**Outlook:**WOODSIDE ENERGY GROUP LTD assigned short-term Ba1 & long-term Ba1 estimated rating.

**Dominant Strategy :**Buy

**Time series to forecast n: 02 Jan 2023**for (n+1 year)

**Methodology :**Modular Neural Network (Speculative Sentiment Analysis)

## Abstract

In recent years there has been a significant growth of interest in the incorporation of historical series of variables related to stock prediction into mathematical models or computational algorithms in order to generate predictions or indications about expected price movements.(Naeini, M.P., Taremian, H. and Hashemi, H.B., 2010, October. Stock market value prediction using neural networks. In 2010 international conference on computer information systems and industrial management applications (CISIM) (pp. 132-136). IEEE.)** We evaluate WOODSIDE ENERGY GROUP LTD prediction models with Modular Neural Network (Speculative Sentiment Analysis) and Wilcoxon Sign-Rank Test ^{1,2,3,4} and conclude that the WDS stock is predictable in the short/long term. **

**According to price forecasts for (n+1 year) period, the dominant strategy among neural network is: Buy**

## Key Points

- Nash Equilibria
- Market Signals
- Market Risk

## WDS Target Price Prediction Modeling Methodology

We consider WOODSIDE ENERGY GROUP LTD Decision Process with Modular Neural Network (Speculative Sentiment Analysis) where A is the set of discrete actions of WDS 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}= $\begin{array}{cccc}{p}_{\mathrm{a}1}& {p}_{\mathrm{a}2}& \dots & {p}_{1n}\\ & \vdots \\ {p}_{j1}& {p}_{j2}& \dots & {p}_{jn}\\ & \vdots \\ {p}_{k1}& {p}_{k2}& \dots & {p}_{kn}\\ & \vdots \\ {p}_{n1}& {p}_{n2}& \dots & {p}_{nn}\end{array}$ X R(Modular Neural Network (Speculative Sentiment Analysis)) X S(n):→ (n+1 year) $R=\left(\begin{array}{ccc}1& 0& 0\\ 0& 1& 0\\ 0& 0& 1\end{array}\right)$

n:Time series to forecast

p:Price signals of WDS 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?

## WDS Stock Forecast (Buy or Sell) for (n+1 year)

**Sample Set:**Neural Network

**Stock/Index:**WDS WOODSIDE ENERGY GROUP LTD

**Time series to forecast n: 02 Jan 2023**for (n+1 year)

**According to price forecasts for (n+1 year) period, the dominant strategy among neural network is: Buy**

**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 WOODSIDE ENERGY GROUP LTD

- When rebalancing a hedging relationship, an entity shall update its analysis of the sources of hedge ineffectiveness that are expected to affect the hedging relationship during its (remaining) term (see paragraph B6.4.2). The documentation of the hedging relationship shall be updated accordingly.
- Paragraphs 6.9.7–6.9.13 provide exceptions to the requirements specified in those paragraphs only. An entity shall apply all other hedge accounting requirements in this Standard, including the qualifying criteria in paragraph 6.4.1, to hedging relationships that were directly affected by interest rate benchmark reform.
- An entity can also designate only changes in the cash flows or fair value of a hedged item above or below a specified price or other variable (a 'one-sided risk'). The intrinsic value of a purchased option hedging instrument (assuming that it has the same principal terms as the designated risk), but not its time value, reflects a one-sided risk in a hedged item. For example, an entity can designate the variability of future cash flow outcomes resulting from a price increase of a forecast commodity purchase. In such a situation, the entity designates only cash flow losses that result from an increase in the price above the specified level. The hedged risk does not include the time value of a purchased option, because the time value is not a component of the forecast transaction that affects profit or loss.
- For the purpose of determining whether a forecast transaction (or a component thereof) is highly probable as required by paragraph 6.3.3, an entity shall assume that the interest rate benchmark on which the hedged cash flows (contractually or non-contractually specified) are based is not altered as a result of interest rate benchmark reform.

*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

WOODSIDE ENERGY GROUP LTD assigned short-term Ba1 & long-term Ba1 estimated rating.** We evaluate the prediction models Modular Neural Network (Speculative Sentiment Analysis) with Wilcoxon Sign-Rank Test ^{1,2,3,4} and conclude that the WDS stock is predictable in the short/long term.**

**According to price forecasts for (n+1 year) period, the dominant strategy among neural network is: Buy**

### WDS WOODSIDE ENERGY GROUP LTD Financial Analysis*

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

Outlook* | Ba1 | Ba1 |

Income Statement | Caa2 | Baa2 |

Balance Sheet | C | Caa2 |

Leverage Ratios | Baa2 | Baa2 |

Cash Flow | Baa2 | B2 |

Rates of Return and Profitability | B1 | C |

*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

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- Imbens GW, Lemieux T. 2008. Regression discontinuity designs: a guide to practice. J. Econom. 142:615–35
- Candès E, Tao T. 2007. The Dantzig selector: statistical estimation when p is much larger than n. Ann. Stat. 35:2313–51
- Allen, P. G. (1994), "Economic forecasting in agriculture," International Journal of Forecasting, 10, 81–135.
- Imai K, Ratkovic M. 2013. Estimating treatment effect heterogeneity in randomized program evaluation. Ann. Appl. Stat. 7:443–70
- Belsley, D. A. (1988), "Modelling and forecast reliability," International Journal of Forecasting, 4, 427–447.
- V. Borkar. A sensitivity formula for the risk-sensitive cost and the actor-critic algorithm. Systems & Control Letters, 44:339–346, 2001

## Frequently Asked Questions

Q: What is the prediction methodology for WDS stock?A: WDS stock prediction methodology: We evaluate the prediction models Modular Neural Network (Speculative Sentiment Analysis) and Wilcoxon Sign-Rank Test

Q: Is WDS stock a buy or sell?

A: The dominant strategy among neural network is to Buy WDS Stock.

Q: Is WOODSIDE ENERGY GROUP LTD stock a good investment?

A: The consensus rating for WOODSIDE ENERGY GROUP LTD is Buy and assigned short-term Ba1 & long-term Ba1 estimated rating.

Q: What is the consensus rating of WDS stock?

A: The consensus rating for WDS is Buy.

Q: What is the prediction period for WDS stock?

A: The prediction period for WDS is (n+1 year)