Modelling A.I. in Economics

LON:AJOT AVI JAPAN OPPORTUNITY TRUST PLC (Forecast)

Outlook: AVI JAPAN OPPORTUNITY TRUST PLC is assigned short-term Ba1 & long-term Ba1 estimated rating.
Dominant Strategy : Sell
Time series to forecast n: 13 Apr 2023 for (n+8 weeks)
Methodology : Modular Neural Network (Market News Sentiment Analysis)

Abstract

AVI JAPAN OPPORTUNITY TRUST PLC prediction model is evaluated with Modular Neural Network (Market News Sentiment Analysis) and Spearman Correlation1,2,3,4 and it is concluded that the LON:AJOT stock is predictable in the short/long term. According to price forecasts for (n+8 weeks) period, the dominant strategy among neural network is: Sell

Key Points

  1. What is neural prediction?
  2. Trading Signals
  3. Nash Equilibria

LON:AJOT Target Price Prediction Modeling Methodology

We consider AVI JAPAN OPPORTUNITY TRUST PLC Decision Process with Modular Neural Network (Market News Sentiment Analysis) where A is the set of discrete actions of LON:AJOT 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(Modular Neural Network (Market News Sentiment Analysis)) X S(n):→ (n+8 weeks) i = 1 n a i

n:Time series to forecast

p:Price signals of LON:AJOT 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:AJOT Stock Forecast (Buy or Sell) for (n+8 weeks)

Sample Set: Neural Network
Stock/Index: LON:AJOT AVI JAPAN OPPORTUNITY TRUST PLC
Time series to forecast n: 13 Apr 2023 for (n+8 weeks)

According to price forecasts for (n+8 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 AVI JAPAN OPPORTUNITY TRUST PLC

  1. An entity is not required to restate prior periods to reflect the application of these amendments. The entity may restate prior periods if, and only if, it is possible without the use of hindsight. If an entity does not restate prior periods, the entity shall recognise any difference between the previous carrying amount and the carrying amount at the beginning of the annual reporting period that includes the date of initial application of these amendments in the opening retained earnings (or other component of equity, as appropriate) of the annual reporting period that includes the date of initial application of these amendments.
  2. Paragraph 6.3.4 permits an entity to designate as hedged items aggregated exposures that are a combination of an exposure and a derivative. When designating such a hedged item, an entity assesses whether the aggregated exposure combines an exposure with a derivative so that it creates a different aggregated exposure that is managed as one exposure for a particular risk (or risks). In that case, the entity may designate the hedged item on the basis of the aggregated exposure
  3. In some cases, the qualitative and non-statistical quantitative information available may be sufficient to determine that a financial instrument has met the criterion for the recognition of a loss allowance at an amount equal to lifetime expected credit losses. That is, the information does not need to flow through a statistical model or credit ratings process in order to determine whether there has been a significant increase in the credit risk of the financial instrument. In other cases, an entity may need to consider other information, including information from its statistical models or credit ratings processes.
  4. When identifying what risk components qualify for designation as a hedged item, an entity assesses such risk components within the context of the particular market structure to which the risk or risks relate and in which the hedging activity takes place. Such a determination requires an evaluation of the relevant facts and circumstances, which differ by risk and market.

*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

AVI JAPAN OPPORTUNITY TRUST PLC is assigned short-term Ba1 & long-term Ba1 estimated rating. AVI JAPAN OPPORTUNITY TRUST PLC prediction model is evaluated with Modular Neural Network (Market News Sentiment Analysis) and Spearman Correlation1,2,3,4 and it is concluded that the LON:AJOT stock is predictable in the short/long term. According to price forecasts for (n+8 weeks) period, the dominant strategy among neural network is: Sell

LON:AJOT AVI JAPAN OPPORTUNITY TRUST PLC Financial Analysis*

Rating Short-Term Long-Term Senior
Outlook*Ba1Ba1
Income StatementCaa2C
Balance SheetCaa2Ba3
Leverage RatiosCaa2Ba2
Cash FlowB2Ba2
Rates of Return and ProfitabilityCaa2Baa2

*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: 90 out of 100 with 520 signals.

References

  1. R. Sutton and A. Barto. Reinforcement Learning. The MIT Press, 1998
  2. Bai J. 2003. Inferential theory for factor models of large dimensions. Econometrica 71:135–71
  3. Bengio Y, Ducharme R, Vincent P, Janvin C. 2003. A neural probabilistic language model. J. Mach. Learn. Res. 3:1137–55
  4. Batchelor, R. P. Dua (1993), "Survey vs ARCH measures of inflation uncertainty," Oxford Bulletin of Economics Statistics, 55, 341–353.
  5. 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
  6. R. Rockafellar and S. Uryasev. Optimization of conditional value-at-risk. Journal of Risk, 2:21–42, 2000.
  7. Dudik M, Erhan D, Langford J, Li L. 2014. Doubly robust policy evaluation and optimization. Stat. Sci. 29:485–511
Frequently Asked QuestionsQ: What is the prediction methodology for LON:AJOT stock?
A: LON:AJOT stock prediction methodology: We evaluate the prediction models Modular Neural Network (Market News Sentiment Analysis) and Spearman Correlation
Q: Is LON:AJOT stock a buy or sell?
A: The dominant strategy among neural network is to Sell LON:AJOT Stock.
Q: Is AVI JAPAN OPPORTUNITY TRUST PLC stock a good investment?
A: The consensus rating for AVI JAPAN OPPORTUNITY TRUST PLC is Sell and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of LON:AJOT stock?
A: The consensus rating for LON:AJOT is Sell.
Q: What is the prediction period for LON:AJOT stock?
A: The prediction period for LON:AJOT is (n+8 weeks)

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.