Dominant Strategy : Sell
Time series to forecast n: 11 Feb 2023 for (n+4 weeks)
Methodology : Ensemble Learning (ML)
Abstract
AQUILA EUROPEAN RENEWABLES INCOME FUND PLC prediction model is evaluated with Ensemble Learning (ML) and Independent T-Test1,2,3,4 and it is concluded that the LON:AERS stock is predictable in the short/long term. According to price forecasts for (n+4 weeks) period, the dominant strategy among neural network is: SellKey Points
- Market Risk
- Trading Signals
- Trust metric by Neural Network
LON:AERS Target Price Prediction Modeling Methodology
We consider AQUILA EUROPEAN RENEWABLES INCOME FUND PLC Decision Process with Ensemble Learning (ML) where A is the set of discrete actions of LON:AERS 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(Independent T-Test)5,6,7= X R(Ensemble Learning (ML)) X S(n):→ (n+4 weeks)
n:Time series to forecast
p:Price signals of LON:AERS 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:AERS Stock Forecast (Buy or Sell) for (n+4 weeks)
Sample Set: Neural NetworkStock/Index: LON:AERS AQUILA EUROPEAN RENEWABLES INCOME FUND PLC
Time series to forecast n: 11 Feb 2023 for (n+4 weeks)
According to price forecasts for (n+4 weeks) 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 AQUILA EUROPEAN RENEWABLES INCOME FUND PLC
- The fair value of a financial instrument at initial recognition is normally the transaction price (ie the fair value of the consideration given or received, see also paragraph B5.1.2A and IFRS 13). However, if part of the consideration given or received is for something other than the financial instrument, an entity shall measure the fair value of the financial instrument. For example, the fair value of a long-term loan or receivable that carries no interest can be measured as the present value of all future cash receipts discounted using the prevailing market rate(s) of interest for a similar instrument (similar as to currency, term, type of interest rate and other factors) with a similar credit rating. Any additional amount lent is an expense or a reduction of income unless it qualifies for recognition as some other type of asset.
- IFRS 16, issued in January 2016, amended paragraphs 2.1, 5.5.15, B4.3.8, B5.5.34 and B5.5.46. An entity shall apply those amendments when it applies IFRS 16.
- 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.
- A net position is eligible for hedge accounting only if an entity hedges on a net basis for risk management purposes. Whether an entity hedges in this way is a matter of fact (not merely of assertion or documentation). Hence, an entity cannot apply hedge accounting on a net basis solely to achieve a particular accounting outcome if that would not reflect its risk management approach. Net position hedging must form part of an established risk management strategy. Normally this would be approved by key management personnel as defined in IAS 24.
*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
AQUILA EUROPEAN RENEWABLES INCOME FUND PLC is assigned short-term Ba1 & long-term Ba1 estimated rating. AQUILA EUROPEAN RENEWABLES INCOME FUND PLC prediction model is evaluated with Ensemble Learning (ML) and Independent T-Test1,2,3,4 and it is concluded that the LON:AERS stock is predictable in the short/long term. According to price forecasts for (n+4 weeks) period, the dominant strategy among neural network is: Sell
LON:AERS AQUILA EUROPEAN RENEWABLES INCOME FUND PLC Financial Analysis*
Rating | Short-Term | Long-Term Senior |
---|---|---|
Outlook* | Ba1 | Ba1 |
Income Statement | Baa2 | C |
Balance Sheet | C | Ba3 |
Leverage Ratios | Caa2 | Caa2 |
Cash Flow | Caa2 | Caa2 |
Rates of Return and Profitability | Baa2 | C |
*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
- White H. 1992. Artificial Neural Networks: Approximation and Learning Theory. Oxford, UK: Blackwell
- Andrews, D. W. K. (1993), "Tests for parameter instability and structural change with unknown change point," Econometrica, 61, 821–856.
- S. Proper and K. Tumer. Modeling difference rewards for multiagent learning (extended abstract). In Proceedings of the Eleventh International Joint Conference on Autonomous Agents and Multiagent Systems, Valencia, Spain, June 2012
- Imbens GW, Rubin DB. 2015. Causal Inference in Statistics, Social, and Biomedical Sciences. Cambridge, UK: Cambridge Univ. Press
- R. Sutton and A. Barto. Reinforcement Learning. The MIT Press, 1998
- 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]
- Bastani H, Bayati M. 2015. Online decision-making with high-dimensional covariates. Work. Pap., Univ. Penn./ Stanford Grad. School Bus., Philadelphia/Stanford, CA
Frequently Asked Questions
Q: What is the prediction methodology for LON:AERS stock?A: LON:AERS stock prediction methodology: We evaluate the prediction models Ensemble Learning (ML) and Independent T-Test
Q: Is LON:AERS stock a buy or sell?
A: The dominant strategy among neural network is to Sell LON:AERS Stock.
Q: Is AQUILA EUROPEAN RENEWABLES INCOME FUND PLC stock a good investment?
A: The consensus rating for AQUILA EUROPEAN RENEWABLES INCOME FUND PLC is Sell and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of LON:AERS stock?
A: The consensus rating for LON:AERS is Sell.
Q: What is the prediction period for LON:AERS stock?
A: The prediction period for LON:AERS is (n+4 weeks)
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