MÉTODO DE INVESTIMENTO EM BOLSA DE VALORES DE EMPRESAS DO AGRONEGÓCIO VIA DIFERENCIAÇÃO DISCRETA

• Published in: Colloquium Exactarum (Online) Vol. 1; no. 1; pp. 36 - 45
• Main Authors: Roberto Almeida Gabriel Filho, uís, Pires Cremasco, Camila, Victor de Souza Aoki, Paulo, Ceber de Mello, Thiago, Pereira de Moraes, Leandro
• Format: Journal Article
• Language: English; Portuguese
• Published: Universidade do Oeste Paulista 01.12.2009
• Subjects: Discrete systems; Financial market; Localization of maximums and minimums
• ISSN: 2178-8332; 2178-8332
• DOI: 10.5747/ce.2009.v01.n1.e004

One of the great desires of investors of the Stock Exchange is predict the behavior of the shares of companies seeking higher profits in its applications. One of the great desires of investors in stock exchange is predict the behavior of the shares of companies seeking higher profits in its applications. The analysis performed here provides a method of investment so that shareholders can follow to profit from investment in business by theorems that we believe are unprecedented, such as tests of the first and second derivative for discrete systems, since the records of prices of the bags are discrete points at intervals of 15 minutes. Therefore, the objective of this study is the establishment of methods of deriving discrete, to define and develop theorems and tests to estimate the location of maximum and minimum values of shares of companies. Oscillations were used in the stock exchange in three Brazilian companies belonging to the South American agribusiness, which called A, B and C, with participation in derivatives of meat, pasta and sugar cane. In general, it is the function which is a fixed real number and define the "discrete derivative" from the point of: . In actual simulations performed, if the investor to carry out their business transactions in accordance with the method could be obtained a profit of 1.2% in shares of company A, company B in 1.4% and 0.7% in the company C in dates chosen for analysis. As the simulations in daily profit was higher at around 1%, we find that the method is extremely efficient, since this is the approximate monthly income of the general funds in the financial market.