1. Mario Antonio Regín Gutiérrez
A Comparative Analysis on the Applicability of Piotroski F-Score in the Mexican Market and Construction of a Software Simulation to Compare Historical Investment Plans Based on the P F-Score
Mario Antonio Regín Gutiérrez

2. Index Introduction A Little Bit of Theory Software Simulation
Final Thoughts

3. Introduction
A Little Bit of Theory
Software Simulation
Final Thoughts

4. This projects objetives are to explore the value of the PFS in the mexican market througth the use of software simulation
Goals
Activities
To test the Piotroski F-Score (PFS) metholodogy against the Mexican current market
To create a software simulation of the Mexican market as both an assessment tool of the PFS and a learning experience
To define the PFS methodology
To uses public available data to create a simple database of the financial statements of the companies int Mexican stock exchange BMX.
To create automatic a software tools that can use public this database to calculate the PFS of the companies in the BMX
To create a software simulation of the BMX that can create and test many portfolios based on user input and the PFS.
To compere the different portfolios against the mexican index IPC

5. Agenda Introduction A Little Bit of Theory Software simulation
Final Thoughts

6. Agenda Introduction A little bit of theory Piotroski F-Score
Mexican index IPC
Modern portfolio theory
Software simulation
Final Thoughts

7. Joseph Piotroski is used to assess strength of company’s financial position.
Overvalue stocks
B2M < 1
Sub-value stocks
B2M > 1
Relación Book to Market (B2M):
B2M
Book value
Market value
Quintile 5
Universe = stocks on the American's market ( )
Quintile 4
Quintile 3
Quintile 2
Quintile 1
Piotroski F-Score (PFS):
Value between 0-9, higher values reflect better financial strengths of a company
Quintile 5 (14,043)
PFS 8-9 (1,448) Vs
PFS 0-2 (393)

8. The original results show than the PFS can be used as a methodology to choose what assets to sell or buy
One year ROA
Two years ROA

9. The PFS is a simple but powerful methodolog base on nine 9 criteria divided into 3 groups
Profitability
ROA
Operating Cash Flow
Change in ROA this year vs last year
Accruals
Operating Efficiency
Change ig Gross Margin This year vs last year
Change in Asset Turnover ratio.
Leverage, Liquidity and Source of Funds
Change in Leverage
Change in Current ratio
Change in the number of shares

10. Piotroski got some not obvious findings
Piotrosky original findings:
Many of them are small companies with low share rotation
The market was not effective to assign stock prices to many high PFS companies, this could mean high return to investors once the market corrects the stock prices
The best source of information to an investor is the financial statements

11. Index Introduction A little bit of theory Piotroski F-Score
Mexican Index IPC
Modern Portfolio Theory
Caso práctico
Conclusiones

12. The IPC is an index that shows the tendcy of Mexican stock market, The IPC I s based on a weigthed sample
El IPC is made by 35 companies. This companies are chosen based on the following criteria::
Market Cap
Stock liquidity
Number of days the stock has been on the BMX.
The ratio between the total stocks and the number of stocks traded.
The companies in the IPC are checked very 12 months to see if they will continue to be part of the IPC
The IPC can be used to asses the tendency of the Mexican stock market.

13. Besides the 2008-2009 global crises the IPC has had a positive return the last 14 years.

14. Agenda Introduction A little Bit of Theory Piotroski F-Score
Mexican Index IPC
Modern portfolio Theory
Software Simulation
Final Thoughts

15. Modern portfolio theory (MPT), or mean-variance analysis, is a mathematical framework for assembling a portfolio
Efficient frontier
Individual assets
Individual assets on the efficient frontier
Rendimiento
Riesgo
MPT seeks to maximize expected return for a given level of risk

16. Agenda Introduction A Little Bit of Theory Software Simulation
Final Thoughts

17. This is the high level design of the software simulation
Financial Satatements
Math and logical functions
Risk
Stock Prices
User input
ROA
Automatically calculate F-Score
σ²ij Pij

18. A human made xls file with all the financial statements and stock prices is used by the software to create the local database

19. The main window

20. Read only access to the local database

21. Simulation Windows, Each steep represents a year, all stocks all sell, and the user choose witch stocks to buy

22. Final portfolio performance is save on a xls file

23. The low F-Score portfolio performs worst than the IPC (2005-2015).
PF-Score (0-3) vs IPC
ROA IPC = 17.1%
Average ROA = 6.8%

24. The Medium F-Score portfolio performs about the same than the IPC (2005-2015).
PF-Score (5) vs IPC
ROA IPC = 17.1%
Average ROA = 18.9%

25. The High F-Score portfolio performs considerably better than the IPC (2005-2015).
PF-Score (7-9) vs IPC
ROA IPC = 17.1%
Average ROA = 41.5%

26. PF-Score vs IPC vs PFS+MVA
We used the mean-variance analysis to choose stocks weighs in a high PFS portfolio, as we can see the reduced volatility and increased return ( ).
PF-Score vs IPC vs PFS+MVA
R. IPC = 17.1%
R. PFS = 26.8%
R. MVA = 29.8%

27. PFS Fecuencies of the F-Score in the BMX, we can see that there most companies have a medium F-Score ( ).

28. Future Return based on Current PFS Value, all companies in the BMX for the analyzed time period ( ).

29. Index Introduction A Little Bit of Theory Software Simulation
Final Thoughts

30. Final Thoughts
The PFS performs relative well as methodology for stock selection in the BMX on the analyzed time frame
There seems to be a high correlation between the F-Score and the average performance of a stock.
High score (7-9) companies’ stocks will in average beat the performance than the IPC for the next year.
Medium score (5) companies’ stocks will in average have about the same performance than the IPC for the next year.
Low score (0-4) companies’ stocks will in average have a worst performance than the IPC for the next year.
Even a portfolio with few stocks (3), can expect good return of investment if we use the F-Score as a methodology to stock selection
The modern portfolio theory can be applied to select the number of stocks of each high F-Score company, this seems to reduce variance thus making the MPT and F-Score methodologies a good 2 steeps process to stock selection.
Some future lines of investigation are:
To calculate correlations between F-Score and performance in the BMX
To create a software tool than can make database updates easier
To update or current simulation software so we can use other methodologies of stock selection and compare them