CV

Siyang Liu

Education

• M.Sc. in Business Administration (Finance) – University of British Columbia, Vancouver
  Sep. 2023 – Present
  GPA: 4.20/4.33
• B.Econ in Finance – University of Science and Technology of China, Anhui, China
  Sep. 2018 – May 2022

Research Experience

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

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

• 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 Program – 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

• High-Frequency Trading - Quant Researcher Intern – Mengxi Investment, Shanghai, China
  Feb. 2022 – June 2022

• 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.
• 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.

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)

Teaching Experience

• Microeconomics – University of Science and Technology of China
  Fall 2020 & Fall 2021
  • Instructor: Prof. Yaping Zhou
  • Evaluation: 4.3 (2020) & 4.75 (2021)

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

Selected Courses

course with Bold are phd level courses , course with Italic are audit courses

• Courses studied in UBC:
  • Monetary Theory and Policy
  • Theory in Finance
  • Advanced Topics in Empirical Corporate Finance
  • Advanced Topics in Theoretical Corporate Finance
  • Empirical Methods in Accounting Research
  • stock market inefficiency
  • Econometric Theory II

• Courses studied in USTC:

  • Microeconomics

  • Macroeconomics

  • Econometrics

  • Ordinary Differential Equations

  • Multivariate Statistical Analysis

  • Stochastic Calculus
  • Advanced Probability Theory