It has never been easy to invest in a set of assets, the abnormally of financial market does not allow simple models to predict future asset values with higher accuracy. Machine learning, which consist of making computers perform tasks that normally requiring human intelligence is currently the dominant trend in scientific research. This article aims to build a model using Recurrent Neural Networks (RNN) and especially Long-Short Term Memory model (LSTM) to predict future stock market values. We evaluate EAGLE EYE SOLUTIONS GROUP PLC prediction models with Transductive Learning (ML) and ElasticNet Regression1,2,3,4 and conclude that the LON:EYE stock is predictable in the short/long term. According to price forecasts for (n+6 month) period: The dominant strategy among neural network is to Hold LON:EYE stock.
Keywords: LON:EYE, EAGLE EYE SOLUTIONS GROUP PLC, stock forecast, machine learning based prediction, risk rating, buy-sell behaviour, stock analysis, target price analysis, options and futures.
Key Points
- Technical Analysis with Algorithmic Trading
- Can machine learning predict?
- What is a prediction confidence?
LON:EYE Target Price Prediction Modeling Methodology
It has never been easy to invest in a set of assets, the abnormally of financial market does not allow simple models to predict future asset values with higher accuracy. Machine learning, which consist of making computers perform tasks that normally requiring human intelligence is currently the dominant trend in scientific research. This article aims to build a model using Recurrent Neural Networks (RNN) and especially Long-Short Term Memory model (LSTM) to predict future stock market values. We consider EAGLE EYE SOLUTIONS GROUP PLC Stock Decision Process with ElasticNet Regression where A is the set of discrete actions of LON:EYE 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(ElasticNet Regression)5,6,7= X R(Transductive Learning (ML)) X S(n):→ (n+6 month)
n:Time series to forecast
p:Price signals of LON:EYE 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:EYE Stock Forecast (Buy or Sell) for (n+6 month)
Sample Set: Neural NetworkStock/Index: LON:EYE EAGLE EYE SOLUTIONS GROUP PLC
Time series to forecast n: 23 Oct 2022 for (n+6 month)
According to price forecasts for (n+6 month) period: The dominant strategy among neural network is to Hold LON:EYE 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
EAGLE EYE SOLUTIONS GROUP PLC assigned short-term B3 & long-term B1 forecasted stock rating. We evaluate the prediction models Transductive Learning (ML) with ElasticNet Regression1,2,3,4 and conclude that the LON:EYE stock is predictable in the short/long term. According to price forecasts for (n+6 month) period: The dominant strategy among neural network is to Hold LON:EYE stock.
Financial State Forecast for LON:EYE Stock Options & Futures
| Rating | Short-Term | Long-Term Senior |
|---|---|---|
| Outlook* | B3 | B1 |
| Operational Risk | 32 | 63 |
| Market Risk | 41 | 48 |
| Technical Analysis | 64 | 65 |
| Fundamental Analysis | 32 | 56 |
| Risk Unsystematic | 68 | 60 |
Prediction Confidence Score
References
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- Thomas P, Brunskill E. 2016. Data-efficient off-policy policy evaluation for reinforcement learning. In Pro- ceedings of the International Conference on Machine Learning, pp. 2139–48. La Jolla, CA: Int. Mach. Learn. Soc.
- Dimakopoulou M, Athey S, Imbens G. 2017. Estimation considerations in contextual bandits. arXiv:1711.07077 [stat.ML]
- Athey S, Imbens G. 2016. Recursive partitioning for heterogeneous causal effects. PNAS 113:7353–60
- O. Bardou, N. Frikha, and G. Pag`es. Computing VaR and CVaR using stochastic approximation and adaptive unconstrained importance sampling. Monte Carlo Methods and Applications, 15(3):173–210, 2009.
Frequently Asked Questions
Q: What is the prediction methodology for LON:EYE stock?A: LON:EYE stock prediction methodology: We evaluate the prediction models Transductive Learning (ML) and ElasticNet Regression
Q: Is LON:EYE stock a buy or sell?
A: The dominant strategy among neural network is to Hold LON:EYE Stock.
Q: Is EAGLE EYE SOLUTIONS GROUP PLC stock a good investment?
A: The consensus rating for EAGLE EYE SOLUTIONS GROUP PLC is Hold and assigned short-term B3 & long-term B1 forecasted stock rating.
Q: What is the consensus rating of LON:EYE stock?
A: The consensus rating for LON:EYE is Hold.
Q: What is the prediction period for LON:EYE stock?
A: The prediction period for LON:EYE is (n+6 month)
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