Short - term price movements, contribute a considerable measure to the unpredictability of the securities exchanges. Accurately predicting the price fluctuations in stock market is a huge economical advantage. The aforementioned task is generally achieved by analyzing the company, this is called as fundamental analysis. Another method, which is undergoing a lot of research work recently, is to create a predictive algorithmic model using machine learning. To train machines to take trading decisions in such short - period of time, the latter method needs to be adopted. Deep Neural Networks, being the most exceptional innovation in Machine Learning, have been utilized to develop a short-term prediction model. We evaluate LIONTRUST ASSET MANAGEMENT PLC prediction models with Modular Neural Network (Market Volatility Analysis) and Multiple Regression1,2,3,4 and conclude that the LON:LIO stock is predictable in the short/long term. According to price forecasts for (n+3 month) period: The dominant strategy among neural network is to Sell LON:LIO stock.
Keywords: LON:LIO, LIONTRUST ASSET MANAGEMENT PLC, stock forecast, machine learning based prediction, risk rating, buy-sell behaviour, stock analysis, target price analysis, options and futures.
Key Points
- What is prediction model?
- Should I buy stocks now or wait amid such uncertainty?
- Stock Forecast Based On a Predictive Algorithm
LON:LIO Target Price Prediction Modeling Methodology
The stock market is one of the key sectors of a country's economy. It provides investors with an opportunity to invest and gain returns on their investment. Predicting the stock market is a very challenging task and has attracted serious interest from researchers from many fields such as statistics, artificial intelligence, economics, and finance. An accurate prediction of the stock market reduces investment risk in the market. Different approaches have been used to predict the stock market. The performances of Machine learning (ML) models are typically superior to those of statistical and econometric models. We consider LIONTRUST ASSET MANAGEMENT PLC Stock Decision Process with Multiple Regression where A is the set of discrete actions of LON:LIO 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(Multiple Regression)5,6,7= X R(Modular Neural Network (Market Volatility Analysis)) X S(n):→ (n+3 month)
n:Time series to forecast
p:Price signals of LON:LIO 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:LIO Stock Forecast (Buy or Sell) for (n+3 month)
Sample Set: Neural NetworkStock/Index: LON:LIO LIONTRUST ASSET MANAGEMENT PLC
Time series to forecast n: 22 Oct 2022 for (n+3 month)
According to price forecasts for (n+3 month) period: The dominant strategy among neural network is to Sell LON:LIO 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
LIONTRUST ASSET MANAGEMENT PLC assigned short-term Ba3 & long-term B2 forecasted stock rating. We evaluate the prediction models Modular Neural Network (Market Volatility Analysis) with Multiple Regression1,2,3,4 and conclude that the LON:LIO stock is predictable in the short/long term. According to price forecasts for (n+3 month) period: The dominant strategy among neural network is to Sell LON:LIO stock.
Financial State Forecast for LON:LIO Stock Options & Futures
| Rating | Short-Term | Long-Term Senior |
|---|---|---|
| Outlook* | Ba3 | B2 |
| Operational Risk | 30 | 51 |
| Market Risk | 76 | 59 |
| Technical Analysis | 73 | 50 |
| Fundamental Analysis | 70 | 47 |
| Risk Unsystematic | 67 | 45 |
Prediction Confidence Score
References
- M. Petrik and D. Subramanian. An approximate solution method for large risk-averse Markov decision processes. In Proceedings of the 28th International Conference on Uncertainty in Artificial Intelligence, 2012.
- Clements, M. P. D. F. Hendry (1995), "Forecasting in cointegrated systems," Journal of Applied Econometrics, 10, 127–146.
- Y. Le Tallec. Robust, risk-sensitive, and data-driven control of Markov decision processes. PhD thesis, Massachusetts Institute of Technology, 2007.
- J. Filar, L. Kallenberg, and H. Lee. Variance-penalized Markov decision processes. Mathematics of Opera- tions Research, 14(1):147–161, 1989
- D. Bertsekas and J. Tsitsiklis. Neuro-dynamic programming. Athena Scientific, 1996.
- Canova, F. B. E. Hansen (1995), "Are seasonal patterns constant over time? A test for seasonal stability," Journal of Business and Economic Statistics, 13, 237–252.
- White H. 1992. Artificial Neural Networks: Approximation and Learning Theory. Oxford, UK: Blackwell
Frequently Asked Questions
Q: What is the prediction methodology for LON:LIO stock?A: LON:LIO stock prediction methodology: We evaluate the prediction models Modular Neural Network (Market Volatility Analysis) and Multiple Regression
Q: Is LON:LIO stock a buy or sell?
A: The dominant strategy among neural network is to Sell LON:LIO Stock.
Q: Is LIONTRUST ASSET MANAGEMENT PLC stock a good investment?
A: The consensus rating for LIONTRUST ASSET MANAGEMENT PLC is Sell and assigned short-term Ba3 & long-term B2 forecasted stock rating.
Q: What is the consensus rating of LON:LIO stock?
A: The consensus rating for LON:LIO is Sell.
Q: What is the prediction period for LON:LIO stock?
A: The prediction period for LON:LIO is (n+3 month)
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