While the existence of a commercial paper (CP) program can provide companies with alternative sources of short-term funding, such a program would not be considered a committed source of liquidity. Additionally, we do not require the presence of a committed facility to back up the full size of the CP program. For liquidity to be at least adequate, an issuer would need sources of liquidity (for example, committed facility and/or cash balances) to cover at least 100% of expected intra-year debt maturities, including CP, over the next 12 months. We estimate SASR Sandy Spring Bancorp stock forecast parameters by: Bollinger Bands %B with Polynomial Regression SASR Sandy Spring Bancorp Stock Forecast (Buy or Sell) as of 01 May 2022 for (n+30) 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 Bollinger Bands %B and Polynomial Regression. Machine Learning

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. We estimate BAFNAPH Bafna Pharmaceuticals Limited stock forecast parameters by: FS with Paired T-Test BAFNAPH Bafna Pharmaceuticals Limited Stock Forecast (Buy or Sell) as of 01 May 2022 for (n+15) 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 Paired T-Test. Machine Learning based stock forecast (n+15) for BAFNAPH Bafna Pharmaceuticals Limited as below: Time series to forecast n: 01 May 2022 for (n+15) How Does Forecast Model Work? x axis:Likelihood % y axis:Potential Impact % z axis:C

Additionally, we exclude revolver borrowing availability that we believe would be inaccessible due to covenant constraints. For revolving credit facilities with extension options, we include the extension period(s) under sources of liquidity only if the option is at the discretion of the borrower. If lenders have the option to terminate commitments at each extension point, we only include the borrowing availability under the facility up to the first extension date. We estimate TRAF TRAFALGAR PROPERTY GROUP PLC stock forecast parameters by: Speculation with Independent T-Test TRAF TRAFALGAR PROPERTY GROUP PLC Stock Forecast (Buy or Sell) as of 01 May 2022 for (n+30) 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 Speculation and Independent T-Test. Machine Learning based stock forecast (n+30) for TRAF TRAFALGAR PROPERTY GROUP PLC as below: Time s

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. We estimate FSL Firstsource Solutions Limited stock forecast parameters by: Demand with Polynomial Regression FSL Firstsource Solutions Limited Stock Forecast (Buy or Sell) as of 01 May 2022 for (n+7) 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 Demand and Polynomial Regression. Machine Learning based stock forecast (n+7) for FSL Firstsource Solutions Limit

Likewise, we do not consider factoring programs under sources of liquidity. Unlike asset-based lending (ABL) facilities, factoring is more of a sales transaction and not a loan. In addition, these transactions tend to be very short term. For this reason, we would not consider them a committed source of future liquidity over a 12-month period. We estimate VIPS Vipshop Holdings Limited American Depositary Shares stock forecast parameters by: Robinson Oscillators with Factor VIPS Vipshop Holdings Limited American Depositary Shares Stock Forecast (Buy or Sell) as of 01 May 2022 for (n+30) 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 Factor. Machine Learning based stock forecast (n+30) for VIPS Vipshop Holdings Limited American Depositary Shares as below: Time series to forecast n: 01 May 2022 for (n+30) How Does Forecast

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. We estimate BF.B Brown Forman Inc Class B stock forecast parameters by: Chaikin Money Flow with Sign Test BF.B Brown Forman Inc Class B Stock Forecast (Buy or Sell) as of 01 May 2022 for (n+1y) 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 Money Flow and Sign Test. Machine Learning based stock forecast (n+1y) for BF.B Brown Forman Inc Class B as below: Time series to forecast n: 01 May 2022 for (n+1y) How Does Forecast Model Work? x axis:Likelihood % y axis:Potential Imp

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. We estimate INDOSTAR IndoStar Capital Finance Limited stock forecast parameters by: OCL with Ridge Regression INDOSTAR IndoStar Capital Finance Limited Stock Forecast (Buy or Sell) as of 01 May 2022 for (n+3m) 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 Ridge Regression. Machine Learning based stock

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. We estimate ARK ARKLE RESOURCES PLC stock forecast parameters by: SMoothed Moving Average (SMMA) with ElasticNet Regression ARK ARKLE RESOURCES PLC Stock Forecast (Buy or Sell) as of 01 May 2022 for (n+3m) 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 SMoothed Moving Average (SMMA) and ElasticNet Regression. Machine Learning based stock forecast (n+3m) for ARK ARKLE RESOURCES PLC as below: Time series to forecast n: 01 May 2022 for (n+3m) How Does Forecast Model Work? x axis:Like

While the existence of a commercial paper (CP) program can provide companies with alternative sources of short-term funding, such a program would not be considered a committed source of liquidity. Additionally, we do not require the presence of a committed facility to back up the full size of the CP program. For liquidity to be at least adequate, an issuer would need sources of liquidity (for example, committed facility and/or cash balances) to cover at least 100% of expected intra-year debt maturities, including CP, over the next 12 months. We estimate OPI Office Properties Income Trust stock forecast parameters by: Cross-Coupled Oscillators with Ridge Regression OPI Office Properties Income Trust Stock Forecast (Buy or Sell) as of 01 May 2022 for (n+3m) 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 Cross-Coupled Oscillators and Ridge Regress

Larger, investment-grade issuers that have access to both public and private debt markets have greater flexibility than companies that depend solely on private bank loans. In addition, we consider whether a company can borrow on an unsecured basis, has access to the commercial paper markets, and issues debt in multiple geographies. It is more costly to raise debt in the public bond markets and often requires a company to establish a track record among investors. These costs and information asymmetry issues sometimes make it impractical for smaller, speculative-grade issuers to raise small amounts of debt in public markets. We estimate ZYT ZYTRONIC PLC stock forecast parameters by: Parabolic SAR (PSAR) with Ridge Regression ZYT ZYTRONIC PLC Stock Forecast (Buy or Sell) as of 01 May 2022 for (n+15) 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 P

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. We estimate RAMKY Ramky Infrastructure Limited stock forecast parameters by: Delay-Line Oscillators with Wilcoxon Sign-Rank Test RAMKY Ramky Infrastructure Limited Stock Forecast (Buy or Sell) as of 01 May 2022 for (n+6m) 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 Delay-Line Oscillators and Wilcoxon Sign-Rank Test. Machine Learning based stock forecast (n

Larger, investment-grade issuers that have access to both public and private debt markets have greater flexibility than companies that depend solely on private bank loans. In addition, we consider whether a company can borrow on an unsecured basis, has access to the commercial paper markets, and issues debt in multiple geographies. It is more costly to raise debt in the public bond markets and often requires a company to establish a track record among investors. These costs and information asymmetry issues sometimes make it impractical for smaller, speculative-grade issuers to raise small amounts of debt in public markets. We estimate AJMERA Ajmera Realty & Infra India Limited stock forecast parameters by: Anomaly with ANOVA AJMERA Ajmera Realty & Infra India Limited Stock Forecast (Buy or Sell) as of 01 May 2022 for (n+7) Machine Learning utilizes multiple learning algorithms to obtain better predictive powers. In our research, we utilize machine learning to combine the res

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. We estimate CMX CATALYST MEDIA GROUP PLC stock forecast parameters by: Multi-Wave Oscillators with Lasso Regression CMX CATALYST MEDIA GROUP PLC Stock Forecast (Buy or Sell) as of 01 May 2022 for (n+6m) 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 Lasso Regression. Machine Learning based stock forecast (n+6m) for CMX CATALYST MEDIA GROUP PLC as below: Time series to forecast n: 01 May 2022 for (n+6m) How Does Forecast Model Work? x axi