The objective of the talk is to provide an introduction of how artificial intelligence could be applied in stock trading.
This session will introduce how to use Python to extract historical open-high-low-close (OHLC) data, perform data processing, recognise patterns in the stock market with artificial intelligence algorithms and eventually backtest the strategy. The talk will also touch on further work that could be done, including the scraping and feature engineering of alternative data.
Buzzwords: artificial intelligence, trading, quant trading
Level: Beginner: Target audiences with basic experience of python programming
Requirements to Audiences: Nil
Speaker: Roger Lee (Hong Kong)
Speaker Bio: Roger Lee works in a private equity firm and specialised in the investment in TMT and in particular artificial intelligence companies. Prior to that, he works in Bloomberg, which is a financial market data provider. Roger was graduated in the University of Hong Kong, specialised in Quantitative Finance and Computer Science. He and his team won the championship in ACM HK in 2014. During his free time, he applies artificial intelligence algorithm and other quant strategies for personal trading.