AFGC American Financial Group Inc. 5.125% Subordinated Debentures due 2059

Outlook: American Financial Group Inc. 5.125% Subordinated Debentures due 2059 is assigned short-term Ba1 & long-term Ba1 estimated rating.
Dominant Strategy : Hold
Time series to forecast n: 28 Jan 2023 for (n+8 weeks)
Methodology : Modular Neural Network (Market Direction Analysis)

Abstract

American Financial Group Inc. 5.125% Subordinated Debentures due 2059 prediction model is evaluated with Modular Neural Network (Market Direction Analysis) and Linear Regression^1,2,3,4 and it is concluded that the AFGC stock is predictable in the short/long term. According to price forecasts for (n+8 weeks) period, the dominant strategy among neural network is: Hold

Key Points

1. Nash Equilibria
2. How do you pick a stock?
3. Is now good time to invest?

AFGC Target Price Prediction Modeling Methodology

We consider American Financial Group Inc. 5.125% Subordinated Debentures due 2059 Decision Process with Modular Neural Network (Market Direction Analysis) where A is the set of discrete actions of AFGC 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+8 weeks) $\overrightarrow{S}=\left(s_1,s_2,s_3\right)$

n:Time series to forecast

p:Price signals of AFGC 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?

AFGC Stock Forecast (Buy or Sell) for (n+8 weeks)

Sample Set: Neural Network
Stock/Index: AFGC American Financial Group Inc. 5.125% Subordinated Debentures due 2059
Time series to forecast n: 28 Jan 2023 for (n+8 weeks)

According to price forecasts for (n+8 weeks) 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 American Financial Group Inc. 5.125% Subordinated Debentures due 2059

1. An entity has not retained control of a transferred asset if the transferee has the practical ability to sell the transferred asset. An entity has retained control of a transferred asset if the transferee does not have the practical ability to sell the transferred asset. A transferee has the practical ability to sell the transferred asset if it is traded in an active market because the transferee could repurchase the transferred asset in the market if it needs to return the asset to the entity. For example, a transferee may have the practical ability to sell a transferred asset if the transferred asset is subject to an option that allows the entity to repurchase it, but the transferee can readily obtain the transferred asset in the market if the option is exercised. A transferee does not have the practical ability to sell the transferred asset if the entity retains such an option and the transferee cannot readily obtain the transferred asset in the market if the entity exercises its option
2. An entity is not required to restate prior periods to reflect the application of these amendments. The entity may restate prior periods only if it is possible to do so without the use of hindsight. If an entity restates prior periods, the restated financial statements must reflect all the requirements in this Standard for the affected financial instruments. If an entity does not restate prior periods, the entity shall recognise any difference between the previous carrying amount and the carrying amount at the beginning of the annual reporting period that includes the date of initial application of these amendments in the opening retained earnings (or other component of equity, as appropriate) of the annual reporting period that includes the date of initial application of these amendments.
3. An example of a fair value hedge is a hedge of exposure to changes in the fair value of a fixed-rate debt instrument arising from changes in interest rates. Such a hedge could be entered into by the issuer or by the holder.
4. It would not be acceptable to designate only some of the financial assets and financial liabilities giving rise to the inconsistency as at fair value through profit or loss if to do so would not eliminate or significantly reduce the inconsistency and would therefore not result in more relevant information. However, it would be acceptable to designate only some of a number of similar financial assets or similar financial liabilities if doing so achieves a significant reduction (and possibly a greater reduction than other allowable designations) in the inconsistency. For example, assume an entity has a number of similar financial liabilities that sum to CU100 and a number of similar financial assets that sum to CU50 but are measured on a different basis. The entity may significantly reduce the measurement inconsistency by designating at initial recognition all of the assets but only some of the liabilities (for example, individual liabilities with a combined total of CU45) as at fair value through profit or loss. However, because designation as at fair value through profit or loss can be applied only to the whole of a financial instrument, the entity in this example must designate one or more liabilities in their entirety. It could not designate either a component of a liability (eg changes in value attributable to only one risk, such as changes in a benchmark interest rate) or a proportion (ie percentage) of a liability.

*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

American Financial Group Inc. 5.125% Subordinated Debentures due 2059 is assigned short-term Ba1 & long-term Ba1 estimated rating. American Financial Group Inc. 5.125% Subordinated Debentures due 2059 prediction model is evaluated with Modular Neural Network (Market Direction Analysis) and Linear Regression^1,2,3,4 and it is concluded that the AFGC stock is predictable in the short/long term. According to price forecasts for (n+8 weeks) period, the dominant strategy among neural network is: Hold

AFGC American Financial Group Inc. 5.125% Subordinated Debentures due 2059 Financial Analysis*

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

*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: 88 out of 100 with 487 signals.

References

1. H. Kushner and G. Yin. Stochastic approximation algorithms and applications. Springer, 1997.
2. Dimakopoulou M, Zhou Z, Athey S, Imbens G. 2018. Balanced linear contextual bandits. arXiv:1812.06227 [cs.LG]
3. Çetinkaya, A., Zhang, Y.Z., Hao, Y.M. and Ma, X.Y., Is DOW Stock Expected to Go Up?(Stock Forecast). AC Investment Research Journal, 101(3).
4. P. Milgrom and I. Segal. Envelope theorems for arbitrary choice sets. Econometrica, 70(2):583–601, 2002
5. G. Shani, R. Brafman, and D. Heckerman. An MDP-based recommender system. In Proceedings of the Eigh- teenth conference on Uncertainty in artificial intelligence, pages 453–460. Morgan Kaufmann Publishers Inc., 2002
6. Breusch, T. S. (1978), "Testing for autocorrelation in dynamic linear models," Australian Economic Papers, 17, 334–355.
7. Hastie T, Tibshirani R, Tibshirani RJ. 2017. Extended comparisons of best subset selection, forward stepwise selection, and the lasso. arXiv:1707.08692 [stat.ME]

Frequently Asked Questions

Q: What is the prediction methodology for AFGC stock?
A: AFGC stock prediction methodology: We evaluate the prediction models Modular Neural Network (Market Direction Analysis) and Linear Regression
Q: Is AFGC stock a buy or sell?
A: The dominant strategy among neural network is to Hold AFGC Stock.
Q: Is American Financial Group Inc. 5.125% Subordinated Debentures due 2059 stock a good investment?
A: The consensus rating for American Financial Group Inc. 5.125% Subordinated Debentures due 2059 is Hold and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of AFGC stock?
A: The consensus rating for AFGC is Hold.
Q: What is the prediction period for AFGC stock?
A: The prediction period for AFGC is (n+8 weeks)

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