**Outlook:**Zions Bancorporation N.A. Depositary Shares (Each representing 1/40th Interest in a Share of Series A Floating-Rate Non-Cumulative Perpetual Preferred Stock) is assigned short-term B2 & long-term Ba1 estimated rating.

**AUC Score :**

**Short-Term Revised**

^{1}:**Dominant Strategy :**Hold

**Time series to forecast n:** for

^{2}

**Methodology :**Modular Neural Network (Market Volatility Analysis)

**Hypothesis Testing :**Multiple Regression

**Surveillance :**Major exchange and OTC

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

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

## Summary

Zions Bancorporation N.A. Depositary Shares (Each representing 1/40th Interest in a Share of Series A Floating-Rate Non-Cumulative Perpetual Preferred Stock) prediction model is evaluated with Modular Neural Network (Market Volatility Analysis) and Multiple Regression^{1,2,3,4}and it is concluded that the ZIONP stock is predictable in the short/long term. Modular neural networks (MNNs) are a type of artificial neural network that can be used for market volatility analysis. MNNs are made up of multiple smaller neural networks, called modules. Each module is responsible for learning a specific task, such as identifying patterns in data or predicting future price movements. The modules are then combined to form a single neural network that can perform multiple tasks.In the context of market volatility analysis, MNNs can be used to identify patterns in market data that suggest that the market is becoming more or less volatile. This information can then be used to make predictions about future price movements.

**According to price forecasts for 16 Weeks period, the dominant strategy among neural network is: Hold**

## Key Points

- What statistical methods are used to analyze data?
- How can neural networks improve predictions?
- Buy, Sell and Hold Signals

## ZIONP Target Price Prediction Modeling Methodology

We consider Zions Bancorporation N.A. Depositary Shares (Each representing 1/40th Interest in a Share of Series A Floating-Rate Non-Cumulative Perpetual Preferred Stock) Decision Process with Modular Neural Network (Market Volatility Analysis) where A is the set of discrete actions of ZIONP 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}= $\begin{array}{cccc}{p}_{\mathrm{a}1}& {p}_{\mathrm{a}2}& \dots & {p}_{1n}\\ & \vdots \\ {p}_{j1}& {p}_{j2}& \dots & {p}_{jn}\\ & \vdots \\ {p}_{k1}& {p}_{k2}& \dots & {p}_{kn}\\ & \vdots \\ {p}_{n1}& {p}_{n2}& \dots & {p}_{nn}\end{array}$ X R(Modular Neural Network (Market Volatility Analysis)) X S(n):→ 16 Weeks $\sum _{i=1}^{n}\left({r}_{i}\right)$

n:Time series to forecast

p:Price signals of ZIONP stock

j:Nash equilibria (Neural Network)

k:Dominated move

a:Best response for target price

### Modular Neural Network (Market Volatility Analysis)

Modular neural networks (MNNs) are a type of artificial neural network that can be used for market volatility analysis. MNNs are made up of multiple smaller neural networks, called modules. Each module is responsible for learning a specific task, such as identifying patterns in data or predicting future price movements. The modules are then combined to form a single neural network that can perform multiple tasks.In the context of market volatility analysis, MNNs can be used to identify patterns in market data that suggest that the market is becoming more or less volatile. This information can then be used to make predictions about future price movements.### Multiple Regression

Multiple regression is a statistical method that analyzes the relationship between a dependent variable and multiple independent variables. The dependent variable is the variable that is being predicted, and the independent variables are the variables that are used to predict the dependent variable. Multiple regression is a more complex statistical method than simple linear regression, which only analyzes the relationship between a dependent variable and one independent variable. Multiple regression can be used to analyze more complex relationships between variables, and it can also be used to control for confounding variables. A confounding variable is a variable that is correlated with both the dependent variable and one or more of the independent variables. Confounding variables can distort the relationship between the dependent variable and the independent variables. Multiple regression can be used to control for confounding variables by including them in the model.

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?

## ZIONP Stock Forecast (Buy or Sell)

**Sample Set:**Neural Network

**Stock/Index:**ZIONP Zions Bancorporation N.A. Depositary Shares (Each representing 1/40th Interest in a Share of Series A Floating-Rate Non-Cumulative Perpetual 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 Modular Neural Network (Market Volatility Analysis) based ZIONP Stock Prediction Model

- Rebalancing is accounted for as a continuation of the hedging relationship in accordance with paragraphs B6.5.9–B6.5.21. On rebalancing, the hedge ineffectiveness of the hedging relationship is determined and recognised immediately before adjusting the hedging relationship.
- The risk of a default occurring on financial instruments that have comparable credit risk is higher the longer the expected life of the instrument; for example, the risk of a default occurring on an AAA-rated bond with an expected life of 10 years is higher than that on an AAA-rated bond with an expected life of five years.
- In the reporting period that includes the date of initial application of these amendments, an entity is not required to present the quantitative information required by paragraph 28(f) of IAS 8.
- An entity that first applies IFRS 17 as amended in June 2020 at the same time it first applies this Standard shall apply paragraphs 7.2.1–7.2.28 instead of paragraphs 7.2.38–7.2.42.

*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.

### ZIONP Zions Bancorporation N.A. Depositary Shares (Each representing 1/40th Interest in a Share of Series A Floating-Rate Non-Cumulative Perpetual Preferred Stock) Financial Analysis*

Rating | Short-Term | Long-Term Senior |
---|---|---|

Outlook* | B2 | Ba1 |

Income Statement | Caa2 | Ba2 |

Balance Sheet | Ba1 | B2 |

Leverage Ratios | Baa2 | Baa2 |

Cash Flow | C | Baa2 |

Rates of Return and Profitability | B2 | Ba1 |

*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

Zions Bancorporation N.A. Depositary Shares (Each representing 1/40th Interest in a Share of Series A Floating-Rate Non-Cumulative Perpetual Preferred Stock) is assigned short-term B2 & long-term Ba1 estimated rating. Zions Bancorporation N.A. Depositary Shares (Each representing 1/40th Interest in a Share of Series A Floating-Rate Non-Cumulative Perpetual Preferred Stock) prediction model is evaluated with Modular Neural Network (Market Volatility Analysis) and Multiple Regression^{1,2,3,4} and it is concluded that the ZIONP 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

## References

- Bierens HJ. 1987. Kernel estimators of regression functions. In Advances in Econometrics: Fifth World Congress, Vol. 1, ed. TF Bewley, pp. 99–144. Cambridge, UK: Cambridge Univ. Press
- Chernozhukov V, Chetverikov D, Demirer M, Duflo E, Hansen C, et al. 2016a. Double machine learning for treatment and causal parameters. Tech. Rep., Cent. Microdata Methods Pract., Inst. Fiscal Stud., London
- Breiman L. 1996. Bagging predictors. Mach. Learn. 24:123–40
- Mikolov T, Sutskever I, Chen K, Corrado GS, Dean J. 2013b. Distributed representations of words and phrases and their compositionality. In Advances in Neural Information Processing Systems, Vol. 26, ed. Z Ghahramani, M Welling, C Cortes, ND Lawrence, KQ Weinberger, pp. 3111–19. San Diego, CA: Neural Inf. Process. Syst. Found.
- Belloni A, Chernozhukov V, Hansen C. 2014. High-dimensional methods and inference on structural and treatment effects. J. Econ. Perspect. 28:29–50
- 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]
- J. Baxter and P. Bartlett. Infinite-horizon policy-gradient estimation. Journal of Artificial Intelligence Re- search, 15:319–350, 2001.

## Frequently Asked Questions

Q: What is the prediction methodology for ZIONP stock?A: ZIONP stock prediction methodology: We evaluate the prediction models Modular Neural Network (Market Volatility Analysis) and Multiple Regression

Q: Is ZIONP stock a buy or sell?

A: The dominant strategy among neural network is to Hold ZIONP Stock.

Q: Is Zions Bancorporation N.A. Depositary Shares (Each representing 1/40th Interest in a Share of Series A Floating-Rate Non-Cumulative Perpetual Preferred Stock) stock a good investment?

A: The consensus rating for Zions Bancorporation N.A. Depositary Shares (Each representing 1/40th Interest in a Share of Series A Floating-Rate Non-Cumulative Perpetual Preferred Stock) is Hold and is assigned short-term B2 & long-term Ba1 estimated rating.

Q: What is the consensus rating of ZIONP stock?

A: The consensus rating for ZIONP is Hold.

Q: What is the prediction period for ZIONP stock?

A: The prediction period for ZIONP is 16 Weeks

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