Speaker
Description
Trading in financial exchanges is becoming increasingly data driven and algorithmic due to the large amount of detailed data available about the limit order book and the increasing speed competitive nature of trading. I will argue that because of this, algorithmic trading is a great playground for machine learning methods.
In this talk I will discuss what kind of real-life data science problems we faced with in a machine learning based trading team. To put the business problem in context I will first talk about the different participants in a financial exchange. We will also briefly discuss how traders interact with the limit order book and what is the role of liquidity and market makers. I will then describe the type of big data which describes the order book dynamics, the different approaches one can take, and learning algorithms one can use when designing market making trading algorithms.
Title
Market liquidity, order book dynamics and machine learning
| authors | Balázs Meszéna |
|---|---|
| affiliation | Optiver Europe (on leave) |
