Buy, Sell, or Hold? (FTI Stock Forecast)

TechnipFMC plc Ordinary Share Research Report

Summary

Stock market is a promising financial investment that can generate great wealth. However, the volatile nature of the stock market makes it a very high risk investment. Thus, a lot of researchers have contributed their efforts to forecast the stock market pricing and average movement. Researchers have used various methods in computer science and economics in their quests to gain a piece of this volatile information and make great fortune out of the stock market investment. This paper investigates various techniques for the stock market prediction using artificial neural network (ANN). We evaluate TechnipFMC plc Ordinary Share prediction models with Modular Neural Network (Speculative Sentiment Analysis) and Pearson Correlation1,2,3,4 and conclude that the FTI 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 Hold FTI stock.

Key Points

  1. How useful are statistical predictions?
  2. Prediction Modeling
  3. What is a prediction confidence?

FTI Target Price Prediction Modeling Methodology

We consider TechnipFMC plc Ordinary Share Stock Decision Process with Modular Neural Network (Speculative Sentiment Analysis) where A is the set of discrete actions of FTI 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(Pearson Correlation)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 (Speculative Sentiment Analysis)) X S(n):→ (n+16 weeks) i = 1 n s i

n:Time series to forecast

p:Price signals of FTI 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?

FTI Stock Forecast (Buy or Sell) for (n+16 weeks)

Sample Set: Neural Network
Stock/Index: FTI TechnipFMC plc Ordinary Share
Time series to forecast n: 24 Nov 2022 for (n+16 weeks)

According to price forecasts for (n+16 weeks) period: The dominant strategy among neural network is to Hold FTI 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 TechnipFMC plc Ordinary Share

  1. An entity has not retained control of a transferred asset if the transferee has the practical ability to sell the transferred asset. An entity has retained control of a transferred asset if the transferee does not have the practical ability to sell the transferred asset. A transferee has the practical ability to sell the transferred asset if it is traded in an active market because the transferee could repurchase the transferred asset in the market if it needs to return the asset to the entity. For example, a transferee may have the practical ability to sell a transferred asset if the transferred asset is subject to an option that allows the entity to repurchase it, but the transferee can readily obtain the transferred asset in the market if the option is exercised. A transferee does not have the practical ability to sell the transferred asset if the entity retains such an option and the transferee cannot readily obtain the transferred asset in the market if the entity exercises its option
  2. If the group of items does not have any offsetting risk positions (for example, a group of foreign currency expenses that affect different line items in the statement of profit or loss and other comprehensive income that are hedged for foreign currency risk) then the reclassified hedging instrument gains or losses shall be apportioned to the line items affected by the hedged items. This apportionment shall be done on a systematic and rational basis and shall not result in the grossing up of the net gains or losses arising from a single hedging instrument.
  3. For the purposes of applying the requirement in paragraph 5.7.7(a), credit risk is different from asset-specific performance risk. Asset-specific performance risk is not related to the risk that an entity will fail to discharge a particular obligation but instead it is related to the risk that a single asset or a group of assets will perform poorly (or not at all).
  4. The fact that a derivative is in or out of the money when it is designated as a hedging instrument does not in itself mean that a qualitative assessment is inappropriate. It depends on the circumstances whether hedge ineffectiveness arising from that fact could have a magnitude that a qualitative assessment would not adequately capture.

*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

TechnipFMC plc Ordinary Share assigned short-term Caa2 & long-term Ba1 forecasted stock rating. We evaluate the prediction models Modular Neural Network (Speculative Sentiment Analysis) with Pearson Correlation1,2,3,4 and conclude that the FTI 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 Hold FTI stock.

Financial State Forecast for FTI TechnipFMC plc Ordinary Share Stock Options & Futures

Rating Short-Term Long-Term Senior
Outlook*Caa2Ba1
Operational Risk 5181
Market Risk4654
Technical Analysis4787
Fundamental Analysis4452
Risk Unsystematic3386

Prediction Confidence Score

Trust metric by Neural Network: 74 out of 100 with 879 signals.

References

  1. Bengio Y, Schwenk H, Senécal JS, Morin F, Gauvain JL. 2006. Neural probabilistic language models. In Innovations in Machine Learning: Theory and Applications, ed. DE Holmes, pp. 137–86. Berlin: Springer
  2. Efron B, Hastie T. 2016. Computer Age Statistical Inference, Vol. 5. Cambridge, UK: Cambridge Univ. Press
  3. J. Filar, L. Kallenberg, and H. Lee. Variance-penalized Markov decision processes. Mathematics of Opera- tions Research, 14(1):147–161, 1989
  4. R. Rockafellar and S. Uryasev. Conditional value-at-risk for general loss distributions. Journal of Banking and Finance, 26(7):1443 – 1471, 2002
  5. Imbens GW, Lemieux T. 2008. Regression discontinuity designs: a guide to practice. J. Econom. 142:615–35
  6. Chernozhukov V, Chetverikov D, Demirer M, Duflo E, Hansen C, et al. 2016a. Double machine learning for treatment and causal parameters. Tech. Rep., Cent. Microdata Methods Pract., Inst. Fiscal Stud., London
  7. J. Filar, D. Krass, and K. Ross. Percentile performance criteria for limiting average Markov decision pro- cesses. IEEE Transaction of Automatic Control, 40(1):2–10, 1995.
Frequently Asked QuestionsQ: What is the prediction methodology for FTI stock?
A: FTI stock prediction methodology: We evaluate the prediction models Modular Neural Network (Speculative Sentiment Analysis) and Pearson Correlation
Q: Is FTI stock a buy or sell?
A: The dominant strategy among neural network is to Hold FTI Stock.
Q: Is TechnipFMC plc Ordinary Share stock a good investment?
A: The consensus rating for TechnipFMC plc Ordinary Share is Hold and assigned short-term Caa2 & long-term Ba1 forecasted stock rating.
Q: What is the consensus rating of FTI stock?
A: The consensus rating for FTI is Hold.
Q: What is the prediction period for FTI stock?
A: The prediction period for FTI is (n+16 weeks)

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