Outlook: Bank of America Corporation Depositary Shares each representing a 1/1000th interest in a share of 6.000% Non-Cumulative Preferred Stock Series GG is assigned short-term Ba1 & long-term Ba1 estimated rating.
Dominant Strategy : Sell
Time series to forecast n: 10 Jun 2023 for 8 Weeks
Methodology : Modular Neural Network (CNN Layer)

## Abstract

Bank of America Corporation Depositary Shares each representing a 1/1000th interest in a share of 6.000% Non-Cumulative Preferred Stock Series GG prediction model is evaluated with Modular Neural Network (CNN Layer) and Ridge Regression1,2,3,4 and it is concluded that the BAC^B stock is predictable in the short/long term. CNN layers are a powerful tool for extracting features from images. They are able to learn to detect patterns in images that are not easily detected by humans. This makes them well-suited for a variety of MNN applications. According to price forecasts for 8 Weeks period, the dominant strategy among neural network is: Sell ## Key Points

1. Short/Long Term Stocks
2. Game Theory
3. Why do we need predictive models?

## BAC^B Target Price Prediction Modeling Methodology

We consider Bank of America Corporation Depositary Shares each representing a 1/1000th interest in a share of 6.000% Non-Cumulative Preferred Stock Series GG Decision Process with Modular Neural Network (CNN Layer) where A is the set of discrete actions of BAC^B 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(Ridge Regression)5,6,7= $\begin{array}{cccc}{p}_{a1}& {p}_{a2}& \dots & {p}_{1n}\\ & ⋮\\ {p}_{j1}& {p}_{j2}& \dots & {p}_{jn}\\ & ⋮\\ {p}_{k1}& {p}_{k2}& \dots & {p}_{kn}\\ & ⋮\\ {p}_{n1}& {p}_{n2}& \dots & {p}_{nn}\end{array}$ X R(Modular Neural Network (CNN Layer)) X S(n):→ 8 Weeks $∑ i = 1 n a i$

n:Time series to forecast

p:Price signals of BAC^B stock

j:Nash equilibria (Neural Network)

k:Dominated move

a:Best response for target price

### Modular Neural Network (CNN Layer)

CNN layers are a powerful tool for extracting features from images. They are able to learn to detect patterns in images that are not easily detected by humans. This makes them well-suited for a variety of MNN applications.

### Ridge Regression

Ridge regression is a type of regression analysis that adds a penalty to the least squares objective function in order to reduce the variance of the estimates. This is done by adding a term to the objective function that is proportional to the sum of the squares of the coefficients. The penalty term is called the "ridge" penalty, and it is controlled by a parameter called the "ridge constant". Ridge regression can be used to address the problem of multicollinearity in linear regression. Multicollinearity occurs when two or more independent variables are highly correlated. This can cause the standard errors of the coefficients to be large, and it can also cause the coefficients to be unstable. Ridge regression can help to reduce the standard errors of the coefficients and to make the coefficients more stable.

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?

## BAC^B Stock Forecast (Buy or Sell) for 8 Weeks

Sample Set: Neural Network
Stock/Index: BAC^B Bank of America Corporation Depositary Shares each representing a 1/1000th interest in a share of 6.000% Non-Cumulative Preferred Stock Series GG
Time series to forecast n: 10 Jun 2023 for 8 Weeks

According to price forecasts for 8 Weeks period, the dominant strategy among neural network is: Sell

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 Bank of America Corporation Depositary Shares each representing a 1/1000th interest in a share of 6.000% Non-Cumulative Preferred Stock Series GG

1. If a call option right retained by an entity prevents a transferred asset from being derecognised and the entity measures the transferred asset at fair value, the asset continues to be measured at its fair value. The associated liability is measured at (i) the option exercise price less the time value of the option if the option is in or at the money, or (ii) the fair value of the transferred asset less the time value of the option if the option is out of the money. The adjustment to the measurement of the associated liability ensures that the net carrying amount of the asset and the associated liability is the fair value of the call option right. For example, if the fair value of the underlying asset is CU80, the option exercise price is CU95 and the time value of the option is CU5, the carrying amount of the associated liability is CU75 (CU80 – CU5) and the carrying amount of the transferred asset is CU80 (ie its fair value)
2. A hedge of a firm commitment (for example, a hedge of the change in fuel price relating to an unrecognised contractual commitment by an electric utility to purchase fuel at a fixed price) is a hedge of an exposure to a change in fair value. Accordingly, such a hedge is a fair value hedge. However, in accordance with paragraph 6.5.4, a hedge of the foreign currency risk of a firm commitment could alternatively be accounted for as a cash flow hedge.
3. Lifetime expected credit losses are generally expected to be recognised before a financial instrument becomes past due. Typically, credit risk increases significantly before a financial instrument becomes past due or other lagging borrower-specific factors (for example, a modification or restructuring) are observed. Consequently when reasonable and supportable information that is more forward-looking than past due information is available without undue cost or effort, it must be used to assess changes in credit risk.
4. A portfolio of financial assets that is managed and whose performance is evaluated on a fair value basis (as described in paragraph 4.2.2(b)) is neither held to collect contractual cash flows nor held both to collect contractual cash flows and to sell financial assets. The entity is primarily focused on fair value information and uses that information to assess the assets' performance and to make decisions. In addition, a portfolio of financial assets that meets the definition of held for trading is not held to collect contractual cash flows or held both to collect contractual cash flows and to sell financial assets. For such portfolios, the collection of contractual cash flows is only incidental to achieving the business model's objective. Consequently, such portfolios of financial assets must be measured at fair value through profit or loss.

*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

Bank of America Corporation Depositary Shares each representing a 1/1000th interest in a share of 6.000% Non-Cumulative Preferred Stock Series GG is assigned short-term Ba1 & long-term Ba1 estimated rating. Bank of America Corporation Depositary Shares each representing a 1/1000th interest in a share of 6.000% Non-Cumulative Preferred Stock Series GG prediction model is evaluated with Modular Neural Network (CNN Layer) and Ridge Regression1,2,3,4 and it is concluded that the BAC^B stock is predictable in the short/long term. According to price forecasts for 8 Weeks period, the dominant strategy among neural network is: Sell

### BAC^B Bank of America Corporation Depositary Shares each representing a 1/1000th interest in a share of 6.000% Non-Cumulative Preferred Stock Series GG Financial Analysis*

Rating Short-Term Long-Term Senior
Outlook*Ba1Ba1
Income StatementBa1Baa2
Balance SheetCaa2Ba2
Leverage RatiosBaa2B1
Cash FlowBa2C
Rates of Return and ProfitabilityBa3Ba1

*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: 75 out of 100 with 861 signals.

## References

1. Arjovsky M, Bottou L. 2017. Towards principled methods for training generative adversarial networks. arXiv:1701.04862 [stat.ML]
2. Abadie A, Diamond A, Hainmueller J. 2010. Synthetic control methods for comparative case studies: estimat- ing the effect of California's tobacco control program. J. Am. Stat. Assoc. 105:493–505
3. V. Borkar. Q-learning for risk-sensitive control. Mathematics of Operations Research, 27:294–311, 2002.
4. Friedberg R, Tibshirani J, Athey S, Wager S. 2018. Local linear forests. arXiv:1807.11408 [stat.ML]
5. Zou H, Hastie T. 2005. Regularization and variable selection via the elastic net. J. R. Stat. Soc. B 67:301–20
6. V. Borkar. Stochastic approximation: a dynamical systems viewpoint. Cambridge University Press, 2008
7. D. Bertsekas. Dynamic programming and optimal control. Athena Scientific, 1995.
Frequently Asked QuestionsQ: What is the prediction methodology for BAC^B stock?
A: BAC^B stock prediction methodology: We evaluate the prediction models Modular Neural Network (CNN Layer) and Ridge Regression
Q: Is BAC^B stock a buy or sell?
A: The dominant strategy among neural network is to Sell BAC^B Stock.
Q: Is Bank of America Corporation Depositary Shares each representing a 1/1000th interest in a share of 6.000% Non-Cumulative Preferred Stock Series GG stock a good investment?
A: The consensus rating for Bank of America Corporation Depositary Shares each representing a 1/1000th interest in a share of 6.000% Non-Cumulative Preferred Stock Series GG is Sell and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of BAC^B stock?
A: The consensus rating for BAC^B is Sell.
Q: What is the prediction period for BAC^B stock?
A: The prediction period for BAC^B is 8 Weeks