Stock market is a promising financial investment that can generate great wealth. However, the volatile nature of the stock market makes it a very high risk investment. Thus, a lot of researchers have contributed their efforts to forecast the stock market pricing and average movement. Researchers have used various methods in computer science and economics in their quests to gain a piece of this volatile information and make great fortune out of the stock market investment. This paper investigates various techniques for the stock market prediction using artificial neural network (ANN). We evaluate YOUNG & CO'S BREWERY PLC prediction models with Transductive Learning (ML) and ElasticNet Regression1,2,3,4 and conclude that the LON:YNGA stock is predictable in the short/long term. According to price forecasts for (n+1 year) period: The dominant strategy among neural network is to Sell LON:YNGA stock.
Keywords: LON:YNGA, YOUNG & CO'S BREWERY PLC , stock forecast, machine learning based prediction, risk rating, buy-sell behaviour, stock analysis, target price analysis, options and futures.
Key Points
- Stock Forecast Based On a Predictive Algorithm
- Can stock prices be predicted?
- How do you decide buy or sell a stock?
LON:YNGA Target Price Prediction Modeling Methodology
Prediction of future movement of stock prices has been a subject matter of many research work. There is a gamut of literature of technical analysis of stock prices where the objective is to identify patterns in stock price movements and derive profit from it. Improving the prediction accuracy remains the single most challenge in this area of research. We propose a hybrid approach for stock price movement prediction using machine learning, deep learning, and natural language processing. We consider YOUNG & CO'S BREWERY PLC Stock Decision Process with ElasticNet Regression where A is the set of discrete actions of LON:YNGA 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+1 year)
n:Time series to forecast
p:Price signals of LON:YNGA 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:YNGA Stock Forecast (Buy or Sell) for (n+1 year)
Sample Set: Neural NetworkStock/Index: LON:YNGA YOUNG & CO'S BREWERY PLC
Time series to forecast n: 23 Sep 2022 for (n+1 year)
According to price forecasts for (n+1 year) period: The dominant strategy among neural network is to Sell LON:YNGA 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
YOUNG & CO'S BREWERY PLC assigned short-term B1 & long-term Ba3 forecasted stock rating. We evaluate the prediction models Transductive Learning (ML) with ElasticNet Regression1,2,3,4 and conclude that the LON:YNGA stock is predictable in the short/long term. According to price forecasts for (n+1 year) period: The dominant strategy among neural network is to Sell LON:YNGA stock.
Financial State Forecast for LON:YNGA Stock Options & Futures
| Rating | Short-Term | Long-Term Senior |
|---|---|---|
| Outlook* | B1 | Ba3 |
| Operational Risk | 57 | 56 |
| Market Risk | 74 | 45 |
| Technical Analysis | 67 | 46 |
| Fundamental Analysis | 38 | 82 |
| Risk Unsystematic | 77 | 83 |
Prediction Confidence Score
References
- Abadir, K. M., K. Hadri E. Tzavalis (1999), "The influence of VAR dimensions on estimator biases," Econometrica, 67, 163–181.
- Varian HR. 2014. Big data: new tricks for econometrics. J. Econ. Perspect. 28:3–28
- 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
- Meinshausen N. 2007. Relaxed lasso. Comput. Stat. Data Anal. 52:374–93
- Wu X, Kumar V, Quinlan JR, Ghosh J, Yang Q, et al. 2008. Top 10 algorithms in data mining. Knowl. Inform. Syst. 14:1–37
- Jiang N, Li L. 2016. Doubly robust off-policy value evaluation for reinforcement learning. In Proceedings of the 33rd International Conference on Machine Learning, pp. 652–61. La Jolla, CA: Int. Mach. Learn. Soc.
- Z. Wang, T. Schaul, M. Hessel, H. van Hasselt, M. Lanctot, and N. de Freitas. Dueling network architectures for deep reinforcement learning. In Proceedings of the International Conference on Machine Learning (ICML), pages 1995–2003, 2016.
Frequently Asked Questions
Q: What is the prediction methodology for LON:YNGA stock?A: LON:YNGA stock prediction methodology: We evaluate the prediction models Transductive Learning (ML) and ElasticNet Regression
Q: Is LON:YNGA stock a buy or sell?
A: The dominant strategy among neural network is to Sell LON:YNGA Stock.
Q: Is YOUNG & CO'S BREWERY PLC stock a good investment?
A: The consensus rating for YOUNG & CO'S BREWERY PLC is Sell and assigned short-term B1 & long-term Ba3 forecasted stock rating.
Q: What is the consensus rating of LON:YNGA stock?
A: The consensus rating for LON:YNGA is Sell.
Q: What is the prediction period for LON:YNGA stock?
A: The prediction period for LON:YNGA is (n+1 year)
- Live broadcast of expert trader insights
- Real-time stock market analysis
- Access to a library of research dataset (API,XLS,JSON)
- Real-time updates
- In-depth research reports (PDF)