**Outlook:**HELIOS TOWERS PLC assigned short-term B2 & long-term Ba1 forecasted stock rating.

**Dominant Strategy :**Buy

**Time series to forecast n: 10 Dec 2022**for (n+4 weeks)

**Methodology :**Modular Neural Network (Financial Sentiment Analysis)

## Abstract

Prediction of future movement of stock prices has been a subject matter of many research work. In this work, we propose a hybrid approach for stock price prediction using machine learning and deep learning-based methods.(Chen, S. and He, H., 2018, October. Stock prediction using convolutional neural network. In IOP Conference series: materials science and engineering (Vol. 435, No. 1, p. 012026). IOP Publishing.)** We evaluate HELIOS TOWERS PLC prediction models with Modular Neural Network (Financial Sentiment Analysis) and Chi-Square ^{1,2,3,4} and conclude that the LON:HTWS stock is predictable in the short/long term. **

**According to price forecasts for (n+4 weeks) period, the dominant strategy among neural network is: Buy**

## Key Points

- Why do we need predictive models?
- Is it better to buy and sell or hold?
- Prediction Modeling

## LON:HTWS Target Price Prediction Modeling Methodology

We consider HELIOS TOWERS PLC Decision Process with Modular Neural Network (Financial Sentiment Analysis) where A is the set of discrete actions of LON:HTWS 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(Chi-Square)

^{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 (Financial Sentiment Analysis)) X S(n):→ (n+4 weeks) $\begin{array}{l}\int {r}^{s}\mathrm{rs}\end{array}$

n:Time series to forecast

p:Price signals of LON:HTWS 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?

## LON:HTWS Stock Forecast (Buy or Sell) for (n+4 weeks)

**Sample Set:**Neural Network

**Stock/Index:**LON:HTWS HELIOS TOWERS PLC

**Time series to forecast n: 10 Dec 2022**for (n+4 weeks)

**According to price forecasts for (n+4 weeks) period, the dominant strategy among neural network is: Buy**

**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 HELIOS TOWERS PLC

- If there is a hedging relationship between a non-derivative monetary asset and a non-derivative monetary liability, changes in the foreign currency component of those financial instruments are presented in profit or loss.
- Because the hedge accounting model is based on a general notion of offset between gains and losses on the hedging instrument and the hedged item, hedge effectiveness is determined not only by the economic relationship between those items (ie the changes in their underlyings) but also by the effect of credit risk on the value of both the hedging instrument and the hedged item. The effect of credit risk means that even if there is an economic relationship between the hedging instrument and the hedged item, the level of offset might become erratic. This can result from a change in the credit risk of either the hedging instrument or the hedged item that is of such a magnitude that the credit risk dominates the value changes that result from the economic relationship (ie the effect of the changes in the underlyings). A level of magnitude that gives rise to dominance is one that would result in the loss (or gain) from credit risk frustrating the effect of changes in the underlyings on the value of the hedging instrument or the hedged item, even if those changes were significant.
- If, at the date of initial application, determining whether there has been a significant increase in credit risk since initial recognition would require undue cost or effort, an entity shall recognise a loss allowance at an amount equal to lifetime expected credit losses at each reporting date until that financial instrument is derecognised (unless that financial instrument is low credit risk at a reporting date, in which case paragraph 7.2.19(a) applies).
- Because the hedge accounting model is based on a general notion of offset between gains and losses on the hedging instrument and the hedged item, hedge effectiveness is determined not only by the economic relationship between those items (ie the changes in their underlyings) but also by the effect of credit risk on the value of both the hedging instrument and the hedged item. The effect of credit risk means that even if there is an economic relationship between the hedging instrument and the hedged item, the level of offset might become erratic. This can result from a change in the credit risk of either the hedging instrument or the hedged item that is of such a magnitude that the credit risk dominates the value changes that result from the economic relationship (ie the effect of the changes in the underlyings). A level of magnitude that gives rise to dominance is one that would result in the loss (or gain) from credit risk frustrating the effect of changes in the underlyings on the value of the hedging instrument or the hedged item, even if those changes were significant.

*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

HELIOS TOWERS PLC assigned short-term B2 & long-term Ba1 forecasted stock rating.** We evaluate the prediction models Modular Neural Network (Financial Sentiment Analysis) with Chi-Square ^{1,2,3,4} and conclude that the LON:HTWS stock is predictable in the short/long term.**

**According to price forecasts for (n+4 weeks) period, the dominant strategy among neural network is: Buy**

### Financial State Forecast for LON:HTWS HELIOS TOWERS PLC Options & Futures

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

Outlook* | B2 | Ba1 |

Operational Risk | 53 | 74 |

Market Risk | 74 | 86 |

Technical Analysis | 58 | 56 |

Fundamental Analysis | 56 | 81 |

Risk Unsystematic | 47 | 51 |

### 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
- S. Bhatnagar and K. Lakshmanan. An online actor-critic algorithm with function approximation for con- strained Markov decision processes. Journal of Optimization Theory and Applications, 153(3):688–708, 2012.
- J. Z. Leibo, V. Zambaldi, M. Lanctot, J. Marecki, and T. Graepel. Multi-agent Reinforcement Learning in Sequential Social Dilemmas. In Proceedings of the 16th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2017), Sao Paulo, Brazil, 2017
- Chernozhukov V, Demirer M, Duflo E, Fernandez-Val I. 2018b. Generic machine learning inference on heteroge- nous treatment effects in randomized experiments. NBER Work. Pap. 24678
- M. J. Hausknecht. Cooperation and Communication in Multiagent Deep Reinforcement Learning. PhD thesis, The University of Texas at Austin, 2016
- D. Bertsekas. Min common/max crossing duality: A geometric view of conjugacy in convex optimization. Lab. for Information and Decision Systems, MIT, Tech. Rep. Report LIDS-P-2796, 2009
- Zou H, Hastie T. 2005. Regularization and variable selection via the elastic net. J. R. Stat. Soc. B 67:301–20

## Frequently Asked Questions

Q: What is the prediction methodology for LON:HTWS stock?A: LON:HTWS stock prediction methodology: We evaluate the prediction models Modular Neural Network (Financial Sentiment Analysis) and Chi-Square

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

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

Q: Is HELIOS TOWERS PLC stock a good investment?

A: The consensus rating for HELIOS TOWERS PLC is Buy and assigned short-term B2 & long-term Ba1 forecasted stock rating.

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

A: The consensus rating for LON:HTWS is Buy.

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

A: The prediction period for LON:HTWS is (n+4 weeks)