Forecasting stock exchange rates is an important financial problem that is receiving increasing attention. During the last few years, a number of neural network models and hybrid models have been proposed for obtaining accurate prediction results, in an attempt to outperform the traditional linear and nonlinear approaches. This paper evaluates the effectiveness of neural network models which are known to be dynamic and effective in stock-market predictions. We evaluate TORTILLA MEXICAN GRILL PLC prediction models with Modular Neural Network (Market Direction Analysis) and Ridge Regression1,2,3,4 and conclude that the LON:MEX stock is predictable in the short/long term. According to price forecasts for (n+4 weeks) period: The dominant strategy among neural network is to Sell LON:MEX stock.

Keywords: LON:MEX, TORTILLA MEXICAN GRILL PLC, stock forecast, machine learning based prediction, risk rating, buy-sell behaviour, stock analysis, target price analysis, options and futures.

## Key Points

1. Probability Distribution
2. Trust metric by Neural Network
3. Which neural network is best for prediction? ## LON:MEX Target Price Prediction Modeling Methodology

Stock markets are affected by many uncertainties and interrelated economic and political factors at both local and global levels. The key to successful stock market forecasting is achieving best results with minimum required input data. To determine the set of relevant factors for making accurate predictions is a complicated task and so regular stock market analysis is very essential. More specifically, the stock market's movements are analyzed and predicted in order to retrieve knowledge that could guide investors on when to buy and sell. We consider TORTILLA MEXICAN GRILL PLC Stock Decision Process with Ridge Regression 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(Ridge Regression)5,6,7= $\begin{array}{cccc}{p}_{a1}& {p}_{a2}& \dots & {p}_{1n}\\ & ⋮\\ {p}_{j1}& {p}_{j2}& \dots & {p}_{jn}\\ & ⋮\\ {p}_{k1}& {p}_{k2}& \dots & {p}_{kn}\\ & ⋮\\ {p}_{n1}& {p}_{n2}& \dots & {p}_{nn}\end{array}$ X R(Modular Neural Network (Market Direction Analysis)) X S(n):→ (n+4 weeks) $∑ i = 1 n s i$

n:Time series to forecast

p:Price signals of LON:MEX stock

j:Nash equilibria

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+4 weeks)

Sample Set: Neural Network
Stock/Index: LON:MEX TORTILLA MEXICAN GRILL PLC
Time series to forecast n: 19 Oct 2022 for (n+4 weeks)

According to price forecasts for (n+4 weeks) period: The dominant strategy among neural network is to Sell LON:MEX stock.

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 (Yellow to Green): *Technical Analysis%

## Conclusions

TORTILLA MEXICAN GRILL PLC assigned short-term Ba3 & long-term B1 forecasted stock rating. We evaluate the prediction models Modular Neural Network (Market Direction Analysis) with Ridge Regression1,2,3,4 and conclude that the LON:MEX stock is predictable in the short/long term. According to price forecasts for (n+4 weeks) period: The dominant strategy among neural network is to Sell LON:MEX stock.

### Financial State Forecast for LON:MEX Stock Options & Futures

Rating Short-Term Long-Term Senior
Outlook*Ba3B1
Operational Risk 8377
Market Risk3948
Technical Analysis6655
Fundamental Analysis6163
Risk Unsystematic7042

### Prediction Confidence Score

Trust metric by Neural Network: 73 out of 100 with 647 signals.

## References

1. Hornik K, Stinchcombe M, White H. 1989. Multilayer feedforward networks are universal approximators. Neural Netw. 2:359–66
2. Bai J. 2003. Inferential theory for factor models of large dimensions. Econometrica 71:135–71
3. Imbens GW, Lemieux T. 2008. Regression discontinuity designs: a guide to practice. J. Econom. 142:615–35
4. R. Rockafellar and S. Uryasev. Optimization of conditional value-at-risk. Journal of Risk, 2:21–42, 2000.
5. 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.
6. Christou, C., P. A. V. B. Swamy G. S. Tavlas (1996), "Modelling optimal strategies for the allocation of wealth in multicurrency investments," International Journal of Forecasting, 12, 483–493.
7. Imbens GW, Lemieux T. 2008. Regression discontinuity designs: a guide to practice. J. Econom. 142:615–35
Frequently Asked QuestionsQ: What is the prediction methodology for LON:MEX stock?
A: LON:MEX stock prediction methodology: We evaluate the prediction models Modular Neural Network (Market Direction Analysis) and Ridge Regression
Q: Is LON:MEX stock a buy or sell?
A: The dominant strategy among neural network is to Sell LON:MEX Stock.
Q: Is TORTILLA MEXICAN GRILL PLC stock a good investment?
A: The consensus rating for TORTILLA MEXICAN GRILL PLC is Sell and assigned short-term Ba3 & long-term B1 forecasted stock rating.
Q: What is the consensus rating of LON:MEX stock?
A: The consensus rating for LON:MEX is Sell.
Q: What is the prediction period for LON:MEX stock?
A: The prediction period for LON:MEX is (n+4 weeks)