Three networks are compared for low false alarm stock trend predictions. Short-term trends, particularly attractive for neural network analysis, can be used profitably in scenarios such as option trading, but only with significant risk. Therefore, we focus on limiting false alarms, which improves the risk/reward ratio by preventing losses. To predict stock trends, we exploit time delay, recurrent, and probabilistic neural networks (TDNN, RNN, and PNN, respectively), utilizing conjugate gradient and multistream extended Kalman filter training for TDNN and RNN. We evaluate BOTSWANA DIAMONDS PLC prediction models with Modular Neural Network (Financial Sentiment Analysis) and Multiple Regression1,2,3,4 and conclude that the LON:BOD 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 Hold LON:BOD stock.
Keywords: LON:BOD, BOTSWANA DIAMONDS PLC, stock forecast, machine learning based prediction, risk rating, buy-sell behaviour, stock analysis, target price analysis, options and futures.
Key Points
- Market Outlook
- What is Markov decision process in reinforcement learning?
- Is now good time to invest?
LON:BOD Target Price Prediction Modeling Methodology
In the finance world stock trading is one of the most important activities. Stock market prediction is an act of trying to determine the future value of a stock other financial instrument traded on a financial exchange. This paper explains the prediction of a stock using Machine Learning. The technical and fundamental or the time series analysis is used by the most of the stockbrokers while making the stock predictions. We consider BOTSWANA DIAMONDS PLC Stock Decision Process with Multiple Regression where A is the set of discrete actions of LON:BOD 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 (Financial Sentiment Analysis)) X S(n):→ (n+3 month)
n:Time series to forecast
p:Price signals of LON:BOD 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:BOD Stock Forecast (Buy or Sell) for (n+3 month)
Sample Set: Neural NetworkStock/Index: LON:BOD BOTSWANA DIAMONDS PLC
Time series to forecast n: 10 Sep 2022 for (n+3 month)
According to price forecasts for (n+3 month) period: The dominant strategy among neural network is to Hold LON:BOD 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
BOTSWANA DIAMONDS PLC assigned short-term B3 & long-term B2 forecasted stock rating. We evaluate the prediction models Modular Neural Network (Financial Sentiment Analysis) with Multiple Regression1,2,3,4 and conclude that the LON:BOD 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 Hold LON:BOD stock.
Financial State Forecast for LON:BOD Stock Options & Futures
| Rating | Short-Term | Long-Term Senior |
|---|---|---|
| Outlook* | B3 | B2 |
| Operational Risk | 59 | 74 |
| Market Risk | 46 | 36 |
| Technical Analysis | 53 | 50 |
| Fundamental Analysis | 38 | 60 |
| Risk Unsystematic | 55 | 54 |
Prediction Confidence Score
References
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- Schapire RE, Freund Y. 2012. Boosting: Foundations and Algorithms. Cambridge, MA: MIT Press
- C. Claus and C. Boutilier. The dynamics of reinforcement learning in cooperative multiagent systems. In Proceedings of the Fifteenth National Conference on Artificial Intelligence and Tenth Innovative Applications of Artificial Intelligence Conference, AAAI 98, IAAI 98, July 26-30, 1998, Madison, Wisconsin, USA., pages 746–752, 1998.
- Mnih A, Teh YW. 2012. A fast and simple algorithm for training neural probabilistic language models. In Proceedings of the 29th International Conference on Machine Learning, pp. 419–26. La Jolla, CA: Int. Mach. Learn. Soc.
- Bengio Y, Schwenk H, Senécal JS, Morin F, Gauvain JL. 2006. Neural probabilistic language models. In Innovations in Machine Learning: Theory and Applications, ed. DE Holmes, pp. 137–86. Berlin: Springer
- Athey S, Blei D, Donnelly R, Ruiz F. 2017b. Counterfactual inference for consumer choice across many prod- uct categories. AEA Pap. Proc. 108:64–67
- Meinshausen N. 2007. Relaxed lasso. Comput. Stat. Data Anal. 52:374–93
Frequently Asked Questions
Q: What is the prediction methodology for LON:BOD stock?A: LON:BOD stock prediction methodology: We evaluate the prediction models Modular Neural Network (Financial Sentiment Analysis) and Multiple Regression
Q: Is LON:BOD stock a buy or sell?
A: The dominant strategy among neural network is to Hold LON:BOD Stock.
Q: Is BOTSWANA DIAMONDS PLC stock a good investment?
A: The consensus rating for BOTSWANA DIAMONDS PLC is Hold and assigned short-term B3 & long-term B2 forecasted stock rating.
Q: What is the consensus rating of LON:BOD stock?
A: The consensus rating for LON:BOD is Hold.
Q: What is the prediction period for LON:BOD stock?
A: The prediction period for LON:BOD is (n+3 month)
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