Should You Buy, Sell, or Hold? (LON:CBP Stock Forecast)

Abstract

We evaluate CURTIS BANKS GROUP PLC prediction models with Statistical Inference (ML) and Spearman Correlation1,2,3,4 and conclude that the LON:CBP stock is predictable in the short/long term. According to price forecasts for (n+3 month) period: The dominant strategy among neural network is to Sell LON:CBP stock.


Keywords: LON:CBP, CURTIS BANKS GROUP PLC, 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. Stock Forecast Based On a Predictive Algorithm
  3. What are the most successful trading algorithms?

LON:CBP Target Price Prediction Modeling Methodology

We consider CURTIS BANKS GROUP PLC Stock Decision Process with Spearman Correlation where A is the set of discrete actions of LON:CBP 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(Statistical Inference (ML)) X S(n):→ (n+3 month) i = 1 n a i

n:Time series to forecast

p:Price signals of LON:CBP 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:CBP Stock Forecast (Buy or Sell) for (n+3 month)

Sample Set: Neural Network
Stock/Index: LON:CBP CURTIS BANKS GROUP PLC
Time series to forecast n: 09 Sep 2022 for (n+3 month)

According to price forecasts for (n+3 month) period: The dominant strategy among neural network is to Sell LON:CBP 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

CURTIS BANKS GROUP PLC assigned short-term Ba3 & long-term Ba3 forecasted stock rating. We evaluate the prediction models Statistical Inference (ML) with Spearman Correlation1,2,3,4 and conclude that the LON:CBP stock is predictable in the short/long term. According to price forecasts for (n+3 month) period: The dominant strategy among neural network is to Sell LON:CBP stock.

Financial State Forecast for LON:CBP Stock Options & Futures

Rating Short-Term Long-Term Senior
Outlook*Ba3Ba3
Operational Risk 8951
Market Risk7271
Technical Analysis6568
Fundamental Analysis3887
Risk Unsystematic5233

Prediction Confidence Score

Trust metric by Neural Network: 75 out of 100 with 670 signals.

References

  1. A. Y. Ng, D. Harada, and S. J. Russell. Policy invariance under reward transformations: Theory and application to reward shaping. In Proceedings of the Sixteenth International Conference on Machine Learning (ICML 1999), Bled, Slovenia, June 27 - 30, 1999, pages 278–287, 1999.
  2. Krizhevsky A, Sutskever I, Hinton GE. 2012. Imagenet classification with deep convolutional neural networks. In Advances in Neural Information Processing Systems, Vol. 25, ed. Z Ghahramani, M Welling, C Cortes, ND Lawrence, KQ Weinberger, pp. 1097–105. San Diego, CA: Neural Inf. Process. Syst. Found.
  3. Chow, G. C. (1960), "Tests of equality between sets of coefficients in two linear regressions," Econometrica, 28, 591–605.
  4. Clements, M. P. D. F. Hendry (1997), "An empirical study of seasonal unit roots in forecasting," International Journal of Forecasting, 13, 341–355.
  5. 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.
  6. Athey S, Bayati M, Doudchenko N, Imbens G, Khosravi K. 2017a. Matrix completion methods for causal panel data models. arXiv:1710.10251 [math.ST]
  7. Clements, M. P. D. F. Hendry (1995), "Forecasting in cointegrated systems," Journal of Applied Econometrics, 10, 127–146.
Frequently Asked QuestionsQ: What is the prediction methodology for LON:CBP stock?
A: LON:CBP stock prediction methodology: We evaluate the prediction models Statistical Inference (ML) and Spearman Correlation
Q: Is LON:CBP stock a buy or sell?
A: The dominant strategy among neural network is to Sell LON:CBP Stock.
Q: Is CURTIS BANKS GROUP PLC stock a good investment?
A: The consensus rating for CURTIS BANKS GROUP PLC is Sell and assigned short-term Ba3 & long-term Ba3 forecasted stock rating.
Q: What is the consensus rating of LON:CBP stock?
A: The consensus rating for LON:CBP is Sell.
Q: What is the prediction period for LON:CBP stock?
A: The prediction period for LON:CBP is (n+3 month)

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