OBE Obsidian Energy Ltd. Common Shares

Obsidian Energy Ltd. Common Shares Research Report

Summary

Stock market is basically nonlinear in nature and the research on stock market is one of the most important issues in recent years. People invest in stock market based on some prediction. For predict, the stock market prices people search such methods and tools which will increase their profits, while minimize their risks. Prediction plays a very important role in stock market business which is very complicated and challenging process. We evaluate Obsidian Energy Ltd. Common Shares prediction models with Modular Neural Network (Market News Sentiment Analysis) and Wilcoxon Sign-Rank Test^1,2,3,4 and conclude that the OBE stock is predictable in the short/long term. According to price forecasts for (n+3 month) period: The dominant strategy among neural network is to Sell OBE stock.

Key Points

1. Fundemental Analysis with Algorithmic Trading
2. What are buy sell or hold recommendations?
3. What are the most successful trading algorithms?

OBE Target Price Prediction Modeling Methodology

We consider Obsidian Energy Ltd. Common Shares Stock Decision Process with Modular Neural Network (Market News Sentiment Analysis) where A is the set of discrete actions of OBE 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= $\begin{array}{cccc}{p}_{\mathrm{a}1}& p_{\mathrm{a}2}& \dots & p_{1n}\\ & ⋮\\ p_{j1}& p_{j2}& \dots & p_{jn}\\ & ⋮\\ p_{k1}& p_{k2}& \dots & p_{kn}\\ & ⋮\\ p_{n1}& p_{n2}& \dots & p_{nn}\end{array}$ X R(Modular Neural Network (Market News Sentiment Analysis)) X S(n):→ (n+3 month) $\sum _{i=1}^n\left(r_i\right)$

n:Time series to forecast

p:Price signals of OBE 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?

OBE Stock Forecast (Buy or Sell) for (n+3 month)

Sample Set: Neural Network
Stock/Index: OBE Obsidian Energy Ltd. Common Shares
Time series to forecast n: 29 Nov 2022 for (n+3 month)

According to price forecasts for (n+3 month) period: The dominant strategy among neural network is to Sell OBE stock.

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 (Yellow to Green): *Technical Analysis%

Adjusted IFRS* Prediction Methods for Obsidian Energy Ltd. Common Shares

1. For the purpose of applying paragraph 6.5.11, at the point when an entity amends the description of a hedged item as required in paragraph 6.9.1(b), the amount accumulated in the cash flow hedge reserve shall be deemed to be based on the alternative benchmark rate on which the hedged future cash flows are determined.
2. For lifetime expected credit losses, an entity shall estimate the risk of a default occurring on the financial instrument during its expected life. 12-month expected credit losses are a portion of the lifetime expected credit losses and represent the lifetime cash shortfalls that will result if a default occurs in the 12 months after the reporting date (or a shorter period if the expected life of a financial instrument is less than 12 months), weighted by the probability of that default occurring. Thus, 12-month expected credit losses are neither the lifetime expected credit losses that an entity will incur on financial instruments that it predicts will default in the next 12 months nor the cash shortfalls that are predicted over the next 12 months.
3. When measuring hedge ineffectiveness, an entity shall consider the time value of money. Consequently, the entity determines the value of the hedged item on a present value basis and therefore the change in the value of the hedged item also includes the effect of the time value of money.
4. The assessment of whether lifetime expected credit losses should be recognised is based on significant increases in the likelihood or risk of a default occurring since initial recognition (irrespective of whether a financial instrument has been repriced to reflect an increase in credit risk) instead of on evidence of a financial asset being credit-impaired at the reporting date or an actual default occurring. Generally, there will be a significant increase in credit risk before a financial asset becomes credit-impaired or an actual default occurs.

*International Financial Reporting Standards (IFRS) are a set of accounting rules for the financial statements of public companies that are intended to make them consistent, transparent, and easily comparable around the world.

Conclusions

Obsidian Energy Ltd. Common Shares assigned short-term Ba3 & long-term B2 forecasted stock rating. We evaluate the prediction models Modular Neural Network (Market News Sentiment Analysis) with Wilcoxon Sign-Rank Test^1,2,3,4 and conclude that the OBE stock is predictable in the short/long term. According to price forecasts for (n+3 month) period: The dominant strategy among neural network is to Sell OBE stock.

Financial State Forecast for OBE Obsidian Energy Ltd. Common Shares Stock Options & Futures

Rating	Short-Term	Long-Term Senior
Outlook*	Ba3	B2
Operational Risk	83	38
Market Risk	81	61
Technical Analysis	45	46
Fundamental Analysis	39	51
Risk Unsystematic	76	62

Prediction Confidence Score

Trust metric by Neural Network: 89 out of 100 with 755 signals.

References

1. Gentzkow M, Kelly BT, Taddy M. 2017. Text as data. NBER Work. Pap. 23276
2. Abadie A, Imbens GW. 2011. Bias-corrected matching estimators for average treatment effects. J. Bus. Econ. Stat. 29:1–11
3. 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]
4. Burkov A. 2019. The Hundred-Page Machine Learning Book. Quebec City, Can.: Andriy Burkov
5. Alexander, J. C. Jr. (1995), "Refining the degree of earnings surprise: A comparison of statistical and analysts' forecasts," Financial Review, 30, 469–506.
6. H. Kushner and G. Yin. Stochastic approximation algorithms and applications. Springer, 1997.
7. L. Busoniu, R. Babuska, and B. D. Schutter. A comprehensive survey of multiagent reinforcement learning. IEEE Transactions of Systems, Man, and Cybernetics Part C: Applications and Reviews, 38(2), 2008.

Frequently Asked Questions

Q: What is the prediction methodology for OBE stock?
A: OBE stock prediction methodology: We evaluate the prediction models Modular Neural Network (Market News Sentiment Analysis) and Wilcoxon Sign-Rank Test
Q: Is OBE stock a buy or sell?
A: The dominant strategy among neural network is to Sell OBE Stock.
Q: Is Obsidian Energy Ltd. Common Shares stock a good investment?
A: The consensus rating for Obsidian Energy Ltd. Common Shares is Sell and assigned short-term Ba3 & long-term B2 forecasted stock rating.
Q: What is the consensus rating of OBE stock?
A: The consensus rating for OBE is Sell.
Q: What is the prediction period for OBE stock?
A: The prediction period for OBE is (n+3 month)

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