How do you know when a stock will go up or down? (STM.PA Stock Forecast)


Abstract

We evaluate STMicroelectronics prediction models with Modular Neural Network (Market News Sentiment Analysis) and Ridge Regression1,2,3,4 and conclude that the STM.PA stock is predictable in the short/long term. According to price forecasts for (n+6 month) period: The dominant strategy among neural network is to Hold STM.PA stock.


Keywords: STM.PA, STMicroelectronics, stock forecast, machine learning based prediction, risk rating, buy-sell behaviour, stock analysis, target price analysis, options and futures.

Key Points

  1. How can neural networks improve predictions?
  2. Can statistics predict the future?
  3. Is now good time to invest?

STM.PA Target Price Prediction Modeling Methodology

We consider STMicroelectronics Stock Decision Process with Ridge Regression where A is the set of discrete actions of STM.PA 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(Ridge 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 (Market News Sentiment Analysis)) X S(n):→ (n+6 month) R = 1 0 0 0 1 0 0 0 1

n:Time series to forecast

p:Price signals of STM.PA 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?

STM.PA Stock Forecast (Buy or Sell) for (n+6 month)

Sample Set: Neural Network
Stock/Index: STM.PA STMicroelectronics
Time series to forecast n: 04 Sep 2022 for (n+6 month)

According to price forecasts for (n+6 month) period: The dominant strategy among neural network is to Hold STM.PA 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

STMicroelectronics assigned short-term B2 & long-term B3 forecasted stock rating. We evaluate the prediction models Modular Neural Network (Market News Sentiment Analysis) with Ridge Regression1,2,3,4 and conclude that the STM.PA stock is predictable in the short/long term. According to price forecasts for (n+6 month) period: The dominant strategy among neural network is to Hold STM.PA stock.

Financial State Forecast for STM.PA Stock Options & Futures

Rating Short-Term Long-Term Senior
Outlook*B2B3
Operational Risk 5152
Market Risk4073
Technical Analysis5630
Fundamental Analysis6349
Risk Unsystematic5534

Prediction Confidence Score

Trust metric by Neural Network: 83 out of 100 with 881 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. D. S. Bernstein, S. Zilberstein, and N. Immerman. The complexity of decentralized control of Markov Decision Processes. In UAI '00: Proceedings of the 16th Conference in Uncertainty in Artificial Intelligence, Stanford University, Stanford, California, USA, June 30 - July 3, 2000, pages 32–37, 2000.
  3. Allen, P. G. (1994), "Economic forecasting in agriculture," International Journal of Forecasting, 10, 81–135.
  4. Bai J. 2003. Inferential theory for factor models of large dimensions. Econometrica 71:135–71
  5. Athey S, Tibshirani J, Wager S. 2016b. Generalized random forests. arXiv:1610.01271 [stat.ME]
  6. R. Sutton and A. Barto. Introduction to reinforcement learning. MIT Press, 1998
  7. Imai K, Ratkovic M. 2013. Estimating treatment effect heterogeneity in randomized program evaluation. Ann. Appl. Stat. 7:443–70
Frequently Asked QuestionsQ: What is the prediction methodology for STM.PA stock?
A: STM.PA stock prediction methodology: We evaluate the prediction models Modular Neural Network (Market News Sentiment Analysis) and Ridge Regression
Q: Is STM.PA stock a buy or sell?
A: The dominant strategy among neural network is to Hold STM.PA Stock.
Q: Is STMicroelectronics stock a good investment?
A: The consensus rating for STMicroelectronics is Hold and assigned short-term B2 & long-term B3 forecasted stock rating.
Q: What is the consensus rating of STM.PA stock?
A: The consensus rating for STM.PA is Hold.
Q: What is the prediction period for STM.PA stock?
A: The prediction period for STM.PA is (n+6 month)

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