Free - Algorithmic Trading Development Workshop (Cantonese Speaker)

Description

Today, algorithmic trading has become a mainstream direction in the investment industry. With algorithmic trading, you can accurately analyze data collected from various sources, use big data technology for rigorous professional analysis, and strictly execute all trading decisions without relying on manual operations, eliminating human weaknesses. Studies indicate that in volatile market conditions, computerized fully automated trading performs better than manual trading; as investment environments become increasingly volatile, algorithmic trading is the only winning approach. What is algorithmic trading? Algorithmic trading is a trading system primarily based on computer programs, whose decision-making foundation derives entirely from pricing models developed from market price and sentiment indicator theories. Commonly used technical indicators in the market are programmed into software systems, which then calculate buy and sell signals. Investors act upon these signals to buy or sell, rather than operating based on subjective investor opinions (Trend View). The advantage of algorithmic trading lies in using computer-generated signals to prevent investors from making irrational trades due to emotional reactions caused by market movements. Additionally, consistent trading rules can eliminate impulsive buying high and selling low behaviors, thereby pursuing stable returns. How exactly can data be used to increase investment success rates? How can important information be identified from massive datasets to make investment decisions? How can algorithmic trading be used to make wise decisions? Instructor Introduction: K.S. Lee K.S. Lee is a senior IT technology developer and current big data analysis expert, graduated from The Hong Kong Polytechnic University, with over twenty years of development experience, consistently dedicated to big data analysis. He is highly proficient and skilled in using open-source platforms R and Python for big data mining and analysis. K.S. Lee actively participates in various big data analysis projects and serves as a lecturer at multiple tertiary institutions, possessing over ten years of teaching experience with numerous students taught. His teaching scope covers various fields including Machine Learning, Data Science, Data Mining, and financial technology. Besides teaching various theories, he also shares industry work experiences with students.