**Outlook:**ANEXO GROUP PLC is assigned short-term Ba1 & long-term Ba1 estimated rating.

**Dominant Strategy :**Hold

**Time series to forecast n: 28 Mar 2023**for (n+3 month)

**Methodology :**Statistical Inference (ML)

## Abstract

ANEXO GROUP PLC prediction model is evaluated with Statistical Inference (ML) and Multiple Regression^{1,2,3,4}and it is concluded that the LON:ANX stock is predictable in the short/long term.

**According to price forecasts for (n+3 month) period, the dominant strategy among neural network is: Hold**

## Key Points

- Short/Long Term Stocks
- Reaction Function
- Decision Making

## LON:ANX Target Price Prediction Modeling Methodology

We consider ANEXO GROUP PLC Decision Process with Statistical Inference (ML) where A is the set of discrete actions of LON:ANX 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(Multiple Regression)

^{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(Statistical Inference (ML)) X S(n):→ (n+3 month) $\overrightarrow{S}=\left({s}_{1},{s}_{2},{s}_{3}\right)$

n:Time series to forecast

p:Price signals of LON:ANX 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?

## LON:ANX Stock Forecast (Buy or Sell) for (n+3 month)

**Sample Set:**Neural Network

**Stock/Index:**LON:ANX ANEXO GROUP PLC

**Time series to forecast n: 28 Mar 2023**for (n+3 month)

**According to price forecasts for (n+3 month) 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 ANEXO GROUP PLC

- Paragraph 5.7.5 permits an entity to make an irrevocable election to present in other comprehensive income subsequent changes in the fair value of particular investments in equity instruments. Such an investment is not a monetary item. Accordingly, the gain or loss that is presented in other comprehensive income in accordance with paragraph 5.7.5 includes any related foreign exchange component.
- To the extent that a transfer of a financial asset does not qualify for derecognition, the transferee does not recognise the transferred asset as its asset. The transferee derecognises the cash or other consideration paid and recognises a receivable from the transferor. If the transferor has both a right and an obligation to reacquire control of the entire transferred asset for a fixed amount (such as under a repurchase agreement), the transferee may measure its receivable at amortised cost if it meets the criteria in paragraph 4.1.2.
- 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.
- In applying the effective interest method, an entity identifies fees that are an integral part of the effective interest rate of a financial instrument. The description of fees for financial services may not be indicative of the nature and substance of the services provided. Fees that are an integral part of the effective interest rate of a financial instrument are treated as an adjustment to the effective interest rate, unless the financial instrument is measured at fair value, with the change in fair value being recognised in profit or loss. In those cases, the fees are recognised as revenue or expense when the instrument is initially recognised.

*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

ANEXO GROUP PLC is assigned short-term Ba1 & long-term Ba1 estimated rating. ANEXO GROUP PLC prediction model is evaluated with Statistical Inference (ML) and Multiple Regression^{1,2,3,4} and it is concluded that the LON:ANX stock is predictable in the short/long term. ** According to price forecasts for (n+3 month) period, the dominant strategy among neural network is: Hold**

### LON:ANX ANEXO GROUP PLC Financial Analysis*

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

Outlook* | Ba1 | Ba1 |

Income Statement | B3 | C |

Balance Sheet | B1 | Baa2 |

Leverage Ratios | Baa2 | Baa2 |

Cash Flow | Baa2 | Caa2 |

Rates of Return and Profitability | C | 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

- N. B ̈auerle and J. Ott. Markov decision processes with average-value-at-risk criteria. Mathematical Methods of Operations Research, 74(3):361–379, 2011
- Candès E, Tao T. 2007. The Dantzig selector: statistical estimation when p is much larger than n. Ann. Stat. 35:2313–51
- Dietterich TG. 2000. Ensemble methods in machine learning. In Multiple Classifier Systems: First International Workshop, Cagliari, Italy, June 21–23, pp. 1–15. Berlin: Springer
- Allen, P. G. (1994), "Economic forecasting in agriculture," International Journal of Forecasting, 10, 81–135.
- Blei DM, Lafferty JD. 2009. Topic models. In Text Mining: Classification, Clustering, and Applications, ed. A Srivastava, M Sahami, pp. 101–24. Boca Raton, FL: CRC Press
- Belsley, D. A. (1988), "Modelling and forecast reliability," International Journal of Forecasting, 4, 427–447.
- E. van der Pol and F. A. Oliehoek. Coordinated deep reinforcement learners for traffic light control. NIPS Workshop on Learning, Inference and Control of Multi-Agent Systems, 2016.

## Frequently Asked Questions

Q: What is the prediction methodology for LON:ANX stock?A: LON:ANX stock prediction methodology: We evaluate the prediction models Statistical Inference (ML) and Multiple Regression

Q: Is LON:ANX stock a buy or sell?

A: The dominant strategy among neural network is to Hold LON:ANX Stock.

Q: Is ANEXO GROUP PLC stock a good investment?

A: The consensus rating for ANEXO GROUP PLC is Hold and is assigned short-term Ba1 & long-term Ba1 estimated rating.

Q: What is the consensus rating of LON:ANX stock?

A: The consensus rating for LON:ANX is Hold.

Q: What is the prediction period for LON:ANX stock?

A: The prediction period for LON:ANX is (n+3 month)