Elaboração e implementação de processos com base em métodos quantitativos, para auxiliar na tomada de decisão e gerenciamento de risco na montagem de carteiras de investimentos.

• Autor(a) principal: Konrad, Cristiano
• Data de Publicação: 2020
• Tipo de documento: Dissertação
• Idioma: por
• Título da fonte: Biblioteca Digital de Teses e Dissertações do UFSM
• Texto Completo: http://repositorio.ufsm.br/handle/1/23415
• topic: Long and short; Pair trading; Quantitative methods; Risk management; Cointegration; Cointegração; Arbitragem estatística; CNPQ::ENGENHARIAS::ENGENHARIA DE PRODUCAO

This study applies quantitative methods in statistical arbitrage operations applied in the financial market. The kind of operations involved in this study are pair trading long and short. This method of arbitration is traditionally used in investment funds, it allows for they more control of operational risk. The results found used data from real accounts. The markets were for derivatives of foreign currency pairs and markets for dollar futures and indexes on the Brazilian stock exchange. The study used some quantitative indicators as filters for statistical arbitrage operations. The use of indicators aimed at mitigating financial operating losses. The resulting operational strategy was automated and tested in a cloud computing environment and on ordinary computers. During the tests, failures that resulted in financial losses were monitored and cataloged. For example, originated from failures in connection with the broker provider and client plataform, abrupt reboots and or freezes of the operational system, and others. All failures have been compared to the results obtained. The results of the tests with the autonomous implementation in real accounts, were relevant, although lower in terms of earned profits, compared to those carried out manually. The products developed are a depth scanner applied in large-scale mapping and an autonomous robot to operate the strategy resulting from process mapping. The proposed work aims to motivate research and guide the construction of new methods of developing financial finance for use in the cloud environment.