In this paper, we introduce a new prediction model depend on Bidirectional Gated Recurrent Unit (BGRU). Our predictive model relies on both online financial news and historical stock prices data to predict the stock movements in the future. We evaluate VIETNAM ENTERPRISE INVESTMENTS LIMITED prediction models with Multi-Instance Learning (ML) and Multiple Regression1,2,3,4 and conclude that the LON:VEIL 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 Buy LON:VEIL stock.

Keywords: LON:VEIL, VIETNAM ENTERPRISE INVESTMENTS LIMITED, stock forecast, machine learning based prediction, risk rating, buy-sell behaviour, stock analysis, target price analysis, options and futures.

## Key Points

1. How accurate is machine learning in stock market?
2. How accurate is machine learning in stock market?
3. What are main components of Markov decision process?

## LON:VEIL Target Price Prediction Modeling Methodology

Accurate stock market prediction is of great interest to investors; however, stock markets are driven by volatile factors such as microblogs and news that make it hard to predict stock market index based on merely the historical data. The enormous stock market volatility emphasizes the need to effectively assess the role of external factors in stock prediction. Stock markets can be predicted using machine learning algorithms on information contained in social media and financial news, as this data can change investors' behavior. We consider VIETNAM ENTERPRISE INVESTMENTS LIMITED Stock Decision Process with Multiple Regression where A is the set of discrete actions of LON:VEIL 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= $\begin{array}{cccc}{p}_{a1}& {p}_{a2}& \dots & {p}_{1n}\\ & ⋮\\ {p}_{j1}& {p}_{j2}& \dots & {p}_{jn}\\ & ⋮\\ {p}_{k1}& {p}_{k2}& \dots & {p}_{kn}\\ & ⋮\\ {p}_{n1}& {p}_{n2}& \dots & {p}_{nn}\end{array}$ X R(Multi-Instance Learning (ML)) X S(n):→ (n+16 weeks) $\stackrel{\to }{S}=\left({s}_{1},{s}_{2},{s}_{3}\right)$

n:Time series to forecast

p:Price signals of LON:VEIL 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:VEIL Stock Forecast (Buy or Sell) for (n+16 weeks)

Sample Set: Neural Network
Stock/Index: LON:VEIL VIETNAM ENTERPRISE INVESTMENTS LIMITED
Time series to forecast n: 13 Sep 2022 for (n+16 weeks)

According to price forecasts for (n+16 weeks) period: The dominant strategy among neural network is to Buy LON:VEIL 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

VIETNAM ENTERPRISE INVESTMENTS LIMITED assigned short-term Ba1 & long-term Ba3 forecasted stock rating. We evaluate the prediction models Multi-Instance Learning (ML) with Multiple Regression1,2,3,4 and conclude that the LON:VEIL 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 Buy LON:VEIL stock.

### Financial State Forecast for LON:VEIL Stock Options & Futures

Rating Short-Term Long-Term Senior
Outlook*Ba1Ba3
Operational Risk 8043
Market Risk6075
Technical Analysis5180
Fundamental Analysis7372
Risk Unsystematic8940

### Prediction Confidence Score

Trust metric by Neural Network: 79 out of 100 with 522 signals.

## References

1. Mikolov T, Yih W, Zweig G. 2013c. Linguistic regularities in continuous space word representations. In Pro- ceedings of the 2013 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pp. 746–51. New York: Assoc. Comput. Linguist.
2. L. Panait and S. Luke. Cooperative multi-agent learning: The state of the art. Autonomous Agents and Multi-Agent Systems, 11(3):387–434, 2005.
3. Breiman L. 1996. Bagging predictors. Mach. Learn. 24:123–40
4. Dudik M, Langford J, Li L. 2011. Doubly robust policy evaluation and learning. In Proceedings of the 28th International Conference on Machine Learning, pp. 1097–104. La Jolla, CA: Int. Mach. Learn. Soc.
5. Bierens HJ. 1987. Kernel estimators of regression functions. In Advances in Econometrics: Fifth World Congress, Vol. 1, ed. TF Bewley, pp. 99–144. Cambridge, UK: Cambridge Univ. Press
6. E. Altman, K. Avrachenkov, and R. N ́u ̃nez-Queija. Perturbation analysis for denumerable Markov chains with application to queueing models. Advances in Applied Probability, pages 839–853, 2004
7. Bai J. 2003. Inferential theory for factor models of large dimensions. Econometrica 71:135–71
Frequently Asked QuestionsQ: What is the prediction methodology for LON:VEIL stock?
A: LON:VEIL stock prediction methodology: We evaluate the prediction models Multi-Instance Learning (ML) and Multiple Regression
Q: Is LON:VEIL stock a buy or sell?
A: The dominant strategy among neural network is to Buy LON:VEIL Stock.
Q: Is VIETNAM ENTERPRISE INVESTMENTS LIMITED stock a good investment?
A: The consensus rating for VIETNAM ENTERPRISE INVESTMENTS LIMITED is Buy and assigned short-term Ba1 & long-term Ba3 forecasted stock rating.
Q: What is the consensus rating of LON:VEIL stock?
A: The consensus rating for LON:VEIL is Buy.
Q: What is the prediction period for LON:VEIL stock?
A: The prediction period for LON:VEIL is (n+16 weeks)