LON:BD15 Stock: In a Bubble?

Outlook: TATE & LYLE PLC is assigned short-term B2 & long-term Baa2 estimated rating.
AUC Score : What is AUC Score?
Short-Term Revised* :
Dominant Strategy : Hold
Time series to forecast n: for 6 Month
Methodology : Inductive Learning (ML)
Hypothesis Testing : Chi-Square
Surveillance : Major exchange and OTC

Summary

TATE & LYLE PLC prediction model is evaluated with Inductive Learning (ML) and Chi-Square^1,2,3,4 and it is concluded that the LON:BD15 stock is predictable in the short/long term. Inductive learning is a type of machine learning in which the model learns from a set of labeled data and makes predictions about new, unlabeled data. The model is trained on the labeled data and then used to make predictions on new data. Inductive learning 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 inductive learning algorithms, including decision trees, support vector machines, and neural networks. Each type of algorithm has its own strengths and weaknesses. According to price forecasts for 6 Month period, the dominant strategy among neural network is: Hold

*Revision

We revised our short-term strategy to .(Based on stock rating surveillance.) We also affirmed our outlook and TATE & LYLE PLC is assigned short-term B2 & long-term Baa2 estimated rating.

Key Points

1. Operational Risk
2. Is now good time to invest?
3. Is now good time to invest?

LON:BD15 Target Price Prediction Modeling Methodology

We consider TATE & LYLE PLC Decision Process with Inductive Learning (ML) where A is the set of discrete actions of LON:BD15 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(Chi-Square)^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(Inductive Learning (ML)) X S(n):→ 6 Month $\sum _{i=1}^n\left(s_i\right)$

n:Time series to forecast

p:Price signals of LON:BD15 stock

j:Nash equilibria (Neural Network)

k:Dominated move

a:Best response for target price

Inductive Learning (ML)

Inductive learning is a type of machine learning in which the model learns from a set of labeled data and makes predictions about new, unlabeled data. The model is trained on the labeled data and then used to make predictions on new data. Inductive learning 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 inductive learning algorithms, including decision trees, support vector machines, and neural networks. Each type of algorithm has its own strengths and weaknesses.

Chi-Square

A chi-squared test is a statistical hypothesis test that assesses whether observed frequencies in a sample differ significantly from expected frequencies. It is one of the most widely used statistical tests in the social sciences and in many areas of observational research. The chi-squared test is a non-parametric test, meaning that it does not assume that the data is normally distributed. This makes it a versatile tool that can be used to analyze a wide variety of data. There are two main types of chi-squared tests: the chi-squared goodness of fit test and the chi-squared test of independence.

 

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:BD15 Stock Forecast (Buy or Sell) for 6 Month

Sample Set: Neural Network
Stock/Index: LON:BD15 TATE & LYLE PLC
Time series to forecast: 6 Month

According to price forecasts for 6 Month 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%

IFRS Reconciliation Adjustments for TATE & LYLE PLC

1. An entity shall assess at the inception of the hedging relationship, and on an ongoing basis, whether a hedging relationship meets the hedge effectiveness requirements. At a minimum, an entity shall perform the ongoing assessment at each reporting date or upon a significant change in the circumstances affecting the hedge effectiveness requirements, whichever comes first. The assessment relates to expectations about hedge effectiveness and is therefore only forward-looking.
2. An entity applies IAS 21 to financial assets and financial liabilities that are monetary items in accordance with IAS 21 and denominated in a foreign currency. IAS 21 requires any foreign exchange gains and losses on monetary assets and monetary liabilities to be recognised in profit or loss. An exception is a monetary item that is designated as a hedging instrument in a cash flow hedge (see paragraph 6.5.11), a hedge of a net investment (see paragraph 6.5.13) or a fair value hedge of an equity instrument for which an entity has elected to present changes in fair value in other comprehensive income in accordance with paragraph 5.7.5 (see paragraph 6.5.8).
3. The decision of an entity to designate a financial asset or financial liability as at fair value through profit or loss is similar to an accounting policy choice (although, unlike an accounting policy choice, it is not required to be applied consistently to all similar transactions). When an entity has such a choice, paragraph 14(b) of IAS 8 requires the chosen policy to result in the financial statements providing reliable and more relevant information about the effects of transactions, other events and conditions on the entity's financial position, financial performance or cash flows. For example, in the case of designation of a financial liability as at fair value through profit or loss, paragraph 4.2.2 sets out the two circumstances when the requirement for more relevant information will be met. Accordingly, to choose such designation in accordance with paragraph 4.2.2, the entity needs to demonstrate that it falls within one (or both) of these two circumstances.
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.

Conclusions

TATE & LYLE PLC is assigned short-term B2 & long-term Baa2 estimated rating. TATE & LYLE PLC prediction model is evaluated with Inductive Learning (ML) and Chi-Square^1,2,3,4 and it is concluded that the LON:BD15 stock is predictable in the short/long term. According to price forecasts for 6 Month period, the dominant strategy among neural network is: Hold

LON:BD15 TATE & LYLE PLC Financial Analysis*

Rating	Short-Term	Long-Term Senior
Outlook*	B2	Baa2
Income Statement	Caa2	Baa2
Balance Sheet	Caa2	Ba3
Leverage Ratios	Baa2	Ba1
Cash Flow	Ba3	Baa2
Rates of Return and Profitability	B3	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?

Prediction Confidence Score

Trust metric by Neural Network: 72 out of 100 with 577 signals.

References

1. Belloni A, Chernozhukov V, Hansen C. 2014. High-dimensional methods and inference on structural and treatment effects. J. Econ. Perspect. 28:29–50
2. J. N. Foerster, Y. M. Assael, N. de Freitas, and S. Whiteson. Learning to communicate with deep multi-agent reinforcement learning. In Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, December 5-10, 2016, Barcelona, Spain, pages 2137–2145, 2016.
3. Mikolov T, Sutskever I, Chen K, Corrado GS, Dean J. 2013b. Distributed representations of words and phrases and their compositionality. In Advances in Neural Information Processing Systems, Vol. 26, ed. Z Ghahramani, M Welling, C Cortes, ND Lawrence, KQ Weinberger, pp. 3111–19. San Diego, CA: Neural Inf. Process. Syst. Found.
4. H. Kushner and G. Yin. Stochastic approximation algorithms and applications. Springer, 1997.
5. Holland PW. 1986. Statistics and causal inference. J. Am. Stat. Assoc. 81:945–60
6. R. Sutton and A. Barto. Reinforcement Learning. The MIT Press, 1998
7. Hirano K, Porter JR. 2009. Asymptotics for statistical treatment rules. Econometrica 77:1683–701

Frequently Asked Questions

Q: What is the prediction methodology for LON:BD15 stock?
A: LON:BD15 stock prediction methodology: We evaluate the prediction models Inductive Learning (ML) and Chi-Square
Q: Is LON:BD15 stock a buy or sell?
A: The dominant strategy among neural network is to Hold LON:BD15 Stock.
Q: Is TATE & LYLE PLC stock a good investment?
A: The consensus rating for TATE & LYLE PLC is Hold and is assigned short-term B2 & long-term Baa2 estimated rating.
Q: What is the consensus rating of LON:BD15 stock?
A: The consensus rating for LON:BD15 is Hold.
Q: What is the prediction period for LON:BD15 stock?
A: The prediction period for LON:BD15 is 6 Month

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