Is AIG^A Stock Buy or Sell?

Outlook: American International Group Inc. Depositary Shares Each Representing a 1/1000th Interest in a Share of Series A 5.85% Non-Cumulative Perpetual Preferred Stock is assigned short-term B2 & long-term Ba3 estimated rating.
AUC Score : What is AUC Score?
Short-Term Revised :
Dominant Strategy : Hold
Time series to forecast n: for 4 Weeks
Methodology : Modular Neural Network (News Feed Sentiment Analysis)
Hypothesis Testing : Wilcoxon Rank-Sum Test
Surveillance : Major exchange and OTC

Summary

American International Group Inc. Depositary Shares Each Representing a 1/1000th Interest in a Share of Series A 5.85% Non-Cumulative Perpetual Preferred Stock prediction model is evaluated with Modular Neural Network (News Feed Sentiment Analysis) and Wilcoxon Rank-Sum Test^1,2,3,4 and it is concluded that the AIG^A stock is predictable in the short/long term. A modular neural network (MNN) is a type of artificial neural network that can be used for news feed sentiment analysis. MNNs are made up of multiple smaller neural networks, called modules. Each module is responsible for learning a specific task, such as identifying sentiment in text or identifying patterns in data. The modules are then combined to form a single neural network that can perform multiple tasks. In the context of news feed sentiment analysis, MNNs can be used to identify the sentiment of news articles, social media posts, and other forms of online content. This information can then be used to filter out irrelevant or unwanted content, to identify trends in public opinion, and to target users with relevant advertising. According to price forecasts for 4 Weeks period, the dominant strategy among neural network is: Hold

Key Points

1. What is the use of Markov decision process?
2. Can stock prices be predicted?
3. Can statistics predict the future?

AIG^A Target Price Prediction Modeling Methodology

We consider American International Group Inc. Depositary Shares Each Representing a 1/1000th Interest in a Share of Series A 5.85% Non-Cumulative Perpetual Preferred Stock Decision Process with Modular Neural Network (News Feed Sentiment Analysis) where A is the set of discrete actions of AIG^A 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(Modular Neural Network (News Feed Sentiment Analysis)) X S(n):→ 4 Weeks $\sum _{i=1}^n\left(a_i\right)$

n:Time series to forecast

p:Price signals of AIG^A stock

j:Nash equilibria (Neural Network)

k:Dominated move

a:Best response for target price

Modular Neural Network (News Feed Sentiment Analysis)

A modular neural network (MNN) is a type of artificial neural network that can be used for news feed sentiment analysis. MNNs are made up of multiple smaller neural networks, called modules. Each module is responsible for learning a specific task, such as identifying sentiment in text or identifying patterns in data. The modules are then combined to form a single neural network that can perform multiple tasks. In the context of news feed sentiment analysis, MNNs can be used to identify the sentiment of news articles, social media posts, and other forms of online content. This information can then be used to filter out irrelevant or unwanted content, to identify trends in public opinion, and to target users with relevant advertising.

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?

AIG^A Stock Forecast (Buy or Sell) for 4 Weeks

Sample Set: Neural Network
Stock/Index: AIG^A American International Group Inc. Depositary Shares Each Representing a 1/1000th Interest in a Share of Series A 5.85% Non-Cumulative Perpetual Preferred Stock
Time series to forecast: 4 Weeks

According to price forecasts for 4 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 International Group Inc. Depositary Shares Each Representing a 1/1000th Interest in a Share of Series A 5.85% Non-Cumulative Perpetual Preferred Stock

1. An entity can also designate only changes in the cash flows or fair value of a hedged item above or below a specified price or other variable (a 'one-sided risk'). The intrinsic value of a purchased option hedging instrument (assuming that it has the same principal terms as the designated risk), but not its time value, reflects a one-sided risk in a hedged item. For example, an entity can designate the variability of future cash flow outcomes resulting from a price increase of a forecast commodity purchase. In such a situation, the entity designates only cash flow losses that result from an increase in the price above the specified level. The hedged risk does not include the time value of a purchased option, because the time value is not a component of the forecast transaction that affects profit or loss.
2. For some types of fair value hedges, the objective of the hedge is not primarily to offset the fair value change of the hedged item but instead to transform the cash flows of the hedged item. For example, an entity hedges the fair value interest rate risk of a fixed-rate debt instrument using an interest rate swap. The entity's hedge objective is to transform the fixed-interest cash flows into floating interest cash flows. This objective is reflected in the accounting for the hedging relationship by accruing the net interest accrual on the interest rate swap in profit or loss. In the case of a hedge of a net position (for example, a net position of a fixed-rate asset and a fixed-rate liability), this net interest accrual must be presented in a separate line item in the statement of profit or loss and other comprehensive income. This is to avoid the grossing up of a single instrument's net gains or losses into offsetting gross amounts and recognising them in different line items (for example, this avoids grossing up a net interest receipt on a single interest rate swap into gross interest revenue and gross interest expense).
3. In accordance with the hedge effectiveness requirements, the hedge ratio of the hedging relationship must be the same as that resulting from the quantity of the hedged item that the entity actually hedges and the quantity of the hedging instrument that the entity actually uses to hedge that quantity of hedged item. Hence, if an entity hedges less than 100 per cent of the exposure on an item, such as 85 per cent, it shall designate the hedging relationship using a hedge ratio that is the same as that resulting from 85 per cent of the exposure and the quantity of the hedging instrument that the entity actually uses to hedge those 85 per cent. Similarly, if, for example, an entity hedges an exposure using a nominal amount of 40 units of a financial instrument, it shall designate the hedging relationship using a hedge ratio that is the same as that resulting from that quantity of 40 units (ie the entity must not use a hedge ratio based on a higher quantity of units that it might hold in total or a lower quantity of units) and the quantity of the hedged item that it actually hedges with those 40 units.
4. 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

*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 International Group Inc. Depositary Shares Each Representing a 1/1000th Interest in a Share of Series A 5.85% Non-Cumulative Perpetual Preferred Stock is assigned short-term B2 & long-term Ba3 estimated rating. American International Group Inc. Depositary Shares Each Representing a 1/1000th Interest in a Share of Series A 5.85% Non-Cumulative Perpetual Preferred Stock prediction model is evaluated with Modular Neural Network (News Feed Sentiment Analysis) and Wilcoxon Rank-Sum Test^1,2,3,4 and it is concluded that the AIG^A stock is predictable in the short/long term. According to price forecasts for 4 Weeks period, the dominant strategy among neural network is: Hold

AIG^A American International Group Inc. Depositary Shares Each Representing a 1/1000th Interest in a Share of Series A 5.85% Non-Cumulative Perpetual Preferred Stock Financial Analysis*

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

Prediction Confidence Score

Trust metric by Neural Network: 74 out of 100 with 819 signals.

References

1. Hastie T, Tibshirani R, Wainwright M. 2015. Statistical Learning with Sparsity: The Lasso and Generalizations. New York: CRC Press
2. V. Mnih, K. Kavukcuoglu, D. Silver, A. Rusu, J. Veness, M. Bellemare, A. Graves, M. Riedmiller, A. Fidjeland, G. Ostrovski, S. Petersen, C. Beattie, A. Sadik, I. Antonoglou, H. King, D. Kumaran, D. Wierstra, S. Legg, and D. Hassabis. Human-level control through deep reinforcement learning. Nature, 518(7540):529–533, 02 2015.
3. Mullainathan S, Spiess J. 2017. Machine learning: an applied econometric approach. J. Econ. Perspect. 31:87–106
4. Alexander, J. C. Jr. (1995), "Refining the degree of earnings surprise: A comparison of statistical and analysts' forecasts," Financial Review, 30, 469–506.
5. Andrews, D. W. K. (1993), "Tests for parameter instability and structural change with unknown change point," Econometrica, 61, 821–856.
6. Burkov A. 2019. The Hundred-Page Machine Learning Book. Quebec City, Can.: Andriy Burkov
7. J. Ott. A Markov decision model for a surveillance application and risk-sensitive Markov decision processes. PhD thesis, Karlsruhe Institute of Technology, 2010.

Frequently Asked Questions

Q: What is the prediction methodology for AIG^A stock?
A: AIG^A stock prediction methodology: We evaluate the prediction models Modular Neural Network (News Feed Sentiment Analysis) and Wilcoxon Rank-Sum Test
Q: Is AIG^A stock a buy or sell?
A: The dominant strategy among neural network is to Hold AIG^A Stock.
Q: Is American International Group Inc. Depositary Shares Each Representing a 1/1000th Interest in a Share of Series A 5.85% Non-Cumulative Perpetual Preferred Stock stock a good investment?
A: The consensus rating for American International Group Inc. Depositary Shares Each Representing a 1/1000th Interest in a Share of Series A 5.85% Non-Cumulative Perpetual Preferred Stock is Hold and is assigned short-term B2 & long-term Ba3 estimated rating.
Q: What is the consensus rating of AIG^A stock?
A: The consensus rating for AIG^A is Hold.
Q: What is the prediction period for AIG^A stock?
A: The prediction period for AIG^A is 4 Weeks

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