| Content | Workshop Description
Program trading, which includes high frequency trading (HFT), has become important that it generated over sixty percent of trading volume at Nasdaq and NYSE as well as close to seventy percent at China A-share. Also, the technologies and models used in algo trading also experienced a huge change in the past five years that AI became the focus spot that several leading hedge funds and banks, such as, Renaissance Technologies, Two-Sigma, and Goldman Sachs, invested significantly on building such AI environment. Where AI technologies can be applied to support algo trading? There are wide range of issues that AI, especially the machine learning, deep learning, or even more specific models like transfer learning, can assist in building solutions, for example, market analysis, market sentiment analysis, trading opportunities identification, market impact and trading cost estimation/optimization, trading strategies selection, order slicing and trade scheduling, capital and exit management, as well as risk management. As a summary, we will discuss how traditional models and AI can be applied to support different stages of algo trading. We will also discuss how to form Algo Trading teams to participate in different competitions.
Learning Objectives
After finishing the workshop, students will be able to
1. Understand the process or operation of algo trading.
2. Understand the cost structure of algo trading and how they affect the performance of trading.
3. Understand the major traditional and AI technologies in supporting algo trading.
4. Understand how to build a trading system with selected trading strategies.
In summary, after taking this workshop, students not only understand the theories from the textbooks, but also have practical and hand-on experience to develop AI-based trading system. |
