LON:GRG GREGGS PLC

Outlook: GREGGS PLC is assigned short-term Ba1 & long-term Ba1 estimated rating.
Dominant Strategy : Hold
Time series to forecast n: 19 Mar 2023 for (n+3 month)
Methodology : Modular Neural Network (Market Volatility Analysis)

Abstract

GREGGS PLC prediction model is evaluated with Modular Neural Network (Market Volatility Analysis) and Wilcoxon Sign-Rank Test^1,2,3,4 and it is concluded that the LON:GRG stock is predictable in the short/long term. According to price forecasts for (n+3 month) period, the dominant strategy among neural network is: Hold

Key Points

1. What are the most successful trading algorithms?
2. Can statistics predict the future?
3. Probability Distribution

LON:GRG Target Price Prediction Modeling Methodology

We consider GREGGS PLC Decision Process with Modular Neural Network (Market Volatility Analysis) where A is the set of discrete actions of LON:GRG 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(Modular Neural Network (Market Volatility Analysis)) X S(n):→ (n+3 month) $\overrightarrow{R}=\left(r_1,r_2,r_3\right)$

n:Time series to forecast

p:Price signals of LON:GRG 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?

LON:GRG Stock Forecast (Buy or Sell) for (n+3 month)

Sample Set: Neural Network
Stock/Index: LON:GRG GREGGS PLC
Time series to forecast n: 19 Mar 2023 for (n+3 month)

According to price forecasts for (n+3 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 GREGGS PLC

1. An entity may use practical expedients when measuring expected credit losses if they are consistent with the principles in paragraph 5.5.17. An example of a practical expedient is the calculation of the expected credit losses on trade receivables using a provision matrix. The entity would use its historical credit loss experience (adjusted as appropriate in accordance with paragraphs B5.5.51–B5.5.52) for trade receivables to estimate the 12-month expected credit losses or the lifetime expected credit losses on the financial assets as relevant. A provision matrix might, for example, specify fixed provision rates depending on the number of days that a trade receivable is past due (for example, 1 per cent if not past due, 2 per cent if less than 30 days past due, 3 per cent if more than 30 days but less than 90 days past due, 20 per cent if 90–180 days past due etc). Depending on the diversity of its customer base, the entity would use appropriate groupings if its historical credit loss experience shows significantly different loss patterns for different customer segments. Examples of criteria that might be used to group assets include geographical region, product type, customer rating, collateral or trade credit insurance and type of customer (such as wholesale or retail)
2. When using historical credit loss experience in estimating expected credit losses, it is important that information about historical credit loss rates is applied to groups that are defined in a manner that is consistent with the groups for which the historical credit loss rates were observed. Consequently, the method used shall enable each group of financial assets to be associated with information about past credit loss experience in groups of financial assets with similar risk characteristics and with relevant observable data that reflects current conditions.
3. A regular way purchase or sale gives rise to a fixed price commitment between trade date and settlement date that meets the definition of a derivative. However, because of the short duration of the commitment it is not recognised as a derivative financial instrument. Instead, this Standard provides for special accounting for such regular way contracts (see paragraphs 3.1.2 and B3.1.3–B3.1.6).
4. A net position is eligible for hedge accounting only if an entity hedges on a net basis for risk management purposes. Whether an entity hedges in this way is a matter of fact (not merely of assertion or documentation). Hence, an entity cannot apply hedge accounting on a net basis solely to achieve a particular accounting outcome if that would not reflect its risk management approach. Net position hedging must form part of an established risk management strategy. Normally this would be approved by key management personnel as defined in IAS 24.

*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

GREGGS PLC is assigned short-term Ba1 & long-term Ba1 estimated rating. GREGGS PLC prediction model is evaluated with Modular Neural Network (Market Volatility Analysis) and Wilcoxon Sign-Rank Test^1,2,3,4 and it is concluded that the LON:GRG stock is predictable in the short/long term. According to price forecasts for (n+3 month) period, the dominant strategy among neural network is: Hold

LON:GRG GREGGS PLC Financial Analysis*

Rating	Short-Term	Long-Term Senior
Outlook*	Ba1	Ba1
Income Statement	C	Ba2
Balance Sheet	C	Baa2
Leverage Ratios	B3	C
Cash Flow	C	Caa2
Rates of Return and Profitability	Caa2	C

*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: 79 out of 100 with 815 signals.

References

1. A. Eck, L. Soh, S. Devlin, and D. Kudenko. Potential-based reward shaping for finite horizon online POMDP planning. Autonomous Agents and Multi-Agent Systems, 30(3):403–445, 2016
2. Miller A. 2002. Subset Selection in Regression. New York: CRC Press
3. Künzel S, Sekhon J, Bickel P, Yu B. 2017. Meta-learners for estimating heterogeneous treatment effects using machine learning. arXiv:1706.03461 [math.ST]
4. Chen, C. L. Liu (1993), "Joint estimation of model parameters and outlier effects in time series," Journal of the American Statistical Association, 88, 284–297.
5. Çetinkaya, A., Zhang, Y.Z., Hao, Y.M. and Ma, X.Y., Can neural networks predict stock market?(ATVI Stock Forecast). AC Investment Research Journal, 101(3).
6. Athey S, Imbens G. 2016. Recursive partitioning for heterogeneous causal effects. PNAS 113:7353–60
7. N. B ̈auerle and J. Ott. Markov decision processes with average-value-at-risk criteria. Mathematical Methods of Operations Research, 74(3):361–379, 2011

Frequently Asked Questions

Q: What is the prediction methodology for LON:GRG stock?
A: LON:GRG stock prediction methodology: We evaluate the prediction models Modular Neural Network (Market Volatility Analysis) and Wilcoxon Sign-Rank Test
Q: Is LON:GRG stock a buy or sell?
A: The dominant strategy among neural network is to Hold LON:GRG Stock.
Q: Is GREGGS PLC stock a good investment?
A: The consensus rating for GREGGS PLC is Hold and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of LON:GRG stock?
A: The consensus rating for LON:GRG is Hold.
Q: What is the prediction period for LON:GRG stock?
A: The prediction period for LON:GRG is (n+3 month)

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