Is LON:AFM Stock Expected to Go Up?

Outlook: ALPHA FINANCIAL MARKETS CONSULTING PLC is assigned short-term B1 & long-term Ba3 estimated rating.
AUC Score : What is AUC Score?
Short-Term Revised¹ :
Dominant Strategy : Hold
Time series to forecast n: for Weeks²
Methodology : Deductive Inference (ML)
Hypothesis Testing : Wilcoxon Sign-Rank Test
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.

Summary

ALPHA FINANCIAL MARKETS CONSULTING PLC prediction model is evaluated with Deductive Inference (ML) and Wilcoxon Sign-Rank Test^1,2,3,4 and it is concluded that the LON:AFM stock is predictable in the short/long term. Deductive inference is a type of reasoning in which a conclusion is drawn based on a set of premises that are assumed to be true. In machine learning (ML), deductive inference can be used to create models that can make predictions about new data based on a set of known rules. Deductive inference is a supervised learning algorithm, which means that it requires labeled data to train. The labeled data is used to train the model to make predictions about new data. There are many different types of deductive inference algorithms, including decision trees, rule-based systems, and expert systems. Each type of algorithm has its own strengths and weaknesses. According to price forecasts for 1 Year period, the dominant strategy among neural network is: Hold

Key Points

1. How do predictive algorithms actually work?
2. Should I buy stocks now or wait amid such uncertainty?
3. What is statistical models in machine learning?

LON:AFM Target Price Prediction Modeling Methodology

We consider ALPHA FINANCIAL MARKETS CONSULTING PLC Decision Process with Deductive Inference (ML) where A is the set of discrete actions of LON:AFM 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(Wilcoxon Sign-Rank Test)^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):→ 1 Year $\sum _{i=1}^n\left(a_i\right)$

n:Time series to forecast

p:Price signals of LON:AFM stock

j:Nash equilibria (Neural Network)

k:Dominated move

a:Best response for target price

Deductive Inference (ML)

Deductive inference is a type of reasoning in which a conclusion is drawn based on a set of premises that are assumed to be true. In machine learning (ML), deductive inference can be used to create models that can make predictions about new data based on a set of known rules. Deductive inference is a supervised learning algorithm, which means that it requires labeled data to train. The labeled data is used to train the model to make predictions about new data. There are many different types of deductive inference algorithms, including decision trees, rule-based systems, and expert systems. Each type of algorithm has its own strengths and weaknesses.

Wilcoxon Sign-Rank Test

The Wilcoxon rank-sum test, also known as the Mann-Whitney U test, is a non-parametric test that is used to compare the medians of two independent samples. It is a rank-based test, which means that it does not assume that the data is normally distributed. The Wilcoxon rank-sum test is calculated by first ranking the data from both samples, and then finding the sum of the ranks for one of the samples. The Wilcoxon rank-sum test statistic is then calculated by subtracting the sum of the ranks for one sample from the sum of the ranks for the other sample. The p-value for the Wilcoxon rank-sum test is calculated using a table of critical values. The p-value is the probability of obtaining a test statistic at least as extreme as the one observed, assuming that the null hypothesis is true.

 

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:AFM Stock Forecast (Buy or Sell)

Sample Set: Neural Network
Stock/Index: LON:AFM ALPHA FINANCIAL MARKETS CONSULTING PLC
Time series to forecast: 1 Year

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

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 Deductive Inference (ML) based LON:AFM Stock Prediction Model

1. As with all fair value measurements, an entity's measurement method for determining the portion of the change in the liability's fair value that is attributable to changes in its credit risk must make maximum use of relevant observable inputs and minimum use of unobservable inputs.
2. 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.
3. Unless paragraph 6.8.8 applies, for a hedge of a non-contractually specified benchmark component of interest rate risk, an entity shall apply the requirement in paragraphs 6.3.7(a) and B6.3.8—that the risk component shall be separately identifiable—only at the inception of the hedging relationship.
4. If the group of items does not have any offsetting risk positions (for example, a group of foreign currency expenses that affect different line items in the statement of profit or loss and other comprehensive income that are hedged for foreign currency risk) then the reclassified hedging instrument gains or losses shall be apportioned to the line items affected by the hedged items. This apportionment shall be done on a systematic and rational basis and shall not result in the grossing up of the net gains or losses arising from a single hedging instrument.

*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.

LON:AFM ALPHA FINANCIAL MARKETS CONSULTING PLC Financial Analysis*

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

*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?

Conclusions

ALPHA FINANCIAL MARKETS CONSULTING PLC is assigned short-term B1 & long-term Ba3 estimated rating. ALPHA FINANCIAL MARKETS CONSULTING PLC prediction model is evaluated with Deductive Inference (ML) and Wilcoxon Sign-Rank Test^1,2,3,4 and it is concluded that the LON:AFM stock is predictable in the short/long term. According to price forecasts for 1 Year period, the dominant strategy among neural network is: Hold

Prediction Confidence Score

Trust metric by Neural Network: 80 out of 100 with 504 signals.

References

1. Dimakopoulou M, Zhou Z, Athey S, Imbens G. 2018. Balanced linear contextual bandits. arXiv:1812.06227 [cs.LG]
2. Varian HR. 2014. Big data: new tricks for econometrics. J. Econ. Perspect. 28:3–28
3. K. Boda and J. Filar. Time consistent dynamic risk measures. Mathematical Methods of Operations Research, 63(1):169–186, 2006
4. A. Tamar, Y. Glassner, and S. Mannor. Policy gradients beyond expectations: Conditional value-at-risk. In AAAI, 2015
5. P. Milgrom and I. Segal. Envelope theorems for arbitrary choice sets. Econometrica, 70(2):583–601, 2002
6. H. Khalil and J. Grizzle. Nonlinear systems, volume 3. Prentice hall Upper Saddle River, 2002.
7. Kallus N. 2017. Balanced policy evaluation and learning. arXiv:1705.07384 [stat.ML]

Frequently Asked Questions

Q: What is the prediction methodology for LON:AFM stock?
A: LON:AFM stock prediction methodology: We evaluate the prediction models Deductive Inference (ML) and Wilcoxon Sign-Rank Test
Q: Is LON:AFM stock a buy or sell?
A: The dominant strategy among neural network is to Hold LON:AFM Stock.
Q: Is ALPHA FINANCIAL MARKETS CONSULTING PLC stock a good investment?
A: The consensus rating for ALPHA FINANCIAL MARKETS CONSULTING PLC is Hold and is assigned short-term B1 & long-term Ba3 estimated rating.
Q: What is the consensus rating of LON:AFM stock?
A: The consensus rating for LON:AFM is Hold.
Q: What is the prediction period for LON:AFM stock?
A: The prediction period for LON:AFM is 1 Year

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