15) for VGSH Vanguard Short as below: VGSH Vanguard Short Stock Forecast (Buy or Sell) as of 18 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: 18 Oct 2021 for (n+15) Our view of a company's financial policy is an

BOSTON (AC Invest Credit Rating Terminal) Mon Oct 18 2021 05:55:02 GMT+0000 (Coordinated Universal Time) AI Credit Ratings today took the rating actions below: Credit Rating Rationales & Model Our view of a company's financial policy is an important input when assessing its current and future liquidity position. For instance, we assess whether a company has historically had a higher risk appetite and an aggressive acquisition strategy that has strained its liquidity position, or whether it has taken actions to preserve liquidity in past downturns. Rating Model for FIRST LACON CORP.: We estimate the credit risk parameters by Dynatron Oscillators and Stepwise Regression Credit Ratings for FIRST LACON CORP. as of 18 Oct 2021 Credit Rating Short-Term Long-Term Senior AI Rating Class* B1 B1 Semantic Signals 70 76 Financial Signals 64 53 Risk Signals 84 36 Substantial Risks 41 59 Speculative Signals 54 61 *Machine Learning utilizes multiple learning al

The stock price realization for NASDAQ:TNAV 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 Independent T-Test. Machine Learning based stock forecast (n+15) for TNAV Telenav as below: TNAV Telenav Stock Forecast (Buy or Sell) as of 18 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: 18 Oct 2021 for (n+15) Our view of a company's financial policy is an important input

BOSTON (AC Invest Credit Rating Terminal) Mon Oct 18 2021 05:25:02 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 Arcosa Inc: We estimate the credit risk parameters by Crystal Oscillators and Linear Regression Credit Ratings for Arcosa Inc as of 18 Oct 2021 Credit Rating Short-Term Long-Term Senior AI Rating Class* Ba3 Ba2 Semantic Signals 87 71 Financial Signals 70 80 Risk Signals 82 35 Substantial Risks 42 88 Speculative Signals 45 68 *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 Ne

The stock price realization for NSE:GODREJPROP 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 Opto-Electronic Oscillators and Stepwise Regression. Machine Learning based stock forecast (n+3m) for GODREJPROP Godrej Properties Limited as below: GODREJPROP Godrej Properties Limited Stock Forecast (Buy or Sell) as of 18 Oct 2021 for (n+3m) 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: 18 Oct 2021 for

BOSTON (AC Invest Credit Rating Terminal) Mon Oct 18 2021 04:55:02 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 CB Pharma Acquisition Corp.: We estimate the credit risk parameters by Envelope (ENV) and Spearman Correlation Credit Ratings for CB Pharma Acquisition Corp. as of 18 Oct 2021 Credit Rating Short-Term Long-Term Senior AI Rating Class* B3 B3 Semantic Signals 46 36 Financial Signals 33 37 Risk Signals 59 43 Sub

The stock price realization for NASDAQ:CSTL 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 FS and Spearman Correlation. Machine Learning based stock forecast (n+7) for CSTL Castle Biosciences as below: CSTL Castle Biosciences Stock Forecast (Buy or Sell) as of 18 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: 18 Oct 2021 for (n+7) Other factors we consider include a company'

BOSTON (AC Invest Credit Rating Terminal) Mon Oct 18 2021 04:25:47 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 Atlantic Capital Bancshares Inc: We estimate the credit risk parameters by Stochastic Oscillator and Ridge Regression Credit Ratings for Atlantic Capital Bancshares Inc as of 18 Oct 2021 Credit Rating Short-Term Long-Term Senior AI Rating Class* B3 B1 Semantic Signals 62 68 Financial Signals 50 36 Risk Signals 32 36 Substantial R

The stock price realization for LON:TLY 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 Linear Regression. Machine Learning based stock forecast (n+6m) for TLY TOTALLY PLC as below: TLY TOTALLY PLC Stock Forecast (Buy or Sell) as of 18 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: 18 Oct 2021 for (n+6m) Asset divestitures. We do not include as

BOSTON (AC Invest Credit Rating Terminal) Mon Oct 18 2021 03:55:02 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 Marquis Bancorp, Inc.: We estimate the credit risk parameters by RC Phase Shift Oscillator and Paired T-Test Credit Ratings for Marquis Bancorp, Inc. as of 18 Oct 2021 Credit Rating Short-Term Long-Term Senior AI Rating Class* B2 B1 Semantic Signals 34 53 Financial Signals 33 40 Risk Signals 67 81 Substantial Risks 85 50 Speculative Signals 52 79 *Machine Learning utilizes multiple learning algorithms to obtain better predictive powers. In our research, we utilize machine learning to combine the results

The stock price realization for NASDAQ:RCKT 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 Ring Oscillators and Factor. Machine Learning based stock forecast (n+15) for RCKT Rocket Pharmaceuticals as below: RCKT Rocket Pharmaceuticals Stock Forecast (Buy or Sell) as of 18 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: 18 Oct 2021 for (n+15) Our view of a company's financial

BOSTON (AC Invest Credit Rating Terminal) Mon Oct 18 2021 03:25:02 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 FIRST COMMUNITY BANK AND TRUST: We estimate the credit risk parameters by Exponential Moving Average (EMA) and Spearman Correlation Credit Ratings for FIRST COMMUNITY BANK AND TRUST as of 18 Oct 2021 Credit Rating Short-Term Long-Term Senior AI Rating Class* B2 B1 Semantic Signals 44 36 Financial Signals 81 77 Risk Signals 44 72 Substantial Risks 47 70 Speculative Signals

The stock price realization for NASDAQ:ROBT 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 Stochastic Oscillator and Linear Regression. Machine Learning based stock forecast (n+3m) for ROBT First Trust Nasdaq Artificial Intelligence and Robotics ETF as below: ROBT First Trust Nasdaq Artificial Intelligence and Robotics ETF Stock Forecast (Buy or Sell) as of 18 Oct 2021 for (n+3m) 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

BOSTON (AC Invest Credit Rating Terminal) Mon Oct 18 2021 02:55:02 GMT+0000 (Coordinated Universal Time) AI Credit Ratings today took the rating actions below: Credit Rating Rationales & Model 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. Rating Model for FIRST STATE BANK OF SAN DIEGO: We estimate the credit risk parameters by Price Oscillator (PPO) and Wilcoxon Rank-Sum Test Credit Ratings for FIRST STATE BANK OF SAN DIEGO as of 18 Oct 2021

The stock price realization for LON:MTL 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 Simple Regression. Machine Learning based stock forecast (n+30) for MTL METALS EXPLORATION PLC as below: MTL METALS EXPLORATION PLC Stock Forecast (Buy or Sell) as of 18 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: 18 Oct 2021 for (n+30) Other factors we con

BOSTON (AC Invest Credit Rating Terminal) Mon Oct 18 2021 02:25:03 GMT+0000 (Coordinated Universal Time) AI Credit Ratings today took the rating actions below: Credit Rating Rationales & Model For these reasons, although the criteria establish no rating threshold for liquidity, we typically expect: Instances of 'B+' and below rated issuers achieving liquidity descriptors higher than adequate to be rare and Few companies to qualify for the exceptional category, and these entities to typically have issuer credit ratings of 'BBB-' or above. Rating Model for SLM Corp: We estimate the credit risk parameters by KDJ and Sign Test Credit Ratings for SLM Corp as of 18 Oct 2021 Credit Rating Short-Term Long-Term Senior AI Rating Class* Ba3 Ba2 Semantic Signals 71 63 Financial Signals 49 81 Risk Signals 68 76 Substantial Risks 57 78 Speculative Signals 83 42 *Machine Learning utilizes multiple learning algorithms to obtain better predictive po

The stock price realization for NYSE:UHT 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 Oscillator (PPO) and Chi-Square. Machine Learning based stock forecast (n+3m) for UHT Universal Health Realty Income Trust as below: UHT Universal Health Realty Income Trust Stock Forecast (Buy or Sell) as of 18 Oct 2021 for (n+3m) 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: 18 Oct 2021 for (n+3m) Addi

BOSTON (AC Invest Credit Rating Terminal) Mon Oct 18 2021 01:55:03 GMT+0000 (Coordinated Universal Time) AI Credit Ratings today took the rating actions below: Credit Rating Rationales & Model The various qualitative factors in the criteria help to identify strengths and weaknesses within a company's future liquidity position that numerical ratios might not fully capture. While there is no size bias in our liquidity assessment, generally, lower-rated entities might meet the quantitative requirements for strong or exceptional liquidity but fail to meet corresponding qualitative factors. Rating Model for Puyi Inc: We estimate the credit risk parameters by Directional Movement Indicator and Wilcoxon Rank-Sum Test Credit Ratings for Puyi Inc as of 18 Oct 2021 Credit Rating Short-Term Long-Term Senior AI Rating Class* Caa2 B1 Semantic Signals 40 62 Financial Signals 47 36 Risk Signals 59 82 Substantial Risks 31 80 Speculative Signals 50 42 *Machine Le

The stock price realization for NYSE:JMP 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+1y) for JMP JMP Group LLC as below: JMP JMP Group LLC Stock Forecast (Buy or Sell) as of 18 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: 18 Oct 2021 for (n+1y) When calculating sources of liquidity, we only in

BOSTON (AC Invest Credit Rating Terminal) Mon Oct 18 2021 01:25:03 GMT+0000 (Coordinated Universal Time) AI Credit Ratings today took the rating actions below: Credit Rating Rationales & Model Given that we exclude proposed "best efforts" or potential financings as a source of liquidity, we also exclude from uses of liquidity acquisitions and other discretionary spending that are contingent on the successful issuance of new financing to support the proposed transaction. Rating Model for BANK OF FRANKLIN: We estimate the credit risk parameters by On Balance Volume (OBV) and Simple Regression Credit Ratings for BANK OF FRANKLIN as of 18 Oct 2021 Credit Rating Short-Term Long-Term Senior AI Rating Class* Caa2 Ba3 Semantic Signals 35 34 Financial Signals 35 89 Risk Signals 44 42 Substantial Risks 57 77 Speculative Signals 45 84 *Machine Learning utilizes multiple learning algorithms to obtain better predictive powers. In our research, we utiliz

The stock price realization for NASDAQ:PFM 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 Colpitts Oscillator and Linear Regression. Machine Learning based stock forecast (n+15) for PFM Invesco Dividend Achievers ETF as below: PFM Invesco Dividend Achievers ETF Stock Forecast (Buy or Sell) as of 18 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: 18 Oct 2021 for (n+15) When calcu

BOSTON (AC Invest Credit Rating Terminal) Mon Oct 18 2021 00:55:02 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 Mustang Bio Inc: We estimate the credit risk parameters by Average True Range (ATR) and Chi-Square Credit Ratings for Mustang Bio Inc as of 18 Oct 2021 Credit Rating Short-Term Long-Term Senior AI Rating Class* B2 B2 Semantic Signals 73 31 Financial Signals 37 45 Risk Signals 68 35 Substantial Risks 51 68 Speculative Signals 31 76 *Machine Learning utilizes multiple learning algorithms to obtain better predictive powers. In our

The stock price realization for NASDAQ:APTO 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 Royer Oscillators and Simple Regression. Machine Learning based stock forecast (n+7) for APTO Aptose Biosciences as below: APTO Aptose Biosciences Stock Forecast (Buy or Sell) as of 18 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: 18 Oct 2021 for (n+7) Our liquidity uses include dividends

BOSTON (AC Invest Credit Rating Terminal) Mon Oct 18 2021 00:25:02 GMT+0000 (Coordinated Universal Time) AI Credit Ratings today took the rating actions below: Credit Rating Rationales & Model While we only include contractual acquisitions when calculating A/B and A-B, when evaluating qualitative factors, we focus more on a company's track record and our expectation for financial management. In this respect, the quantitative and qualitative factors under the liquidity criteria are meant to complement each other and produce a more comprehensive view of a company's future liquidity position. Rating Model for ES Bancshares Inc: We estimate the credit risk parameters by Bollinger Bands Width and Pearson Correlation Credit Ratings for ES Bancshares Inc as of 18 Oct 2021 Credit Rating Short-Term Long-Term Senior AI Rating Class* B1 Ba3 Semantic Signals 65 70 Financial Signals 64 67 Risk Signals 37 72 Substantial Risks 79 32 Speculative Signals 67 73

The stock price realization for NSE:MANUGRAPH 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 Penetration and Spearman Correlation. Machine Learning based stock forecast (n+1y) for MANUGRAPH Manugraph India Limited as below: MANUGRAPH Manugraph India Limited Stock Forecast (Buy or Sell) as of 17 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: 17 Oct 2021 for (n+1y) We do not excl

BOSTON (AC Invest Credit Rating Terminal) Sun Oct 17 2021 23:55:02 GMT+0000 (Coordinated Universal Time) AI Credit Ratings today took the rating actions below: Credit Rating Rationales & Model 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. Rating Model for OSSIAN STATE BANK: We estimate the credit risk parameters by Wien Bridge Oscillator and Chi-Square Credit Ratings for OSSIAN STATE BANK as of 17 Oct 2021 Credit Rating Short-Term

The stock price realization for NYSE:EXP 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 Tri-tet Oscillators and Sign Test. Machine Learning based stock forecast (n+3m) for EXP Eagle Materials Inc as below: EXP Eagle Materials Inc Stock Forecast (Buy or Sell) as of 17 Oct 2021 for (n+3m) 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: 17 Oct 2021 for (n+3m) Likewise, we do not consider factoring pro

BOSTON (AC Invest Credit Rating Terminal) Sun Oct 17 2021 23:25:02 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 DSA Financial Corporation: We estimate the credit risk parameters by Cross-Coupled Oscillators and Polynomial Regression Credit Ratings for DSA Financial Corporation as of 17 Oct