LEV:TSX Stock Forecast: A Hold For The Next 6 Month

Outlook: Lion Electric Company (The) is assigned short-term B2 & long-term Baa2 estimated rating.
Dominant Strategy : Hold
Time series to forecast n: 22 Jun 2023 for 6 Month
Methodology : Modular Neural Network (Market Direction Analysis)

Abstract

Lion Electric Company (The) prediction model is evaluated with Modular Neural Network (Market Direction Analysis) and Stepwise Regression^1,2,3,4 and it is concluded that the LEV:TSX stock is predictable in the short/long term. Modular neural networks (MNNs) are a type of artificial neural network that can be used for market direction analysis. MNNs are made up of multiple smaller neural networks, called modules. Each module is responsible for learning a specific task, such as identifying patterns in data or predicting future price movements. The modules are then combined to form a single neural network that can perform multiple tasks.In the context of market direction analysis, MNNs can be used to identify patterns in market data that suggest that the market is likely to move in a particular direction. This information can then be used to make predictions about future price movements. According to price forecasts for 6 Month period, the dominant strategy among neural network is: Hold

Key Points

1. What is prediction in deep learning?
2. How do you decide buy or sell a stock?
3. What is a prediction confidence?

LEV:TSX Target Price Prediction Modeling Methodology

We consider Lion Electric Company (The) Decision Process with Modular Neural Network (Market Direction Analysis) where A is the set of discrete actions of LEV:TSX 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(Stepwise 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(Modular Neural Network (Market Direction Analysis)) X S(n):→ 6 Month $R=\left(\begin{array}{ccc}1& 0& 0\\ 0& 1& 0\\ 0& 0& 1\end{array}\right)$

n:Time series to forecast

p:Price signals of LEV:TSX stock

j:Nash equilibria (Neural Network)

k:Dominated move

a:Best response for target price

Modular Neural Network (Market Direction Analysis)

Modular neural networks (MNNs) are a type of artificial neural network that can be used for market direction analysis. MNNs are made up of multiple smaller neural networks, called modules. Each module is responsible for learning a specific task, such as identifying patterns in data or predicting future price movements. The modules are then combined to form a single neural network that can perform multiple tasks.In the context of market direction analysis, MNNs can be used to identify patterns in market data that suggest that the market is likely to move in a particular direction. This information can then be used to make predictions about future price movements.

Stepwise Regression

Stepwise regression is a method of variable selection in which variables are added or removed from a model one at a time, based on their statistical significance. There are two main types of stepwise regression: forward selection and backward elimination. In forward selection, variables are added to the model one at a time, starting with the variable with the highest F-statistic. The F-statistic is a measure of how much improvement in the model is gained by adding the variable. Variables are added to the model until no variable adds a statistically significant improvement to the model.

 

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?

LEV:TSX Stock Forecast (Buy or Sell) for 6 Month

Sample Set: Neural Network
Stock/Index: LEV:TSX Lion Electric Company (The)
Time series to forecast n: 22 Jun 2023 for 6 Month

According to price forecasts for 6 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%

IFRS Reconciliation Adjustments for Lion Electric Company (The)

1. For the purpose of this Standard, reasonable and supportable information is that which is reasonably available at the reporting date without undue cost or effort, including information about past events, current conditions and forecasts of future economic conditions. Information that is available for financial reporting purposes is considered to be available without undue cost or effort.
2. If an entity prepares interim financial reports in accordance with IAS 34 Interim Financial Reporting the entity need not apply the requirements in this Standard to interim periods prior to the date of initial application if it is impracticable (as defined in IAS 8).
3. An entity shall amend a hedging relationship as required in paragraph 6.9.1 by the end of the reporting period during which a change required by interest rate benchmark reform is made to the hedged risk, hedged item or hedging instrument. For the avoidance of doubt, such an amendment to the formal designation of a hedging relationship constitutes neither the discontinuation of the hedging relationship nor the designation of a new hedging relationship.
4. If subsequently an entity reasonably expects that the alternative benchmark rate will not be separately identifiable within 24 months from the date the entity designated it as a non-contractually specified risk component for the first time, the entity shall cease applying the requirement in paragraph 6.9.11 to that alternative benchmark rate and discontinue hedge accounting prospectively from the date of that reassessment for all hedging relationships in which the alternative benchmark rate was designated as a noncontractually specified risk component.

*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

Lion Electric Company (The) is assigned short-term B2 & long-term Baa2 estimated rating. Lion Electric Company (The) prediction model is evaluated with Modular Neural Network (Market Direction Analysis) and Stepwise Regression^1,2,3,4 and it is concluded that the LEV:TSX stock is predictable in the short/long term. According to price forecasts for 6 Month period, the dominant strategy among neural network is: Hold

LEV:TSX Lion Electric Company (The) Financial Analysis*

Rating	Short-Term	Long-Term Senior
Outlook*	B2	Baa2
Income Statement	Caa2	Baa2
Balance Sheet	B3	Baa2
Leverage Ratios	B2	Baa2
Cash Flow	B3	Baa2
Rates of Return and Profitability	Ba1	Baa2

*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: 73 out of 100 with 638 signals.

References

1. Jacobs B, Donkers B, Fok D. 2014. Product Recommendations Based on Latent Purchase Motivations. Rotterdam, Neth.: ERIM
2. Belsley, D. A. (1988), "Modelling and forecast reliability," International Journal of Forecasting, 4, 427–447.
3. V. Borkar. An actor-critic algorithm for constrained Markov decision processes. Systems & Control Letters, 54(3):207–213, 2005.
4. Lai TL, Robbins H. 1985. Asymptotically efficient adaptive allocation rules. Adv. Appl. Math. 6:4–22
5. T. Morimura, M. Sugiyama, M. Kashima, H. Hachiya, and T. Tanaka. Nonparametric return distribution ap- proximation for reinforcement learning. In Proceedings of the 27th International Conference on Machine Learning, pages 799–806, 2010
6. Athey S, Imbens G, Wager S. 2016a. Efficient inference of average treatment effects in high dimensions via approximate residual balancing. arXiv:1604.07125 [math.ST]
7. T. Morimura, M. Sugiyama, M. Kashima, H. Hachiya, and T. Tanaka. Nonparametric return distribution ap- proximation for reinforcement learning. In Proceedings of the 27th International Conference on Machine Learning, pages 799–806, 2010

Frequently Asked Questions

Q: What is the prediction methodology for LEV:TSX stock?
A: LEV:TSX stock prediction methodology: We evaluate the prediction models Modular Neural Network (Market Direction Analysis) and Stepwise Regression
Q: Is LEV:TSX stock a buy or sell?
A: The dominant strategy among neural network is to Hold LEV:TSX Stock.
Q: Is Lion Electric Company (The) stock a good investment?
A: The consensus rating for Lion Electric Company (The) is Hold and is assigned short-term B2 & long-term Baa2 estimated rating.
Q: What is the consensus rating of LEV:TSX stock?
A: The consensus rating for LEV:TSX is Hold.
Q: What is the prediction period for LEV:TSX stock?
A: The prediction period for LEV:TSX is 6 Month

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