As part of this research, different techniques have been studied for data extraction and analysis. After having reviewed the work related to the initial idea of the research, it is shown the development carried out, together with the data extraction and the machine learning algorithms for prediction used. The calculation of technical analysis metrics is also included. The development of a visualization platform has been proposed for high-level interaction between the user and the recommendation system.** We evaluate United Utilities prediction models with Modular Neural Network (DNN Layer) and Stepwise Regression ^{1,2,3,4} and conclude that the UU 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 Buy UU stock.**

**UU, United Utilities, stock forecast, machine learning based prediction, risk rating, buy-sell behaviour, stock analysis, target price analysis, options and futures.**

*Keywords:*## Key Points

- How useful are statistical predictions?
- Short/Long Term Stocks
- Trading Interaction

## UU Target Price Prediction Modeling Methodology

We present an Artificial Neural Network (ANN) approach to predict stock market indices, particularly with respect to the forecast of their trend movements up or down. Exploiting different Neural Networks architectures, we provide numerical analysis of concrete financial time series. In particular, after a brief r ́esum ́e of the existing literature on the subject, we consider the Multi-layer Perceptron (MLP), the Convolutional Neural Net- works (CNN), and the Long Short-Term Memory (LSTM) recurrent neural networks techniques. We consider United Utilities Stock Decision Process with Stepwise Regression where A is the set of discrete actions of UU 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(Stepwise 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 (DNN Layer)) X S(n):→ (n+8 weeks) $\sum _{i=1}^{n}\left({a}_{i}\right)$

n:Time series to forecast

p:Price signals of UU stock

j:Nash equilibria

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?

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

**Sample Set:**Neural Network

**Stock/Index:**UU United Utilities

**Time series to forecast n: 15 Oct 2022**for (n+8 weeks)

**According to price forecasts for (n+8 weeks) period: The dominant strategy among neural network is to Buy UU 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%**

## Conclusions

United Utilities assigned short-term B1 & long-term B2 forecasted stock rating.** We evaluate the prediction models Modular Neural Network (DNN Layer) with Stepwise Regression ^{1,2,3,4} and conclude that the UU 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 Buy UU stock.**

### Financial State Forecast for UU Stock Options & Futures

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

Outlook* | B1 | B2 |

Operational Risk | 86 | 88 |

Market Risk | 33 | 41 |

Technical Analysis | 36 | 30 |

Fundamental Analysis | 88 | 50 |

Risk Unsystematic | 50 | 41 |

### Prediction Confidence Score

## References

- Athey S, Imbens GW. 2017b. The state of applied econometrics: causality and policy evaluation. J. Econ. Perspect. 31:3–32
- Andrews, D. W. K. W. Ploberger (1994), "Optimal tests when a nuisance parameter is present only under the alternative," Econometrica, 62, 1383–1414.
- Banerjee, A., J. J. Dolado, J. W. Galbraith, D. F. Hendry (1993), Co-integration, Error-correction, and the Econometric Analysis of Non-stationary Data. Oxford: Oxford University Press.
- Bessler, D. A. T. Covey (1991), "Cointegration: Some results on U.S. cattle prices," Journal of Futures Markets, 11, 461–474.
- Athey S, Bayati M, Doudchenko N, Imbens G, Khosravi K. 2017a. Matrix completion methods for causal panel data models. arXiv:1710.10251 [math.ST]
- Sutton RS, Barto AG. 1998. Reinforcement Learning: An Introduction. Cambridge, MA: MIT Press
- T. Morimura, M. Sugiyama, M. Kashima, H. Hachiya, and T. Tanaka. Nonparametric return distribution ap- proximation for reinforcement learning. In Proceedings of the 27th International Conference on Machine Learning, pages 799–806, 2010

## Frequently Asked Questions

Q: What is the prediction methodology for UU stock?A: UU stock prediction methodology: We evaluate the prediction models Modular Neural Network (DNN Layer) and Stepwise Regression

Q: Is UU stock a buy or sell?

A: The dominant strategy among neural network is to Buy UU Stock.

Q: Is United Utilities stock a good investment?

A: The consensus rating for United Utilities is Buy and assigned short-term B1 & long-term B2 forecasted stock rating.

Q: What is the consensus rating of UU stock?

A: The consensus rating for UU is Buy.

Q: What is the prediction period for UU stock?

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