Dominant Strategy : Hold
Time series to forecast n: 06 Jun 2023 for 4 Weeks
Methodology : Deductive Inference (ML)
Abstract
Ardagh Metal Packaging S.A. Ordinary Shares prediction model is evaluated with Deductive Inference (ML) and Logistic Regression1,2,3,4 and it is concluded that the AMBP stock is predictable in the short/long term. According to price forecasts for 4 Weeks period, the dominant strategy among neural network is: HoldKey Points
- How useful are statistical predictions?
- Decision Making
- What is a prediction confidence?
AMBP Target Price Prediction Modeling Methodology
We consider Ardagh Metal Packaging S.A. Ordinary Shares Decision Process with Deductive Inference (ML) where A is the set of discrete actions of AMBP 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= X R(Deductive Inference (ML)) X S(n):→ 4 Weeks
n:Time series to forecast
p:Price signals of AMBP 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?
AMBP Stock Forecast (Buy or Sell) for 4 Weeks
Sample Set: Neural NetworkStock/Index: AMBP Ardagh Metal Packaging S.A. Ordinary Shares
Time series to forecast n: 06 Jun 2023 for 4 Weeks
According to price forecasts for 4 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 Ardagh Metal Packaging S.A. Ordinary Shares
- For the purpose of applying paragraph 6.5.11, at the point when an entity amends the description of a hedged item as required in paragraph 6.9.1(b), the amount accumulated in the cash flow hedge reserve shall be deemed to be based on the alternative benchmark rate on which the hedged future cash flows are determined.
- An entity that first applies these amendments after it first applies this Standard shall apply paragraphs 7.2.32–7.2.34. The entity shall also apply the other transition requirements in this Standard necessary for applying these amendments. For that purpose, references to the date of initial application shall be read as referring to the beginning of the reporting period in which an entity first applies these amendments (date of initial application of these amendments).
- However, depending on the nature of the financial instruments and the credit risk information available for particular groups of financial instruments, an entity may not be able to identify significant changes in credit risk for individual financial instruments before the financial instrument becomes past due. This may be the case for financial instruments such as retail loans for which there is little or no updated credit risk information that is routinely obtained and monitored on an individual instrument until a customer breaches the contractual terms. If changes in the credit risk for individual financial instruments are not captured before they become past due, a loss allowance based only on credit information at an individual financial instrument level would not faithfully represent the changes in credit risk since initial recognition.
- 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.
*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
Ardagh Metal Packaging S.A. Ordinary Shares is assigned short-term Ba1 & long-term Ba1 estimated rating. Ardagh Metal Packaging S.A. Ordinary Shares prediction model is evaluated with Deductive Inference (ML) and Logistic Regression1,2,3,4 and it is concluded that the AMBP stock is predictable in the short/long term. According to price forecasts for 4 Weeks period, the dominant strategy among neural network is: Hold
AMBP Ardagh Metal Packaging S.A. Ordinary Shares Financial Analysis*
Rating | Short-Term | Long-Term Senior |
---|---|---|
Outlook* | Ba1 | Ba1 |
Income Statement | Baa2 | Caa2 |
Balance Sheet | Baa2 | B2 |
Leverage Ratios | C | Caa2 |
Cash Flow | B2 | Caa2 |
Rates of Return and Profitability | B3 | B1 |
*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

References
- Rumelhart DE, Hinton GE, Williams RJ. 1986. Learning representations by back-propagating errors. Nature 323:533–36
- Breiman L. 2001b. Statistical modeling: the two cultures (with comments and a rejoinder by the author). Stat. Sci. 16:199–231
- Banerjee, A., J. J. Dolado, J. W. Galbraith, D. F. Hendry (1993), Co-integration, Error-correction, and the Econometric Analysis of Non-stationary Data. Oxford: Oxford University Press.
- Byron, R. P. O. Ashenfelter (1995), "Predicting the quality of an unborn grange," Economic Record, 71, 40–53.
- V. Mnih, A. P. Badia, M. Mirza, A. Graves, T. P. Lillicrap, T. Harley, D. Silver, and K. Kavukcuoglu. Asynchronous methods for deep reinforcement learning. In Proceedings of the 33nd International Conference on Machine Learning, ICML 2016, New York City, NY, USA, June 19-24, 2016, pages 1928–1937, 2016
- D. Bertsekas. Min common/max crossing duality: A geometric view of conjugacy in convex optimization. Lab. for Information and Decision Systems, MIT, Tech. Rep. Report LIDS-P-2796, 2009
- K. Tuyls and G. Weiss. Multiagent learning: Basics, challenges, and prospects. AI Magazine, 33(3): 41–52, 2012
Frequently Asked Questions
Q: What is the prediction methodology for AMBP stock?A: AMBP stock prediction methodology: We evaluate the prediction models Deductive Inference (ML) and Logistic Regression
Q: Is AMBP stock a buy or sell?
A: The dominant strategy among neural network is to Hold AMBP Stock.
Q: Is Ardagh Metal Packaging S.A. Ordinary Shares stock a good investment?
A: The consensus rating for Ardagh Metal Packaging S.A. Ordinary Shares is Hold and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of AMBP stock?
A: The consensus rating for AMBP is Hold.
Q: What is the prediction period for AMBP stock?
A: The prediction period for AMBP is 4 Weeks
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