GRANGE RESOURCES LIMITED. is assigned short-term Ba2 & long-term B3 estimated rating.

Outlook: GRANGE RESOURCES LIMITED. is assigned short-term Ba2 & long-term B3 estimated rating.
AUC Score : What is AUC Score?
Short-Term Revised1 :
Dominant Strategy : Sell
Time series to forecast n: for Weeks2
Methodology : Active Learning (ML)
Hypothesis Testing : Wilcoxon Sign-Rank Test
Surveillance : Major exchange and OTC

1The accuracy of the model is being monitored on a regular basis.(15-minute period)

2Time series is updated based on short-term trends.

Summary

GRANGE RESOURCES LIMITED. prediction model is evaluated with Active Learning (ML) and Wilcoxon Sign-Rank Test1,2,3,4 and it is concluded that the GRR stock is predictable in the short/long term. Active learning (AL) is a machine learning (ML) method in which the model actively queries the user for labels on data points. This allows the model to learn more efficiently, as it is only learning about the data points that are most informative. According to price forecasts for 3 Month period, the dominant strategy among neural network is: Sell

Graph 8

Key Points

  1. What is the best way to predict stock prices?
  2. How do you pick a stock?
  3. How do you pick a stock?

GRR Target Price Prediction Modeling Methodology

We consider GRANGE RESOURCES LIMITED. Decision Process with Active Learning (ML) where A is the set of discrete actions of GRR 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 Sign-Rank Test)5,6,7= p a 1 p a 2 p 1 n p j 1 p j 2 p j n p k 1 p k 2 p k n p n 1 p n 2 p n n X R(Active Learning (ML)) X S(n):→ 3 Month r s rs

n:Time series to forecast

p:Price signals of GRR stock

j:Nash equilibria (Neural Network)

k:Dominated move

a:Best response for target price

Active Learning (ML)

Active learning (AL) is a machine learning (ML) method in which the model actively queries the user for labels on data points. This allows the model to learn more efficiently, as it is only learning about the data points that are most informative.

Wilcoxon Sign-Rank 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?

GRR Stock Forecast (Buy or Sell)

Sample Set: Neural Network
Stock/Index: GRR GRANGE RESOURCES LIMITED.
Time series to forecast: 3 Month

According to price forecasts, the dominant strategy among neural network is: Sell

Strategic Interaction Table Legend:

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%

Financial Data Adjustments for Active Learning (ML) based GRR Stock Prediction Model

  1. A net position is eligible for hedge accounting only if an entity hedges on a net basis for risk management purposes. Whether an entity hedges in this way is a matter of fact (not merely of assertion or documentation). Hence, an entity cannot apply hedge accounting on a net basis solely to achieve a particular accounting outcome if that would not reflect its risk management approach. Net position hedging must form part of an established risk management strategy. Normally this would be approved by key management personnel as defined in IAS 24.
  2. An entity has not retained control of a transferred asset if the transferee has the practical ability to sell the transferred asset. An entity has retained control of a transferred asset if the transferee does not have the practical ability to sell the transferred asset. A transferee has the practical ability to sell the transferred asset if it is traded in an active market because the transferee could repurchase the transferred asset in the market if it needs to return the asset to the entity. For example, a transferee may have the practical ability to sell a transferred asset if the transferred asset is subject to an option that allows the entity to repurchase it, but the transferee can readily obtain the transferred asset in the market if the option is exercised. A transferee does not have the practical ability to sell the transferred asset if the entity retains such an option and the transferee cannot readily obtain the transferred asset in the market if the entity exercises its option
  3. Subject to the conditions in paragraphs 4.1.5 and 4.2.2, this Standard allows an entity to designate a financial asset, a financial liability, or a group of financial instruments (financial assets, financial liabilities or both) as at fair value through profit or loss provided that doing so results in more relevant information.
  4. An entity that first applies these amendments at the same time it first applies this Standard shall apply paragraphs 7.2.1–7.2.28 instead of paragraphs 7.2.31–7.2.34.

*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.

GRR GRANGE RESOURCES LIMITED. Financial Analysis*

Rating Short-Term Long-Term Senior
Outlook*Ba2B3
Income StatementBa2C
Balance SheetBa3Caa2
Leverage RatiosBaa2Caa2
Cash FlowBaa2B2
Rates of Return and ProfitabilityCaa2Ba3

*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?

Conclusions

GRANGE RESOURCES LIMITED. is assigned short-term Ba2 & long-term B3 estimated rating. GRANGE RESOURCES LIMITED. prediction model is evaluated with Active Learning (ML) and Wilcoxon Sign-Rank Test1,2,3,4 and it is concluded that the GRR stock is predictable in the short/long term. According to price forecasts for 3 Month period, the dominant strategy among neural network is: Sell

Prediction Confidence Score

Trust metric by Neural Network: 82 out of 100 with 568 signals.

References

  1. Chernozhukov V, Newey W, Robins J. 2018c. Double/de-biased machine learning using regularized Riesz representers. arXiv:1802.08667 [stat.ML]
  2. Knox SW. 2018. Machine Learning: A Concise Introduction. Hoboken, NJ: Wiley
  3. Mazumder R, Hastie T, Tibshirani R. 2010. Spectral regularization algorithms for learning large incomplete matrices. J. Mach. Learn. Res. 11:2287–322
  4. Bessler, D. A. R. A. Babula, (1987), "Forecasting wheat exports: Do exchange rates matter?" Journal of Business and Economic Statistics, 5, 397–406.
  5. J. Ott. A Markov decision model for a surveillance application and risk-sensitive Markov decision processes. PhD thesis, Karlsruhe Institute of Technology, 2010.
  6. Abadie A, Cattaneo MD. 2018. Econometric methods for program evaluation. Annu. Rev. Econ. 10:465–503
  7. 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 QuestionsQ: What is the prediction methodology for GRR stock?
A: GRR stock prediction methodology: We evaluate the prediction models Active Learning (ML) and Wilcoxon Sign-Rank Test
Q: Is GRR stock a buy or sell?
A: The dominant strategy among neural network is to Sell GRR Stock.
Q: Is GRANGE RESOURCES LIMITED. stock a good investment?
A: The consensus rating for GRANGE RESOURCES LIMITED. is Sell and is assigned short-term Ba2 & long-term B3 estimated rating.
Q: What is the consensus rating of GRR stock?
A: The consensus rating for GRR is Sell.
Q: What is the prediction period for GRR stock?
A: The prediction period for GRR is 3 Month

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