Summary

In this chapter, we considered the pros and cons of using Python for algorithmic trading strategy research and development. We considered various options for using native Python data structures to handle market data. We learned about the various ecosystems, third-party libraries, and environments that speed up the development process. We also learned about the most important phases of development and the essential procedures that aim to make sure that the strategy has the potential to make money in live markets.

However, as with any project in any domain, before we can proceed to actual coding, we should get acquainted with the subject. In our case, it is the market itself, its basic elements, structure, and the organization that we will consider in order to see how it operates and what we should take into account to build robust trading applications. This is what we are going to do in the very next chapter.