RIO:TSXV Rio2 Limited

Outlook: Rio2 Limited is assigned short-term Ba1 & long-term Ba1 estimated rating.
Dominant Strategy : Sell
Time series to forecast n: 16 Jan 2023 for (n+3 month)
Methodology : Supervised Machine Learning (ML)

Abstract

Rio2 Limited prediction model is evaluated with Supervised Machine Learning (ML) and Beta^1,2,3,4 and it is concluded that the RIO:TSXV 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. Stock Forecast Based On a Predictive Algorithm
2. What are buy sell or hold recommendations?
3. Nash Equilibria

RIO:TSXV Target Price Prediction Modeling Methodology

We consider Rio2 Limited Decision Process with Supervised Machine Learning (ML) where A is the set of discrete actions of RIO:TSXV 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(Beta)^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(Supervised Machine Learning (ML)) X S(n):→ (n+3 month) $\sum _{i=1}^n\left(r_i\right)$

n:Time series to forecast

p:Price signals of RIO:TSXV 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?

RIO:TSXV Stock Forecast (Buy or Sell) for (n+3 month)

Sample Set: Neural Network
Stock/Index: RIO:TSXV Rio2 Limited
Time series to forecast n: 16 Jan 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 Rio2 Limited

1. An entity is not required to incorporate forecasts of future conditions over the entire expected life of a financial instrument. The degree of judgement that is required to estimate expected credit losses depends on the availability of detailed information. As the forecast horizon increases, the availability of detailed information decreases and the degree of judgement required to estimate expected credit losses increases. The estimate of expected credit losses does not require a detailed estimate for periods that are far in the future—for such periods, an entity may extrapolate projections from available, detailed information.
2. Alternatively, the entity may base the assessment on both types of information, ie qualitative factors that are not captured through the internal ratings process and a specific internal rating category at the reporting date, taking into consideration the credit risk characteristics at initial recognition, if both types of information are relevant.
3. An entity shall apply the impairment requirements in Section 5.5 retrospectively in accordance with IAS 8 subject to paragraphs 7.2.15 and 7.2.18–7.2.20.
4. The requirement that an economic relationship exists means that the hedging instrument and the hedged item have values that generally move in the opposite direction because of the same risk, which is the hedged risk. Hence, there must be an expectation that the value of the hedging instrument and the value of the hedged item will systematically change in response to movements in either the same underlying or underlyings that are economically related in such a way that they respond in a similar way to the risk that is being hedged (for example, Brent and WTI crude oil).

*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

Rio2 Limited is assigned short-term Ba1 & long-term Ba1 estimated rating. Rio2 Limited prediction model is evaluated with Supervised Machine Learning (ML) and Beta^1,2,3,4 and it is concluded that the RIO:TSXV 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

RIO:TSXV Rio2 Limited Financial Analysis*

Rating	Short-Term	Long-Term Senior
Outlook*	Ba1	Ba1
Income Statement	B3	Ba2
Balance Sheet	B2	Caa2
Leverage Ratios	Baa2	Ba3
Cash Flow	C	B3
Rates of Return and Profitability	Baa2	B1

*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: 87 out of 100 with 747 signals.

References

1. uyer, S. Whiteson, B. Bakker, and N. A. Vlassis. Multiagent reinforcement learning for urban traffic control using coordination graphs. In Machine Learning and Knowledge Discovery in Databases, European Conference, ECML/PKDD 2008, Antwerp, Belgium, September 15-19, 2008, Proceedings, Part I, pages 656–671, 2008.
2. Clements, M. P. D. F. Hendry (1997), "An empirical study of seasonal unit roots in forecasting," International Journal of Forecasting, 13, 341–355.
3. Breiman L. 1996. Bagging predictors. Mach. Learn. 24:123–40
4. Mazumder R, Hastie T, Tibshirani R. 2010. Spectral regularization algorithms for learning large incomplete matrices. J. Mach. Learn. Res. 11:2287–322
5. Dietterich TG. 2000. Ensemble methods in machine learning. In Multiple Classifier Systems: First International Workshop, Cagliari, Italy, June 21–23, pp. 1–15. Berlin: Springer
6. V. Borkar. Stochastic approximation: a dynamical systems viewpoint. Cambridge University Press, 2008
7. E. Altman. Constrained Markov decision processes, volume 7. CRC Press, 1999

Frequently Asked Questions

Q: What is the prediction methodology for RIO:TSXV stock?
A: RIO:TSXV stock prediction methodology: We evaluate the prediction models Supervised Machine Learning (ML) and Beta
Q: Is RIO:TSXV stock a buy or sell?
A: The dominant strategy among neural network is to Sell RIO:TSXV Stock.
Q: Is Rio2 Limited stock a good investment?
A: The consensus rating for Rio2 Limited is Sell and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of RIO:TSXV stock?
A: The consensus rating for RIO:TSXV is Sell.
Q: What is the prediction period for RIO:TSXV stock?
A: The prediction period for RIO:TSXV is (n+3 month)

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