ERF Enerplus Corporation Stock Forecast Period (n+7) 24 Feb 2021


Stock Forecast


As of Wed Feb 24 2021 00:00:02 GMT+0000 (Coordinated Universal Time) shares of ERF Enerplus Corporation 4.48 percentage change in price since the previous day's close. Around 3855797 of 256235000 changed hand on the market. The Stock opened at 4.87 with high and low of 4.66 and 5.17 respectively. The price/earnings ratio is: - and earning per share is -3.29. The stock quoted a 52 week high and low of 1.15 and 5.17 respectively.

BOSTON (AI Forecast Terminal) Wed, Feb 24, '21 AI Forecast today took the forecast actions: In the context of stock price realization of ERF Enerplus Corporation 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 and Support Vector Machines. Machine Learning based technical analysis (n+7) for ERF Enerplus Corporation as below:
Using machine learning modified The random walk index model RWI equivalent to a model of stock market dynamics with price expectations, we analyze the reaction of investors to speculations. Analyzing those data we were able to establish the amount by which each stock felt the speculative attacks, a dampening factor which expresses the capacity of a market of absorving a shock, and also a frequency related with volatility after the speculation. Using the correlation matrices, the speculative buffer for the shares of ERF Enerplus Corporation as below:

ERF Enerplus Corporation Credit Rating Overview


We rerate ERF Enerplus Corporation because of the firm's business is modestly more concentrated than average for peers, and the concentration represents modest incremental risk above what is captured in the anchor, but it is not a key credit weakness. We use econometric methods for period (n+7) simulate with Gunn Oscillator ANOVA. Reference code is: 4608. Beta DRL value REG 46 Rational Demand Factor LD 6088.3284. 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. Credit Rating AI Process rely on primary sources of information: Sec Filings, Financial Statements, Credit Ratings, Semantic Signals. Take a look at Machine Learning section for Financial Deep Reinforcement Learning.

Oscillators are used for generating credit risk signals by using the semantic and financial signals. The value of the oscillators indicate the strength of trend. Using the correlation matrices, the risk map for ERF Enerplus Corporation as below:
Frequently Asked QuestionsQ: What is ERF Enerplus Corporation stock symbol?
A: ERF Enerplus Corporation stock referred as NYSE:ERF
Q: What is ERF Enerplus Corporation stock price?
A: On share of ERF Enerplus Corporation stock can currently be purchased for approximately 5.13
Q: Do analysts recommend investors buy shares of ERF Enerplus Corporation ?
A: 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. View Machine Learning based technical analysis for ERF Enerplus Corporation at daily forecast section
Q: What is the earning per share of ERF Enerplus Corporation ?
A: The earning per share of ERF Enerplus Corporation is -3.29
Q: What is the market capitalization of ERF Enerplus Corporation ?
A: The market capitalization of ERF Enerplus Corporation is 1314485579
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Disclaimers: AC Investment Inc. currently does not act as an equities executing broker, credit rating agency or route orders containing equities securities. In our Machine Learning experiment, we focus on an approach known as Decision making using game theory. We apply principles from game theory to model the relationships between rating actions, news, market signals and decision making.The rating information provided is for informational, non-commercial purposes only, does not constitute investment advice and is subject to conditions available in our Legal Disclaimer. Usage as a credit rating or as a benchmark is not permitted.

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