**Outlook:**MIRAMAR RESOURCES LIMITED is assigned short-term B2 & long-term B2 estimated rating.

**AUC Score :**

**Short-Term Revised* :**

**Dominant Strategy :**Speculative Trend

**Time series to forecast n:** for 8 Weeks

**Methodology :**Modular Neural Network (Market Volatility Analysis)

**Hypothesis Testing :**Wilcoxon Rank-Sum Test

**Surveillance :**Major exchange and OTC

## Summary

MIRAMAR RESOURCES 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 M2R stock is predictable in the short/long term. Modular neural networks (MNNs) are a type of artificial neural network that can be used for market volatility analysis. MNNs are made up of multiple smaller neural networks, called modules. Each module is responsible for learning a specific task, such as identifying patterns in data or predicting future price movements. The modules are then combined to form a single neural network that can perform multiple tasks.In the context of market volatility analysis, MNNs can be used to identify patterns in market data that suggest that the market is becoming more or less volatile. This information can then be used to make predictions about future price movements.

**According to price forecasts for 8 Weeks period, the dominant strategy among neural network is: Speculative Trend**

## Key Points

- How useful are statistical predictions?
- Short/Long Term Stocks
- Can we predict stock market using machine learning?

## M2R Target Price Prediction Modeling Methodology

We consider MIRAMAR RESOURCES LIMITED Decision Process with Modular Neural Network (Market Volatility Analysis) where A is the set of discrete actions of M2R 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}= $\begin{array}{cccc}{p}_{\mathrm{a}1}& {p}_{\mathrm{a}2}& \dots & {p}_{1n}\\ & \vdots \\ {p}_{j1}& {p}_{j2}& \dots & {p}_{jn}\\ & \vdots \\ {p}_{k1}& {p}_{k2}& \dots & {p}_{kn}\\ & \vdots \\ {p}_{n1}& {p}_{n2}& \dots & {p}_{nn}\end{array}$ X R(Modular Neural Network (Market Volatility Analysis)) X S(n):→ 8 Weeks $\overrightarrow{R}=\left({r}_{1},{r}_{2},{r}_{3}\right)$

n:Time series to forecast

p:Price signals of M2R stock

j:Nash equilibria (Neural Network)

k:Dominated move

a:Best response for target price

### Modular Neural Network (Market Volatility Analysis)

Modular neural networks (MNNs) are a type of artificial neural network that can be used for market volatility analysis. MNNs are made up of multiple smaller neural networks, called modules. Each module is responsible for learning a specific task, such as identifying patterns in data or predicting future price movements. The modules are then combined to form a single neural network that can perform multiple tasks.In the context of market volatility analysis, MNNs can be used to identify patterns in market data that suggest that the market is becoming more or less volatile. This information can then be used to make predictions about future price movements.### Wilcoxon Rank-Sum Test

The Wilcoxon rank-sum test, also known as the Mann-Whitney U test, is a non-parametric test that is used to compare the medians of two independent samples. It is a rank-based test, which means that it does not assume that the data is normally distributed. The Wilcoxon rank-sum test is calculated by first ranking the data from both samples, and then finding the sum of the ranks for one of the samples. The Wilcoxon rank-sum test statistic is then calculated by subtracting the sum of the ranks for one sample from the sum of the ranks for the other sample. The p-value for the Wilcoxon rank-sum test is calculated using a table of critical values. The p-value is the probability of obtaining a test statistic at least as extreme as the one observed, assuming that the null hypothesis is true.

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?

## M2R Stock Forecast (Buy or Sell) for 8 Weeks

**Sample Set:**Neural Network

**Stock/Index:**M2R MIRAMAR RESOURCES LIMITED

**Time series to forecast:**8 Weeks

**According to price forecasts for 8 Weeks period, the dominant strategy among neural network is: Speculative Trend**

**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 MIRAMAR RESOURCES LIMITED

- Rebalancing refers to the adjustments made to the designated quantities of the hedged item or the hedging instrument of an already existing hedging relationship for the purpose of maintaining a hedge ratio that complies with the hedge effectiveness requirements. Changes to designated quantities of a hedged item or of a hedging instrument for a different purpose do not constitute rebalancing for the purpose of this Standard
- As with all fair value measurements, an entity's measurement method for determining the portion of the change in the liability's fair value that is attributable to changes in its credit risk must make maximum use of relevant observable inputs and minimum use of unobservable inputs.
- For the purposes of the transition provisions in paragraphs 7.2.1, 7.2.3–7.2.28 and 7.3.2, the date of initial application is the date when an entity first applies those requirements of this Standard and must be the beginning of a reporting period after the issue of this Standard. Depending on the entity's chosen approach to applying IFRS 9, the transition can involve one or more than one date of initial application for different requirements.
- 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.

*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

MIRAMAR RESOURCES LIMITED is assigned short-term B2 & long-term B2 estimated rating. MIRAMAR RESOURCES 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 M2R stock is predictable in the short/long term. ** According to price forecasts for 8 Weeks period, the dominant strategy among neural network is: Speculative Trend**

### M2R MIRAMAR RESOURCES LIMITED Financial Analysis*

Rating | Short-Term | Long-Term Senior |
---|---|---|

Outlook* | B2 | B2 |

Income Statement | Caa2 | Baa2 |

Balance Sheet | C | B3 |

Leverage Ratios | Baa2 | Caa2 |

Cash Flow | Caa2 | C |

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

## References

- 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.
- D. White. Mean, variance, and probabilistic criteria in finite Markov decision processes: A review. Journal of Optimization Theory and Applications, 56(1):1–29, 1988.
- Chen, C. L. Liu (1993), "Joint estimation of model parameters and outlier effects in time series," Journal of the American Statistical Association, 88, 284–297.
- Zubizarreta JR. 2015. Stable weights that balance covariates for estimation with incomplete outcome data. J. Am. Stat. Assoc. 110:910–22
- Li L, Chu W, Langford J, Moon T, Wang X. 2012. An unbiased offline evaluation of contextual bandit algo- rithms with generalized linear models. In Proceedings of 4th ACM International Conference on Web Search and Data Mining, pp. 297–306. New York: ACM
- Banerjee, A., J. J. Dolado, J. W. Galbraith, D. F. Hendry (1993), Co-integration, Error-correction, and the Econometric Analysis of Non-stationary Data. Oxford: Oxford University Press.
- Çetinkaya, A., Zhang, Y.Z., Hao, Y.M. and Ma, X.Y., How do you decide buy or sell a stock?(SAIC Stock Forecast). AC Investment Research Journal, 101(3).

## Frequently Asked Questions

Q: What is the prediction methodology for M2R stock?A: M2R stock prediction methodology: We evaluate the prediction models Modular Neural Network (Market Volatility Analysis) and Wilcoxon Rank-Sum Test

Q: Is M2R stock a buy or sell?

A: The dominant strategy among neural network is to Speculative Trend M2R Stock.

Q: Is MIRAMAR RESOURCES LIMITED stock a good investment?

A: The consensus rating for MIRAMAR RESOURCES LIMITED is Speculative Trend and is assigned short-term B2 & long-term B2 estimated rating.

Q: What is the consensus rating of M2R stock?

A: The consensus rating for M2R is Speculative Trend.

Q: What is the prediction period for M2R stock?

A: The prediction period for M2R is 8 Weeks

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