**Outlook:**CASTELNAU GROUP LIMITED is assigned short-term Ba1 & long-term Ba1 estimated rating.

**Dominant Strategy :**Buy

**Time series to forecast n: 09 Jun 2023**for 4 Weeks

**Methodology :**Modular Neural Network (DNN Layer)

## Abstract

CASTELNAU GROUP LIMITED prediction model is evaluated with Modular Neural Network (DNN Layer) and Wilcoxon Rank-Sum Test^{1,2,3,4}and it is concluded that the LON:CGL stock is predictable in the short/long term. In a modular neural network (MNN), a DNN layer is a type of module that is used to learn complex relationships between input and output data. DNN layers are made up of a series of artificial neurons, which are connected to each other by weighted edges. The weights of the edges are adjusted during training to minimize the error between the network's predictions and the desired output. DNN layers are used in a variety of MNN applications, including natural language processing, speech recognition, and machine translation. In natural language processing, DNN layers are used to extract features from text data, such as the sentiment of a sentence or the topic of a conversation. In speech recognition, DNN layers are used to convert audio data into text data. In machine translation, DNN layers are used to translate text from one language to another.

**According to price forecasts for 4 Weeks period, the dominant strategy among neural network is: Buy**

## Key Points

- What is the use of Markov decision process?
- Can machine learning predict?
- Game Theory

## LON:CGL Target Price Prediction Modeling Methodology

We consider CASTELNAU GROUP LIMITED Decision Process with Modular Neural Network (DNN Layer) where A is the set of discrete actions of LON:CGL 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 Rank-Sum 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 (DNN Layer)) X S(n):→ 4 Weeks $R=\left(\begin{array}{ccc}1& 0& 0\\ 0& 1& 0\\ 0& 0& 1\end{array}\right)$

n:Time series to forecast

p:Price signals of LON:CGL stock

j:Nash equilibria (Neural Network)

k:Dominated move

a:Best response for target price

### Modular Neural Network (DNN Layer)

In a modular neural network (MNN), a DNN layer is a type of module that is used to learn complex relationships between input and output data. DNN layers are made up of a series of artificial neurons, which are connected to each other by weighted edges. The weights of the edges are adjusted during training to minimize the error between the network's predictions and the desired output. DNN layers are used in a variety of MNN applications, including natural language processing, speech recognition, and machine translation. In natural language processing, DNN layers are used to extract features from text data, such as the sentiment of a sentence or the topic of a conversation. In speech recognition, DNN layers are used to convert audio data into text data. In machine translation, DNN layers are used to translate text from one language to another.### Wilcoxon Rank-Sum Test

The Wilcoxon rank-sum test, also known as the Mann-Whitney U test, is a non-parametric test that is used to compare the medians of two independent samples. It is a rank-based test, which means that it does not assume that the data is normally distributed. The Wilcoxon rank-sum test is calculated by first ranking the data from both samples, and then finding the sum of the ranks for one of the samples. The Wilcoxon rank-sum test statistic is then calculated by subtracting the sum of the ranks for one sample from the sum of the ranks for the other sample. The p-value for the Wilcoxon rank-sum test is calculated using a table of critical values. The p-value is the probability of obtaining a test statistic at least as extreme as the one observed, assuming that the null hypothesis is true.

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:CGL Stock Forecast (Buy or Sell) for 4 Weeks

**Sample Set:**Neural Network

**Stock/Index:**LON:CGL CASTELNAU GROUP LIMITED

**Time series to forecast n: 09 Jun 2023**for 4 Weeks

**According to price forecasts for 4 Weeks 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 CASTELNAU GROUP LIMITED

- An entity shall apply the impairment requirements in Section 5.5 retrospectively in accordance with IAS 8 subject to paragraphs 7.2.15 and 7.2.18–7.2.20.
- 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.
- For some types of fair value hedges, the objective of the hedge is not primarily to offset the fair value change of the hedged item but instead to transform the cash flows of the hedged item. For example, an entity hedges the fair value interest rate risk of a fixed-rate debt instrument using an interest rate swap. The entity's hedge objective is to transform the fixed-interest cash flows into floating interest cash flows. This objective is reflected in the accounting for the hedging relationship by accruing the net interest accrual on the interest rate swap in profit or loss. In the case of a hedge of a net position (for example, a net position of a fixed-rate asset and a fixed-rate liability), this net interest accrual must be presented in a separate line item in the statement of profit or loss and other comprehensive income. This is to avoid the grossing up of a single instrument's net gains or losses into offsetting gross amounts and recognising them in different line items (for example, this avoids grossing up a net interest receipt on a single interest rate swap into gross interest revenue and gross interest expense).
- If items are hedged together as a group in a cash flow hedge, they might affect different line items in the statement of profit or loss and other comprehensive income. The presentation of hedging gains or losses in that statement depends on the group of items

*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

CASTELNAU GROUP LIMITED is assigned short-term Ba1 & long-term Ba1 estimated rating. CASTELNAU GROUP LIMITED prediction model is evaluated with Modular Neural Network (DNN Layer) and Wilcoxon Rank-Sum Test^{1,2,3,4} and it is concluded that the LON:CGL stock is predictable in the short/long term. ** According to price forecasts for 4 Weeks period, the dominant strategy among neural network is: Buy**

### LON:CGL CASTELNAU GROUP LIMITED Financial Analysis*

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

Outlook* | Ba1 | Ba1 |

Income Statement | B2 | Baa2 |

Balance Sheet | Caa2 | B2 |

Leverage Ratios | Baa2 | C |

Cash Flow | Baa2 | Baa2 |

Rates of Return and Profitability | B2 | Ba3 |

*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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- Künzel S, Sekhon J, Bickel P, Yu B. 2017. Meta-learners for estimating heterogeneous treatment effects using machine learning. arXiv:1706.03461 [math.ST]
- S. Bhatnagar, H. Prasad, and L. Prashanth. Stochastic recursive algorithms for optimization, volume 434. Springer, 2013
- M. L. Littman. Markov games as a framework for multi-agent reinforcement learning. In Ma- chine Learning, Proceedings of the Eleventh International Conference, Rutgers University, New Brunswick, NJ, USA, July 10-13, 1994, pages 157–163, 1994
- V. Borkar. Stochastic approximation: a dynamical systems viewpoint. Cambridge University Press, 2008
- R. Sutton and A. Barto. Introduction to reinforcement learning. MIT Press, 1998
- J. Z. Leibo, V. Zambaldi, M. Lanctot, J. Marecki, and T. Graepel. Multi-agent Reinforcement Learning in Sequential Social Dilemmas. In Proceedings of the 16th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2017), Sao Paulo, Brazil, 2017

## Frequently Asked Questions

Q: What is the prediction methodology for LON:CGL stock?A: LON:CGL stock prediction methodology: We evaluate the prediction models Modular Neural Network (DNN Layer) and Wilcoxon Rank-Sum Test

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

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

Q: Is CASTELNAU GROUP LIMITED stock a good investment?

A: The consensus rating for CASTELNAU GROUP LIMITED is Buy and is assigned short-term Ba1 & long-term Ba1 estimated rating.

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

A: The consensus rating for LON:CGL is Buy.

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

A: The prediction period for LON:CGL is 4 Weeks

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