Yanzhong(Eric) Huang

  • Current Master of Quantitative Finance at Rutgers Business School
  • Master’s degree in Banking and Finance from Monash University
  • three years of experience as a quantitative analyst and developer in the Fund of Funds (FoF) industry in China

Contact me:
Email: [email protected]
Github: https://github.com/bagelquant
Linkedin: https://www.linkedin.com/in/eric-huang-506185181/
X: https://x.com/EricYanzhongH

Education

RUTGERS, THE STATE UNIVERSITY OF NEW JERSEY

Rutgers Business School, Newark, NJ - Dec 2025
Master of Quantitative Finance

MONASH UNIVERSITY

Melbourne, Australia - Jan 2021
Master of Banking and Finance

CAPITAL UNIVERSITY OF ECONOMICS AND BUSINESS

Beijing, China - Jun 2018
Bachelor of Business Administration with a major in Accounting

Experience

Sincere Digits Co., Ltd- Beijing, China

Quantitative Developer, 2022 - 2024

  • Python-based backend APIs: led the development of APIs responsible for all algorithms related to fund selection and portfolio construction as the leader of a four-member backend development team. These APIs are central to our core business and assist over 500 clients in selecting funds and optimizing portfolios, as detailed below.
  • Fund performance evaluation: risk-adjusted ratios, factor-based exposure analysis, and risk metrics such as AVaR, VaR, and drawdown.
  • Event-driven back-testing system: served both internal single-factor construction and external clients by providing visualized performance back-testing results.
  • Portfolio Optimizer: provided mean-risk optimization algorithms allow clients to choose from various risk measures, including variance, AVaR, and a combined approach, while imposing constraints on drawdown and factor exposure.
  • Data cleaning: constructed a separate database for cleaned data and applied several logic rules to fill or remove data entries based on different needs.

HongChou Investment Co., Beijing, China

Fund Analyst, 2021 - 2022

  • Portfolio management: managed a China Construction Bank collaborative FoF portfolio from July 2021 to September 2022, overseeing assets of 500 million CNY and achieving a 5.47% excess return against the benchmark of CSI Aggregate Bond Index.
  • Data mining: designed a workflow includes sampling, classification, clustering, sequential patterns, and frequent subgraph mining for 4,000 private fund datasets from China.
  • Risk measurement: built a comprehensive score-based risk measurement system negatively screens all funds to create a pool of 300 funds ready for further investigation.
  • VBA fund managing tool: developed a Microsoft Excel VBA-based program to manage all outstanding funds. The program automatically fetches data provided by brokers and visualizes key information.

Skills

  • Programming: Python (scikit-learn, TensorFlow, PyTorch, tkinter, PySide/PyQT), C++, R, SQL, VBA, Lua, Git
  • Knowledge Areas: Multi-factor Models, Portfolio Optimization, Data Mining, Regression

Projects

McGill International Portfolio Challenge

  • Case study proposing a liquidity-integrated pension fund plan for the Florida Department of Financial Services. Developed an income projection model, portfolio allocation plan, and a comprehensive customer engagement strategy. Advanced to the semi-finals.

BagelQuant Blog

  • https://bagelquant.com, a personal blog sharing quant methods, tips and projects.

TushareDownloader (Python)

  • Created a Python package to download China A market stock data leveraging tushare-apis, and automatically store to a local MySQL database using sqlalchemy package.