Union Bank of India Stock Forecast Outlook:Negative Period (n+6m) 19 May 2020


Stock Forecast


As of Tue May 19 2020 11:38:47 GMT+0000 (Coordinated Universal Time) shares of Union Bank of India -2.12 percentage change in price since the previous day's close. Around 1970441 of 1168573440 changed hand on the market. The Stock opened at 23.65 with high and low of 22.9 and 23.85 respectively. The price/earnings ratio is: #N/A and earning per share is -31.44. The stock quoted a 52 week high and low of 22.9 and 86.6 respectively.

BOSTON (AI Forecast Terminal) Tue, May 19, '20 AI Forecast today took the forecast actions: In the context of stock price realization of Union Bank of India 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+6m) for Union Bank of India 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 Union Bank of India as below:

Union Bank of India Credit Rating Overview


We rerate Union Bank of India 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+6m) simulate with Exponential Moving Average (EMA) Independent T-Test. Reference code is: 4969. Beta DRL value REG 36 Rational Demand Factor LD 4068.7836. 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. 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 Union Bank of India as below:
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