AGM^E Federal Agricultural Mortgage Corporation 5.750% Non-Cumulative Preferred Stock Series E

Outlook: Federal Agricultural Mortgage Corporation 5.750% Non-Cumulative Preferred Stock Series E is assigned short-term Ba1 & long-term Ba1 estimated rating.
Dominant Strategy : Buy
Time series to forecast n: 25 Mar 2023 for (n+1 year)
Methodology : Modular Neural Network (CNN Layer)

Abstract

Federal Agricultural Mortgage Corporation 5.750% Non-Cumulative Preferred Stock Series E prediction model is evaluated with Modular Neural Network (CNN Layer) and Wilcoxon Sign-Rank Test^1,2,3,4 and it is concluded that the AGM^E stock is predictable in the short/long term. According to price forecasts for (n+1 year) period, the dominant strategy among neural network is: Buy

Key Points

1. What are the most successful trading algorithms?
2. What are main components of Markov decision process?
3. Nash Equilibria

AGM^E Target Price Prediction Modeling Methodology

We consider Federal Agricultural Mortgage Corporation 5.750% Non-Cumulative Preferred Stock Series E Decision Process with Modular Neural Network (CNN Layer) where A is the set of discrete actions of AGM^E 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 Sign-Rank Test)^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 (CNN Layer)) X S(n):→ (n+1 year) $\sum _{i=1}^n\left(s_i\right)$

n:Time series to forecast

p:Price signals of AGM^E 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?

AGM^E Stock Forecast (Buy or Sell) for (n+1 year)

Sample Set: Neural Network
Stock/Index: AGM^E Federal Agricultural Mortgage Corporation 5.750% Non-Cumulative Preferred Stock Series E
Time series to forecast n: 25 Mar 2023 for (n+1 year)

According to price forecasts for (n+1 year) 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 Federal Agricultural Mortgage Corporation 5.750% Non-Cumulative Preferred Stock Series E

1. 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.
2. An entity may retain the right to a part of the interest payments on transferred assets as compensation for servicing those assets. The part of the interest payments that the entity would give up upon termination or transfer of the servicing contract is allocated to the servicing asset or servicing liability. The part of the interest payments that the entity would not give up is an interest-only strip receivable. For example, if the entity would not give up any interest upon termination or transfer of the servicing contract, the entire interest spread is an interest-only strip receivable. For the purposes of applying paragraph 3.2.13, the fair values of the servicing asset and interest-only strip receivable are used to allocate the carrying amount of the receivable between the part of the asset that is derecognised and the part that continues to be recognised. If there is no servicing fee specified or the fee to be received is not expected to compensate the entity adequately for performing the servicing, a liability for the servicing obligation is recognised at fair value.
3. Paragraph 5.7.5 permits an entity to make an irrevocable election to present in other comprehensive income changes in the fair value of an investment in an equity instrument that is not held for trading. This election is made on an instrument-by-instrument (ie share-by-share) basis. Amounts presented in other comprehensive income shall not be subsequently transferred to profit or loss. However, the entity may transfer the cumulative gain or loss within equity. Dividends on such investments are recognised in profit or loss in accordance with paragraph 5.7.6 unless the dividend clearly represents a recovery of part of the cost of the investment.
4. If a put option written by an entity prevents a transferred asset from being derecognised and the entity measures the transferred asset at fair value, the associated liability is measured at the option exercise price plus the time value of the option. The measurement of the asset at fair value is limited to the lower of the fair value and the option exercise price because the entity has no right to increases in the fair value of the transferred asset above the exercise price of the option. This ensures that the net carrying amount of the asset and the associated liability is the fair value of the put option obligation. For example, if the fair value of the underlying asset is CU120, the option exercise price is CU100 and the time value of the option is CU5, the carrying amount of the associated liability is CU105 (CU100 + CU5) and the carrying amount of the asset is CU100 (in this case the option exercise price).

*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

Federal Agricultural Mortgage Corporation 5.750% Non-Cumulative Preferred Stock Series E is assigned short-term Ba1 & long-term Ba1 estimated rating. Federal Agricultural Mortgage Corporation 5.750% Non-Cumulative Preferred Stock Series E prediction model is evaluated with Modular Neural Network (CNN Layer) and Wilcoxon Sign-Rank Test^1,2,3,4 and it is concluded that the AGM^E stock is predictable in the short/long term. According to price forecasts for (n+1 year) period, the dominant strategy among neural network is: Buy

AGM^E Federal Agricultural Mortgage Corporation 5.750% Non-Cumulative Preferred Stock Series E Financial Analysis*

Rating	Short-Term	Long-Term Senior
Outlook*	Ba1	Ba1
Income Statement	C	Caa2
Balance Sheet	B1	Ba3
Leverage Ratios	Baa2	Ba2
Cash Flow	C	B1
Rates of Return and Profitability	Baa2	B2

*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: 85 out of 100 with 490 signals.

References

1. Keane MP. 2013. Panel data discrete choice models of consumer demand. In The Oxford Handbook of Panel Data, ed. BH Baltagi, pp. 54–102. Oxford, UK: Oxford Univ. Press
2. Bennett J, Lanning S. 2007. The Netflix prize. In Proceedings of KDD Cup and Workshop 2007, p. 35. New York: ACM
3. Angrist JD, Pischke JS. 2008. Mostly Harmless Econometrics: An Empiricist's Companion. Princeton, NJ: Princeton Univ. Press
4. Doudchenko N, Imbens GW. 2016. Balancing, regression, difference-in-differences and synthetic control methods: a synthesis. NBER Work. Pap. 22791
5. G. Theocharous and A. Hallak. Lifetime value marketing using reinforcement learning. RLDM 2013, page 19, 2013
6. R. Rockafellar and S. Uryasev. Conditional value-at-risk for general loss distributions. Journal of Banking and Finance, 26(7):1443 – 1471, 2002
7. Canova, F. B. E. Hansen (1995), "Are seasonal patterns constant over time? A test for seasonal stability," Journal of Business and Economic Statistics, 13, 237–252.

Frequently Asked Questions

Q: What is the prediction methodology for AGM^E stock?
A: AGM^E stock prediction methodology: We evaluate the prediction models Modular Neural Network (CNN Layer) and Wilcoxon Sign-Rank Test
Q: Is AGM^E stock a buy or sell?
A: The dominant strategy among neural network is to Buy AGM^E Stock.
Q: Is Federal Agricultural Mortgage Corporation 5.750% Non-Cumulative Preferred Stock Series E stock a good investment?
A: The consensus rating for Federal Agricultural Mortgage Corporation 5.750% Non-Cumulative Preferred Stock Series E is Buy and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of AGM^E stock?
A: The consensus rating for AGM^E is Buy.
Q: What is the prediction period for AGM^E stock?
A: The prediction period for AGM^E is (n+1 year)

Premium

• Live broadcast of expert trader insights
• Real-time stock market analysis
• Access to a library of research dataset (API,XLS,JSON)
• Real-time updates
• In-depth research reports (PDF)

Login