Modelling A.I. in Economics

VNTR Venator Materials PLC Ordinary Shares Stock Forecast (Forecast)

Venator Materials PLC Ordinary Shares Research Report

Summary

This paper surveys machine learning techniques for stock market prediction. The prediction of stock markets is regarded as a challenging task of financial time series prediction. We evaluate Venator Materials PLC Ordinary Shares prediction models with Modular Neural Network (Financial Sentiment Analysis) and Linear Regression1,2,3,4 and conclude that the VNTR stock is predictable in the short/long term. According to price forecasts for (n+1 year) period: The dominant strategy among neural network is to Hold VNTR stock.

Key Points

  1. Market Signals
  2. Fundemental Analysis with Algorithmic Trading
  3. Nash Equilibria

VNTR Target Price Prediction Modeling Methodology

We consider Venator Materials PLC Ordinary Shares Stock Decision Process with Modular Neural Network (Financial Sentiment Analysis) where A is the set of discrete actions of VNTR 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= p a 1 p a 2 p 1 n p j 1 p j 2 p j n p k 1 p k 2 p k n p n 1 p n 2 p n n X R(Modular Neural Network (Financial Sentiment Analysis)) X S(n):→ (n+1 year) i = 1 n a i

n:Time series to forecast

p:Price signals of VNTR stock

j:Nash equilibria (Neural Network)

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?

VNTR Stock Forecast (Buy or Sell) for (n+1 year)

Sample Set: Neural Network
Stock/Index: VNTR Venator Materials PLC Ordinary Shares
Time series to forecast n: 26 Nov 2022 for (n+1 year)

According to price forecasts for (n+1 year) period: The dominant strategy among neural network is to Hold VNTR 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%

Adjusted IFRS* Prediction Methods for Venator Materials PLC Ordinary Shares

  1. An entity is not required to restate prior periods to reflect the application of these amendments. The entity may restate prior periods only if it is possible to do so without the use of hindsight. If an entity restates prior periods, the restated financial statements must reflect all the requirements in this Standard for the affected financial instruments. If an entity does not restate prior periods, the entity shall recognise any difference between the previous carrying amount and the carrying amount at the beginning of the annual reporting period that includes the date of initial application of these amendments in the opening retained earnings (or other component of equity, as appropriate) of the annual reporting period that includes the date of initial application of these amendments.
  2. There is a rebuttable presumption that unless inflation risk is contractually specified, it is not separately identifiable and reliably measurable and hence cannot be designated as a risk component of a financial instrument. However, in limited cases, it is possible to identify a risk component for inflation risk that is separately identifiable and reliably measurable because of the particular circumstances of the inflation environment and the relevant debt market
  3. Paragraph 4.1.1(b) requires an entity to classify a financial asset on the basis of its contractual cash flow characteristics if the financial asset is held within a business model whose objective is to hold assets to collect contractual cash flows or within a business model whose objective is achieved by both collecting contractual cash flows and selling financial assets, unless paragraph 4.1.5 applies. To do so, the condition in paragraphs 4.1.2(b) and 4.1.2A(b) requires an entity to determine whether the asset's contractual cash flows are solely payments of principal and interest on the principal amount outstanding.
  4. The significance of a change in the credit risk since initial recognition depends on the risk of a default occurring as at initial recognition. Thus, a given change, in absolute terms, in the risk of a default occurring will be more significant for a financial instrument with a lower initial risk of a default occurring compared to a financial instrument with a higher initial risk of a default occurring.

*International Financial Reporting Standards (IFRS) are a set of accounting rules for the financial statements of public companies that are intended to make them consistent, transparent, and easily comparable around the world.

Conclusions

Venator Materials PLC Ordinary Shares assigned short-term B1 & long-term B2 forecasted stock rating. We evaluate the prediction models Modular Neural Network (Financial Sentiment Analysis) with Linear Regression1,2,3,4 and conclude that the VNTR stock is predictable in the short/long term. According to price forecasts for (n+1 year) period: The dominant strategy among neural network is to Hold VNTR stock.

Financial State Forecast for VNTR Venator Materials PLC Ordinary Shares Stock Options & Futures

Rating Short-Term Long-Term Senior
Outlook*B1B2
Operational Risk 7931
Market Risk4477
Technical Analysis5737
Fundamental Analysis6087
Risk Unsystematic5544

Prediction Confidence Score

Trust metric by Neural Network: 89 out of 100 with 560 signals.

References

  1. Efron B, Hastie T. 2016. Computer Age Statistical Inference, Vol. 5. Cambridge, UK: Cambridge Univ. Press
  2. 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.
  3. Holland PW. 1986. Statistics and causal inference. J. Am. Stat. Assoc. 81:945–60
  4. Abadie A, Cattaneo MD. 2018. Econometric methods for program evaluation. Annu. Rev. Econ. 10:465–503
  5. Bessler, D. A. S. W. Fuller (1993), "Cointegration between U.S. wheat markets," Journal of Regional Science, 33, 481–501.
  6. S. Bhatnagar, H. Prasad, and L. Prashanth. Stochastic recursive algorithms for optimization, volume 434. Springer, 2013
  7. Y. Le Tallec. Robust, risk-sensitive, and data-driven control of Markov decision processes. PhD thesis, Massachusetts Institute of Technology, 2007.
Frequently Asked QuestionsQ: What is the prediction methodology for VNTR stock?
A: VNTR stock prediction methodology: We evaluate the prediction models Modular Neural Network (Financial Sentiment Analysis) and Linear Regression
Q: Is VNTR stock a buy or sell?
A: The dominant strategy among neural network is to Hold VNTR Stock.
Q: Is Venator Materials PLC Ordinary Shares stock a good investment?
A: The consensus rating for Venator Materials PLC Ordinary Shares is Hold and assigned short-term B1 & long-term B2 forecasted stock rating.
Q: What is the consensus rating of VNTR stock?
A: The consensus rating for VNTR is Hold.
Q: What is the prediction period for VNTR stock?
A: The prediction period for VNTR is (n+1 year)

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