Modelling A.I. in Economics

Is CM stock expected to rise?

Abstract

We evaluate Canadian Imperial Bank of Commerce prediction models with Modular Neural Network (Market News Sentiment Analysis) and Chi-Square1,2,3,4 and conclude that the CM stock is predictable in the short/long term. According to price forecasts for (n+8 weeks) period: The dominant strategy among neural network is to Hold CM stock.


Keywords: CM, Canadian Imperial Bank of Commerce, stock forecast, machine learning based prediction, risk rating, buy-sell behaviour, stock analysis, target price analysis, options and futures.

Key Points

  1. What statistical methods are used to analyze data?
  2. Technical Analysis with Algorithmic Trading
  3. Is it better to buy and sell or hold?

CM Target Price Prediction Modeling Methodology

We consider Canadian Imperial Bank of Commerce Stock Decision Process with Chi-Square where A is the set of discrete actions of CM 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(Chi-Square)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+8 weeks) R = 1 0 0 0 1 0 0 0 1

n:Time series to forecast

p:Price signals of CM 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?

CM Stock Forecast (Buy or Sell) for (n+8 weeks)

Sample Set: Neural Network
Stock/Index: CM Canadian Imperial Bank of Commerce
Time series to forecast n: 04 Sep 2022 for (n+8 weeks)

According to price forecasts for (n+8 weeks) period: The dominant strategy among neural network is to Hold CM 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

Canadian Imperial Bank of Commerce assigned short-term B1 & long-term B1 forecasted stock rating. We evaluate the prediction models Modular Neural Network (Market News Sentiment Analysis) with Chi-Square1,2,3,4 and conclude that the CM stock is predictable in the short/long term. According to price forecasts for (n+8 weeks) period: The dominant strategy among neural network is to Hold CM stock.

Financial State Forecast for CM Stock Options & Futures

Rating Short-Term Long-Term Senior
Outlook*B1B1
Operational Risk 8082
Market Risk5664
Technical Analysis4672
Fundamental Analysis7941
Risk Unsystematic3938

Prediction Confidence Score

Trust metric by Neural Network: 72 out of 100 with 568 signals.

References

  1. S. J. Russell and A. Zimdars. Q-decomposition for reinforcement learning agents. In Machine Learning, Proceedings of the Twentieth International Conference (ICML 2003), August 21-24, 2003, Washington, DC, USA, pages 656–663, 2003.
  2. K. Tuyls and G. Weiss. Multiagent learning: Basics, challenges, and prospects. AI Magazine, 33(3): 41–52, 2012
  3. Andrews, D. W. K. W. Ploberger (1994), "Optimal tests when a nuisance parameter is present only under the alternative," Econometrica, 62, 1383–1414.
  4. Jacobs B, Donkers B, Fok D. 2014. Product Recommendations Based on Latent Purchase Motivations. Rotterdam, Neth.: ERIM
  5. Athey S, Tibshirani J, Wager S. 2016b. Generalized random forests. arXiv:1610.01271 [stat.ME]
  6. Mikolov T, Chen K, Corrado GS, Dean J. 2013a. Efficient estimation of word representations in vector space. arXiv:1301.3781 [cs.CL]
  7. V. Mnih, A. P. Badia, M. Mirza, A. Graves, T. P. Lillicrap, T. Harley, D. Silver, and K. Kavukcuoglu. Asynchronous methods for deep reinforcement learning. In Proceedings of the 33nd International Conference on Machine Learning, ICML 2016, New York City, NY, USA, June 19-24, 2016, pages 1928–1937, 2016
Frequently Asked QuestionsQ: What is the prediction methodology for CM stock?
A: CM stock prediction methodology: We evaluate the prediction models Modular Neural Network (Market News Sentiment Analysis) and Chi-Square
Q: Is CM stock a buy or sell?
A: The dominant strategy among neural network is to Hold CM Stock.
Q: Is Canadian Imperial Bank of Commerce stock a good investment?
A: The consensus rating for Canadian Imperial Bank of Commerce is Hold and assigned short-term B1 & long-term B1 forecasted stock rating.
Q: What is the consensus rating of CM stock?
A: The consensus rating for CM is Hold.
Q: What is the prediction period for CM stock?
A: The prediction period for CM is (n+8 weeks)



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