**Outlook:**Coca Cola Femsa S.A.B. de C.V. American Depositary Shares each representing 10 Units (each Unit consists of 3 Series B Shares and 5 Series L Shares) is assigned short-term B1 & long-term Ba3 estimated rating.

**AUC Score :**

**Short-Term Revised**

^{1}:**Dominant Strategy :**Buy

**Time series to forecast n:** for

^{2}

**Methodology :**Supervised Machine Learning (ML)

**Hypothesis Testing :**Chi-Square

**Surveillance :**Major exchange and OTC

^{1}The accuracy of the model is being monitored on a regular basis.(15-minute period)

^{2}Time series is updated based on short-term trends.

## Summary

Coca Cola Femsa S.A.B. de C.V. American Depositary Shares each representing 10 Units (each Unit consists of 3 Series B Shares and 5 Series L Shares) prediction model is evaluated with Supervised Machine Learning (ML) and Chi-Square^{1,2,3,4}and it is concluded that the KOF stock is predictable in the short/long term. Supervised machine learning (ML) is a type of machine learning where a model is trained on labeled data. This means that the data has been tagged with the correct output for the input data. The model learns to predict the output for new input data based on the labeled data. Supervised ML is a powerful tool that can be used for a variety of tasks, including classification, regression, and forecasting. Classification tasks involve predicting the category of an input data, such as whether an email is spam or not. Regression tasks involve predicting a numerical value for an input data, such as the price of a house. Forecasting tasks involve predicting future values for a time series, such as the sales of a product.

^{5}

**According to price forecasts for 1 Year period, the dominant strategy among neural network is: Buy**

## Key Points

- Supervised Machine Learning (ML) for KOF stock price prediction process.
- Chi-Square
- Trading Interaction
- Trust metric by Neural Network
- What are main components of Markov decision process?

## KOF Stock Price Forecast

We consider Coca Cola Femsa S.A.B. de C.V. American Depositary Shares each representing 10 Units (each Unit consists of 3 Series B Shares and 5 Series L Shares) Decision Process with Supervised Machine Learning (ML) where A is the set of discrete actions of KOF 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}

**Sample Set:**Neural Network

**Stock/Index:**KOF Coca Cola Femsa S.A.B. de C.V. American Depositary Shares each representing 10 Units (each Unit consists of 3 Series B Shares and 5 Series L Shares)

**Time series to forecast:**1 Year

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

^{6,7}= $\begin{array}{cccc}{p}_{\mathrm{a}1}& {p}_{\mathrm{a}2}& \dots & {p}_{1n}\\ & \vdots \\ {p}_{j1}& {p}_{j2}& \dots & {p}_{jn}\\ & \vdots \\ {p}_{k1}& {p}_{k2}& \dots & {p}_{kn}\\ & \vdots \\ {p}_{n1}& {p}_{n2}& \dots & {p}_{nn}\end{array}$ X R(Supervised Machine Learning (ML)) X S(n):→ 1 Year $\begin{array}{l}\int {e}^{x}\mathrm{rx}\end{array}$

n:Time series to forecast

p:Price signals of KOF stock

j:Nash equilibria (Neural Network)

k:Dominated move of KOF stock holders

a:Best response for KOF target price

Supervised machine learning (ML) is a type of machine learning where a model is trained on labeled data. This means that the data has been tagged with the correct output for the input data. The model learns to predict the output for new input data based on the labeled data. Supervised ML is a powerful tool that can be used for a variety of tasks, including classification, regression, and forecasting. Classification tasks involve predicting the category of an input data, such as whether an email is spam or not. Regression tasks involve predicting a numerical value for an input data, such as the price of a house. Forecasting tasks involve predicting future values for a time series, such as the sales of a product.

^{5}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.

^{6,7}

For further technical information as per how our model work we invite you to visit the article below:

### KOF Stock Forecast (Buy or Sell) Strategic Interaction Table

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 Supervised Machine Learning (ML) based KOF Stock Prediction Model

- When an entity separates the foreign currency basis spread from a financial instrument and excludes it from the designation of that financial instrument as the hedging instrument (see paragraph 6.2.4(b)), the application guidance in paragraphs B6.5.34–B6.5.38 applies to the foreign currency basis spread in the same manner as it is applied to the forward element of a forward contract.
- An entity shall assess separately whether each subgroup meets the requirements in paragraph 6.6.1 to be an eligible hedged item. If any subgroup fails to meet the requirements in paragraph 6.6.1, the entity shall discontinue hedge accounting prospectively for the hedging relationship in its entirety. An entity also shall apply the requirements in paragraphs 6.5.8 and 6.5.11 to account for ineffectiveness related to the hedging relationship in its entirety.
- An entity shall apply this Standard retrospectively, in accordance with IAS 8 Accounting Policies, Changes in Accounting Estimates and Errors, except as specified in paragraphs 7.2.4–7.2.26 and 7.2.28. This Standard shall not be applied to items that have already been derecognised at the date of initial application.
- To calculate the change in the value of the hedged item for the purpose of measuring hedge ineffectiveness, an entity may use a derivative that would have terms that match the critical terms of the hedged item (this is commonly referred to as a 'hypothetical derivative'), and, for example for a hedge of a forecast transaction, would be calibrated using the hedged price (or rate) level. For example, if the hedge was for a two-sided risk at the current market level, the hypothetical derivative would represent a hypothetical forward contract that is calibrated to a value of nil at the time of designation of the hedging relationship. If the hedge was for example for a one-sided risk, the hypothetical derivative would represent the intrinsic value of a hypothetical option that at the time of designation of the hedging relationship is at the money if the hedged price level is the current market level, or out of the money if the hedged price level is above (or, for a hedge of a long position, below) the current market level. Using a hypothetical derivative is one possible way of calculating the change in the value of the hedged item. The hypothetical derivative replicates the hedged item and hence results in the same outcome as if that change in value was determined by a different approach. Hence, using a 'hypothetical derivative' is not a method in its own right but a mathematical expedient that can only be used to calculate the value of the hedged item. Consequently, a 'hypothetical derivative' cannot be used to include features in the value of the hedged item that only exist in the hedging instrument (but not in the hedged item). An example is debt denominated in a foreign currency (irrespective of whether it is fixed-rate or variable-rate debt). When using a hypothetical derivative to calculate the change in the value of such debt or the present value of the cumulative change in its cash flows, the hypothetical derivative cannot simply impute a charge for exchanging different currencies even though actual derivatives under which different currencies are exchanged might include such a charge (for example, cross-currency interest rate swaps).

*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.

### KOF Coca Cola Femsa S.A.B. de C.V. American Depositary Shares each representing 10 Units (each Unit consists of 3 Series B Shares and 5 Series L Shares) Financial Analysis*

Rating | Short-Term | Long-Term Senior |
---|---|---|

Outlook* | B1 | Ba3 |

Income Statement | B3 | B1 |

Balance Sheet | Baa2 | B3 |

Leverage Ratios | C | Baa2 |

Cash Flow | B2 | B3 |

Rates of Return and Profitability | Ba1 | B2 |

*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?

## References

- Farrell MH, Liang T, Misra S. 2018. Deep neural networks for estimation and inference: application to causal effects and other semiparametric estimands. arXiv:1809.09953 [econ.EM]
- Imbens GW, Lemieux T. 2008. Regression discontinuity designs: a guide to practice. J. Econom. 142:615–35
- J. Peters, S. Vijayakumar, and S. Schaal. Natural actor-critic. In Proceedings of the Sixteenth European Conference on Machine Learning, pages 280–291, 2005.
- A. K. Agogino and K. Tumer. Analyzing and visualizing multiagent rewards in dynamic and stochastic environments. Journal of Autonomous Agents and Multi-Agent Systems, 17(2):320–338, 2008
- Greene WH. 2000. Econometric Analysis. Upper Saddle River, N J: Prentice Hall. 4th ed.
- Breusch, T. S. (1978), "Testing for autocorrelation in dynamic linear models," Australian Economic Papers, 17, 334–355.
- Mnih A, Hinton GE. 2007. Three new graphical models for statistical language modelling. In International Conference on Machine Learning, pp. 641–48. La Jolla, CA: Int. Mach. Learn. Soc.

## Frequently Asked Questions

Q: Is KOF stock expected to rise?A: KOF stock prediction model is evaluated with Supervised Machine Learning (ML) and Chi-Square and it is concluded that dominant strategy for KOF stock is Buy

Q: Is KOF stock a buy or sell?

A: The dominant strategy among neural network is to Buy KOF Stock.

Q: Is Coca Cola Femsa S.A.B. de C.V. American Depositary Shares each representing 10 Units (each Unit consists of 3 Series B Shares and 5 Series L Shares) stock a good investment?

A: The consensus rating for Coca Cola Femsa S.A.B. de C.V. American Depositary Shares each representing 10 Units (each Unit consists of 3 Series B Shares and 5 Series L Shares) is Buy and is assigned short-term B1 & long-term Ba3 estimated rating.

Q: What is the consensus rating of KOF stock?

A: The consensus rating for KOF is Buy.

Q: What is the forecast for KOF stock?

A: KOF target price forecast: Buy

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