Outlook: BLACK MOUNTAIN ENERGY LTD is assigned short-term Ba1 & long-term Ba1 estimated rating.
Dominant Strategy : Sell
Time series to forecast n: 12 Mar 2023 for (n+4 weeks)

## Abstract

BLACK MOUNTAIN ENERGY LTD prediction model is evaluated with Multi-Task Learning (ML) and Lasso Regression1,2,3,4 and it is concluded that the BME stock is predictable in the short/long term. According to price forecasts for (n+4 weeks) period, the dominant strategy among neural network is: Sell

## Key Points

1. How useful are statistical predictions?
2. Reaction Function
3. What are the most successful trading algorithms?

## BME Target Price Prediction Modeling Methodology

We consider BLACK MOUNTAIN ENERGY LTD Decision Process with Multi-Task Learning (ML) where A is the set of discrete actions of BME 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= $\begin{array}{cccc}{p}_{a1}& {p}_{a2}& \dots & {p}_{1n}\\ & ⋮\\ {p}_{j1}& {p}_{j2}& \dots & {p}_{jn}\\ & ⋮\\ {p}_{k1}& {p}_{k2}& \dots & {p}_{kn}\\ & ⋮\\ {p}_{n1}& {p}_{n2}& \dots & {p}_{nn}\end{array}$ X R(Multi-Task Learning (ML)) X S(n):→ (n+4 weeks) $\stackrel{\to }{S}=\left({s}_{1},{s}_{2},{s}_{3}\right)$

n:Time series to forecast

p:Price signals of BME 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?

## BME Stock Forecast (Buy or Sell) for (n+4 weeks)

Sample Set: Neural Network
Stock/Index: BME BLACK MOUNTAIN ENERGY LTD
Time series to forecast n: 12 Mar 2023 for (n+4 weeks)

According to price forecasts for (n+4 weeks) 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 BLACK MOUNTAIN ENERGY LTD

1. IFRS 15, issued in May 2014, amended paragraphs 3.1.1, 4.2.1, 5.1.1, 5.2.1, 5.7.6, B3.2.13, B5.7.1, C5 and C42 and deleted paragraph C16 and its related heading. Paragraphs 5.1.3 and 5.7.1A, and a definition to Appendix A, were added. An entity shall apply those amendments when it applies IFRS 15.
2. An entity's business model refers to how an entity manages its financial assets in order to generate cash flows. That is, the entity's business model determines whether cash flows will result from collecting contractual cash flows, selling financial assets or both. Consequently, this assessment is not performed on the basis of scenarios that the entity does not reasonably expect to occur, such as so-called 'worst case' or 'stress case' scenarios. For example, if an entity expects that it will sell a particular portfolio of financial assets only in a stress case scenario, that scenario would not affect the entity's assessment of the business model for those assets if the entity reasonably expects that such a scenario will not occur. If cash flows are realised in a way that is different from the entity's expectations at the date that the entity assessed the business model (for example, if the entity sells more or fewer financial assets than it expected when it classified the assets), that does not give rise to a prior period error in the entity's financial statements (see IAS 8 Accounting Policies, Changes in Accounting Estimates and Errors) nor does it change the classification of the remaining financial assets held in that business model (ie those assets that the entity recognised in prior periods and still holds) as long as the entity considered all relevant information that was available at the time that it made the business model assessment.
3. 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.
4. The characteristics of the hedged item, including how and when the hedged item affects profit or loss, also affect the period over which the forward element of a forward contract that hedges a time-period related hedged item is amortised, which is over the period to which the forward element relates. For example, if a forward contract hedges the exposure to variability in threemonth interest rates for a three-month period that starts in six months' time, the forward element is amortised during the period that spans months seven to nine.

*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

BLACK MOUNTAIN ENERGY LTD is assigned short-term Ba1 & long-term Ba1 estimated rating. BLACK MOUNTAIN ENERGY LTD prediction model is evaluated with Multi-Task Learning (ML) and Lasso Regression1,2,3,4 and it is concluded that the BME stock is predictable in the short/long term. According to price forecasts for (n+4 weeks) period, the dominant strategy among neural network is: Sell

### BME BLACK MOUNTAIN ENERGY LTD Financial Analysis*

Rating Short-Term Long-Term Senior
Outlook*Ba1Ba1
Income StatementCaa2Baa2
Balance SheetCaa2Baa2
Leverage RatiosBaa2Ba3
Cash FlowBaa2Baa2
Rates of Return and ProfitabilityCaa2Baa2

*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: 89 out of 100 with 855 signals.

## References

1. Rosenbaum PR, Rubin DB. 1983. The central role of the propensity score in observational studies for causal effects. Biometrika 70:41–55
2. Knox SW. 2018. Machine Learning: A Concise Introduction. Hoboken, NJ: Wiley
3. Breiman L, Friedman J, Stone CJ, Olshen RA. 1984. Classification and Regression Trees. Boca Raton, FL: CRC Press
4. Farrell MH, Liang T, Misra S. 2018. Deep neural networks for estimation and inference: application to causal effects and other semiparametric estimands. arXiv:1809.09953 [econ.EM]
5. Ashley, R. (1983), "On the usefulness of macroeconomic forecasts as inputs to forecasting models," Journal of Forecasting, 2, 211–223.
6. Mikolov T, Yih W, Zweig G. 2013c. Linguistic regularities in continuous space word representations. In Pro- ceedings of the 2013 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pp. 746–51. New York: Assoc. Comput. Linguist.
7. Greene WH. 2000. Econometric Analysis. Upper Saddle River, N J: Prentice Hall. 4th ed.
Frequently Asked QuestionsQ: What is the prediction methodology for BME stock?
A: BME stock prediction methodology: We evaluate the prediction models Multi-Task Learning (ML) and Lasso Regression
Q: Is BME stock a buy or sell?
A: The dominant strategy among neural network is to Sell BME Stock.
Q: Is BLACK MOUNTAIN ENERGY LTD stock a good investment?
A: The consensus rating for BLACK MOUNTAIN ENERGY LTD is Sell and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of BME stock?
A: The consensus rating for BME is Sell.
Q: What is the prediction period for BME stock?
A: The prediction period for BME is (n+4 weeks)