Stock market prediction is a major exertion in the field of finance and establishing businesses. Stock market is totally uncertain as the prices of stocks keep fluctuating on a daily basis because of numerous factors that influence it. One of the traditional ways of predicting stock prices was by using only historical data. But with time it was observed that other factors such as peoples' sentiments and other news events occurring in and around the country affect the stock market, for e.g. national elections, natural calamity etc. We evaluate AIQ LIMITED prediction models with Modular Neural Network (News Feed Sentiment Analysis) and Linear Regression1,2,3,4 and conclude that the LON:AIQ stock is predictable in the short/long term. According to price forecasts for (n+16 weeks) period: The dominant strategy among neural network is to SellBuy LON:AIQ stock.
Keywords: LON:AIQ, AIQ LIMITED, stock forecast, machine learning based prediction, risk rating, buy-sell behaviour, stock analysis, target price analysis, options and futures.
Key Points
- Is it better to buy and sell or hold?
- Trust metric by Neural Network
- What is a prediction confidence?
LON:AIQ Target Price Prediction Modeling Methodology
Understanding the pattern of financial activities and predicting their development and changes are research hotspots in academic and financial circles. Because financial data contain complex, incomplete and fuzzy information, predicting their development trends is an extremely difficult challenge. Fluctuations in financial data depend on a myriad of correlated constantly changing factors. Therefore, predicting and analysing financial data are a nonlinear, time-dependent problem. Deep neural networks (DNNs) combine the advantages of deep learning (DL) and neural networks and can be used to solve nonlinear problems more satisfactorily compared to conventional machine learning algorithms. We consider AIQ LIMITED Stock Decision Process with Linear Regression where A is the set of discrete actions of LON:AIQ 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(Linear Regression)5,6,7= X R(Modular Neural Network (News Feed Sentiment Analysis)) X S(n):→ (n+16 weeks)
n:Time series to forecast
p:Price signals of LON:AIQ stock
j:Nash equilibria
k:Dominated move
a:Best response for target price
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How do AC Investment Research machine learning (predictive) algorithms actually work?
LON:AIQ Stock Forecast (Buy or Sell) for (n+16 weeks)
Sample Set: Neural NetworkStock/Index: LON:AIQ AIQ LIMITED
Time series to forecast n: 23 Oct 2022 for (n+16 weeks)
According to price forecasts for (n+16 weeks) period: The dominant strategy among neural network is to SellBuy LON:AIQ 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
AIQ LIMITED assigned short-term Ba2 & long-term B2 forecasted stock rating. We evaluate the prediction models Modular Neural Network (News Feed Sentiment Analysis) with Linear Regression1,2,3,4 and conclude that the LON:AIQ stock is predictable in the short/long term. According to price forecasts for (n+16 weeks) period: The dominant strategy among neural network is to SellBuy LON:AIQ stock.
Financial State Forecast for LON:AIQ Stock Options & Futures
| Rating | Short-Term | Long-Term Senior |
|---|---|---|
| Outlook* | Ba2 | B2 |
| Operational Risk | 86 | 55 |
| Market Risk | 54 | 64 |
| Technical Analysis | 68 | 34 |
| Fundamental Analysis | 51 | 56 |
| Risk Unsystematic | 83 | 43 |
Prediction Confidence Score
References
- E. Altman. Constrained Markov decision processes, volume 7. CRC Press, 1999
- Arora S, Li Y, Liang Y, Ma T. 2016. RAND-WALK: a latent variable model approach to word embeddings. Trans. Assoc. Comput. Linguist. 4:385–99
- 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.
- Clements, M. P. D. F. Hendry (1996), "Intercept corrections and structural change," Journal of Applied Econometrics, 11, 475–494.
- B. Derfer, N. Goodyear, K. Hung, C. Matthews, G. Paoni, K. Rollins, R. Rose, M. Seaman, and J. Wiles. Online marketing platform, August 17 2007. US Patent App. 11/893,765
- L. Prashanth and M. Ghavamzadeh. Actor-critic algorithms for risk-sensitive MDPs. In Proceedings of Advances in Neural Information Processing Systems 26, pages 252–260, 2013.
- E. Collins. Using Markov decision processes to optimize a nonlinear functional of the final distribution, with manufacturing applications. In Stochastic Modelling in Innovative Manufacturing, pages 30–45. Springer, 1997
Frequently Asked Questions
Q: What is the prediction methodology for LON:AIQ stock?A: LON:AIQ stock prediction methodology: We evaluate the prediction models Modular Neural Network (News Feed Sentiment Analysis) and Linear Regression
Q: Is LON:AIQ stock a buy or sell?
A: The dominant strategy among neural network is to SellBuy LON:AIQ Stock.
Q: Is AIQ LIMITED stock a good investment?
A: The consensus rating for AIQ LIMITED is SellBuy and assigned short-term Ba2 & long-term B2 forecasted stock rating.
Q: What is the consensus rating of LON:AIQ stock?
A: The consensus rating for LON:AIQ is SellBuy.
Q: What is the prediction period for LON:AIQ stock?
A: The prediction period for LON:AIQ is (n+16 weeks)
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