RMS RAMELIUS RESOURCES LIMITED (Forecast)

Outlook: RAMELIUS RESOURCES LIMITED is assigned short-term Ba1 & long-term Ba1 estimated rating.
Dominant Strategy : Wait until speculative trend diminishes
Time series to forecast n: 06 Feb 2023 for (n+16 weeks)
Methodology : Transfer Learning (ML)

Abstract

RAMELIUS RESOURCES LIMITED prediction model is evaluated with Transfer Learning (ML) and Lasso Regression^1,2,3,4 and it is concluded that the RMS stock is predictable in the short/long term. According to price forecasts for (n+16 weeks) period, the dominant strategy among neural network is: Wait until speculative trend diminishes

Key Points

1. How do you decide buy or sell a stock?
2. Can machine learning predict?
3. Decision Making

RMS Target Price Prediction Modeling Methodology

We consider RAMELIUS RESOURCES LIMITED Decision Process with Transfer Learning (ML) where A is the set of discrete actions of RMS 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(Lasso Regression)^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(Transfer Learning (ML)) X S(n):→ (n+16 weeks) $\sum _{i=1}^n\left(r_i\right)$

n:Time series to forecast

p:Price signals of RMS 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?

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

Sample Set: Neural Network
Stock/Index: RMS RAMELIUS RESOURCES LIMITED
Time series to forecast n: 06 Feb 2023 for (n+16 weeks)

According to price forecasts for (n+16 weeks) period, the dominant strategy among neural network is: Wait 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 RAMELIUS RESOURCES LIMITED

1. IFRS 7 defines credit risk as 'the risk that one party to a financial instrument will cause a financial loss for the other party by failing to discharge an obligation'. The requirement in paragraph 5.7.7(a) relates to the risk that the issuer will fail to perform on that particular liability. It does not necessarily relate to the creditworthiness of the issuer. For example, if an entity issues a collateralised liability and a non-collateralised liability that are otherwise identical, the credit risk of those two liabilities will be different, even though they are issued by the same entity. The credit risk on the collateralised liability will be less than the credit risk of the non-collateralised liability. The credit risk for a collateralised liability may be close to zero.
2. Expected credit losses are a probability-weighted estimate of credit losses (ie the present value of all cash shortfalls) over the expected life of the financial instrument. A cash shortfall is the difference between the cash flows that are due to an entity in accordance with the contract and the cash flows that the entity expects to receive. Because expected credit losses consider the amount and timing of payments, a credit loss arises even if the entity expects to be paid in full but later than when contractually due.
3. Paragraph 4.1.1(a) requires an entity to classify financial assets on the basis of the entity's business model for managing the financial assets, unless paragraph 4.1.5 applies. An entity assesses whether its financial assets meet the condition in paragraph 4.1.2(a) or the condition in paragraph 4.1.2A(a) on the basis of the business model as determined by the entity's key management personnel (as defined in IAS 24 Related Party Disclosures).
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

RAMELIUS RESOURCES LIMITED is assigned short-term Ba1 & long-term Ba1 estimated rating. RAMELIUS RESOURCES LIMITED prediction model is evaluated with Transfer Learning (ML) and Lasso Regression^1,2,3,4 and it is concluded that the RMS stock is predictable in the short/long term. According to price forecasts for (n+16 weeks) period, the dominant strategy among neural network is: Wait until speculative trend diminishes

RMS RAMELIUS RESOURCES LIMITED Financial Analysis*

Rating	Short-Term	Long-Term Senior
Outlook*	Ba1	Ba1
Income Statement	Caa2	Baa2
Balance Sheet	Baa2	B2
Leverage Ratios	Ba2	B1
Cash Flow	B3	Caa2
Rates of Return and Profitability	B1	B3

*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: 79 out of 100 with 556 signals.

References

1. Breiman L, Friedman J, Stone CJ, Olshen RA. 1984. Classification and Regression Trees. Boca Raton, FL: CRC Press
2. Christou, C., P. A. V. B. Swamy G. S. Tavlas (1996), "Modelling optimal strategies for the allocation of wealth in multicurrency investments," International Journal of Forecasting, 12, 483–493.
3. M. Babes, E. M. de Cote, and M. L. Littman. Social reward shaping in the prisoner's dilemma. In 7th International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS 2008), Estoril, Portugal, May 12-16, 2008, Volume 3, pages 1389–1392, 2008.
4. M. Puterman. Markov Decision Processes: Discrete Stochastic Dynamic Programming. Wiley, New York, 1994.
5. Robins J, Rotnitzky A. 1995. Semiparametric efficiency in multivariate regression models with missing data. J. Am. Stat. Assoc. 90:122–29
6. Çetinkaya, A., Zhang, Y.Z., Hao, Y.M. and Ma, X.Y., Is TPL a Buy?. AC Investment Research Journal, 101(3).
7. Bell RM, Koren Y. 2007. Lessons from the Netflix prize challenge. ACM SIGKDD Explor. Newsl. 9:75–79

Frequently Asked Questions

Q: What is the prediction methodology for RMS stock?
A: RMS stock prediction methodology: We evaluate the prediction models Transfer Learning (ML) and Lasso Regression
Q: Is RMS stock a buy or sell?
A: The dominant strategy among neural network is to Wait until speculative trend diminishes RMS Stock.
Q: Is RAMELIUS RESOURCES LIMITED stock a good investment?
A: The consensus rating for RAMELIUS RESOURCES LIMITED is Wait until speculative trend diminishes and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of RMS stock?
A: The consensus rating for RMS is Wait until speculative trend diminishes.
Q: What is the prediction period for RMS stock?
A: The prediction period for RMS is (n+16 weeks)

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