Dissertação
Estratégias de investimento baseadas em microestrutura de mercado
Fecha
2019-07-03Autor
Alef Willis Magno Miranda
Institución
Resumen
The use of autonomous trading agents in stock markets is becoming more common over
time, although it is yet little explored in Brazil. With the large amount of available
financial data, the construction of new trading models is feasible. The main objective
of this work is to propose new financial indicators based on market micro-structure in
order to create new automated investment strategies. To achieve this goal, a stock exchange simulator is built, a set of financial indicators based on market micro-structure
and the principles for labelling prices series are defined and, finally, an autonomous
trading agent is constructed. Firstly, the simulator, capable of reproduction of the
orders and trades sent to the stock exchange of past trading days, is presented.
Secondly, the set of financial indicators based on market micro-structure aspects and
the necessary principles to label price series are defined. Lastly, the autonomous agent
based on such indicators is built and, then, experimental validation is performed
analysing financial metrics of the agent. In order to perform the experimental validation, data from future contracts of dollar of 2018 from B3 are chosen. The financial results obtained from the agent are evaluated in multiple scenarios varying parameters of network latency and operational costs. Such financial results show the potential of using micro-structure market data to construct automated investment strategies.