LON:CCP CELTIC PLC

Outlook: CELTIC PLC is assigned short-term Ba1 & long-term Ba1 estimated rating.
Dominant Strategy : Hold
Time series to forecast n: 27 Apr 2023 for (n+3 month)
Methodology : Modular Neural Network (Emotional Trigger/Responses Analysis)

Abstract

CELTIC PLC prediction model is evaluated with Modular Neural Network (Emotional Trigger/Responses Analysis) and Logistic Regression^1,2,3,4 and it is concluded that the LON:CCP 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

1. Nash Equilibria
2. Operational Risk
3. Dominated Move

LON:CCP Target Price Prediction Modeling Methodology

We consider CELTIC PLC Decision Process with Modular Neural Network (Emotional Trigger/Responses Analysis) where A is the set of discrete actions of LON:CCP 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(Logistic Regression)^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 (Emotional Trigger/Responses Analysis)) X S(n):→ (n+3 month) $\sum _{i=1}^n\left(a_i\right)$

n:Time series to forecast

p:Price signals of LON:CCP 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:CCP Stock Forecast (Buy or Sell) for (n+3 month)

Sample Set: Neural Network
Stock/Index: LON:CCP CELTIC PLC
Time series to forecast n: 27 Apr 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 CELTIC PLC

1. The business model may be to hold assets to collect contractual cash flows even if the entity sells financial assets when there is an increase in the assets' credit risk. To determine whether there has been an increase in the assets' credit risk, the entity considers reasonable and supportable information, including forward looking information. Irrespective of their frequency and value, sales due to an increase in the assets' credit risk are not inconsistent with a business model whose objective is to hold financial assets to collect contractual cash flows because the credit quality of financial assets is relevant to the entity's ability to collect contractual cash flows. Credit risk management activities that are aimed at minimising potential credit losses due to credit deterioration are integral to such a business model. Selling a financial asset because it no longer meets the credit criteria specified in the entity's documented investment policy is an example of a sale that has occurred due to an increase in credit risk. However, in the absence of such a policy, the entity may demonstrate in other ways that the sale occurred due to an increase in credit risk.
2. If subsequently an entity reasonably expects that the alternative benchmark rate will not be separately identifiable within 24 months from the date the entity designated it as a non-contractually specified risk component for the first time, the entity shall cease applying the requirement in paragraph 6.9.11 to that alternative benchmark rate and discontinue hedge accounting prospectively from the date of that reassessment for all hedging relationships in which the alternative benchmark rate was designated as a noncontractually specified risk component.
3. If a component of the cash flows of a financial or a non-financial item is designated as the hedged item, that component must be less than or equal to the total cash flows of the entire item. However, all of the cash flows of the entire item may be designated as the hedged item and hedged for only one particular risk (for example, only for those changes that are attributable to changes in LIBOR or a benchmark commodity price).
4. However, depending on the nature of the financial instruments and the credit risk information available for particular groups of financial instruments, an entity may not be able to identify significant changes in credit risk for individual financial instruments before the financial instrument becomes past due. This may be the case for financial instruments such as retail loans for which there is little or no updated credit risk information that is routinely obtained and monitored on an individual instrument until a customer breaches the contractual terms. If changes in the credit risk for individual financial instruments are not captured before they become past due, a loss allowance based only on credit information at an individual financial instrument level would not faithfully represent the changes in credit risk since initial recognition.

*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

CELTIC PLC is assigned short-term Ba1 & long-term Ba1 estimated rating. CELTIC PLC prediction model is evaluated with Modular Neural Network (Emotional Trigger/Responses Analysis) and Logistic Regression^1,2,3,4 and it is concluded that the LON:CCP 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:CCP CELTIC PLC Financial Analysis*

Rating	Short-Term	Long-Term Senior
Outlook*	Ba1	Ba1
Income Statement	B3	C
Balance Sheet	Caa2	Baa2
Leverage Ratios	B2	Baa2
Cash Flow	Ba2	Baa2
Rates of Return and Profitability	Caa2	B1

*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: 93 out of 100 with 616 signals.

References

1. Banerjee, A., J. J. Dolado, J. W. Galbraith, D. F. Hendry (1993), Co-integration, Error-correction, and the Econometric Analysis of Non-stationary Data. Oxford: Oxford University Press.
2. Andrews, D. W. K. (1993), "Tests for parameter instability and structural change with unknown change point," Econometrica, 61, 821–856.
3. V. Mnih, A. P. Badia, M. Mirza, A. Graves, T. P. Lillicrap, T. Harley, D. Silver, and K. Kavukcuoglu. Asynchronous methods for deep reinforcement learning. In Proceedings of the 33nd International Conference on Machine Learning, ICML 2016, New York City, NY, USA, June 19-24, 2016, pages 1928–1937, 2016
4. R. Sutton, D. McAllester, S. Singh, and Y. Mansour. Policy gradient methods for reinforcement learning with function approximation. In Proceedings of Advances in Neural Information Processing Systems 12, pages 1057–1063, 2000
5. M. L. Littman. Friend-or-foe q-learning in general-sum games. In Proceedings of the Eighteenth International Conference on Machine Learning (ICML 2001), Williams College, Williamstown, MA, USA, June 28 - July 1, 2001, pages 322–328, 2001
6. Clements, M. P. D. F. Hendry (1997), "An empirical study of seasonal unit roots in forecasting," International Journal of Forecasting, 13, 341–355.
7. Bierens HJ. 1987. Kernel estimators of regression functions. In Advances in Econometrics: Fifth World Congress, Vol. 1, ed. TF Bewley, pp. 99–144. Cambridge, UK: Cambridge Univ. Press

Frequently Asked Questions

Q: What is the prediction methodology for LON:CCP stock?
A: LON:CCP stock prediction methodology: We evaluate the prediction models Modular Neural Network (Emotional Trigger/Responses Analysis) and Logistic Regression
Q: Is LON:CCP stock a buy or sell?
A: The dominant strategy among neural network is to Hold LON:CCP Stock.
Q: Is CELTIC PLC stock a good investment?
A: The consensus rating for CELTIC PLC is Hold and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of LON:CCP stock?
A: The consensus rating for LON:CCP is Hold.
Q: What is the prediction period for LON:CCP stock?
A: The prediction period for LON:CCP is (n+3 month)

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