Methanex Corporation Forecast & Analysis

Outlook: Methanex Corporation is assigned short-term Ba3 & long-term Ba3 estimated rating.
Dominant Strategy : Sell
Time series to forecast n: 23 Jun 2023 for 3 Month
Methodology : Transductive Learning (ML)

Summary

Methanex Corporation is a Canadian company that is the world's largest producer and supplier of methanol.
The company was founded in 1969 and is headquartered in Vancouver, British Columbia.
Methanex has operations in Canada, Chile, Egypt, New Zealand, Trinidad and Tobago, and the United States.
The company's methanol is used in a variety of applications, including as a fuel, a feedstock for other chemicals, and a refrigerant.
Methanex's stock is listed on the Toronto Stock Exchange and the New York Stock Exchange.

Methanex is a well-established company with a strong track record. The company is also well-positioned to benefit from the growing demand for methanol. However, the company faces some challenges, including the volatility of the methanol market and the rising cost of natural gas.

Methanex Corporation prediction model is evaluated with Transductive Learning (ML) and Multiple Regression^1,2,3,4 and it is concluded that the MX:TSX stock is predictable in the short/long term.

Transductive learning is a supervised machine learning (ML) method in which the model is trained on both labeled and unlabeled data. The goal of transductive learning is to predict the labels of the unlabeled data. Transductive learning is a hybrid of inductive and semi-supervised learning. Inductive learning algorithms are trained on labeled data only, while semi-supervised learning algorithms are trained on a combination of labeled and unlabeled data. Transductive learning algorithms can achieve better performance than inductive learning algorithms on tasks where there is a small amount of labeled data. This is because transductive learning algorithms can use the unlabeled data to help them learn the relationships between the features and the labels. According to price forecasts for 3 Month period, the dominant strategy among neural network is: Sell Graph 12

Key Points

Reaction Function
Stock Forecast Based On a Predictive Algorithm
Reaction Function

MX:TSX Target Price Prediction Modeling Methodology

We consider Methanex Corporation Decision Process with Transductive Learning (ML) where A is the set of discrete actions of MX: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(Multiple Regression)^5,6,7=

\begin{matrix} p_{a 1} & p_{a 2} & \dots & p_{1 n} \\ ⋮ \\ p_{j 1} & p_{j 2} & \dots & p_{j n} \\ ⋮ \\ p_{k 1} & p_{k 2} & \dots & p_{k n} \\ ⋮ \\ p_{n 1} & p_{n 2} & \dots & p_{n n} \end{matrix}

X R(Transductive Learning (ML)) X S(n):→ 3 Month

\vec{R} = (r_{1}, r_{2}, r_{3})

n:Time series to forecast

p:Price signals of MX:TSX stock

j:Nash equilibria (Neural Network)

k:Dominated move

a:Best response for target price

Transductive Learning (ML)

Multiple Regression

Multiple regression is a statistical method that analyzes the relationship between a dependent variable and multiple independent variables. The dependent variable is the variable that is being predicted, and the independent variables are the variables that are used to predict the dependent variable. Multiple regression is a more complex statistical method than simple linear regression, which only analyzes the relationship between a dependent variable and one independent variable. Multiple regression can be used to analyze more complex relationships between variables, and it can also be used to control for confounding variables. A confounding variable is a variable that is correlated with both the dependent variable and one or more of the independent variables. Confounding variables can distort the relationship between the dependent variable and the independent variables. Multiple regression can be used to control for confounding variables by including them in 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?

MX:TSX Stock Forecast (Buy or Sell) for 3 Month

Sample Set: Neural Network
Stock/Index: MX:TSX Methanex Corporation
Time series to forecast n: 23 Jun 2023 for 3 Month

According to price forecasts for 3 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 Methanex Corporation

Subject to the conditions in paragraphs 4.1.5 and 4.2.2, this Standard allows an entity to designate a financial asset, a financial liability, or a group of financial instruments (financial assets, financial liabilities or both) as at fair value through profit or loss provided that doing so results in more relevant information.
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.
Unless paragraph 6.8.8 applies, for a hedge of a non-contractually specified benchmark component of interest rate risk, an entity shall apply the requirement in paragraphs 6.3.7(a) and B6.3.8—that the risk component shall be separately identifiable—only at the inception of the hedging relationship.
If the group of items does not have any offsetting risk positions (for example, a group of foreign currency expenses that affect different line items in the statement of profit or loss and other comprehensive income that are hedged for foreign currency risk) then the reclassified hedging instrument gains or losses shall be apportioned to the line items affected by the hedged items. This apportionment shall be done on a systematic and rational basis and shall not result in the grossing up of the net gains or losses arising from a single hedging instrument.

*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

Methanex Corporation is assigned short-term Ba3 & long-term Ba3 estimated rating. Methanex Corporation prediction model is evaluated with Transductive Learning (ML) and Multiple Regression^1,2,3,4 and it is concluded that the MX:TSX stock is predictable in the short/long term.

According to price forecasts for 3 Month period, the dominant strategy among neural network is: Sell

MX:TSX Methanex Corporation Financial Analysis*

Rating	Short-Term	Long-Term Senior
Outlook*	Ba3	Ba3
Income Statement	B2	B3
Balance Sheet	Baa2	Baa2
Leverage Ratios	Baa2	B1
Cash Flow	Caa2	C
Rates of Return and Profitability	Baa2	Ba3

*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: 82 out of 100 with 718 signals.

References

Athey S, Imbens GW. 2017b. The state of applied econometrics: causality and policy evaluation. J. Econ. Perspect. 31:3–32
T. Shardlow and A. Stuart. A perturbation theory for ergodic Markov chains and application to numerical approximations. SIAM journal on numerical analysis, 37(4):1120–1137, 2000
Dimakopoulou M, Zhou Z, Athey S, Imbens G. 2018. Balanced linear contextual bandits. arXiv:1812.06227 [cs.LG]
R. Sutton, D. McAllester, S. Singh, and Y. Mansour. Policy gradient methods for reinforcement learning with function approximation. In Proceedings of Advances in Neural Information Processing Systems 12, pages 1057–1063, 2000
Bera, A. M. L. Higgins (1997), "ARCH and bilinearity as competing models for nonlinear dependence," Journal of Business Economic Statistics, 15, 43–50.
Abadie A, Diamond A, Hainmueller J. 2010. Synthetic control methods for comparative case studies: estimat- ing the effect of California's tobacco control program. J. Am. Stat. Assoc. 105:493–505
N. B ̈auerle and J. Ott. Markov decision processes with average-value-at-risk criteria. Mathematical Methods of Operations Research, 74(3):361–379, 2011

Frequently Asked Questions

Q: What is the prediction methodology for MX:TSX stock?
A: MX:TSX stock prediction methodology: We evaluate the prediction models Transductive Learning (ML) and Multiple Regression
Q: Is MX:TSX stock a buy or sell?
A: The dominant strategy among neural network is to Sell MX:TSX Stock.
Q: Is Methanex Corporation stock a good investment?
A: The consensus rating for Methanex Corporation is Sell and is assigned short-term Ba3 & long-term Ba3 estimated rating.
Q: What is the consensus rating of MX:TSX stock?
A: The consensus rating for MX:TSX is Sell.
Q: What is the prediction period for MX:TSX stock?
A: The prediction period for MX:TSX is 3 Month