Behind the scenes of algorithmic trading

Now more than ever, with the emergence of excessive speculation and social trading, it makes sense to talk about this topic, algorithmic trading. The objective of this thesis will be the implementation of an autonomous trading software. This software should be able to operate without human intervention in the financial markets. It will follow a predefined strategy to find buying and selling opportunities. The criteria that will be used to evaluate the work will be the speed and performance of our software. Throughout this report, a theoretical framework will be set up. This framework will be used for the implementation of the software. Every effort will be made to ensure that as many people as possible can develop the same software or duplicate it. No investment will be necessary. No real accounts will be used. The development of this software will be done at no cost. This work is aimed at all readers who are passionate about algorithmic trading. Financial skills are not necessary, but programming skills are more than recommended to understand the importance of the work. The process of the development carried out will also be explained in detail. Every reader should be able to understand all the work that has been done. From the architecture to the algorithm, every element of this development will be shared in this document. As for the full code of the software written in Java, it will be available for download on the official GitHub repository for those readers who want it. Finally, the algorithmic trading software that works and can be used on the stock markets will be tested. The results obtained will show that the performance in terms of analysis speed (about 6 milliseconds) will logically be better than that of a human for the same task. But also, that the strategy that will be implemented, although it works perfectly, could be improved afterwards to increase the performance