Machine Learning stock prediction: LON:DEV Stock Prediction

Accurate prediction of stock price movements is highly challenging and significant topic for investors. Investors need to understand that stock price data is the most essential information which is highly volatile, non-linear, and non-parametric and are affected by many uncertainties and interrelated economic and political factors across the globe. Artificial Neural Networks (ANN) have been found to be an efficient tool in modeling stock prices and quite a large number of studies have been done on it. We evaluate DEV CLEVER HOLDINGS PLC prediction models with Modular Neural Network (Speculative Sentiment Analysis) and Lasso Regression^1,2,3,4 and conclude that the LON:DEV 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:DEV stock.

Keywords: LON:DEV, DEV CLEVER HOLDINGS PLC, stock forecast, machine learning based prediction, risk rating, buy-sell behaviour, stock analysis, target price analysis, options and futures.

Key Points

1. What are buy sell or hold recommendations?
2. Trading Signals
3. Should I buy stocks now or wait amid such uncertainty?

LON:DEV Target Price Prediction Modeling Methodology

Prediction of future movement of stock prices has always been a challenging task for the researchers. While the advocates of the efficient market hypothesis (EMH) believe that it is impossible to design any predictive framework that can accurately predict the movement of stock prices, there are seminal work in the literature that have clearly demonstrated that the seemingly random movement patterns in the time series of a stock price can be predicted with a high level of accuracy. We consider DEV CLEVER HOLDINGS PLC Stock Decision Process with Lasso Regression where A is the set of discrete actions of LON:DEV 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(Lasso Regression)^5,6,7= $\begin{array}{cccc}{p}_{\mathrm{a}1}& p_{\mathrm{a}2}& \dots & p_{1n}\\ & ⋮\\ p_{j1}& p_{j2}& \dots & p_{jn}\\ & ⋮\\ p_{k1}& p_{k2}& \dots & p_{kn}\\ & ⋮\\ p_{n1}& p_{n2}& \dots & p_{nn}\end{array}$ X R(Modular Neural Network (Speculative Sentiment Analysis)) X S(n):→ (n+6 month) $R=\left(\begin{array}{ccc}1& 0& 0\\ 0& 1& 0\\ 0& 0& 1\end{array}\right)$

n:Time series to forecast

p:Price signals of LON:DEV 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:DEV Stock Forecast (Buy or Sell) for (n+6 month)

Sample Set: Neural Network
Stock/Index: LON:DEV DEV CLEVER HOLDINGS PLC
Time series to forecast n: 12 Sep 2022 for (n+6 month)

According to price forecasts for (n+6 month) period: The dominant strategy among neural network is to Hold LON:DEV 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

DEV CLEVER HOLDINGS PLC assigned short-term B3 & long-term Ba1 forecasted stock rating. We evaluate the prediction models Modular Neural Network (Speculative Sentiment Analysis) with Lasso Regression^1,2,3,4 and conclude that the LON:DEV 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:DEV stock.

Financial State Forecast for LON:DEV Stock Options & Futures

Rating	Short-Term	Long-Term Senior
Outlook*	B3	Ba1
Operational Risk	44	49
Market Risk	33	86
Technical Analysis	36	86
Fundamental Analysis	63	75
Risk Unsystematic	67	60

Prediction Confidence Score

Trust metric by Neural Network: 86 out of 100 with 484 signals.

References

1. Hirano K, Porter JR. 2009. Asymptotics for statistical treatment rules. Econometrica 77:1683–701
2. Chipman HA, George EI, McCulloch RE. 2010. Bart: Bayesian additive regression trees. Ann. Appl. Stat. 4:266–98
3. S. Bhatnagar, R. Sutton, M. Ghavamzadeh, and M. Lee. Natural actor-critic algorithms. Automatica, 45(11): 2471–2482, 2009
4. R. Sutton and A. Barto. Introduction to reinforcement learning. MIT Press, 1998
5. Hastie T, Tibshirani R, Tibshirani RJ. 2017. Extended comparisons of best subset selection, forward stepwise selection, and the lasso. arXiv:1707.08692 [stat.ME]
6. G. Shani, R. Brafman, and D. Heckerman. An MDP-based recommender system. In Proceedings of the Eigh- teenth conference on Uncertainty in artificial intelligence, pages 453–460. Morgan Kaufmann Publishers Inc., 2002
7. M. J. Hausknecht. Cooperation and Communication in Multiagent Deep Reinforcement Learning. PhD thesis, The University of Texas at Austin, 2016

Frequently Asked Questions

Q: What is the prediction methodology for LON:DEV stock?
A: LON:DEV stock prediction methodology: We evaluate the prediction models Modular Neural Network (Speculative Sentiment Analysis) and Lasso Regression
Q: Is LON:DEV stock a buy or sell?
A: The dominant strategy among neural network is to Hold LON:DEV Stock.
Q: Is DEV CLEVER HOLDINGS PLC stock a good investment?
A: The consensus rating for DEV CLEVER HOLDINGS PLC is Hold and assigned short-term B3 & long-term Ba1 forecasted stock rating.
Q: What is the consensus rating of LON:DEV stock?
A: The consensus rating for LON:DEV is Hold.
Q: What is the prediction period for LON:DEV stock?
A: The prediction period for LON:DEV is (n+6 month)

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