Modelling A.I. in Economics

LON:TGL Target Price Prediction (Forecast)

Application of machine learning for stock prediction is attracting a lot of attention in recent years. A large amount of research has been conducted in this area and multiple existing results have shown that machine learning methods could be successfully used toward stock predicting using stocks' historical data. Most of these existing approaches have focused on short term prediction using stocks' historical price and technical indicators. We evaluate TRANSGLOBE ENERGY CORPORATION prediction models with Supervised Machine Learning (ML) and Linear Regression1,2,3,4 and conclude that the LON:TGL 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 LON:TGL stock.


Keywords: LON:TGL, TRANSGLOBE ENERGY CORPORATION, stock forecast, machine learning based prediction, risk rating, buy-sell behaviour, stock analysis, target price analysis, options and futures.

Key Points

  1. How do you pick a stock?
  2. How can neural networks improve predictions?
  3. Fundemental Analysis with Algorithmic Trading

LON:TGL Target Price Prediction Modeling Methodology

Sentiment Analysis is new way of machine learning to extract opinion orientation (positive, negative, neutral) from a text segment written for any product, organization, person or any other entity. Sentiment Analysis can be used to predict the mood of people that have impact on stock prices, therefore it can help in prediction of actual stock movement. We consider TRANSGLOBE ENERGY CORPORATION Stock Decision Process with Linear Regression where A is the set of discrete actions of LON:TGL 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(Supervised Machine Learning (ML)) X S(n):→ (n+16 weeks) i = 1 n a i

n:Time series to forecast

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

Sample Set: Neural Network
Stock/Index: LON:TGL TRANSGLOBE ENERGY CORPORATION
Time series to forecast n: 16 Oct 2022 for (n+16 weeks)

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

TRANSGLOBE ENERGY CORPORATION assigned short-term Ba3 & long-term B1 forecasted stock rating. We evaluate the prediction models Supervised Machine Learning (ML) with Linear Regression1,2,3,4 and conclude that the LON:TGL 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 LON:TGL stock.

Financial State Forecast for LON:TGL Stock Options & Futures

Rating Short-Term Long-Term Senior
Outlook*Ba3B1
Operational Risk 7539
Market Risk6074
Technical Analysis7976
Fundamental Analysis3850
Risk Unsystematic6738

Prediction Confidence Score

Trust metric by Neural Network: 91 out of 100 with 604 signals.

References

  1. Keane MP. 2013. Panel data discrete choice models of consumer demand. In The Oxford Handbook of Panel Data, ed. BH Baltagi, pp. 54–102. Oxford, UK: Oxford Univ. Press
  2. Mikolov T, Chen K, Corrado GS, Dean J. 2013a. Efficient estimation of word representations in vector space. arXiv:1301.3781 [cs.CL]
  3. Barkan O. 2016. Bayesian neural word embedding. arXiv:1603.06571 [math.ST]
  4. Dudik M, Erhan D, Langford J, Li L. 2014. Doubly robust policy evaluation and optimization. Stat. Sci. 29:485–511
  5. Cheung, Y. M.D. Chinn (1997), "Further investigation of the uncertain unit root in GNP," Journal of Business and Economic Statistics, 15, 68–73.
  6. S. Bhatnagar, R. Sutton, M. Ghavamzadeh, and M. Lee. Natural actor-critic algorithms. Automatica, 45(11): 2471–2482, 2009
  7. Breusch, T. S. A. R. Pagan (1979), "A simple test for heteroskedasticity and random coefficient variation," Econometrica, 47, 1287–1294.
Frequently Asked QuestionsQ: What is the prediction methodology for LON:TGL stock?
A: LON:TGL stock prediction methodology: We evaluate the prediction models Supervised Machine Learning (ML) and Linear Regression
Q: Is LON:TGL stock a buy or sell?
A: The dominant strategy among neural network is to Hold LON:TGL Stock.
Q: Is TRANSGLOBE ENERGY CORPORATION stock a good investment?
A: The consensus rating for TRANSGLOBE ENERGY CORPORATION is Hold and assigned short-term Ba3 & long-term B1 forecasted stock rating.
Q: What is the consensus rating of LON:TGL stock?
A: The consensus rating for LON:TGL is Hold.
Q: What is the prediction period for LON:TGL stock?
A: The prediction period for LON:TGL is (n+16 weeks)

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