## Abstract

**We evaluate HICL INFRASTRUCTURE PLC prediction models with Modular Neural Network (Speculative Sentiment Analysis) and Logistic Regression ^{1,2,3,4} and conclude that the LON:HICL stock is predictable in the short/long term. **

**According to price forecasts for (n+1 year) period: The dominant strategy among neural network is to Hold LON:HICL stock.**

**LON:HICL, HICL INFRASTRUCTURE PLC, stock forecast, machine learning based prediction, risk rating, buy-sell behaviour, stock analysis, target price analysis, options and futures.**

*Keywords:*## Key Points

- Which neural network is best for prediction?
- Trading Interaction
- How accurate is machine learning in stock market?

## LON:HICL Target Price Prediction Modeling Methodology

We consider HICL INFRASTRUCTURE PLC Stock Decision Process with Logistic Regression where A is the set of discrete actions of LON:HICL 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(Logistic 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 (Speculative Sentiment Analysis)) X S(n):→ (n+1 year) $\sum _{i=1}^{n}\left({r}_{i}\right)$

n:Time series to forecast

p:Price signals of LON:HICL 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?

## LON:HICL Stock Forecast (Buy or Sell) for (n+1 year)

**Sample Set:**Neural Network

**Stock/Index:**LON:HICL HICL INFRASTRUCTURE PLC

**Time series to forecast n: 06 Sep 2022**for (n+1 year)

**According to price forecasts for (n+1 year) period: The dominant strategy among neural network is to Hold LON:HICL 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

HICL INFRASTRUCTURE PLC assigned short-term B3 & long-term Ba3 forecasted stock rating.** We evaluate the prediction models Modular Neural Network (Speculative Sentiment Analysis) with Logistic Regression ^{1,2,3,4} and conclude that the LON:HICL stock is predictable in the short/long term.**

**According to price forecasts for (n+1 year) period: The dominant strategy among neural network is to Hold LON:HICL stock.**

### Financial State Forecast for LON:HICL Stock Options & Futures

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

Outlook* | B3 | Ba3 |

Operational Risk | 49 | 52 |

Market Risk | 53 | 51 |

Technical Analysis | 34 | 59 |

Fundamental Analysis | 83 | 60 |

Risk Unsystematic | 38 | 89 |

### Prediction Confidence Score

## References

- Burkov A. 2019. The Hundred-Page Machine Learning Book. Quebec City, Can.: Andriy Burkov
- F. A. Oliehoek and C. Amato. A Concise Introduction to Decentralized POMDPs. SpringerBriefs in Intelligent Systems. Springer, 2016
- Dietterich TG. 2000. Ensemble methods in machine learning. In Multiple Classifier Systems: First International Workshop, Cagliari, Italy, June 21–23, pp. 1–15. Berlin: Springer
- Imbens G, Wooldridge J. 2009. Recent developments in the econometrics of program evaluation. J. Econ. Lit. 47:5–86
- V. Mnih, A. P. Badia, M. Mirza, A. Graves, T. P. Lillicrap, T. Harley, D. Silver, and K. Kavukcuoglu. Asynchronous methods for deep reinforcement learning. In Proceedings of the 33nd International Conference on Machine Learning, ICML 2016, New York City, NY, USA, June 19-24, 2016, pages 1928–1937, 2016
- 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.
- H. Kushner and G. Yin. Stochastic approximation algorithms and applications. Springer, 1997.

## Frequently Asked Questions

Q: What is the prediction methodology for LON:HICL stock?A: LON:HICL stock prediction methodology: We evaluate the prediction models Modular Neural Network (Speculative Sentiment Analysis) and Logistic Regression

Q: Is LON:HICL stock a buy or sell?

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

Q: Is HICL INFRASTRUCTURE PLC stock a good investment?

A: The consensus rating for HICL INFRASTRUCTURE PLC is Hold and assigned short-term B3 & long-term Ba3 forecasted stock rating.

Q: What is the consensus rating of LON:HICL stock?

A: The consensus rating for LON:HICL is Hold.

Q: What is the prediction period for LON:HICL stock?

A: The prediction period for LON:HICL is (n+1 year)