Trading with Evolution

Genetic Algorithms in Elixir — by Sean Moriarity (96 / 101)

👈 Designing with Evolution | TOC | Networking with Evolution 👉

In Chapter 4, ​Evaluating Solutions and Populations​, we briefly introduced portfolio optimization using genetic algorithms. In that chapter, you learned a little about how genetic algorithms can be used to balance risk and reward in financial portfolios. The best portfolio with respect to risk and reward is called the efficient frontier.

Genetic algorithms can also be used to make trades. Institutional quantitative traders use genetic algorithms to evolve the parameters that help them decide which assets to trade. They can also be used to identify which parameters most significantly impact the price of a given asset.

Financial trading has used genetic algorithms for almost as long as genetic algorithms have been around. The abundance of available financial information coupled with the power of genetic algorithms to find useful solutions in a sea of information makes the combination incredibly powerful.

👈 Designing with Evolution | TOC | Networking with Evolution 👉

Genetic Algorithms in Elixir by Sean Moriarity can be purchased in other book formats directly from the Pragmatic Programmers. If you notice a code error or formatting mistake, please let us know here so that we can fix it.