Is AFA Stock Expected to Go Up?

Outlook: ASF GROUP LIMITED is assigned short-term B2 & long-term B2 estimated rating.
Dominant Strategy : Sell
Time series to forecast n: 21 Jun 2023 for 16 Weeks
Methodology : Statistical Inference (ML)

Summary

ASF GROUP LIMITED prediction model is evaluated with Statistical Inference (ML) and Linear Regression^1,2,3,4 and it is concluded that the AFA stock is predictable in the short/long term. Statistical inference is a process of drawing conclusions about a population based on data from a sample of that population. In machine learning (ML), statistical inference is used to make predictions about new data based on data that has already been seen. According to price forecasts for 16 Weeks period, the dominant strategy among neural network is: Sell

Key Points

1. Can stock prices be predicted?
2. Understanding Buy, Sell, and Hold Ratings
3. Should I buy stocks now or wait amid such uncertainty?

AFA Target Price Prediction Modeling Methodology

We consider ASF GROUP LIMITED Decision Process with Statistical Inference (ML) where A is the set of discrete actions of AFA 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(Linear 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(Statistical Inference (ML)) X S(n):→ 16 Weeks $\begin{array}{l}\int r^s\mathrm{rs}\end{array}$

n:Time series to forecast

p:Price signals of AFA stock

j:Nash equilibria (Neural Network)

k:Dominated move

a:Best response for target price

Statistical Inference (ML)

Statistical inference is a process of drawing conclusions about a population based on data from a sample of that population. In machine learning (ML), statistical inference is used to make predictions about new data based on data that has already been seen.

Linear Regression

In statistics, linear regression is a method for estimating the relationship between a dependent variable and one or more independent variables. The dependent variable is the variable that is being predicted, and the independent variables are the variables that are used to predict the dependent variable. Linear regression assumes that the relationship between the dependent variable and the independent variables is linear. This means that the dependent variable can be represented as a straight line function of the independent variables.

 

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?

AFA Stock Forecast (Buy or Sell) for 16 Weeks

Sample Set: Neural Network
Stock/Index: AFA ASF GROUP LIMITED
Time series to forecast n: 21 Jun 2023 for 16 Weeks

According to price forecasts for 16 Weeks period, the dominant strategy among neural network is: Sell

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%

IFRS Reconciliation Adjustments for ASF GROUP LIMITED

1. Alternatively, the entity may base the assessment on both types of information, ie qualitative factors that are not captured through the internal ratings process and a specific internal rating category at the reporting date, taking into consideration the credit risk characteristics at initial recognition, if both types of information are relevant.
2. There are two types of components of nominal amounts that can be designated as the hedged item in a hedging relationship: a component that is a proportion of an entire item or a layer component. The type of component changes the accounting outcome. An entity shall designate the component for accounting purposes consistently with its risk management objective.
3. To calculate the change in the value of the hedged item for the purpose of measuring hedge ineffectiveness, an entity may use a derivative that would have terms that match the critical terms of the hedged item (this is commonly referred to as a 'hypothetical derivative'), and, for example for a hedge of a forecast transaction, would be calibrated using the hedged price (or rate) level. For example, if the hedge was for a two-sided risk at the current market level, the hypothetical derivative would represent a hypothetical forward contract that is calibrated to a value of nil at the time of designation of the hedging relationship. If the hedge was for example for a one-sided risk, the hypothetical derivative would represent the intrinsic value of a hypothetical option that at the time of designation of the hedging relationship is at the money if the hedged price level is the current market level, or out of the money if the hedged price level is above (or, for a hedge of a long position, below) the current market level. Using a hypothetical derivative is one possible way of calculating the change in the value of the hedged item. The hypothetical derivative replicates the hedged item and hence results in the same outcome as if that change in value was determined by a different approach. Hence, using a 'hypothetical derivative' is not a method in its own right but a mathematical expedient that can only be used to calculate the value of the hedged item. Consequently, a 'hypothetical derivative' cannot be used to include features in the value of the hedged item that only exist in the hedging instrument (but not in the hedged item). An example is debt denominated in a foreign currency (irrespective of whether it is fixed-rate or variable-rate debt). When using a hypothetical derivative to calculate the change in the value of such debt or the present value of the cumulative change in its cash flows, the hypothetical derivative cannot simply impute a charge for exchanging different currencies even though actual derivatives under which different currencies are exchanged might include such a charge (for example, cross-currency interest rate swaps).
4. If a call option right retained by an entity prevents a transferred asset from being derecognised and the entity measures the transferred asset at fair value, the asset continues to be measured at its fair value. The associated liability is measured at (i) the option exercise price less the time value of the option if the option is in or at the money, or (ii) the fair value of the transferred asset less the time value of the option if the option is out of the money. The adjustment to the measurement of the associated liability ensures that the net carrying amount of the asset and the associated liability is the fair value of the call option right. For example, if the fair value of the underlying asset is CU80, the option exercise price is CU95 and the time value of the option is CU5, the carrying amount of the associated liability is CU75 (CU80 – CU5) and the carrying amount of the transferred asset is CU80 (ie its fair value)

*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.

Conclusions

ASF GROUP LIMITED is assigned short-term B2 & long-term B2 estimated rating. ASF GROUP LIMITED prediction model is evaluated with Statistical Inference (ML) and Linear Regression^1,2,3,4 and it is concluded that the AFA stock is predictable in the short/long term. According to price forecasts for 16 Weeks period, the dominant strategy among neural network is: Sell

AFA ASF GROUP LIMITED Financial Analysis*

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

*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?

Prediction Confidence Score

Trust metric by Neural Network: 76 out of 100 with 466 signals.

References

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2. M. Babes, E. M. de Cote, and M. L. Littman. Social reward shaping in the prisoner's dilemma. In 7th International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS 2008), Estoril, Portugal, May 12-16, 2008, Volume 3, pages 1389–1392, 2008.
3. Matzkin RL. 1994. Restrictions of economic theory in nonparametric methods. In Handbook of Econometrics, Vol. 4, ed. R Engle, D McFadden, pp. 2523–58. Amsterdam: Elsevier
4. M. Sobel. The variance of discounted Markov decision processes. Applied Probability, pages 794–802, 1982
5. Varian HR. 2014. Big data: new tricks for econometrics. J. Econ. Perspect. 28:3–28
6. Arjovsky M, Bottou L. 2017. Towards principled methods for training generative adversarial networks. arXiv:1701.04862 [stat.ML]
7. A. Shapiro, W. Tekaya, J. da Costa, and M. Soares. Risk neutral and risk averse stochastic dual dynamic programming method. European journal of operational research, 224(2):375–391, 2013

Frequently Asked Questions

Q: What is the prediction methodology for AFA stock?
A: AFA stock prediction methodology: We evaluate the prediction models Statistical Inference (ML) and Linear Regression
Q: Is AFA stock a buy or sell?
A: The dominant strategy among neural network is to Sell AFA Stock.
Q: Is ASF GROUP LIMITED stock a good investment?
A: The consensus rating for ASF GROUP LIMITED is Sell and is assigned short-term B2 & long-term B2 estimated rating.
Q: What is the consensus rating of AFA stock?
A: The consensus rating for AFA is Sell.
Q: What is the prediction period for AFA stock?
A: The prediction period for AFA is 16 Weeks