VOLTA FINANCE LIMITED Stock Forecast, Price & Rating (LON:VTAS)

Abstract

We evaluate VOLTA FINANCE LIMITED prediction models with Deductive Inference (ML) and Paired T-Test^1,2,3,4 and conclude that the LON:VTAS stock is predictable in the short/long term. According to price forecasts for (n+8 weeks) period: The dominant strategy among neural network is to Hold LON:VTAS stock.

Keywords: LON:VTAS, VOLTA FINANCE LIMITED, stock forecast, machine learning based prediction, risk rating, buy-sell behaviour, stock analysis, target price analysis, options and futures.

Key Points

1. Short/Long Term Stocks
2. What statistical methods are used to analyze data?
3. What statistical methods are used to analyze data?

LON:VTAS Target Price Prediction Modeling Methodology

We consider VOLTA FINANCE LIMITED Stock Decision Process with Paired T-Test where A is the set of discrete actions of LON:VTAS 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(Paired T-Test)^5,6,7= $\begin{array}{cccc}{p}_{\mathrm{a}1}& p_{\mathrm{a}2}& \dots & p_{1n}\\ & ⋮\\ p_{j1}& p_{j2}& \dots & p_{jn}\\ & ⋮\\ p_{k1}& p_{k2}& \dots & p_{kn}\\ & ⋮\\ p_{n1}& p_{n2}& \dots & p_{nn}\end{array}$ X R(Deductive Inference (ML)) X S(n):→ (n+8 weeks) $\overrightarrow{R}=\left(r_1,r_2,r_3\right)$

n:Time series to forecast

p:Price signals of LON:VTAS 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:VTAS Stock Forecast (Buy or Sell) for (n+8 weeks)

Sample Set: Neural Network
Stock/Index: LON:VTAS VOLTA FINANCE LIMITED
Time series to forecast n: 05 Sep 2022 for (n+8 weeks)

According to price forecasts for (n+8 weeks) period: The dominant strategy among neural network is to Hold LON:VTAS 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

VOLTA FINANCE LIMITED assigned short-term Ba3 & long-term B2 forecasted stock rating. We evaluate the prediction models Deductive Inference (ML) with Paired T-Test^1,2,3,4 and conclude that the LON:VTAS stock is predictable in the short/long term. According to price forecasts for (n+8 weeks) period: The dominant strategy among neural network is to Hold LON:VTAS stock.

Financial State Forecast for LON:VTAS Stock Options & Futures

Rating	Short-Term	Long-Term Senior
Outlook*	Ba3	B2
Operational Risk	70	63
Market Risk	50	46
Technical Analysis	78	56
Fundamental Analysis	62	35
Risk Unsystematic	65	59

Prediction Confidence Score

Trust metric by Neural Network: 87 out of 100 with 830 signals.

References

1. uyer, S. Whiteson, B. Bakker, and N. A. Vlassis. Multiagent reinforcement learning for urban traffic control using coordination graphs. In Machine Learning and Knowledge Discovery in Databases, European Conference, ECML/PKDD 2008, Antwerp, Belgium, September 15-19, 2008, Proceedings, Part I, pages 656–671, 2008.
2. Chipman HA, George EI, McCulloch RE. 2010. Bart: Bayesian additive regression trees. Ann. Appl. Stat. 4:266–98
3. Bastani H, Bayati M. 2015. Online decision-making with high-dimensional covariates. Work. Pap., Univ. Penn./ Stanford Grad. School Bus., Philadelphia/Stanford, CA
4. Bewley, R. M. Yang (1998), "On the size and power of system tests for cointegration," Review of Economics and Statistics, 80, 675–679.
5. L. Busoniu, R. Babuska, and B. D. Schutter. A comprehensive survey of multiagent reinforcement learning. IEEE Transactions of Systems, Man, and Cybernetics Part C: Applications and Reviews, 38(2), 2008.
6. 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.
7. Blei DM, Lafferty JD. 2009. Topic models. In Text Mining: Classification, Clustering, and Applications, ed. A Srivastava, M Sahami, pp. 101–24. Boca Raton, FL: CRC Press

Frequently Asked Questions

Q: What is the prediction methodology for LON:VTAS stock?
A: LON:VTAS stock prediction methodology: We evaluate the prediction models Deductive Inference (ML) and Paired T-Test
Q: Is LON:VTAS stock a buy or sell?
A: The dominant strategy among neural network is to Hold LON:VTAS Stock.
Q: Is VOLTA FINANCE LIMITED stock a good investment?
A: The consensus rating for VOLTA FINANCE LIMITED is Hold and assigned short-term Ba3 & long-term B2 forecasted stock rating.
Q: What is the consensus rating of LON:VTAS stock?
A: The consensus rating for LON:VTAS is Hold.
Q: What is the prediction period for LON:VTAS stock?
A: The prediction period for LON:VTAS is (n+8 weeks)

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