CV

Siyang Liu

Education

• Ph.D. in Business Administration (Finance) – University of British Columbia, Vancouver
  Sep. 2025 – Present
• M.Sc. in Business Administration (Finance) – University of British Columbia, Vancouver
  Sep. 2023 – April 2025
  GPA: 4.06/4.33
• B.Econ in Finance – University of Science and Technology of China, Anhui, China
  Sep. 2018 – May 2022

Work in Progress

The wisdom of crowd or the wisdom of insider? - Insider trading on prediction market

Research Experience

• Research Assistant for Prof. Ella D.S. Patelli – University of British Columbia Apr. 2025 – Sept. 2025

• Research Assistant for Prof. Lorenzo Garlappi and Prof. Ali Lazrak – University of British Columbia Apr. 2024 – Apr. 2025

• Research Assistant for Prof. Ella D.S. Patelli, Prof. Ron Giammarino, and Prof. Jack Favilukis – University of British Columbia Jul. 2024 – Sep. 2024

• Thesis – Research on Chinese Stock Market Return Predictability – University of Science and Technology of China
  Feb. 2022 – Apr. 2022
  Advisor: Prof. Yulong Sun
  • This is a Chinese version of Goyal and Welch (2008) with machine learning to improve out of sample forecast.
  • Most predictor have poor out-of-sample performance.
  • A small number of variables perform reasonably well both in-sample and out-of-sample.
  • Machine learning combination method help improve this performance.
• Research Project – The Effect of Audit Failure on SEC Monitoring of Peer Firms – University of Science and Technology of China
  Jul. 2020 – May 2021
  Advisor: Prof. Yue He
  • Showed that not only the firm’s own characteristic, but also its peers’ disclosures, had an impact on the monitoring intensity of SEC.

Working Experience

• Alpha Research - Quant Researcher – Jiuqian Investment, Shanghai, China
  Nov. 2022 – June 2023
  • Built Chinese stock market databases in collaboration with IT teams.
  • Explored daily frequency features to predict cross-section stock returns.
• High-Frequency Trading - Quant Researcher – Mengxi Investment, Shanghai, China
  July 2022 – October 2022
  • Explored market microstructure features that predict short-term returns in futures markets.
  • Used genetic algorithms to develop profitable market-taking strategies.
  • Applied machine learning algorithms for better prediction of future returns.
• High-Frequency Trading - Quant Researcher Intern – Mengxi Investment, Shanghai, China
  Feb. 2022 – June 2022

Teaching Experience

• COMM 475 Investment Policy – University of British Columbia, Vancouver, Canada
  Winter 2025
  • Role: Teaching Assistant
  • Instructor: Prof. Lorenzo Garlappi, UBC Sauder School of Business
• COMM 671 (PhD) Theory of Finance – University of British Columbia, Vancouver, Canada
  Fall 2024 & Fall 2025
  • Role: Teaching Assistant
  • Instructor: Prof. Ali Lazrak, UBC Sauder School of Business
• COMM 377 International Financial Markets and Institutions – University of British Columbia, Vancouver, Canada
  Fall 2024
  • Role: Teaching Assistant
  • Instructor: Prof. Ali Lazrak, UBC Sauder School of Business
• Microeconomics – University of Science and Technology of China
  Fall 2020 & Fall 2021
  • Role: Teaching Assistant
  • Instructor: Prof. Yaping Zhou
  • Evaluation: 4.3 (2020) & 4.75 (2021)

Honors & Awards

• Outstanding Student Scholarship – University of Science and Technology of China (2020-2021)
• International Tuition Award – University of British Columbia (2023-2024)
• BPOC Graduate Excellence Award – University of British Columbia (2023)

Skills

• Programming: Python (Proficient), R (Familiar), Julia (Familiar), Stata (Familiar), SAS (Basic), LaTeX, SQL, HTML & CSS
• CS-related Skills: Deep Learning, Machine Learning, Web Scraping, Natural Language Processing, Parallel Programming