ICL Stock Price Prediction

Name: ICL Stock Price Prediction
Uploaded: Monday, October 30, 2023
Duration: 37 min 14 s
Description: ICL Stock Price Prediction

Outlook: ICL Group Ltd. Ordinary Shares is assigned short-term Ba2 & long-term Ba3 estimated rating.
AUC Score : What is AUC Score?
Short-Term Revised¹ :
Dominant Strategy : Buy
Time series to forecast n: for Weeks²
Methodology : Ensemble Learning (ML)
Hypothesis Testing : Factor
Surveillance : Major exchange and OTC

¹The accuracy of the model is being monitored on a regular basis.(15-minute period)

²Time series is updated based on short-term trends.

ICL Group Ltd. Ordinary Shares prediction model is evaluated with Ensemble Learning (ML) and Factor^1,2,3,4 and it is concluded that the ICL stock is predictable in the short/long term. Ensemble learning is a machine learning (ML) technique that combines multiple models to create a single model that is more accurate than any of the individual models. This is done by combining the predictions of the individual models, typically using a voting scheme or a weighted average.⁵ According to price forecasts for 3 Month period, the dominant strategy among neural network is: Buy

Key Points

Prediction Modeling
Market Risk
Dominated Move

ICL Stock Price Forecast

We consider ICL Group Ltd. Ordinary Shares Decision Process with Ensemble Learning (ML) where A is the set of discrete actions of ICL 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

Sample Set: Neural Network
Stock/Index: ICL ICL Group Ltd. Ordinary Shares
Time series to forecast: 3 Month

According to price forecasts, the dominant strategy among neural network is: Buy

F(Factor)^6,7=

\begin{matrix} p_{a 1} & p_{a 2} & \dots & p_{1 n} \\ ⋮ \\ p_{j 1} & p_{j 2} & \dots & p_{j n} \\ ⋮ \\ p_{k 1} & p_{k 2} & \dots & p_{k n} \\ ⋮ \\ p_{n 1} & p_{n 2} & \dots & p_{n n} \end{matrix}

X R(Ensemble Learning (ML)) X S(n):→ 3 Month

\begin{array}{l} \int e^{x} rx \end{array}

n:Time series to forecast

p:Price signals of ICL stock

j:Nash equilibria (Neural Network)

k:Dominated move of ICL stock holders

a:Best response for ICL target price

Ensemble learning is a machine learning (ML) technique that combines multiple models to create a single model that is more accurate than any of the individual models. This is done by combining the predictions of the individual models, typically using a voting scheme or a weighted average.⁵ In statistics, a factor is a variable that can influence the value of another variable. Factors can be categorical or continuous. Categorical factors have a limited number of possible values, such as gender (male or female) or blood type (A, B, AB, or O). Continuous factors can have an infinite number of possible values, such as height or weight. Factors can be used to explain the variation in a dependent variable. For example, a study might find that there is a relationship between gender and height. In this case, gender would be the independent variable, height would be the dependent variable, and the factor would be gender.^6,7

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?

ICL Stock Forecast (Buy or Sell) Strategic Interaction Table

Strategic Interaction Table Legend:

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%

Financial Data Adjustments for Ensemble Learning (ML) based ICL Stock Prediction Model

For loan commitments, an entity considers changes in the risk of a default occurring on the loan to which a loan commitment relates. For financial guarantee contracts, an entity considers the changes in the risk that the specified debtor will default on the contract.
The significance of a change in the credit risk since initial recognition depends on the risk of a default occurring as at initial recognition. Thus, a given change, in absolute terms, in the risk of a default occurring will be more significant for a financial instrument with a lower initial risk of a default occurring compared to a financial instrument with a higher initial risk of a default occurring.
The underlying pool must contain one or more instruments that have contractual cash flows that are solely payments of principal and interest on the principal amount outstanding
For example, when the critical terms (such as the nominal amount, maturity and underlying) of the hedging instrument and the hedged item match or are closely aligned, it might be possible for an entity to conclude on the basis of a qualitative assessment of those critical terms that the hedging instrument and the hedged item have values that will generally move in the opposite direction because of the same risk and hence that an economic relationship exists between the hedged item and the hedging instrument (see paragraphs B6.4.4–B6.4.6).

*International Financial Reporting Standards (IFRS) adjustment process involves reviewing the company's financial statements and identifying any differences between the company's current accounting practices and the requirements of the IFRS. If there are any such differences, neural network makes adjustments to financial statements to bring them into compliance with the IFRS.

ICL ICL Group Ltd. Ordinary Shares Financial Analysis*

Rating	Short-Term	Long-Term Senior
Outlook*	Ba2	Ba3
Income Statement	Baa2	Ba3
Balance Sheet	B1	Caa2
Leverage Ratios	Baa2	Baa2
Cash Flow	B2	Baa2
Rates of Return and Profitability	B2	Caa2

*Financial analysis is the process of evaluating a company's financial performance and position by neural network. It involves reviewing the company's financial statements, including the balance sheet, income statement, and cash flow statement, as well as other financial reports and documents.
How does neural network examine financial reports and understand financial state of the company?

References

V. Borkar. An actor-critic algorithm for constrained Markov decision processes. Systems & Control Letters, 54(3):207–213, 2005.
Babula, R. A. (1988), "Contemporaneous correlation and modeling Canada's imports of U.S. crops," Journal of Agricultural Economics Research, 41, 33–38.
Allen, P. G. (1994), "Economic forecasting in agriculture," International Journal of Forecasting, 10, 81–135.
Friedman JH. 2002. Stochastic gradient boosting. Comput. Stat. Data Anal. 38:367–78
E. Altman, K. Avrachenkov, and R. N ́u ̃nez-Queija. Perturbation analysis for denumerable Markov chains with application to queueing models. Advances in Applied Probability, pages 839–853, 2004
Chow, G. C. (1960), "Tests of equality between sets of coefficients in two linear regressions," Econometrica, 28, 591–605.
Candès E, Tao T. 2007. The Dantzig selector: statistical estimation when p is much larger than n. Ann. Stat. 35:2313–51

Frequently Asked Questions

Q: What is the prediction methodology for ICL stock?
A: ICL stock prediction methodology: We evaluate the prediction models Ensemble Learning (ML) and Factor
Q: Is ICL stock a buy or sell?
A: The dominant strategy among neural network is to Buy ICL Stock.
Q: Is ICL Group Ltd. Ordinary Shares stock a good investment?
A: The consensus rating for ICL Group Ltd. Ordinary Shares is Buy and is assigned short-term Ba2 & long-term Ba3 estimated rating.
Q: What is the consensus rating of ICL stock?
A: The consensus rating for ICL is Buy.
Q: What is the prediction period for ICL stock?
A: The prediction period for ICL is 3 Month

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