Outlook: Equity Bancshares Inc. Class A Common Stock assigned short-term B2 & long-term Ba3 forecasted stock rating.
Dominant Strategy : Wait until speculative trend diminishes
Time series to forecast n: 10 Dec 2022 for (n+1 year)
Methodology : Reinforcement Machine Learning (ML)

## Abstract

Stock price forecasting is a popular and important topic in financial and academic studies. Share market is an volatile place for predicting since there are no significant rules to estimate or predict the price of a share in the share market. Many methods like technical analysis, fundamental analysis, time series analysis and statistical analysis etc. are used to predict the price in tie share market but none of these methods are proved as a consistently acceptable prediction tool. In this paper, we implemented a Random Forest approach to predict stock market prices. (Pang, X., Zhou, Y., Wang, P., Lin, W. and Chang, V., 2020. An innovative neural network approach for stock market prediction. The Journal of Supercomputing, 76(3), pp.2098-2118.) We evaluate Equity Bancshares Inc. Class A Common Stock prediction models with Reinforcement Machine Learning (ML) and Multiple Regression1,2,3,4 and conclude that the EQBK stock is predictable in the short/long term. According to price forecasts for (n+1 year) period, the dominant strategy among neural network is: Wait until speculative trend diminishes

## Key Points

1. What are main components of Markov decision process?
2. Market Signals
3. Market Risk

## EQBK Target Price Prediction Modeling Methodology

We consider Equity Bancshares Inc. Class A Common Stock Decision Process with Reinforcement Machine Learning (ML) where A is the set of discrete actions of EQBK 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(Multiple 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(Reinforcement Machine Learning (ML)) X S(n):→ (n+1 year) $\begin{array}{l}\int {e}^{x}\mathrm{rx}\end{array}$

n:Time series to forecast

p:Price signals of EQBK 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?

## EQBK Stock Forecast (Buy or Sell) for (n+1 year)

Sample Set: Neural Network
Stock/Index: EQBK Equity Bancshares Inc. Class A Common Stock
Time series to forecast n: 10 Dec 2022 for (n+1 year)

According to price forecasts for (n+1 year) period, the dominant strategy among neural network is: Wait until speculative trend diminishes

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%

## Adjusted IFRS* Prediction Methods for Equity Bancshares Inc. Class A Common Stock

1. The rebuttable presumption in paragraph 5.5.11 is not an absolute indicator that lifetime expected credit losses should be recognised, but is presumed to be the latest point at which lifetime expected credit losses should be recognised even when using forward-looking information (including macroeconomic factors on a portfolio level).
2. There is a rebuttable presumption that unless inflation risk is contractually specified, it is not separately identifiable and reliably measurable and hence cannot be designated as a risk component of a financial instrument. However, in limited cases, it is possible to identify a risk component for inflation risk that is separately identifiable and reliably measurable because of the particular circumstances of the inflation environment and the relevant debt market
3. If a financial asset contains a contractual term that could change the timing or amount of contractual cash flows (for example, if the asset can be prepaid before maturity or its term can be extended), the entity must determine whether the contractual cash flows that could arise over the life of the instrument due to that contractual term are solely payments of principal and interest on the principal amount outstanding. To make this determination, the entity must assess the contractual cash flows that could arise both before, and after, the change in contractual cash flows. The entity may also need to assess the nature of any contingent event (ie the trigger) that would change the timing or amount of the contractual cash flows. While the nature of the contingent event in itself is not a determinative factor in assessing whether the contractual cash flows are solely payments of principal and interest, it may be an indicator. For example, compare a financial instrument with an interest rate that is reset to a higher rate if the debtor misses a particular number of payments to a financial instrument with an interest rate that is reset to a higher rate if a specified equity index reaches a particular level. It is more likely in the former case that the contractual cash flows over the life of the instrument will be solely payments of principal and interest on the principal amount outstanding because of the relationship between missed payments and an increase in credit risk. (See also paragraph B4.1.18.)
4. A regular way purchase or sale gives rise to a fixed price commitment between trade date and settlement date that meets the definition of a derivative. However, because of the short duration of the commitment it is not recognised as a derivative financial instrument. Instead, this Standard provides for special accounting for such regular way contracts (see paragraphs 3.1.2 and B3.1.3–B3.1.6).

*International Financial Reporting Standards (IFRS) are a set of accounting rules for the financial statements of public companies that are intended to make them consistent, transparent, and easily comparable around the world.

## Conclusions

Equity Bancshares Inc. Class A Common Stock assigned short-term B2 & long-term Ba3 forecasted stock rating. We evaluate the prediction models Reinforcement Machine Learning (ML) with Multiple Regression1,2,3,4 and conclude that the EQBK stock is predictable in the short/long term. According to price forecasts for (n+1 year) period, the dominant strategy among neural network is: Wait until speculative trend diminishes

### Financial State Forecast for EQBK Equity Bancshares Inc. Class A Common Stock Options & Futures

Rating Short-Term Long-Term Senior
Outlook*B2Ba3
Operational Risk 3752
Market Risk3339
Technical Analysis4183
Fundamental Analysis7879
Risk Unsystematic8462

### Prediction Confidence Score

Trust metric by Neural Network: 75 out of 100 with 688 signals.

## References

1. Bera, A. M. L. Higgins (1997), "ARCH and bilinearity as competing models for nonlinear dependence," Journal of Business Economic Statistics, 15, 43–50.
2. L. Prashanth and M. Ghavamzadeh. Actor-critic algorithms for risk-sensitive MDPs. In Proceedings of Advances in Neural Information Processing Systems 26, pages 252–260, 2013.
3. M. Ono, M. Pavone, Y. Kuwata, and J. Balaram. Chance-constrained dynamic programming with application to risk-aware robotic space exploration. Autonomous Robots, 39(4):555–571, 2015
4. S. Bhatnagar, R. Sutton, M. Ghavamzadeh, and M. Lee. Natural actor-critic algorithms. Automatica, 45(11): 2471–2482, 2009
5. Chernozhukov V, Newey W, Robins J. 2018c. Double/de-biased machine learning using regularized Riesz representers. arXiv:1802.08667 [stat.ML]
6. Matzkin RL. 1994. Restrictions of economic theory in nonparametric methods. In Handbook of Econometrics, Vol. 4, ed. R Engle, D McFadden, pp. 2523–58. Amsterdam: Elsevier
7. Cortes C, Vapnik V. 1995. Support-vector networks. Mach. Learn. 20:273–97
Frequently Asked QuestionsQ: What is the prediction methodology for EQBK stock?
A: EQBK stock prediction methodology: We evaluate the prediction models Reinforcement Machine Learning (ML) and Multiple Regression
Q: Is EQBK stock a buy or sell?
A: The dominant strategy among neural network is to Wait until speculative trend diminishes EQBK Stock.
Q: Is Equity Bancshares Inc. Class A Common Stock stock a good investment?
A: The consensus rating for Equity Bancshares Inc. Class A Common Stock is Wait until speculative trend diminishes and assigned short-term B2 & long-term Ba3 forecasted stock rating.
Q: What is the consensus rating of EQBK stock?
A: The consensus rating for EQBK is Wait until speculative trend diminishes.
Q: What is the prediction period for EQBK stock?
A: The prediction period for EQBK is (n+1 year)