Is AGNCO Stock Expected to Go Up?

Outlook: AGNC Investment Corp. Depositary Shares each representing a 1/1000th interest in a share of 6.50% Series E Fixed-to-Floating Cumulative Redeemable Preferred Stock is assigned short-term B1 & long-term B1 estimated rating.
AUC Score : What is AUC Score?
Short-Term Revised¹ :
Dominant Strategy : Hold
Time series to forecast n: for Weeks²
Methodology : Supervised Machine Learning (ML)
Hypothesis Testing : Wilcoxon Rank-Sum Test
Surveillance : Major exchange and OTC

¹The accuracy of the model is being monitored on a regular basis.(15-minute period)

²Time series is updated based on short-term trends.

Summary

AGNC Investment Corp. Depositary Shares each representing a 1/1000th interest in a share of 6.50% Series E Fixed-to-Floating Cumulative Redeemable Preferred Stock prediction model is evaluated with Supervised Machine Learning (ML) and Wilcoxon Rank-Sum Test^1,2,3,4 and it is concluded that the AGNCO stock is predictable in the short/long term. Supervised machine learning (ML) is a type of machine learning where a model is trained on labeled data. This means that the data has been tagged with the correct output for the input data. The model learns to predict the output for new input data based on the labeled data. Supervised ML is a powerful tool that can be used for a variety of tasks, including classification, regression, and forecasting. Classification tasks involve predicting the category of an input data, such as whether an email is spam or not. Regression tasks involve predicting a numerical value for an input data, such as the price of a house. Forecasting tasks involve predicting future values for a time series, such as the sales of a product. According to price forecasts for 16 Weeks period, the dominant strategy among neural network is: Hold

Key Points

1. Can machine learning predict?
2. Market Outlook
3. What is a prediction confidence?

AGNCO Target Price Prediction Modeling Methodology

We consider AGNC Investment Corp. Depositary Shares each representing a 1/1000th interest in a share of 6.50% Series E Fixed-to-Floating Cumulative Redeemable Preferred Stock Decision Process with Supervised Machine Learning (ML) where A is the set of discrete actions of AGNCO 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= $\begin{array}{cccc}{p}_{\mathrm{a}1}& p_{\mathrm{a}2}& \dots & p_{1n}\\ & ⋮\\ p_{j1}& p_{j2}& \dots & p_{jn}\\ & ⋮\\ p_{k1}& p_{k2}& \dots & p_{kn}\\ & ⋮\\ p_{n1}& p_{n2}& \dots & p_{nn}\end{array}$ X R(Supervised Machine Learning (ML)) X S(n):→ 16 Weeks $\sum _{i=1}^n\left(s_i\right)$

n:Time series to forecast

p:Price signals of AGNCO stock

j:Nash equilibria (Neural Network)

k:Dominated move

a:Best response for target price

Supervised Machine Learning (ML)

Supervised machine learning (ML) is a type of machine learning where a model is trained on labeled data. This means that the data has been tagged with the correct output for the input data. The model learns to predict the output for new input data based on the labeled data. Supervised ML is a powerful tool that can be used for a variety of tasks, including classification, regression, and forecasting. Classification tasks involve predicting the category of an input data, such as whether an email is spam or not. Regression tasks involve predicting a numerical value for an input data, such as the price of a house. Forecasting tasks involve predicting future values for a time series, such as the sales of a product.

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?

AGNCO Stock Forecast (Buy or Sell)

Sample Set: Neural Network
Stock/Index: AGNCO AGNC Investment Corp. Depositary Shares each representing a 1/1000th interest in a share of 6.50% Series E Fixed-to-Floating Cumulative Redeemable Preferred Stock
Time series to forecast: 16 Weeks

According to price forecasts, the dominant strategy among neural network is: Hold

Strategic Interaction Table Legend:

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%

Financial Data Adjustments for Supervised Machine Learning (ML) based AGNCO Stock Prediction Model

1. Interest Rate Benchmark Reform, which amended IFRS 9, IAS 39 and IFRS 7, issued in September 2019, added Section 6.8 and amended paragraph 7.2.26. An entity shall apply these amendments for annual periods beginning on or after 1 January 2020. Earlier application is permitted. If an entity applies these amendments for an earlier period, it shall disclose that fact.
2. For the purposes of applying the requirements in paragraphs 5.7.7 and 5.7.8, an accounting mismatch is not caused solely by the measurement method that an entity uses to determine the effects of changes in a liability's credit risk. An accounting mismatch in profit or loss would arise only when the effects of changes in the liability's credit risk (as defined in IFRS 7) are expected to be offset by changes in the fair value of another financial instrument. A mismatch that arises solely as a result of the measurement method (ie because an entity does not isolate changes in a liability's credit risk from some other changes in its fair value) does not affect the determination required by paragraphs 5.7.7 and 5.7.8. For example, an entity may not isolate changes in a liability's credit risk from changes in liquidity risk. If the entity presents the combined effect of both factors in other comprehensive income, a mismatch may occur because changes in liquidity risk may be included in the fair value measurement of the entity's financial assets and the entire fair value change of those assets is presented in profit or loss. However, such a mismatch is caused by measurement imprecision, not the offsetting relationship described in paragraph B5.7.6 and, therefore, does not affect the determination required by paragraphs 5.7.7 and 5.7.8.
3. For example, Entity A, whose functional currency is its local currency, has a firm commitment to pay FC150,000 for advertising expenses in nine months' time and a firm commitment to sell finished goods for FC150,000 in 15 months' time. Entity A enters into a foreign currency derivative that settles in nine months' time under which it receives FC100 and pays CU70. Entity A has no other exposures to FC. Entity A does not manage foreign currency risk on a net basis. Hence, Entity A cannot apply hedge accounting for a hedging relationship between the foreign currency derivative and a net position of FC100 (consisting of FC150,000 of the firm purchase commitment—ie advertising services—and FC149,900 (of the FC150,000) of the firm sale commitment) for a nine-month period.
4. The assessment of whether lifetime expected credit losses should be recognised is based on significant increases in the likelihood or risk of a default occurring since initial recognition (irrespective of whether a financial instrument has been repriced to reflect an increase in credit risk) instead of on evidence of a financial asset being credit-impaired at the reporting date or an actual default occurring. Generally, there will be a significant increase in credit risk before a financial asset becomes credit-impaired or an actual default occurs.

*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.

AGNCO AGNC Investment Corp. Depositary Shares each representing a 1/1000th interest in a share of 6.50% Series E Fixed-to-Floating Cumulative Redeemable Preferred Stock Financial Analysis*

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

*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?

Conclusions

AGNC Investment Corp. Depositary Shares each representing a 1/1000th interest in a share of 6.50% Series E Fixed-to-Floating Cumulative Redeemable Preferred Stock is assigned short-term B1 & long-term B1 estimated rating. AGNC Investment Corp. Depositary Shares each representing a 1/1000th interest in a share of 6.50% Series E Fixed-to-Floating Cumulative Redeemable Preferred Stock prediction model is evaluated with Supervised Machine Learning (ML) and Wilcoxon Rank-Sum Test^1,2,3,4 and it is concluded that the AGNCO stock is predictable in the short/long term. According to price forecasts for 16 Weeks period, the dominant strategy among neural network is: Hold

Prediction Confidence Score

Trust metric by Neural Network: 86 out of 100 with 827 signals.

References

1. Tibshirani R. 1996. Regression shrinkage and selection via the lasso. J. R. Stat. Soc. B 58:267–88
2. Wu X, Kumar V, Quinlan JR, Ghosh J, Yang Q, et al. 2008. Top 10 algorithms in data mining. Knowl. Inform. Syst. 14:1–37
3. J. Hu and M. P. Wellman. Nash q-learning for general-sum stochastic games. Journal of Machine Learning Research, 4:1039–1069, 2003.
4. Zou H, Hastie T. 2005. Regularization and variable selection via the elastic net. J. R. Stat. Soc. B 67:301–20
5. Li L, Chen S, Kleban J, Gupta A. 2014. Counterfactual estimation and optimization of click metrics for search engines: a case study. In Proceedings of the 24th International Conference on the World Wide Web, pp. 929–34. New York: ACM
6. D. Bertsekas. Dynamic programming and optimal control. Athena Scientific, 1995.
7. Jorgenson, D.W., Weitzman, M.L., ZXhang, Y.X., Haxo, Y.M. and Mat, Y.X., 2023. Can Neural Networks Predict Stock Market?. AC Investment Research Journal, 220(44).

Frequently Asked Questions

Q: What is the prediction methodology for AGNCO stock?
A: AGNCO stock prediction methodology: We evaluate the prediction models Supervised Machine Learning (ML) and Wilcoxon Rank-Sum Test
Q: Is AGNCO stock a buy or sell?
A: The dominant strategy among neural network is to Hold AGNCO Stock.
Q: Is AGNC Investment Corp. Depositary Shares each representing a 1/1000th interest in a share of 6.50% Series E Fixed-to-Floating Cumulative Redeemable Preferred Stock stock a good investment?
A: The consensus rating for AGNC Investment Corp. Depositary Shares each representing a 1/1000th interest in a share of 6.50% Series E Fixed-to-Floating Cumulative Redeemable Preferred Stock is Hold and is assigned short-term B1 & long-term B1 estimated rating.
Q: What is the consensus rating of AGNCO stock?
A: The consensus rating for AGNCO is Hold.
Q: What is the prediction period for AGNCO stock?
A: The prediction period for AGNCO is 16 Weeks