Two-day Workshop: Artificial Intelligence in Algorithmic Trading
Organized by: Centre for Artificial Intelligence, Institute of Collaborative Innovation
2-3 September 2019
Limit to 40
UM Students with priority to postgraduate students. Other related and interested parties such as market practitioners are welcome to register, subject to university confirmation
N1-1004, UM Guest House N1
Deadline: 28 August 2019
30 August 2019
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.
After finishing the workshop, students will be able to
- Understand the process or operation of algo trading.
- Understand the cost structure of algo trading and how they affect the performance of trading.
- Understand the major traditional and AI technologies in supporting algo trading.
- 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.
Tentative Schedule with Content (75 minutes for each session)
|Day 1 – 2 September|
|9:30||Opening Remark – Impacts of AI on Financial Industry||Prof. Cheng-Zhong Xu|
|9:45||Session 1 – Application of AI in Algo Trading||Prof. Simon Lin|
|11:15||Session 2 – Process and Frameworks in Algo Trading|
Case Study: the SPEER System (A stock selection and portfolio management system) and Vol-term Structure based Volatility Trading
|Prof. Jerome Yen|
|12:30||Light lunch with market practitioners and group discussion|
|14:15||Session 3 – AI and Machine Learning in Algo Trading||Prof. Jiantao Zhou|
|15:45||Session 4 – Case Study: Ellman Neural Network and GA as well as Wavelet Neural Network and Particle Swamp Optimization in HSI open price prediction||Prof. Jerome Yen|
|Day 2 – 3 September|
|9:30||Session 5 – Numerical Methods in Option Pricing||Prof. Deng Ding|
|11:00||Session 6 – Volatility Estimation: High Frequency and Market Microstructure||Prof. Zhi Liu|
|12:15||Light lunch and group discussion (formation of trading team)|
|14:00||Session 7 – AI in Market Sentiment Analysis – NLP and Textual Mining||Dr. Yi Long|
|15:30||Session 8 – Key Trading Strategies in Trend, Mean Reversion, and Oscillation Market|
Case Study: Chart pattern classification, Trend Following, and transfer learning for time series forecasting
|Prof. Lawrence Si|
|16:45||Closing Remark||Prof. Jiantao Zhou|
Participants with attendance reaching 75% and completing the class requirements (including but not limited to forming a team to participate in related Algo Trading Competition) will be awarded a certificate issued by the Institute of Collaborative Innovation.