How accurate is machine learning in stock market? (NRG Stock Forecast)


Abstract

We evaluate NRG Energy prediction models with Modular Neural Network (Emotional Trigger/Responses Analysis) and Spearman Correlation1,2,3,4 and conclude that the NRG 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 NRG stock.


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

Key Points

  1. What is a prediction confidence?
  2. Technical Analysis with Algorithmic Trading
  3. Which neural network is best for prediction?

NRG Target Price Prediction Modeling Methodology

We consider NRG Energy Stock Decision Process with Spearman Correlation where A is the set of discrete actions of NRG 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(Spearman 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 (Emotional Trigger/Responses Analysis)) X S(n):→ (n+16 weeks) r s rs

n:Time series to forecast

p:Price signals of NRG 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?

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

Sample Set: Neural Network
Stock/Index: NRG NRG Energy
Time series to forecast n: 06 Sep 2022 for (n+16 weeks)

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

NRG Energy assigned short-term B2 & long-term B1 forecasted stock rating. We evaluate the prediction models Modular Neural Network (Emotional Trigger/Responses Analysis) with Spearman Correlation1,2,3,4 and conclude that the NRG 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 NRG stock.

Financial State Forecast for NRG Stock Options & Futures

Rating Short-Term Long-Term Senior
Outlook*B2B1
Operational Risk 5043
Market Risk4577
Technical Analysis7739
Fundamental Analysis5987
Risk Unsystematic4535

Prediction Confidence Score

Trust metric by Neural Network: 93 out of 100 with 790 signals.

References

  1. Li L, Chu W, Langford J, Moon T, Wang X. 2012. An unbiased offline evaluation of contextual bandit algo- rithms with generalized linear models. In Proceedings of 4th ACM International Conference on Web Search and Data Mining, pp. 297–306. New York: ACM
  2. N. B ̈auerle and A. Mundt. Dynamic mean-risk optimization in a binomial model. Mathematical Methods of Operations Research, 70(2):219–239, 2009.
  3. Wan M, Wang D, Goldman M, Taddy M, Rao J, et al. 2017. Modeling consumer preferences and price sensitiv- ities from large-scale grocery shopping transaction logs. In Proceedings of the 26th International Conference on the World Wide Web, pp. 1103–12. New York: ACM
  4. Thomas P, Brunskill E. 2016. Data-efficient off-policy policy evaluation for reinforcement learning. In Pro- ceedings of the International Conference on Machine Learning, pp. 2139–48. La Jolla, CA: Int. Mach. Learn. Soc.
  5. S. J. Russell and P. Norvig. Artificial Intelligence: A Modern Approach. Prentice Hall, Englewood Cliffs, NJ, 3nd edition, 2010
  6. H. Khalil and J. Grizzle. Nonlinear systems, volume 3. Prentice hall Upper Saddle River, 2002.
  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 NRG stock?
A: NRG stock prediction methodology: We evaluate the prediction models Modular Neural Network (Emotional Trigger/Responses Analysis) and Spearman Correlation
Q: Is NRG stock a buy or sell?
A: The dominant strategy among neural network is to Hold NRG Stock.
Q: Is NRG Energy stock a good investment?
A: The consensus rating for NRG Energy is Hold and assigned short-term B2 & long-term B1 forecasted stock rating.
Q: What is the consensus rating of NRG stock?
A: The consensus rating for NRG is Hold.
Q: What is the prediction period for NRG stock?
A: The prediction period for NRG is (n+16 weeks)

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