LON:MEX TORTILLA MEXICAN GRILL PLC

Outlook: TORTILLA MEXICAN GRILL PLC is assigned short-term Ba1 & long-term Ba1 estimated rating.
Dominant Strategy : Hold
Time series to forecast n: 13 Jan 2023 for (n+8 weeks)
Methodology : Modular Neural Network (DNN Layer)

Abstract

TORTILLA MEXICAN GRILL PLC prediction model is evaluated with Modular Neural Network (DNN Layer) and Spearman Correlation^1,2,3,4 and it is concluded that the LON:MEX stock is predictable in the short/long term. According to price forecasts for (n+8 weeks) period, the dominant strategy among neural network is: Hold

Key Points

1. What is Markov decision process in reinforcement learning?
2. What are main components of Markov decision process?
3. What is statistical models in machine learning?

LON:MEX Target Price Prediction Modeling Methodology

We consider TORTILLA MEXICAN GRILL PLC Decision Process with Modular Neural Network (DNN Layer) where A is the set of discrete actions of LON:MEX 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(Spearman Correlation)^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 (DNN Layer)) X S(n):→ (n+8 weeks) $\begin{array}{l}\int r^s\mathrm{rs}\end{array}$

n:Time series to forecast

p:Price signals of LON:MEX 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:MEX Stock Forecast (Buy or Sell) for (n+8 weeks)

Sample Set: Neural Network
Stock/Index: LON:MEX TORTILLA MEXICAN GRILL PLC
Time series to forecast n: 13 Jan 2023 for (n+8 weeks)

According to price forecasts for (n+8 weeks) 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 TORTILLA MEXICAN GRILL PLC

1. Although the objective of an entity's business model may be to hold financial assets in order to collect contractual cash flows, the entity need not hold all of those instruments until maturity. Thus an entity's business model can be to hold financial assets to collect contractual cash flows even when sales of financial assets occur or are expected to occur in the future.
2. The accounting for the forward element of forward contracts in accordance with paragraph 6.5.16 applies only to the extent that the forward element relates to the hedged item (aligned forward element). The forward element of a forward contract relates to the hedged item if the critical terms of the forward contract (such as the nominal amount, life and underlying) are aligned with the hedged item. Hence, if the critical terms of the forward contract and the hedged item are not fully aligned, an entity shall determine the aligned forward element, ie how much of the forward element included in the forward contract (actual forward element) relates to the hedged item (and therefore should be treated in accordance with paragraph 6.5.16). An entity determines the aligned forward element using the valuation of the forward contract that would have critical terms that perfectly match the hedged item.
3. An entity's documentation of the hedging relationship includes how it will assess the hedge effectiveness requirements, including the method or methods used. The documentation of the hedging relationship shall be updated for any changes to the methods (see paragraph B6.4.17).
4. An entity that first applies IFRS 17 as amended in June 2020 at the same time it first applies this Standard shall apply paragraphs 7.2.1–7.2.28 instead of paragraphs 7.2.38–7.2.42.

*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

TORTILLA MEXICAN GRILL PLC is assigned short-term Ba1 & long-term Ba1 estimated rating. TORTILLA MEXICAN GRILL PLC prediction model is evaluated with Modular Neural Network (DNN Layer) and Spearman Correlation^1,2,3,4 and it is concluded that the LON:MEX stock is predictable in the short/long term. According to price forecasts for (n+8 weeks) period, the dominant strategy among neural network is: Hold

LON:MEX TORTILLA MEXICAN GRILL PLC Financial Analysis*

Rating	Short-Term	Long-Term Senior
Outlook*	Ba1	Ba1
Income Statement	B3	B3
Balance Sheet	B3	Caa2
Leverage Ratios	Ba2	Baa2
Cash Flow	Baa2	Caa2
Rates of Return and Profitability	B1	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: 87 out of 100 with 747 signals.

References

1. K. Tumer and D. Wolpert. A survey of collectives. In K. Tumer and D. Wolpert, editors, Collectives and the Design of Complex Systems, pages 1–42. Springer, 2004.
2. Imbens GW, Rubin DB. 2015. Causal Inference in Statistics, Social, and Biomedical Sciences. Cambridge, UK: Cambridge Univ. Press
3. Greene WH. 2000. Econometric Analysis. Upper Saddle River, N J: Prentice Hall. 4th ed.
4. L. Prashanth and M. Ghavamzadeh. Actor-critic algorithms for risk-sensitive MDPs. In Proceedings of Advances in Neural Information Processing Systems 26, pages 252–260, 2013.
5. K. Boda, J. Filar, Y. Lin, and L. Spanjers. Stochastic target hitting time and the problem of early retirement. Automatic Control, IEEE Transactions on, 49(3):409–419, 2004
6. O. Bardou, N. Frikha, and G. Pag`es. Computing VaR and CVaR using stochastic approximation and adaptive unconstrained importance sampling. Monte Carlo Methods and Applications, 15(3):173–210, 2009.
7. Y. Chow and M. Ghavamzadeh. Algorithms for CVaR optimization in MDPs. In Advances in Neural Infor- mation Processing Systems, pages 3509–3517, 2014.

Frequently Asked Questions

Q: What is the prediction methodology for LON:MEX stock?
A: LON:MEX stock prediction methodology: We evaluate the prediction models Modular Neural Network (DNN Layer) and Spearman Correlation
Q: Is LON:MEX stock a buy or sell?
A: The dominant strategy among neural network is to Hold LON:MEX Stock.
Q: Is TORTILLA MEXICAN GRILL PLC stock a good investment?
A: The consensus rating for TORTILLA MEXICAN GRILL PLC is Hold and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of LON:MEX stock?
A: The consensus rating for LON:MEX is Hold.
Q: What is the prediction period for LON:MEX stock?
A: The prediction period for LON:MEX is (n+8 weeks)

Premium

• Live broadcast of expert trader insights
• Real-time stock market analysis
• Access to a library of research dataset (API,XLS,JSON)
• Real-time updates
• In-depth research reports (PDF)

Login