CF CF Industries Holdings Inc. Common Stock

Outlook: CF Industries Holdings Inc. Common Stock assigned short-term Ba2 & long-term B1 forecasted stock rating.
Dominant Strategy : Hold
Time series to forecast n: 12 Dec 2022 for (n+1 year)
Methodology : Deductive Inference (ML)

Abstract

The nature of stock market movement has always been ambiguous for investors because of various influential factors. This study aims to significantly reduce the risk of trend prediction with machine learning and deep learning algorithms.(Yoo, P.D., Kim, M.H. and Jan, T., 2005, November. Machine learning techniques and use of event information for stock market prediction: A survey and evaluation. In International Conference on Computational Intelligence for Modelling, Control and Automation and International Conference on Intelligent Agents, Web Technologies and Internet Commerce (CIMCA-IAWTIC'06) (Vol. 2, pp. 835-841). IEEE.) We evaluate CF Industries Holdings Inc. Common Stock prediction models with Deductive Inference (ML) and Ridge Regression^1,2,3,4 and conclude that the CF stock is predictable in the short/long term. According to price forecasts for (n+1 year) period, the dominant strategy among neural network is: Hold

Key Points

1. How do you pick a stock?
2. How do you know when a stock will go up or down?
3. What is Markov decision process in reinforcement learning?

CF Target Price Prediction Modeling Methodology

We consider CF Industries Holdings Inc. Common Stock Decision Process with Deductive Inference (ML) where A is the set of discrete actions of CF 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(Ridge Regression)^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(Deductive Inference (ML)) X S(n):→ (n+1 year) $\overrightarrow{R}=\left(r_1,r_2,r_3\right)$

n:Time series to forecast

p:Price signals of CF stock

j:Nash equilibria (Neural Network)

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?

CF Stock Forecast (Buy or Sell) for (n+1 year)

Sample Set: Neural Network
Stock/Index: CF CF Industries Holdings Inc. Common Stock
Time series to forecast n: 12 Dec 2022 for (n+1 year)

According to price forecasts for (n+1 year) period, the dominant strategy among neural network is: Hold

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 (Grey to Black): *Technical Analysis%

Adjusted IFRS* Prediction Methods for CF Industries Holdings Inc. Common Stock

1. To be eligible for designation as a hedged item, a risk component must be a separately identifiable component of the financial or the non-financial item, and the changes in the cash flows or the fair value of the item attributable to changes in that risk component must be reliably measurable.
2. Subject to the conditions in paragraphs 4.1.5 and 4.2.2, this Standard allows an entity to designate a financial asset, a financial liability, or a group of financial instruments (financial assets, financial liabilities or both) as at fair value through profit or loss provided that doing so results in more relevant information.
3. Annual Improvements to IFRSs 2010–2012 Cycle, issued in December 2013, amended paragraphs 4.2.1 and 5.7.5 as a consequential amendment derived from the amendment to IFRS 3. An entity shall apply that amendment prospectively to business combinations to which the amendment to IFRS 3 applies.
4. Paragraph 4.1.1(a) requires an entity to classify financial assets on the basis of the entity's business model for managing the financial assets, unless paragraph 4.1.5 applies. An entity assesses whether its financial assets meet the condition in paragraph 4.1.2(a) or the condition in paragraph 4.1.2A(a) on the basis of the business model as determined by the entity's key management personnel (as defined in IAS 24 Related Party Disclosures).

*International Financial Reporting Standards (IFRS) are a set of accounting rules for the financial statements of public companies that are intended to make them consistent, transparent, and easily comparable around the world.

Conclusions

CF Industries Holdings Inc. Common Stock assigned short-term Ba2 & long-term B1 forecasted stock rating. We evaluate the prediction models Deductive Inference (ML) with Ridge Regression^1,2,3,4 and conclude that the CF stock is predictable in the short/long term. According to price forecasts for (n+1 year) period, the dominant strategy among neural network is: Hold

Financial State Forecast for CF CF Industries Holdings Inc. Common Stock Options & Futures

Rating	Short-Term	Long-Term Senior
Outlook*	Ba2	B1
Operational Risk	30	33
Market Risk	72	83
Technical Analysis	89	41
Fundamental Analysis	79	89
Risk Unsystematic	71	35

Prediction Confidence Score

Trust metric by Neural Network: 76 out of 100 with 782 signals.

References

1. Breiman L. 2001b. Statistical modeling: the two cultures (with comments and a rejoinder by the author). Stat. Sci. 16:199–231
2. Gentzkow M, Kelly BT, Taddy M. 2017. Text as data. NBER Work. Pap. 23276
3. Bewley, R. M. Yang (1998), "On the size and power of system tests for cointegration," Review of Economics and Statistics, 80, 675–679.
4. Bera, A. M. L. Higgins (1997), "ARCH and bilinearity as competing models for nonlinear dependence," Journal of Business Economic Statistics, 15, 43–50.
5. S. Bhatnagar, H. Prasad, and L. Prashanth. Stochastic recursive algorithms for optimization, volume 434. Springer, 2013
6. V. Borkar. Stochastic approximation: a dynamical systems viewpoint. Cambridge University Press, 2008
7. Artis, M. J. W. Zhang (1990), "BVAR forecasts for the G-7," International Journal of Forecasting, 6, 349–362.

Frequently Asked Questions

Q: What is the prediction methodology for CF stock?
A: CF stock prediction methodology: We evaluate the prediction models Deductive Inference (ML) and Ridge Regression
Q: Is CF stock a buy or sell?
A: The dominant strategy among neural network is to Hold CF Stock.
Q: Is CF Industries Holdings Inc. Common Stock stock a good investment?
A: The consensus rating for CF Industries Holdings Inc. Common Stock is Hold and assigned short-term Ba2 & long-term B1 forecasted stock rating.
Q: What is the consensus rating of CF stock?
A: The consensus rating for CF is Hold.
Q: What is the prediction period for CF stock?
A: The prediction period for CF is (n+1 year)

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