## Summary

In recent years there has been a significant growth of interest in the incorporation of historical series of variables related to stock prediction into mathematical models or computational algorithms in order to generate predictions or indications about expected price movements.** We evaluate Applied UV Inc. Common Stock prediction models with Reinforcement Machine Learning (ML) and Wilcoxon Rank-Sum Test ^{1,2,3,4} and conclude that the AUVI stock is predictable in the short/long term. **

**According to price forecasts for (n+8 weeks) period: The dominant strategy among neural network is to Hold AUVI stock.**

## Key Points

- Can statistics predict the future?
- Can stock prices be predicted?
- What is statistical models in machine learning?

## AUVI Target Price Prediction Modeling Methodology

We consider Applied UV Inc. Common Stock Stock Decision Process with Reinforcement Machine Learning (ML) where A is the set of discrete actions of AUVI 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 Î³ ∈ [0, 1] is a move factor for expectation.^{1,2,3,4}

F(Wilcoxon Rank-Sum Test)

^{5,6,7}= $\begin{array}{cccc}{p}_{\mathrm{a}1}& {p}_{\mathrm{a}2}& \dots & {p}_{1n}\\ & \vdots \\ {p}_{j1}& {p}_{j2}& \dots & {p}_{jn}\\ & \vdots \\ {p}_{k1}& {p}_{k2}& \dots & {p}_{kn}\\ & \vdots \\ {p}_{n1}& {p}_{n2}& \dots & {p}_{nn}\end{array}$ X R(Reinforcement Machine Learning (ML)) X S(n):→ (n+8 weeks) $\sum _{i=1}^{n}\left({s}_{i}\right)$

n:Time series to forecast

p:Price signals of AUVI 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?

## AUVI Stock Forecast (Buy or Sell) for (n+8 weeks)

**Sample Set:**Neural Network

**Stock/Index:**AUVI Applied UV Inc. Common Stock

**Time series to forecast n: 24 Nov 2022**for (n+8 weeks)

**According to price forecasts for (n+8 weeks) period: The dominant strategy among neural network is to Hold AUVI stock.**

**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 (Yellow to Green): *Technical Analysis%**

## Adjusted IFRS* Prediction Methods for Applied UV Inc. Common Stock

- 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.
- Lifetime expected credit losses are not recognised on a financial instrument simply because it was considered to have low credit risk in the previous reporting period and is not considered to have low credit risk at the reporting date. In such a case, an entity shall determine whether there has been a significant increase in credit risk since initial recognition and thus whether lifetime expected credit losses are required to be recognised in accordance with paragraph 5.5.3.
- When using historical credit loss experience in estimating expected credit losses, it is important that information about historical credit loss rates is applied to groups that are defined in a manner that is consistent with the groups for which the historical credit loss rates were observed. Consequently, the method used shall enable each group of financial assets to be associated with information about past credit loss experience in groups of financial assets with similar risk characteristics and with relevant observable data that reflects current conditions.
- For purchased or originated credit-impaired financial assets, expected credit losses shall be discounted using the credit-adjusted effective interest rate determined at initial recognition.

*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

Applied UV Inc. Common Stock assigned short-term B3 & long-term Ba2 forecasted stock rating.** We evaluate the prediction models Reinforcement Machine Learning (ML) with Wilcoxon Rank-Sum Test ^{1,2,3,4} and conclude that the AUVI stock is predictable in the short/long term.**

**According to price forecasts for (n+8 weeks) period: The dominant strategy among neural network is to Hold AUVI stock.**

### Financial State Forecast for AUVI Applied UV Inc. Common Stock Stock Options & Futures

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

Outlook* | B3 | Ba2 |

Operational Risk | 38 | 31 |

Market Risk | 44 | 74 |

Technical Analysis | 61 | 81 |

Fundamental Analysis | 64 | 60 |

Risk Unsystematic | 41 | 90 |

### Prediction Confidence Score

## References

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## Frequently Asked Questions

Q: What is the prediction methodology for AUVI stock?A: AUVI stock prediction methodology: We evaluate the prediction models Reinforcement Machine Learning (ML) and Wilcoxon Rank-Sum Test

Q: Is AUVI stock a buy or sell?

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

Q: Is Applied UV Inc. Common Stock stock a good investment?

A: The consensus rating for Applied UV Inc. Common Stock is Hold and assigned short-term B3 & long-term Ba2 forecasted stock rating.

Q: What is the consensus rating of AUVI stock?

A: The consensus rating for AUVI is Hold.

Q: What is the prediction period for AUVI stock?

A: The prediction period for AUVI is (n+8 weeks)