Plataforma para negociação FOREX

• Autor(a) principal: Campos, Miguel Marreiros Inácio de
• Data de Publicação: 2017
• Tipo de documento: Dissertação
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10773/23463
• topic: Engenharia de computadores e telemática; Mercados financeiros; Algoritmos heurísticos; Aprendizagem automática

The growing democratization of financial markets fueled by new technologies openedthedoortonewinvestorsandresearchers. Marketschanged,continuouslynegotiationbeganandthenumberoffinancialordersroseexponentially. With the increase in flexibility and accessibility to markets, algorithmic trading grew at the retail level, with traders starting to implement their own algorithms in trading strategies. The use of machine learning algorithms and time series analysis became widely popular, adding complexity to trading strategies. In order to create and test profitable algorithms there are rules that must be followed. This dissertation presents the development of a new generation of research and trading system that aims to help researchers and traders to be more productive and efficient. It was developed as an event-driven backtest and live trading system with an innovative approach to sharing backtest reports. Also, by merging the technical analysis based trading with new techniques, and complying with the backtest paradigm, the aim is to provide a richer environment to users.