Salesforce Stock Forecast, Price & Rating (CRM)

Abstract

We evaluate Salesforce prediction models with Bollinger Bands Width and Factor^1,2,3,4 and conclude that the CRM stock is predictable in the short/long term. According to price forecasts for (n+6 month) period: The dominant strategy among neural network is to Hold CRM stock.

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

Key Points

1. How do predictive algorithms actually work?
2. Market Risk
3. What are buy sell or hold recommendations?

CRM Target Price Prediction Modeling Methodology

We consider Salesforce Stock Decision Process with Factor where A is the set of discrete actions of CRM 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(Factor)^5,6,7= $\begin{array}{cccc}{p}_{\mathrm{a}1}& p_{\mathrm{a}2}& \dots & p_{1n}\\ & ⋮\\ p_{j1}& p_{j2}& \dots & p_{jn}\\ & ⋮\\ p_{k1}& p_{k2}& \dots & p_{kn}\\ & ⋮\\ p_{n1}& p_{n2}& \dots & p_{nn}\end{array}$ X R(Bollinger Bands Width) X S(n):→ (n+6 month) $R=\left(\begin{array}{ccc}1& 0& 0\\ 0& 1& 0\\ 0& 0& 1\end{array}\right)$

n:Time series to forecast

p:Price signals of CRM 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?

CRM Stock Forecast (Buy or Sell) for (n+6 month)

Sample Set: Neural Network
Stock/Index: CRM Salesforce
Time series to forecast n: 01 Sep 2022 for (n+6 month)

According to price forecasts for (n+6 month) period: The dominant strategy among neural network is to Hold CRM 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

Salesforce assigned short-term Caa2 & long-term B3 forecasted stock rating. We evaluate the prediction models Bollinger Bands Width with Factor^1,2,3,4 and conclude that the CRM stock is predictable in the short/long term. According to price forecasts for (n+6 month) period: The dominant strategy among neural network is to Hold CRM stock.

Financial State Forecast for CRM Stock Options & Futures

Rating	Short-Term	Long-Term Senior
Outlook*	Caa2	B3
Operational Risk	30	49
Market Risk	51	41
Technical Analysis	58	38
Fundamental Analysis	37	57
Risk Unsystematic	41	32

Prediction Confidence Score

Trust metric by Neural Network: 90 out of 100 with 491 signals.

References

1. Athey S, Bayati M, Doudchenko N, Imbens G, Khosravi K. 2017a. Matrix completion methods for causal panel data models. arXiv:1710.10251 [math.ST]
2. A. Tamar and S. Mannor. Variance adjusted actor critic algorithms. arXiv preprint arXiv:1310.3697, 2013.
3. M. J. Hausknecht and P. Stone. Deep recurrent Q-learning for partially observable MDPs. CoRR, abs/1507.06527, 2015
4. 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.
5. M. Colby, T. Duchow-Pressley, J. J. Chung, and K. Tumer. Local approximation of difference evaluation functions. In Proceedings of the Fifteenth International Joint Conference on Autonomous Agents and Multiagent Systems, Singapore, May 2016
6. 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.
7. 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.

Frequently Asked Questions

Q: What is the prediction methodology for CRM stock?
A: CRM stock prediction methodology: We evaluate the prediction models Bollinger Bands Width and Factor
Q: Is CRM stock a buy or sell?
A: The dominant strategy among neural network is to Hold CRM Stock.
Q: Is Salesforce stock a good investment?
A: The consensus rating for Salesforce is Hold and assigned short-term Caa2 & long-term B3 forecasted stock rating.
Q: What is the consensus rating of CRM stock?
A: The consensus rating for CRM is Hold.
Q: What is the prediction period for CRM stock?
A: The prediction period for CRM is (n+6 month)

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