Outlook: Battalion Oil Corporation Common Stock is assigned short-term Ba1 & long-term Ba1 estimated rating.
Dominant Strategy : Hold
Time series to forecast n: 31 Jan 2023 for (n+8 weeks)
Methodology : Modular Neural Network (CNN Layer)

## Abstract

Battalion Oil Corporation Common Stock prediction model is evaluated with Modular Neural Network (CNN Layer) and Stepwise Regression1,2,3,4 and it is concluded that the BATL stock is predictable in the short/long term. According to price forecasts for (n+8 weeks) period, the dominant strategy among neural network is: Hold

## Key Points

1. How accurate is machine learning in stock market?
2. What is statistical models in machine learning?
3. Buy, Sell and Hold Signals

## BATL Target Price Prediction Modeling Methodology

We consider Battalion Oil Corporation Common Stock Decision Process with Modular Neural Network (CNN Layer) where A is the set of discrete actions of BATL 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(Stepwise 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(Modular Neural Network (CNN Layer)) X S(n):→ (n+8 weeks) $\stackrel{\to }{R}=\left({r}_{1},{r}_{2},{r}_{3}\right)$

n:Time series to forecast

p:Price signals of BATL 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?

## BATL Stock Forecast (Buy or Sell) for (n+8 weeks)

Sample Set: Neural Network
Stock/Index: BATL Battalion Oil Corporation Common Stock
Time series to forecast n: 31 Jan 2023 for (n+8 weeks)

According to price forecasts for (n+8 weeks) period, the dominant strategy among neural network is: Hold

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 Battalion Oil Corporation Common Stock

1. An entity shall assess separately whether each subgroup meets the requirements in paragraph 6.6.1 to be an eligible hedged item. If any subgroup fails to meet the requirements in paragraph 6.6.1, the entity shall discontinue hedge accounting prospectively for the hedging relationship in its entirety. An entity also shall apply the requirements in paragraphs 6.5.8 and 6.5.11 to account for ineffectiveness related to the hedging relationship in its entirety.
2. If the group of items does not have any offsetting risk positions (for example, a group of foreign currency expenses that affect different line items in the statement of profit or loss and other comprehensive income that are hedged for foreign currency risk) then the reclassified hedging instrument gains or losses shall be apportioned to the line items affected by the hedged items. This apportionment shall be done on a systematic and rational basis and shall not result in the grossing up of the net gains or losses arising from a single hedging instrument.
3. For the purpose of this Standard, reasonable and supportable information is that which is reasonably available at the reporting date without undue cost or effort, including information about past events, current conditions and forecasts of future economic conditions. Information that is available for financial reporting purposes is considered to be available without undue cost or effort.
4. For hedges other than hedges of foreign currency risk, when an entity designates a non-derivative financial asset or a non-derivative financial liability measured at fair value through profit or loss as a hedging instrument, it may only designate the non-derivative financial instrument in its entirety or a proportion of it.

*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

Battalion Oil Corporation Common Stock is assigned short-term Ba1 & long-term Ba1 estimated rating. Battalion Oil Corporation Common Stock prediction model is evaluated with Modular Neural Network (CNN Layer) and Stepwise Regression1,2,3,4 and it is concluded that the BATL stock is predictable in the short/long term. According to price forecasts for (n+8 weeks) period, the dominant strategy among neural network is: Hold

### BATL Battalion Oil Corporation Common Stock Financial Analysis*

Rating Short-Term Long-Term Senior
Outlook*Ba1Ba1
Income StatementBa3Ba3
Balance SheetBa1Baa2
Leverage RatiosB3B1
Cash FlowCBaa2
Rates of Return and ProfitabilityB1Baa2

*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: 78 out of 100 with 654 signals.

## References

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2. Breusch, T. S. A. R. Pagan (1979), "A simple test for heteroskedasticity and random coefficient variation," Econometrica, 47, 1287–1294.
3. Athey S. 2019. The impact of machine learning on economics. In The Economics of Artificial Intelligence: An Agenda, ed. AK Agrawal, J Gans, A Goldfarb. Chicago: Univ. Chicago Press. In press
4. Mazumder R, Hastie T, Tibshirani R. 2010. Spectral regularization algorithms for learning large incomplete matrices. J. Mach. Learn. Res. 11:2287–322
5. Wu X, Kumar V, Quinlan JR, Ghosh J, Yang Q, et al. 2008. Top 10 algorithms in data mining. Knowl. Inform. Syst. 14:1–37
6. J. Ott. A Markov decision model for a surveillance application and risk-sensitive Markov decision processes. PhD thesis, Karlsruhe Institute of Technology, 2010.
7. Bertsimas D, King A, Mazumder R. 2016. Best subset selection via a modern optimization lens. Ann. Stat. 44:813–52
Frequently Asked QuestionsQ: What is the prediction methodology for BATL stock?
A: BATL stock prediction methodology: We evaluate the prediction models Modular Neural Network (CNN Layer) and Stepwise Regression
Q: Is BATL stock a buy or sell?
A: The dominant strategy among neural network is to Hold BATL Stock.
Q: Is Battalion Oil Corporation Common Stock stock a good investment?
A: The consensus rating for Battalion Oil Corporation Common Stock is Hold and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of BATL stock?
A: The consensus rating for BATL is Hold.
Q: What is the prediction period for BATL stock?
A: The prediction period for BATL is (n+8 weeks)