ESBK Elmira Savings Bank NY (The) Stock Forecast Period (n+1y) 17 Feb 2021


Stock Forecast


As of Wed Feb 17 2021 00:00:02 GMT+0000 (Coordinated Universal Time) shares of ESBK Elmira Savings Bank NY (The) -0.64 percentage change in price since the previous day's close. Around 109 of 3483000 changed hand on the market. The Stock opened at 12.81 with high and low of 12.71 and 12.81 respectively. The price/earnings ratio is: 10.72 and earning per share is 1.19. The stock quoted a 52 week high and low of 10.3 and 16.48 respectively.

BOSTON (AI Forecast Terminal) Wed, Feb 17, '21 AI Forecast today took the forecast actions: In the context of stock price realization of ESBK Elmira Savings Bank NY (The) 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+1y) for ESBK Elmira Savings Bank NY (The) 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 ESBK Elmira Savings Bank NY (The) as below:

ESBK Elmira Savings Bank NY (The) Credit Rating Overview


We rerate ESBK Elmira Savings Bank NY (The) because of deduct interest-only strips. We use econometric methods for period (n+1y) simulate with Momentum ElasticNet Regression. Reference code is: 3909. Beta DRL value REG 26 Rational Demand Factor LD 6238.386. When determining the cash to be included under sources (A), we use cash that will be available to cover monetary outflows. As a result, we may make haircuts to account for cash trapped overseas (for example, haircut for taxes payable upon repatriation of cash held abroad), apply a discount to lower-quality marketable securities, and exclude restricted cash held for specific purposes. 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 ESBK Elmira Savings Bank NY (The) as below:
Frequently Asked QuestionsQ: What is ESBK Elmira Savings Bank NY (The) stock symbol?
A: ESBK Elmira Savings Bank NY (The) stock referred as NASDAQ:ESBK
Q: What is ESBK Elmira Savings Bank NY (The) stock price?
A: On share of ESBK Elmira Savings Bank NY (The) stock can currently be purchased for approximately 12.71
Q: Do analysts recommend investors buy shares of ESBK Elmira Savings Bank NY (The) ?
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 ESBK Elmira Savings Bank NY (The) at daily forecast section
Q: What is the earning per share of ESBK Elmira Savings Bank NY (The) ?
A: The earning per share of ESBK Elmira Savings Bank NY (The) is 1.19
Q: What is the market capitalization of ESBK Elmira Savings Bank NY (The) ?
A: The market capitalization of ESBK Elmira Savings Bank NY (The) is 44271497
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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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