This paper surveys machine learning techniques for stock market prediction. The prediction of stock markets is regarded as a challenging task of financial time series prediction.** We evaluate YOURGENE HEALTH PLC prediction models with Modular Neural Network (Emotional Trigger/Responses Analysis) and Spearman Correlation ^{1,2,3,4} and conclude that the LON:YGEN stock is predictable in the short/long term. **

**According to price forecasts for (n+4 weeks) period: The dominant strategy among neural network is to Hold LON:YGEN stock.**

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

*Keywords:*## Key Points

- What are main components of Markov decision process?
- How do predictive algorithms actually work?
- Can statistics predict the future?

## LON:YGEN Target Price Prediction Modeling Methodology

This paper addresses problem of predicting direction of movement of stock and stock price index. The study compares four prediction models, Artificial Neural Network (ANN), Support Vector Machine (SVM), random forest and naive-Bayes with two approaches for input to these models. We consider YOURGENE HEALTH PLC Stock Decision Process with Spearman Correlation where A is the set of discrete actions of LON:YGEN 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(Spearman Correlation)

^{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 (Emotional Trigger/Responses Analysis)) X S(n):→ (n+4 weeks) $R=\left(\begin{array}{ccc}1& 0& 0\\ 0& 1& 0\\ 0& 0& 1\end{array}\right)$

n:Time series to forecast

p:Price signals of LON:YGEN 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:YGEN Stock Forecast (Buy or Sell) for (n+4 weeks)

**Sample Set:**Neural Network

**Stock/Index:**LON:YGEN YOURGENE HEALTH PLC

**Time series to forecast n: 28 Sep 2022**for (n+4 weeks)

**According to price forecasts for (n+4 weeks) period: The dominant strategy among neural network is to Hold LON:YGEN 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

YOURGENE HEALTH PLC assigned short-term B3 & long-term Ba2 forecasted stock rating.** We evaluate the prediction models Modular Neural Network (Emotional Trigger/Responses Analysis) with Spearman Correlation ^{1,2,3,4} and conclude that the LON:YGEN stock is predictable in the short/long term.**

**According to price forecasts for (n+4 weeks) period: The dominant strategy among neural network is to Hold LON:YGEN stock.**

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

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

Outlook* | B3 | Ba2 |

Operational Risk | 62 | 54 |

Market Risk | 53 | 59 |

Technical Analysis | 46 | 78 |

Fundamental Analysis | 40 | 87 |

Risk Unsystematic | 46 | 62 |

### Prediction Confidence Score

## References

- Babula, R. A. (1988), "Contemporaneous correlation and modeling Canada's imports of U.S. crops," Journal of Agricultural Economics Research, 41, 33–38.
- Van der Vaart AW. 2000. Asymptotic Statistics. Cambridge, UK: Cambridge Univ. Press
- L. Busoniu, R. Babuska, and B. D. Schutter. A comprehensive survey of multiagent reinforcement learning. IEEE Transactions of Systems, Man, and Cybernetics Part C: Applications and Reviews, 38(2), 2008.
- Allen, P. G. (1994), "Economic forecasting in agriculture," International Journal of Forecasting, 10, 81–135.
- Efron B, Hastie T. 2016. Computer Age Statistical Inference, Vol. 5. Cambridge, UK: Cambridge Univ. Press
- R. Sutton, D. McAllester, S. Singh, and Y. Mansour. Policy gradient methods for reinforcement learning with function approximation. In Proceedings of Advances in Neural Information Processing Systems 12, pages 1057–1063, 2000
- S. J. Russell and A. Zimdars. Q-decomposition for reinforcement learning agents. In Machine Learning, Proceedings of the Twentieth International Conference (ICML 2003), August 21-24, 2003, Washington, DC, USA, pages 656–663, 2003.

## Frequently Asked Questions

Q: What is the prediction methodology for LON:YGEN stock?A: LON:YGEN stock prediction methodology: We evaluate the prediction models Modular Neural Network (Emotional Trigger/Responses Analysis) and Spearman Correlation

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

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

Q: Is YOURGENE HEALTH PLC stock a good investment?

A: The consensus rating for YOURGENE HEALTH PLC is Hold and assigned short-term B3 & long-term Ba2 forecasted stock rating.

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

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

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

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

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