Modelling A.I. in Economics

LON:ECO ECO (ATLANTIC) OIL & GAS LTD (Forecast)

Outlook: ECO (ATLANTIC) OIL & GAS LTD is assigned short-term Ba1 & long-term Ba1 estimated rating.
Dominant Strategy : Sell
Time series to forecast n: 28 Mar 2023 for (n+3 month)
Methodology : Modular Neural Network (CNN Layer)

Abstract

ECO (ATLANTIC) OIL & GAS LTD prediction model is evaluated with Modular Neural Network (CNN Layer) and Statistical Hypothesis Testing1,2,3,4 and it is concluded that the LON:ECO 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

Key Points

  1. Market Outlook
  2. What are the most successful trading algorithms?
  3. Nash Equilibria

LON:ECO Target Price Prediction Modeling Methodology

We consider ECO (ATLANTIC) OIL & GAS LTD Decision Process with Modular Neural Network (CNN Layer) where A is the set of discrete actions of LON:ECO 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(Statistical Hypothesis Testing)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(Modular Neural Network (CNN Layer)) X S(n):→ (n+3 month) R = 1 0 0 0 1 0 0 0 1

n:Time series to forecast

p:Price signals of LON:ECO 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:ECO Stock Forecast (Buy or Sell) for (n+3 month)

Sample Set: Neural Network
Stock/Index: LON:ECO ECO (ATLANTIC) OIL & GAS LTD
Time series to forecast n: 28 Mar 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 ECO (ATLANTIC) OIL & GAS LTD

  1. 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.
  2. An alternative benchmark rate designated as a non-contractually specified risk component that is not separately identifiable (see paragraphs 6.3.7(a) and B6.3.8) at the date it is designated shall be deemed to have met that requirement at that date, if, and only if, the entity reasonably expects the alternative benchmark rate will be separately identifiable within 24 months. The 24-month period applies to each alternative benchmark rate separately and starts from the date the entity designates the alternative benchmark rate as a non-contractually specified risk component for the first time (ie the 24- month period applies on a rate-by-rate basis).
  3. When an entity, consistent with its hedge documentation, frequently resets (ie discontinues and restarts) a hedging relationship because both the hedging instrument and the hedged item frequently change (ie the entity uses a dynamic process in which both the hedged items and the hedging instruments used to manage that exposure do not remain the same for long), the entity shall apply the requirement in paragraphs 6.3.7(a) and B6.3.8—that the risk component is separately identifiable—only when it initially designates a hedged item in that hedging relationship. A hedged item that has been assessed at the time of its initial designation in the hedging relationship, whether it was at the time of the hedge inception or subsequently, is not reassessed at any subsequent redesignation in the same hedging relationship.
  4. An entity shall apply Annual Improvements to IFRS Standards 2018–2020 to financial liabilities that are modified or exchanged on or after the beginning of the annual reporting period in which the entity first applies the amendment.

*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

ECO (ATLANTIC) OIL & GAS LTD is assigned short-term Ba1 & long-term Ba1 estimated rating. ECO (ATLANTIC) OIL & GAS LTD prediction model is evaluated with Modular Neural Network (CNN Layer) and Statistical Hypothesis Testing1,2,3,4 and it is concluded that the LON:ECO 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:ECO ECO (ATLANTIC) OIL & GAS LTD Financial Analysis*

Rating Short-Term Long-Term Senior
Outlook*Ba1Ba1
Income StatementBaa2B2
Balance SheetBaa2B1
Leverage RatiosB1B1
Cash FlowB2Baa2
Rates of Return and ProfitabilityCBaa2

*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: 93 out of 100 with 790 signals.

References

  1. Hastie T, Tibshirani R, Wainwright M. 2015. Statistical Learning with Sparsity: The Lasso and Generalizations. New York: CRC Press
  2. V. Borkar and R. Jain. Risk-constrained Markov decision processes. IEEE Transaction on Automatic Control, 2014
  3. J. Harb and D. Precup. Investigating recurrence and eligibility traces in deep Q-networks. In Deep Reinforcement Learning Workshop, NIPS 2016, Barcelona, Spain, 2016.
  4. Breusch, T. S. (1978), "Testing for autocorrelation in dynamic linear models," Australian Economic Papers, 17, 334–355.
  5. 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
  6. Chernozhukov V, Newey W, Robins J. 2018c. Double/de-biased machine learning using regularized Riesz representers. arXiv:1802.08667 [stat.ML]
  7. Akgiray, V. (1989), "Conditional heteroscedasticity in time series of stock returns: Evidence and forecasts," Journal of Business, 62, 55–80.
Frequently Asked QuestionsQ: What is the prediction methodology for LON:ECO stock?
A: LON:ECO stock prediction methodology: We evaluate the prediction models Modular Neural Network (CNN Layer) and Statistical Hypothesis Testing
Q: Is LON:ECO stock a buy or sell?
A: The dominant strategy among neural network is to Sell LON:ECO Stock.
Q: Is ECO (ATLANTIC) OIL & GAS LTD stock a good investment?
A: The consensus rating for ECO (ATLANTIC) OIL & GAS LTD is Sell and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of LON:ECO stock?
A: The consensus rating for LON:ECO is Sell.
Q: What is the prediction period for LON:ECO stock?
A: The prediction period for LON:ECO is (n+3 month)

Premium

  • Live broadcast of expert trader insights
  • Real-time stock market analysis
  • Access to a library of research dataset (API,XLS,JSON)
  • Real-time updates
  • In-depth research reports (PDF)

Login
This project is licensed under the license; additional terms may apply.