Outlook: Bank of America Corporation Bank of America Corporation Depositary Shares (Each representing a 1/1200th interest in a Share of Floating Rate Non-Cumulative Preferred Stock Series 2) assigned short-term Ba1 & long-term Ba1 estimated rating.
Dominant Strategy : Sell
Time series to forecast n: 28 Dec 2022 for (n+1 year)
Methodology : Modular Neural Network (Market Volatility Analysis)

## Abstract

The research reported in the paper focuses on the stock market prediction problem, the main aim being the development of a methodology to forecast the stock closing price. The methodology is based on some novel variable selection methods and an analysis of neural network and support vector machines based prediction models. Also, a hybrid approach which combines the use of the variables derived from technical and fundamental analysis of stock market indicators in order to improve prediction results of the proposed approaches is reported in this paper. (Rouf, N., Malik, M.B., Arif, T., Sharma, S., Singh, S., Aich, S. and Kim, H.C., 2021. Stock market prediction using machine learning techniques: a decade survey on methodologies, recent developments, and future directions. Electronics, 10(21), p.2717.) We evaluate Bank of America Corporation Bank of America Corporation Depositary Shares (Each representing a 1/1200th interest in a Share of Floating Rate Non-Cumulative Preferred Stock Series 2) prediction models with Modular Neural Network (Market Volatility Analysis) and Statistical Hypothesis Testing1,2,3,4 and conclude that the BML^H stock is predictable in the short/long term. According to price forecasts for (n+1 year) period, the dominant strategy among neural network is: Sell

## Key Points

1. Investment Risk
2. What are the most successful trading algorithms?
3. What are the most successful trading algorithms?

## BML^H Target Price Prediction Modeling Methodology

We consider Bank of America Corporation Bank of America Corporation Depositary Shares (Each representing a 1/1200th interest in a Share of Floating Rate Non-Cumulative Preferred Stock Series 2) Decision Process with Modular Neural Network (Market Volatility Analysis) where A is the set of discrete actions of BML^H 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(Statistical Hypothesis Testing)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 (Market Volatility Analysis)) X S(n):→ (n+1 year) $\begin{array}{l}\int {r}^{s}\mathrm{rs}\end{array}$

n:Time series to forecast

p:Price signals of BML^H 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?

## BML^H Stock Forecast (Buy or Sell) for (n+1 year)

Sample Set: Neural Network
Stock/Index: BML^H Bank of America Corporation Bank of America Corporation Depositary Shares (Each representing a 1/1200th interest in a Share of Floating Rate Non-Cumulative Preferred Stock Series 2)
Time series to forecast n: 28 Dec 2022 for (n+1 year)

According to price forecasts for (n+1 year) 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 Bank of America Corporation Depositary Shares (Each representing a 1/1200th interest in a Share of Floating Rate Non-Cumulative Preferred Stock Series 2)

1. An entity may manage and evaluate the performance of a group of financial liabilities or financial assets and financial liabilities in such a way that measuring that group at fair value through profit or loss results in more relevant information. The focus in this instance is on the way the entity manages and evaluates performance, instead of on the nature of its financial instruments.
2. If a collar, in the form of a purchased call and written put, prevents a transferred asset from being derecognised and the entity measures the asset at fair value, it continues to measure the asset at fair value. The associated liability is measured at (i) the sum of the call exercise price and fair value of the put option less the time value of the call option, if the call option is in or at the money, or (ii) the sum of the fair value of the asset and the fair value of the put option less the time value of the call option if the call option is out of the money. The adjustment to the associated liability ensures that the net carrying amount of the asset and the associated liability is the fair value of the options held and written by the entity. For example, assume an entity transfers a financial asset that is measured at fair value while simultaneously purchasing a call with an exercise price of CU120 and writing a put with an exercise price of CU80. Assume also that the fair value of the asset is CU100 at the date of the transfer. The time value of the put and call are CU1 and CU5 respectively. In this case, the entity recognises an asset of CU100 (the fair value of the asset) and a liability of CU96 [(CU100 + CU1) – CU5]. This gives a net asset value of CU4, which is the fair value of the options held and written by the entity.
3. Expected credit losses shall be discounted to the reporting date, not to the expected default or some other date, using the effective interest rate determined at initial recognition or an approximation thereof. If a financial instrument has a variable interest rate, expected credit losses shall be discounted using the current effective interest rate determined in accordance with paragraph B5.4.5.
4. When an entity designates a financial liability as at fair value through profit or loss, it must determine whether presenting in other comprehensive income the effects of changes in the liability's credit risk would create or enlarge an accounting mismatch in profit or loss. An accounting mismatch would be created or enlarged if presenting the effects of changes in the liability's credit risk in other comprehensive income would result in a greater mismatch in profit or loss than if those amounts were presented in 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 Bank of America Corporation Depositary Shares (Each representing a 1/1200th interest in a Share of Floating Rate Non-Cumulative Preferred Stock Series 2) assigned short-term Ba1 & long-term Ba1 estimated rating. We evaluate the prediction models Modular Neural Network (Market Volatility Analysis) with Statistical Hypothesis Testing1,2,3,4 and conclude that the BML^H stock is predictable in the short/long term. According to price forecasts for (n+1 year) period, the dominant strategy among neural network is: Sell

### BML^H Bank of America Corporation Bank of America Corporation Depositary Shares (Each representing a 1/1200th interest in a Share of Floating Rate Non-Cumulative Preferred Stock Series 2) Financial Analysis*

Rating Short-Term Long-Term Senior
Outlook*Ba1Ba1
Income StatementBaa2Baa2
Balance SheetCaa2B2
Leverage RatiosBaa2Baa2
Cash FlowB3Baa2
Rates of Return and ProfitabilityCB3

*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: 82 out of 100 with 831 signals.

## References

1. Farrell MH, Liang T, Misra S. 2018. Deep neural networks for estimation and inference: application to causal effects and other semiparametric estimands. arXiv:1809.09953 [econ.EM]
2. V. Borkar. Stochastic approximation: a dynamical systems viewpoint. Cambridge University Press, 2008
3. Z. Wang, T. Schaul, M. Hessel, H. van Hasselt, M. Lanctot, and N. de Freitas. Dueling network architectures for deep reinforcement learning. In Proceedings of the International Conference on Machine Learning (ICML), pages 1995–2003, 2016.
4. 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.
5. V. Borkar. Stochastic approximation: a dynamical systems viewpoint. Cambridge University Press, 2008
6. Abadir, K. M., K. Hadri E. Tzavalis (1999), "The influence of VAR dimensions on estimator biases," Econometrica, 67, 163–181.
7. R. Howard and J. Matheson. Risk sensitive Markov decision processes. Management Science, 18(7):356– 369, 1972
Frequently Asked QuestionsQ: What is the prediction methodology for BML^H stock?
A: BML^H stock prediction methodology: We evaluate the prediction models Modular Neural Network (Market Volatility Analysis) and Statistical Hypothesis Testing
Q: Is BML^H stock a buy or sell?
A: The dominant strategy among neural network is to Sell BML^H Stock.
Q: Is Bank of America Corporation Bank of America Corporation Depositary Shares (Each representing a 1/1200th interest in a Share of Floating Rate Non-Cumulative Preferred Stock Series 2) stock a good investment?
A: The consensus rating for Bank of America Corporation Bank of America Corporation Depositary Shares (Each representing a 1/1200th interest in a Share of Floating Rate Non-Cumulative Preferred Stock Series 2) is Sell and assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of BML^H stock?
A: The consensus rating for BML^H is Sell.
Q: What is the prediction period for BML^H stock?
A: The prediction period for BML^H is (n+1 year)