Prediction of stock market movement is extremely difficult due to its high mutable nature. The rapid ups and downs occur in stock market because of impact from foreign commodities like emotional behavior of investors, political, psychological and economical factors. Continuous unsettlement in the stock market is major reason why investors sell out at the wrong time and often fail to gain the benefit. While investing in stock market investors must not forget the risk of reward rule and expose their holdings to greater risks. Although it is not possible predict stock market movement with full accuracy, losses from selling stocks at wrong time and its impacts can be reduce to greater extent using prediction of stock market movement based on analysis of historical data. We evaluate DEKEL AGRI-VISION PLC prediction models with Ensemble Learning (ML) and Factor1,2,3,4 and conclude that the LON:DKL 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:DKL stock.
Keywords: LON:DKL, DEKEL AGRI-VISION PLC, stock forecast, machine learning based prediction, risk rating, buy-sell behaviour, stock analysis, target price analysis, options and futures.
Key Points
- Can we predict stock market using machine learning?
- How useful are statistical predictions?
- Operational Risk
LON:DKL Target Price Prediction Modeling Methodology
The research reported in the paper focuses on the stock market prediction problem, the main aim being the development of a methodology to forecast the stock closing price. The methodology is based on some novel variable selection methods and an analysis of neural network and support vector machines based prediction models. Also, a hybrid approach which combines the use of the variables derived from technical and fundamental analysis of stock market indicators in order to improve prediction results of the proposed approaches is reported in this paper. We consider DEKEL AGRI-VISION PLC Stock Decision Process with Factor where A is the set of discrete actions of LON:DKL 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(Factor)5,6,7= X R(Ensemble Learning (ML)) X S(n):→ (n+4 weeks)
n:Time series to forecast
p:Price signals of LON:DKL stock
j:Nash equilibria
k:Dominated move
a:Best response for target price
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LON:DKL Stock Forecast (Buy or Sell) for (n+4 weeks)
Sample Set: Neural NetworkStock/Index: LON:DKL DEKEL AGRI-VISION PLC
Time series to forecast n: 15 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:DKL 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
DEKEL AGRI-VISION PLC assigned short-term Ba3 & long-term B3 forecasted stock rating. We evaluate the prediction models Ensemble Learning (ML) with Factor1,2,3,4 and conclude that the LON:DKL 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:DKL stock.
Financial State Forecast for LON:DKL Stock Options & Futures
| Rating | Short-Term | Long-Term Senior |
|---|---|---|
| Outlook* | Ba3 | B3 |
| Operational Risk | 49 | 30 |
| Market Risk | 89 | 30 |
| Technical Analysis | 73 | 32 |
| Fundamental Analysis | 71 | 71 |
| Risk Unsystematic | 35 | 50 |
Prediction Confidence Score
References
- A. K. Agogino and K. Tumer. Analyzing and visualizing multiagent rewards in dynamic and stochastic environments. Journal of Autonomous Agents and Multi-Agent Systems, 17(2):320–338, 2008
- Imbens GW, Rubin DB. 2015. Causal Inference in Statistics, Social, and Biomedical Sciences. Cambridge, UK: Cambridge Univ. Press
- Armstrong, J. S. M. C. Grohman (1972), "A comparative study of methods for long-range market forecasting," Management Science, 19, 211–221.
- Bai J, Ng S. 2017. Principal components and regularized estimation of factor models. arXiv:1708.08137 [stat.ME]
- Alpaydin E. 2009. Introduction to Machine Learning. Cambridge, MA: MIT Press
- Brailsford, T.J. R.W. Faff (1996), "An evaluation of volatility forecasting techniques," Journal of Banking Finance, 20, 419–438.
- Mnih A, Hinton GE. 2007. Three new graphical models for statistical language modelling. In International Conference on Machine Learning, pp. 641–48. La Jolla, CA: Int. Mach. Learn. Soc.
Frequently Asked Questions
Q: What is the prediction methodology for LON:DKL stock?A: LON:DKL stock prediction methodology: We evaluate the prediction models Ensemble Learning (ML) and Factor
Q: Is LON:DKL stock a buy or sell?
A: The dominant strategy among neural network is to Hold LON:DKL Stock.
Q: Is DEKEL AGRI-VISION PLC stock a good investment?
A: The consensus rating for DEKEL AGRI-VISION PLC is Hold and assigned short-term Ba3 & long-term B3 forecasted stock rating.
Q: What is the consensus rating of LON:DKL stock?
A: The consensus rating for LON:DKL is Hold.
Q: What is the prediction period for LON:DKL stock?
A: The prediction period for LON:DKL is (n+4 weeks)
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