Dominant Strategy : Sell
Time series to forecast n: 18 Feb 2023 for (n+3 month)
Methodology : Modular Neural Network (DNN Layer)
Abstract
AMTE POWER PLC prediction model is evaluated with Modular Neural Network (DNN Layer) and Logistic Regression1,2,3,4 and it is concluded that the LON:AMTE stock is predictable in the short/long term. According to price forecasts for (n+3 month) period, the dominant strategy among neural network is: SellKey Points
- Nash Equilibria
- Trading Interaction
- Should I buy stocks now or wait amid such uncertainty?
LON:AMTE Target Price Prediction Modeling Methodology
We consider AMTE POWER PLC Decision Process with Modular Neural Network (DNN Layer) where A is the set of discrete actions of LON:AMTE 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(Modular Neural Network (DNN Layer)) X S(n):→ (n+3 month)
n:Time series to forecast
p:Price signals of LON:AMTE 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?
LON:AMTE Stock Forecast (Buy or Sell) for (n+3 month)
Sample Set: Neural NetworkStock/Index: LON:AMTE AMTE POWER PLC
Time series to forecast n: 18 Feb 2023 for (n+3 month)
According to price forecasts for (n+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 AMTE POWER PLC
- An entity may manage and evaluate the performance of a group of financial liabilities or financial assets and financial liabilities in such a way that measuring that group at fair value through profit or loss results in more relevant information. The focus in this instance is on the way the entity manages and evaluates performance, instead of on the nature of its financial instruments.
- To the extent that a transfer of a financial asset does not qualify for derecognition, the transferee does not recognise the transferred asset as its asset. The transferee derecognises the cash or other consideration paid and recognises a receivable from the transferor. If the transferor has both a right and an obligation to reacquire control of the entire transferred asset for a fixed amount (such as under a repurchase agreement), the transferee may measure its receivable at amortised cost if it meets the criteria in paragraph 4.1.2.
- 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.
- Paragraph 5.7.5 permits an entity to make an irrevocable election to present in other comprehensive income changes in the fair value of an investment in an equity instrument that is not held for trading. This election is made on an instrument-by-instrument (ie share-by-share) basis. Amounts presented in other comprehensive income shall not be subsequently transferred to profit or loss. However, the entity may transfer the cumulative gain or loss within equity. Dividends on such investments are recognised in profit or loss in accordance with paragraph 5.7.6 unless the dividend clearly represents a recovery of part of the cost of the investment.
*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
AMTE POWER PLC is assigned short-term Ba1 & long-term Ba1 estimated rating. AMTE POWER PLC prediction model is evaluated with Modular Neural Network (DNN Layer) and Logistic Regression1,2,3,4 and it is concluded that the LON:AMTE stock is predictable in the short/long term. According to price forecasts for (n+3 month) period, the dominant strategy among neural network is: Sell
LON:AMTE AMTE POWER PLC Financial Analysis*
Rating | Short-Term | Long-Term Senior |
---|---|---|
Outlook* | Ba1 | Ba1 |
Income Statement | Baa2 | Baa2 |
Balance Sheet | Baa2 | Baa2 |
Leverage Ratios | Baa2 | C |
Cash Flow | B3 | Ba3 |
Rates of Return and Profitability | Baa2 | B2 |
*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
- Allen, P. G. (1994), "Economic forecasting in agriculture," International Journal of Forecasting, 10, 81–135.
- Chernozhukov V, Escanciano JC, Ichimura H, Newey WK. 2016b. Locally robust semiparametric estimation. arXiv:1608.00033 [math.ST]
- LeCun Y, Bengio Y, Hinton G. 2015. Deep learning. Nature 521:436–44
- Athey S, Blei D, Donnelly R, Ruiz F. 2017b. Counterfactual inference for consumer choice across many prod- uct categories. AEA Pap. Proc. 108:64–67
- Batchelor, R. P. Dua (1993), "Survey vs ARCH measures of inflation uncertainty," Oxford Bulletin of Economics Statistics, 55, 341–353.
- Bottomley, P. R. Fildes (1998), "The role of prices in models of innovation diffusion," Journal of Forecasting, 17, 539–555.
- J. Baxter and P. Bartlett. Infinite-horizon policy-gradient estimation. Journal of Artificial Intelligence Re- search, 15:319–350, 2001.
Frequently Asked Questions
Q: What is the prediction methodology for LON:AMTE stock?A: LON:AMTE stock prediction methodology: We evaluate the prediction models Modular Neural Network (DNN Layer) and Logistic Regression
Q: Is LON:AMTE stock a buy or sell?
A: The dominant strategy among neural network is to Sell LON:AMTE Stock.
Q: Is AMTE POWER PLC stock a good investment?
A: The consensus rating for AMTE POWER PLC is Sell and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of LON:AMTE stock?
A: The consensus rating for LON:AMTE is Sell.
Q: What is the prediction period for LON:AMTE stock?
A: The prediction period for LON:AMTE is (n+3 month)
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