Dominant Strategy : Sell
Time series to forecast n: 09 May 2023 for (n+16 weeks)
Methodology : Reinforcement Machine Learning (ML)
Abstract
EUREKA GROUP HOLDINGS LIMITED prediction model is evaluated with Reinforcement Machine Learning (ML) and Chi-Square1,2,3,4 and it is concluded that the EGH stock is predictable in the short/long term. According to price forecasts for (n+16 weeks) period, the dominant strategy among neural network is: SellKey Points
- How can neural networks improve predictions?
- Game Theory
- How do you pick a stock?
EGH Target Price Prediction Modeling Methodology
We consider EUREKA GROUP HOLDINGS LIMITED Decision Process with Reinforcement Machine Learning (ML) where A is the set of discrete actions of EGH 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(Chi-Square)5,6,7= X R(Reinforcement Machine Learning (ML)) X S(n):→ (n+16 weeks)
n:Time series to forecast
p:Price signals of EGH 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?
EGH Stock Forecast (Buy or Sell) for (n+16 weeks)
Sample Set: Neural NetworkStock/Index: EGH EUREKA GROUP HOLDINGS LIMITED
Time series to forecast n: 09 May 2023 for (n+16 weeks)
According to price forecasts for (n+16 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 EUREKA GROUP HOLDINGS LIMITED
- 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.
- An equity method investment cannot be a hedged item in a fair value hedge. This is because the equity method recognises in profit or loss the investor's share of the investee's profit or loss, instead of changes in the investment's fair value. For a similar reason, an investment in a consolidated subsidiary cannot be a hedged item in a fair value hedge. This is because consolidation recognises in profit or loss the subsidiary's profit or loss, instead of changes in the investment's fair value. A hedge of a net investment in a foreign operation is different because it is a hedge of the foreign currency exposure, not a fair value hedge of the change in the value of the investment.
- In addition to those hedging relationships specified in paragraph 6.9.1, an entity shall apply the requirements in paragraphs 6.9.11 and 6.9.12 to new hedging relationships in which an alternative benchmark rate is designated as a non-contractually specified risk component (see paragraphs 6.3.7(a) and B6.3.8) when, because of interest rate benchmark reform, that risk component is not separately identifiable at the date it is designated.
- In accordance with the hedge effectiveness requirements, the hedge ratio of the hedging relationship must be the same as that resulting from the quantity of the hedged item that the entity actually hedges and the quantity of the hedging instrument that the entity actually uses to hedge that quantity of hedged item. Hence, if an entity hedges less than 100 per cent of the exposure on an item, such as 85 per cent, it shall designate the hedging relationship using a hedge ratio that is the same as that resulting from 85 per cent of the exposure and the quantity of the hedging instrument that the entity actually uses to hedge those 85 per cent. Similarly, if, for example, an entity hedges an exposure using a nominal amount of 40 units of a financial instrument, it shall designate the hedging relationship using a hedge ratio that is the same as that resulting from that quantity of 40 units (ie the entity must not use a hedge ratio based on a higher quantity of units that it might hold in total or a lower quantity of units) and the quantity of the hedged item that it actually hedges with those 40 units.
*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
EUREKA GROUP HOLDINGS LIMITED is assigned short-term Ba1 & long-term Ba1 estimated rating. EUREKA GROUP HOLDINGS LIMITED prediction model is evaluated with Reinforcement Machine Learning (ML) and Chi-Square1,2,3,4 and it is concluded that the EGH stock is predictable in the short/long term. According to price forecasts for (n+16 weeks) period, the dominant strategy among neural network is: Sell
EGH EUREKA GROUP HOLDINGS LIMITED Financial Analysis*
Rating | Short-Term | Long-Term Senior |
---|---|---|
Outlook* | Ba1 | Ba1 |
Income Statement | Baa2 | B2 |
Balance Sheet | Caa2 | C |
Leverage Ratios | Baa2 | Baa2 |
Cash Flow | C | B2 |
Rates of Return and Profitability | B2 | Ba1 |
*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
- Efron B, Hastie T. 2016. Computer Age Statistical Inference, Vol. 5. Cambridge, UK: Cambridge Univ. Press
- Arora S, Li Y, Liang Y, Ma T. 2016. RAND-WALK: a latent variable model approach to word embeddings. Trans. Assoc. Comput. Linguist. 4:385–99
- Chernozhukov V, Chetverikov D, Demirer M, Duflo E, Hansen C, et al. 2018a. Double/debiased machine learning for treatment and structural parameters. Econom. J. 21:C1–68
- K. Tumer and D. Wolpert. A survey of collectives. In K. Tumer and D. Wolpert, editors, Collectives and the Design of Complex Systems, pages 1–42. Springer, 2004.
- Chen X. 2007. Large sample sieve estimation of semi-nonparametric models. In Handbook of Econometrics, Vol. 6B, ed. JJ Heckman, EE Learner, pp. 5549–632. Amsterdam: Elsevier
- V. Borkar and R. Jain. Risk-constrained Markov decision processes. IEEE Transaction on Automatic Control, 2014
- L. Panait and S. Luke. Cooperative multi-agent learning: The state of the art. Autonomous Agents and Multi-Agent Systems, 11(3):387–434, 2005.
Frequently Asked Questions
Q: What is the prediction methodology for EGH stock?A: EGH stock prediction methodology: We evaluate the prediction models Reinforcement Machine Learning (ML) and Chi-Square
Q: Is EGH stock a buy or sell?
A: The dominant strategy among neural network is to Sell EGH Stock.
Q: Is EUREKA GROUP HOLDINGS LIMITED stock a good investment?
A: The consensus rating for EUREKA GROUP HOLDINGS LIMITED is Sell and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of EGH stock?
A: The consensus rating for EGH is Sell.
Q: What is the prediction period for EGH stock?
A: The prediction period for EGH is (n+16 weeks)