Modelling A.I. in Economics

ASTL Algoma Steel Group Inc. Common Shares

Outlook: Algoma Steel Group Inc. Common Shares is assigned short-term Ba1 & long-term Ba1 estimated rating.
Dominant Strategy : Hold
Time series to forecast n: 03 Apr 2023 for (n+8 weeks)
Methodology : Inductive Learning (ML)

Abstract

Algoma Steel Group Inc. Common Shares prediction model is evaluated with Inductive Learning (ML) and Spearman Correlation1,2,3,4 and it is concluded that the ASTL stock is predictable in the short/long term. According to price forecasts for (n+8 weeks) period, the dominant strategy among neural network is: Hold

Key Points

  1. Market Signals
  2. Market Risk
  3. What statistical methods are used to analyze data?

ASTL Target Price Prediction Modeling Methodology

We consider Algoma Steel Group Inc. Common Shares Decision Process with Inductive Learning (ML) where A is the set of discrete actions of ASTL 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(Spearman Correlation)5,6,7= p a 1 p a 2 p 1 n p j 1 p j 2 p j n p k 1 p k 2 p k n p n 1 p n 2 p n n X R(Inductive Learning (ML)) X S(n):→ (n+8 weeks) r s rs

n:Time series to forecast

p:Price signals of ASTL 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?

ASTL Stock Forecast (Buy or Sell) for (n+8 weeks)

Sample Set: Neural Network
Stock/Index: ASTL Algoma Steel Group Inc. Common Shares
Time series to forecast n: 03 Apr 2023 for (n+8 weeks)

According to price forecasts for (n+8 weeks) 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 Algoma Steel Group Inc. Common Shares

  1. For the purpose of applying paragraphs B4.1.11(b) and B4.1.12(b), irrespective of the event or circumstance that causes the early termination of the contract, a party may pay or receive reasonable compensation for that early termination. For example, a party may pay or receive reasonable compensation when it chooses to terminate the contract early (or otherwise causes the early termination to occur).
  2. A portfolio of financial assets that is managed and whose performance is evaluated on a fair value basis (as described in paragraph 4.2.2(b)) is neither held to collect contractual cash flows nor held both to collect contractual cash flows and to sell financial assets. The entity is primarily focused on fair value information and uses that information to assess the assets' performance and to make decisions. In addition, a portfolio of financial assets that meets the definition of held for trading is not held to collect contractual cash flows or held both to collect contractual cash flows and to sell financial assets. For such portfolios, the collection of contractual cash flows is only incidental to achieving the business model's objective. Consequently, such portfolios of financial assets must be measured at fair value through profit or loss.
  3. Paragraph 5.5.4 requires that lifetime expected credit losses are recognised on all financial instruments for which there has been significant increases in credit risk since initial recognition. In order to meet this objective, if an entity is not able to group financial instruments for which the credit risk is considered to have increased significantly since initial recognition based on shared credit risk characteristics, the entity should recognise lifetime expected credit losses on a portion of the financial assets for which credit risk is deemed to have increased significantly. The aggregation of financial instruments to assess whether there are changes in credit risk on a collective basis may change over time as new information becomes available on groups of, or individual, financial instruments.
  4. Annual Improvements to IFRS Standards 2018–2020, issued in May 2020, added paragraphs 7.2.35 and B3.3.6A and amended paragraph B3.3.6. An entity shall apply that amendment for annual reporting periods beginning on or after 1 January 2022. Earlier application is permitted. If an entity applies the amendment for an earlier period, it shall disclose that fact.

*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

Algoma Steel Group Inc. Common Shares is assigned short-term Ba1 & long-term Ba1 estimated rating. Algoma Steel Group Inc. Common Shares prediction model is evaluated with Inductive Learning (ML) and Spearman Correlation1,2,3,4 and it is concluded that the ASTL stock is predictable in the short/long term. According to price forecasts for (n+8 weeks) period, the dominant strategy among neural network is: Hold

ASTL Algoma Steel Group Inc. Common Shares Financial Analysis*

Rating Short-Term Long-Term Senior
Outlook*Ba1Ba1
Income StatementB1Ba2
Balance SheetBaa2Caa2
Leverage RatiosBaa2Baa2
Cash FlowCC
Rates of Return and ProfitabilityBaa2Baa2

*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 469 signals.

References

  1. Jiang N, Li L. 2016. Doubly robust off-policy value evaluation for reinforcement learning. In Proceedings of the 33rd International Conference on Machine Learning, pp. 652–61. La Jolla, CA: Int. Mach. Learn. Soc.
  2. Bessler, D. A. R. A. Babula, (1987), "Forecasting wheat exports: Do exchange rates matter?" Journal of Business and Economic Statistics, 5, 397–406.
  3. Miller A. 2002. Subset Selection in Regression. New York: CRC Press
  4. Lai TL, Robbins H. 1985. Asymptotically efficient adaptive allocation rules. Adv. Appl. Math. 6:4–22
  5. D. Bertsekas and J. Tsitsiklis. Neuro-dynamic programming. Athena Scientific, 1996.
  6. Tibshirani R, Hastie T. 1987. Local likelihood estimation. J. Am. Stat. Assoc. 82:559–67
  7. Tibshirani R, Hastie T. 1987. Local likelihood estimation. J. Am. Stat. Assoc. 82:559–67
Frequently Asked QuestionsQ: What is the prediction methodology for ASTL stock?
A: ASTL stock prediction methodology: We evaluate the prediction models Inductive Learning (ML) and Spearman Correlation
Q: Is ASTL stock a buy or sell?
A: The dominant strategy among neural network is to Hold ASTL Stock.
Q: Is Algoma Steel Group Inc. Common Shares stock a good investment?
A: The consensus rating for Algoma Steel Group Inc. Common Shares is Hold and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of ASTL stock?
A: The consensus rating for ASTL is Hold.
Q: What is the prediction period for ASTL stock?
A: The prediction period for ASTL is (n+8 weeks)

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