MAY MELBANA ENERGY LIMITED

Outlook: MELBANA ENERGY LIMITED is assigned short-term Ba1 & long-term Ba1 estimated rating.
Dominant Strategy : BuyWait until speculative trend diminishes
Time series to forecast n: 03 Jun 2023 for (n+16 weeks)
Methodology : Modular Neural Network (Market Volatility Analysis)

Abstract

MELBANA ENERGY LIMITED prediction model is evaluated with Modular Neural Network (Market Volatility Analysis) and Wilcoxon Rank-Sum Test^1,2,3,4 and it is concluded that the MAY stock is predictable in the short/long term. According to price forecasts for (n+16 weeks) period, the dominant strategy among neural network is: BuyWait until speculative trend diminishes

Key Points

1. What are the most successful trading algorithms?
2. How do predictive algorithms actually work?
3. Is now good time to invest?

MAY Target Price Prediction Modeling Methodology

We consider MELBANA ENERGY LIMITED Decision Process with Modular Neural Network (Market Volatility Analysis) where A is the set of discrete actions of MAY 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(Wilcoxon Rank-Sum Test)^5,6,7= $\begin{array}{cccc}{p}_{\mathrm{a}1}& p_{\mathrm{a}2}& \dots & p_{1n}\\ & ⋮\\ p_{j1}& p_{j2}& \dots & p_{jn}\\ & ⋮\\ p_{k1}& p_{k2}& \dots & p_{kn}\\ & ⋮\\ p_{n1}& p_{n2}& \dots & p_{nn}\end{array}$ X R(Modular Neural Network (Market Volatility Analysis)) X S(n):→ (n+16 weeks) $\begin{array}{l}\int r^s\mathrm{rs}\end{array}$

n:Time series to forecast

p:Price signals of MAY 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?

MAY Stock Forecast (Buy or Sell) for (n+16 weeks)

Sample Set: Neural Network
Stock/Index: MAY MELBANA ENERGY LIMITED
Time series to forecast n: 03 Jun 2023 for (n+16 weeks)

According to price forecasts for (n+16 weeks) period, the dominant strategy among neural network is: BuyWait until speculative trend diminishes

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 MELBANA ENERGY LIMITED

1. Paragraph 4.1.1(b) requires an entity to classify a financial asset on the basis of its contractual cash flow characteristics if the financial asset is held within a business model whose objective is to hold assets to collect contractual cash flows or within a business model whose objective is achieved by both collecting contractual cash flows and selling financial assets, unless paragraph 4.1.5 applies. To do so, the condition in paragraphs 4.1.2(b) and 4.1.2A(b) requires an entity to determine whether the asset's contractual cash flows are solely payments of principal and interest on the principal amount outstanding.
2. An entity is not required to restate prior periods to reflect the application of these amendments. The entity may restate prior periods only if it is possible to do so without the use of hindsight. If an entity restates prior periods, the restated financial statements must reflect all the requirements in this Standard for the affected financial instruments. 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.
3. When an entity separates the foreign currency basis spread from a financial instrument and excludes it from the designation of that financial instrument as the hedging instrument (see paragraph 6.2.4(b)), the application guidance in paragraphs B6.5.34–B6.5.38 applies to the foreign currency basis spread in the same manner as it is applied to the forward element of a forward contract.
4. Expected credit losses reflect an entity's own expectations of credit losses. However, when considering all reasonable and supportable information that is available without undue cost or effort in estimating expected credit losses, an entity should also consider observable market information about the credit risk of the particular financial instrument or similar financial instruments.

*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

MELBANA ENERGY LIMITED is assigned short-term Ba1 & long-term Ba1 estimated rating. MELBANA ENERGY LIMITED prediction model is evaluated with Modular Neural Network (Market Volatility Analysis) and Wilcoxon Rank-Sum Test^1,2,3,4 and it is concluded that the MAY stock is predictable in the short/long term. According to price forecasts for (n+16 weeks) period, the dominant strategy among neural network is: BuyWait until speculative trend diminishes

MAY MELBANA ENERGY LIMITED Financial Analysis*

Rating	Short-Term	Long-Term Senior
Outlook*	Ba1	Ba1
Income Statement	B3	B2
Balance Sheet	Baa2	Caa2
Leverage Ratios	B2	Caa2
Cash Flow	Ba1	B2
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

Trust metric by Neural Network: 93 out of 100 with 795 signals.

References

1. R. Sutton, D. McAllester, S. Singh, and Y. Mansour. Policy gradient methods for reinforcement learning with function approximation. In Proceedings of Advances in Neural Information Processing Systems 12, pages 1057–1063, 2000
2. Tibshirani R. 1996. Regression shrinkage and selection via the lasso. J. R. Stat. Soc. B 58:267–88
3. Imbens GW, Rubin DB. 2015. Causal Inference in Statistics, Social, and Biomedical Sciences. Cambridge, UK: Cambridge Univ. Press
4. Challen, D. W. A. J. Hagger (1983), Macroeconomic Systems: Construction, Validation and Applications. New York: St. Martin's Press.
5. A. Tamar and S. Mannor. Variance adjusted actor critic algorithms. arXiv preprint arXiv:1310.3697, 2013.
6. Çetinkaya, A., Zhang, Y.Z., Hao, Y.M. and Ma, X.Y., Can stock prices be predicted?(SMI Index Stock Forecast). AC Investment Research Journal, 101(3).
7. E. van der Pol and F. A. Oliehoek. Coordinated deep reinforcement learners for traffic light control. NIPS Workshop on Learning, Inference and Control of Multi-Agent Systems, 2016.

Frequently Asked Questions

Q: What is the prediction methodology for MAY stock?
A: MAY stock prediction methodology: We evaluate the prediction models Modular Neural Network (Market Volatility Analysis) and Wilcoxon Rank-Sum Test
Q: Is MAY stock a buy or sell?
A: The dominant strategy among neural network is to BuyWait until speculative trend diminishes MAY Stock.
Q: Is MELBANA ENERGY LIMITED stock a good investment?
A: The consensus rating for MELBANA ENERGY LIMITED is BuyWait until speculative trend diminishes and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of MAY stock?
A: The consensus rating for MAY is BuyWait until speculative trend diminishes.
Q: What is the prediction period for MAY stock?
A: The prediction period for MAY is (n+16 weeks)