CCNEP CNB Financial Corporation Depositary Shares each representing a 1/40th ownership interest in a share of 7.125% Series A Fixed-Rate Non-Cumulative Perpetual Preferred Stock

Outlook: CNB Financial Corporation Depositary Shares each representing a 1/40th ownership interest in a share of 7.125% Series A Fixed-Rate Non-Cumulative Perpetual Preferred Stock is assigned short-term Ba1 & long-term Ba1 estimated rating.
Dominant Strategy : Hold
Time series to forecast n: 31 May 2023 for (n+6 month)
Methodology : Modular Neural Network (Market Direction Analysis)

Abstract

CNB Financial Corporation Depositary Shares each representing a 1/40th ownership interest in a share of 7.125% Series A Fixed-Rate Non-Cumulative Perpetual Preferred Stock prediction model is evaluated with Modular Neural Network (Market Direction Analysis) and Linear Regression^1,2,3,4 and it is concluded that the CCNEP stock is predictable in the short/long term. According to price forecasts for (n+6 month) period, the dominant strategy among neural network is: Hold

Key Points

1. Trust metric by Neural Network
2. Game Theory
3. What is prediction model?

CCNEP Target Price Prediction Modeling Methodology

We consider CNB Financial Corporation Depositary Shares each representing a 1/40th ownership interest in a share of 7.125% Series A Fixed-Rate Non-Cumulative Perpetual Preferred Stock Decision Process with Modular Neural Network (Market Direction Analysis) where A is the set of discrete actions of CCNEP 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(Linear 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 (Market Direction Analysis)) X S(n):→ (n+6 month) $\sum _{i=1}^n\left(s_i\right)$

n:Time series to forecast

p:Price signals of CCNEP 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?

CCNEP Stock Forecast (Buy or Sell) for (n+6 month)

Sample Set: Neural Network
Stock/Index: CCNEP CNB Financial Corporation Depositary Shares each representing a 1/40th ownership interest in a share of 7.125% Series A Fixed-Rate Non-Cumulative Perpetual Preferred Stock
Time series to forecast n: 31 May 2023 for (n+6 month)

According to price forecasts for (n+6 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 CNB Financial Corporation Depositary Shares each representing a 1/40th ownership interest in a share of 7.125% Series A Fixed-Rate Non-Cumulative Perpetual Preferred Stock

1. Expected credit losses are a probability-weighted estimate of credit losses (ie the present value of all cash shortfalls) over the expected life of the financial instrument. A cash shortfall is the difference between the cash flows that are due to an entity in accordance with the contract and the cash flows that the entity expects to receive. Because expected credit losses consider the amount and timing of payments, a credit loss arises even if the entity expects to be paid in full but later than when contractually due.
2. IFRS 15, issued in May 2014, amended paragraphs 3.1.1, 4.2.1, 5.1.1, 5.2.1, 5.7.6, B3.2.13, B5.7.1, C5 and C42 and deleted paragraph C16 and its related heading. Paragraphs 5.1.3 and 5.7.1A, and a definition to Appendix A, were added. An entity shall apply those amendments when it applies IFRS 15.
3. In some circumstances, the renegotiation or modification of the contractual cash flows of a financial asset can lead to the derecognition of the existing financial asset in accordance with this Standard. When the modification of a financial asset results in the derecognition of the existing financial asset and the subsequent recognition of the modified financial asset, the modified asset is considered a 'new' financial asset for the purposes of this Standard.
4. If a financial asset contains a contractual term that could change the timing or amount of contractual cash flows (for example, if the asset can be prepaid before maturity or its term can be extended), the entity must determine whether the contractual cash flows that could arise over the life of the instrument due to that contractual term are solely payments of principal and interest on the principal amount outstanding. To make this determination, the entity must assess the contractual cash flows that could arise both before, and after, the change in contractual cash flows. The entity may also need to assess the nature of any contingent event (ie the trigger) that would change the timing or amount of the contractual cash flows. While the nature of the contingent event in itself is not a determinative factor in assessing whether the contractual cash flows are solely payments of principal and interest, it may be an indicator. For example, compare a financial instrument with an interest rate that is reset to a higher rate if the debtor misses a particular number of payments to a financial instrument with an interest rate that is reset to a higher rate if a specified equity index reaches a particular level. It is more likely in the former case that the contractual cash flows over the life of the instrument will be solely payments of principal and interest on the principal amount outstanding because of the relationship between missed payments and an increase in credit risk. (See also paragraph B4.1.18.)

*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

CNB Financial Corporation Depositary Shares each representing a 1/40th ownership interest in a share of 7.125% Series A Fixed-Rate Non-Cumulative Perpetual Preferred Stock is assigned short-term Ba1 & long-term Ba1 estimated rating. CNB Financial Corporation Depositary Shares each representing a 1/40th ownership interest in a share of 7.125% Series A Fixed-Rate Non-Cumulative Perpetual Preferred Stock prediction model is evaluated with Modular Neural Network (Market Direction Analysis) and Linear Regression^1,2,3,4 and it is concluded that the CCNEP stock is predictable in the short/long term. According to price forecasts for (n+6 month) period, the dominant strategy among neural network is: Hold

CCNEP CNB Financial Corporation Depositary Shares each representing a 1/40th ownership interest in a share of 7.125% Series A Fixed-Rate Non-Cumulative Perpetual Preferred Stock Financial Analysis*

Rating	Short-Term	Long-Term Senior
Outlook*	Ba1	Ba1
Income Statement	Ba3	Caa2
Balance Sheet	C	Caa2
Leverage Ratios	C	B2
Cash Flow	C	C
Rates of Return and Profitability	Baa2	Baa2

*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: 91 out of 100 with 858 signals.

References

1. Çetinkaya, A., Zhang, Y.Z., Hao, Y.M. and Ma, X.Y., When to Sell and When to Hold FTNT Stock. AC Investment Research Journal, 101(3).
2. B. Derfer, N. Goodyear, K. Hung, C. Matthews, G. Paoni, K. Rollins, R. Rose, M. Seaman, and J. Wiles. Online marketing platform, August 17 2007. US Patent App. 11/893,765
3. Mnih A, Kavukcuoglu K. 2013. Learning word embeddings efficiently with noise-contrastive estimation. In Advances in Neural Information Processing Systems, Vol. 26, ed. Z Ghahramani, M Welling, C Cortes, ND Lawrence, KQ Weinberger, pp. 2265–73. San Diego, CA: Neural Inf. Process. Syst. Found.
4. ZXhang, Y.X., Haxo, Y.M. and Mat, Y.X., 2023. The Dow Jones Industrial Average (No. Stock Analysis). AC Investment Research.
5. J. Baxter and P. Bartlett. Infinite-horizon policy-gradient estimation. Journal of Artificial Intelligence Re- search, 15:319–350, 2001.
6. ZXhang, Y.X., Haxo, Y.M. and Mat, Y.X., 2023. How is the price of gold determined? (No. Stock Analysis). AC Investment Research.
7. Tibshirani R. 1996. Regression shrinkage and selection via the lasso. J. R. Stat. Soc. B 58:267–88

Frequently Asked Questions

Q: What is the prediction methodology for CCNEP stock?
A: CCNEP stock prediction methodology: We evaluate the prediction models Modular Neural Network (Market Direction Analysis) and Linear Regression
Q: Is CCNEP stock a buy or sell?
A: The dominant strategy among neural network is to Hold CCNEP Stock.
Q: Is CNB Financial Corporation Depositary Shares each representing a 1/40th ownership interest in a share of 7.125% Series A Fixed-Rate Non-Cumulative Perpetual Preferred Stock stock a good investment?
A: The consensus rating for CNB Financial Corporation Depositary Shares each representing a 1/40th ownership interest in a share of 7.125% Series A Fixed-Rate Non-Cumulative Perpetual Preferred Stock is Hold and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of CCNEP stock?
A: The consensus rating for CCNEP is Hold.
Q: What is the prediction period for CCNEP stock?
A: The prediction period for CCNEP is (n+6 month)

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