Is EMS Stock Buy or Sell?

Outlook: EASTERN METALS LIMITED is assigned short-term Ba1 & long-term Ba1 estimated rating.
Dominant Strategy : Sell
Time series to forecast n: 18 Jun 2023 for 6 Month
Methodology : Modular Neural Network (Market News Sentiment Analysis)

Abstract

EASTERN METALS LIMITED prediction model is evaluated with Modular Neural Network (Market News Sentiment Analysis) and Pearson Correlation^1,2,3,4 and it is concluded that the EMS stock is predictable in the short/long term. A modular neural network (MNN) is a type of artificial neural network that can be used for news feed sentiment analysis. MNNs are made up of multiple smaller neural networks, called modules. Each module is responsible for learning a specific task, such as identifying sentiment in text or identifying patterns in data. The modules are then combined to form a single neural network that can perform multiple tasks. In the context of news feed sentiment analysis, MNNs can be used to identify the sentiment of news articles, social media posts, and other forms of online content. This information can then be used to filter out irrelevant or unwanted content, to identify trends in public opinion, and to target users with relevant advertising. According to price forecasts for 6 Month period, the dominant strategy among neural network is: Sell

Key Points

1. Trust metric by Neural Network
2. Operational Risk
3. What is the use of Markov decision process?

EMS Target Price Prediction Modeling Methodology

We consider EASTERN METALS LIMITED Decision Process with Modular Neural Network (Market News Sentiment Analysis) where A is the set of discrete actions of EMS stock holders, F is the set of discrete states, P : S × F × S → R is the transition probability distribution, R : S × F → R is the reaction function, and γ ∈ [0, 1] is a move factor for expectation.^1,2,3,4

F(Pearson Correlation)^5,6,7= $\begin{array}{cccc}{p}_{\mathrm{a}1}& p_{\mathrm{a}2}& \dots & p_{1n}\\ & ⋮\\ p_{j1}& p_{j2}& \dots & p_{jn}\\ & ⋮\\ p_{k1}& p_{k2}& \dots & p_{kn}\\ & ⋮\\ p_{n1}& p_{n2}& \dots & p_{nn}\end{array}$ X R(Modular Neural Network (Market News Sentiment Analysis)) X S(n):→ 6 Month $\overrightarrow{S}=\left(s_1,s_2,s_3\right)$

n:Time series to forecast

p:Price signals of EMS stock

j:Nash equilibria (Neural Network)

k:Dominated move

a:Best response for target price

Modular Neural Network (Market News Sentiment Analysis)

A modular neural network (MNN) is a type of artificial neural network that can be used for news feed sentiment analysis. MNNs are made up of multiple smaller neural networks, called modules. Each module is responsible for learning a specific task, such as identifying sentiment in text or identifying patterns in data. The modules are then combined to form a single neural network that can perform multiple tasks. In the context of news feed sentiment analysis, MNNs can be used to identify the sentiment of news articles, social media posts, and other forms of online content. This information can then be used to filter out irrelevant or unwanted content, to identify trends in public opinion, and to target users with relevant advertising.

Pearson Correlation

Pearson correlation, also known as Pearson's product-moment correlation, is a measure of the linear relationship between two variables. It is a statistical measure that assesses the strength and direction of a linear relationship between two variables. The sign of the correlation coefficient indicates the direction of the relationship, while the magnitude of the correlation coefficient indicates the strength of the relationship. A correlation coefficient of 0.9 indicates a strong positive correlation, while a correlation coefficient of 0.2 indicates a weak positive correlation.

 

For further technical information as per how our model work we invite you to visit the article below: 

How do AC Investment Research machine learning (predictive) algorithms actually work?

EMS Stock Forecast (Buy or Sell) for 6 Month

Sample Set: Neural Network
Stock/Index: EMS EASTERN METALS LIMITED
Time series to forecast n: 18 Jun 2023 for 6 Month

According to price forecasts for 6 Month period, the dominant strategy among neural network is: Sell

X axis: *Likelihood% (The higher the percentage value, the more likely the event will occur.)

Y axis: *Potential Impact% (The higher the percentage value, the more likely the price will deviate.)

Z axis (Grey to Black): *Technical Analysis%

IFRS Reconciliation Adjustments for EASTERN METALS LIMITED

1. Lifetime expected credit losses are not recognised on a financial instrument simply because it was considered to have low credit risk in the previous reporting period and is not considered to have low credit risk at the reporting date. In such a case, an entity shall determine whether there has been a significant increase in credit risk since initial recognition and thus whether lifetime expected credit losses are required to be recognised in accordance with paragraph 5.5.3.
2. An entity shall assess at the inception of the hedging relationship, and on an ongoing basis, whether a hedging relationship meets the hedge effectiveness requirements. At a minimum, an entity shall perform the ongoing assessment at each reporting date or upon a significant change in the circumstances affecting the hedge effectiveness requirements, whichever comes first. The assessment relates to expectations about hedge effectiveness and is therefore only forward-looking.
3. An entity shall assess at the inception of the hedging relationship, and on an ongoing basis, whether a hedging relationship meets the hedge effectiveness requirements. At a minimum, an entity shall perform the ongoing assessment at each reporting date or upon a significant change in the circumstances affecting the hedge effectiveness requirements, whichever comes first. The assessment relates to expectations about hedge effectiveness and is therefore only forward-looking.
4. In addition to those hedging relationships specified in paragraph 6.9.1, an entity shall apply the requirements in paragraphs 6.9.11 and 6.9.12 to new hedging relationships in which an alternative benchmark rate is designated as a non-contractually specified risk component (see paragraphs 6.3.7(a) and B6.3.8) when, because of interest rate benchmark reform, that risk component is not separately identifiable at the date it is designated.

*International Financial Reporting Standards (IFRS) adjustment process involves reviewing the company's financial statements and identifying any differences between the company's current accounting practices and the requirements of the IFRS. If there are any such differences, neural network makes adjustments to financial statements to bring them into compliance with the IFRS.

Conclusions

EASTERN METALS LIMITED is assigned short-term Ba1 & long-term Ba1 estimated rating. EASTERN METALS LIMITED prediction model is evaluated with Modular Neural Network (Market News Sentiment Analysis) and Pearson Correlation^1,2,3,4 and it is concluded that the EMS stock is predictable in the short/long term. According to price forecasts for 6 Month period, the dominant strategy among neural network is: Sell

EMS EASTERN METALS LIMITED Financial Analysis*

Rating	Short-Term	Long-Term Senior
Outlook*	Ba1	Ba1
Income Statement	B2	Baa2
Balance Sheet	Baa2	Baa2
Leverage Ratios	B2	Caa2
Cash Flow	C	C
Rates of Return and Profitability	Caa2	C

*Financial analysis is the process of evaluating a company's financial performance and position by neural network. It involves reviewing the company's financial statements, including the balance sheet, income statement, and cash flow statement, as well as other financial reports and documents.
How does neural network examine financial reports and understand financial state of the company?

Prediction Confidence Score

Trust metric by Neural Network: 87 out of 100 with 469 signals.

References

1. ZXhang, Y.X., Haxo, Y.M. and Mat, Y.X., 2023. Can Neural Networks Predict Stock Market? (No. Stock Analysis). AC Investment Research.
2. ZXhang, Y.X., Haxo, Y.M. and Mat, Y.X., 2023. The Dow Jones Industrial Average (No. Stock Analysis). AC Investment Research.
3. Abadir, K. M., K. Hadri E. Tzavalis (1999), "The influence of VAR dimensions on estimator biases," Econometrica, 67, 163–181.
4. M. L. Littman. Friend-or-foe q-learning in general-sum games. In Proceedings of the Eighteenth International Conference on Machine Learning (ICML 2001), Williams College, Williamstown, MA, USA, June 28 - July 1, 2001, pages 322–328, 2001
5. M. J. Hausknecht. Cooperation and Communication in Multiagent Deep Reinforcement Learning. PhD thesis, The University of Texas at Austin, 2016
6. Chow, G. C. (1960), "Tests of equality between sets of coefficients in two linear regressions," Econometrica, 28, 591–605.
7. D. Bertsekas. Nonlinear programming. Athena Scientific, 1999.

Frequently Asked Questions

Q: What is the prediction methodology for EMS stock?
A: EMS stock prediction methodology: We evaluate the prediction models Modular Neural Network (Market News Sentiment Analysis) and Pearson Correlation
Q: Is EMS stock a buy or sell?
A: The dominant strategy among neural network is to Sell EMS Stock.
Q: Is EASTERN METALS LIMITED stock a good investment?
A: The consensus rating for EASTERN METALS LIMITED is Sell and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of EMS stock?
A: The consensus rating for EMS is Sell.
Q: What is the prediction period for EMS stock?
A: The prediction period for EMS is 6 Month

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