EMN:TSXV Euro Manganese Inc.

Outlook: Euro Manganese Inc. assigned short-term B1 & long-term B1 forecasted stock rating.
Dominant Strategy : Hold
Time series to forecast n: 13 Dec 2022 for (n+3 month)
Methodology : Active Learning (ML)

Abstract

Three networks are compared for low false alarm stock trend predictions. Short-term trends, particularly attractive for neural network analysis, can be used profitably in scenarios such as option trading, but only with significant risk. Therefore, we focus on limiting false alarms, which improves the risk/reward ratio by preventing losses. To predict stock trends, we exploit time delay, recurrent, and probabilistic neural networks (TDNN, RNN, and PNN, respectively), utilizing conjugate gradient and multistream extended Kalman filter training for TDNN and RNN.(Sirimevan, N., Mamalgaha, I.G.U.H., Jayasekara, C., Mayuran, Y.S. and Jayawardena, C., 2019, December. Stock market prediction using machine learning techniques. In 2019 International Conference on Advancements in Computing (ICAC) (pp. 192-197). IEEE.) We evaluate Euro Manganese Inc. prediction models with Active Learning (ML) and Logistic Regression^1,2,3,4 and conclude that the EMN:TSXV stock is predictable in the short/long term. According to price forecasts for (n+3 month) period, the dominant strategy among neural network is: Hold

Key Points

1. Market Outlook
2. Is now good time to invest?
3. Which neural network is best for prediction?

EMN:TSXV Target Price Prediction Modeling Methodology

We consider Euro Manganese Inc. Decision Process with Active Learning (ML) where A is the set of discrete actions of EMN:TSXV 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(Logistic Regression)^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(Active Learning (ML)) X S(n):→ (n+3 month) $\begin{array}{l}\int r^s\mathrm{rs}\end{array}$

n:Time series to forecast

p:Price signals of EMN:TSXV stock

j:Nash equilibria (Neural Network)

k:Dominated move

a:Best response for target price

 

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?

EMN:TSXV Stock Forecast (Buy or Sell) for (n+3 month)

Sample Set: Neural Network
Stock/Index: EMN:TSXV Euro Manganese Inc.
Time series to forecast n: 13 Dec 2022 for (n+3 month)

According to price forecasts for (n+3 month) period, the dominant strategy among neural network is: Hold

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%

Adjusted IFRS* Prediction Methods for Euro Manganese Inc.

1. As noted in paragraph B4.3.1, when an entity becomes a party to a hybrid contract with a host that is not an asset within the scope of this Standard and with one or more embedded derivatives, paragraph 4.3.3 requires the entity to identify any such embedded derivative, assess whether it is required to be separated from the host contract and, for those that are required to be separated, measure the derivatives at fair value at initial recognition and subsequently. These requirements can be more complex, or result in less reliable measures, than measuring the entire instrument at fair value through profit or loss. For that reason this Standard permits the entire hybrid contract to be designated as at fair value through profit or loss.
2. For the purposes of the transition provisions in paragraphs 7.2.1, 7.2.3–7.2.28 and 7.3.2, the date of initial application is the date when an entity first applies those requirements of this Standard and must be the beginning of a reporting period after the issue of this Standard. Depending on the entity's chosen approach to applying IFRS 9, the transition can involve one or more than one date of initial application for different requirements.
3. An embedded prepayment option in an interest-only or principal-only strip is closely related to the host contract provided the host contract (i) initially resulted from separating the right to receive contractual cash flows of a financial instrument that, in and of itself, did not contain an embedded derivative, and (ii) does not contain any terms not present in the original host debt contract.
4. If a component of the cash flows of a financial or a non-financial item is designated as the hedged item, that component must be less than or equal to the total cash flows of the entire item. However, all of the cash flows of the entire item may be designated as the hedged item and hedged for only one particular risk (for example, only for those changes that are attributable to changes in LIBOR or a benchmark commodity price).

*International Financial Reporting Standards (IFRS) are a set of accounting rules for the financial statements of public companies that are intended to make them consistent, transparent, and easily comparable around the world.

Conclusions

Euro Manganese Inc. assigned short-term B1 & long-term B1 forecasted stock rating. We evaluate the prediction models Active Learning (ML) with Logistic Regression^1,2,3,4 and conclude that the EMN:TSXV stock is predictable in the short/long term. According to price forecasts for (n+3 month) period, the dominant strategy among neural network is: Hold

Financial State Forecast for EMN:TSXV Euro Manganese Inc. Options & Futures

Rating	Short-Term	Long-Term Senior
Outlook*	B1	B1
Operational Risk	74	34
Market Risk	74	54
Technical Analysis	47	79
Fundamental Analysis	52	32
Risk Unsystematic	56	85

Prediction Confidence Score

Trust metric by Neural Network: 83 out of 100 with 751 signals.

References

1. Imai K, Ratkovic M. 2013. Estimating treatment effect heterogeneity in randomized program evaluation. Ann. Appl. Stat. 7:443–70
2. Bottou L. 2012. Stochastic gradient descent tricks. In Neural Networks: Tricks of the Trade, ed. G Montavon, G Orr, K-R Müller, pp. 421–36. Berlin: Springer
3. V. Borkar. A sensitivity formula for the risk-sensitive cost and the actor-critic algorithm. Systems & Control Letters, 44:339–346, 2001
4. Greene WH. 2000. Econometric Analysis. Upper Saddle River, N J: Prentice Hall. 4th ed.
5. M. Benaim, J. Hofbauer, and S. Sorin. Stochastic approximations and differential inclusions, Part II: Appli- cations. Mathematics of Operations Research, 31(4):673–695, 2006
6. Harris ZS. 1954. Distributional structure. Word 10:146–62
7. V. Borkar. Q-learning for risk-sensitive control. Mathematics of Operations Research, 27:294–311, 2002.

Frequently Asked Questions

Q: What is the prediction methodology for EMN:TSXV stock?
A: EMN:TSXV stock prediction methodology: We evaluate the prediction models Active Learning (ML) and Logistic Regression
Q: Is EMN:TSXV stock a buy or sell?
A: The dominant strategy among neural network is to Hold EMN:TSXV Stock.
Q: Is Euro Manganese Inc. stock a good investment?
A: The consensus rating for Euro Manganese Inc. is Hold and assigned short-term B1 & long-term B1 forecasted stock rating.
Q: What is the consensus rating of EMN:TSXV stock?
A: The consensus rating for EMN:TSXV is Hold.
Q: What is the prediction period for EMN:TSXV stock?
A: The prediction period for EMN:TSXV is (n+3 month)

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