Columbia University, Operations Research

Relevant Coursework: Data Analysis, Stochastic Processes, Introduction to Financial Engineering, etc.

Central University of Finance and Economics, Financial Engineering

Relevant Coursework: Econometrics, Operations Research, Optimization Theory, Python, etc.

University of California, Berkeley

Relevant Coursework: Time Series Analysis, Convex Optimization, Algorithm Theory

NDV GROUP, Strategy Intern

Backtested multiple factor sets on the AskJimmy platform to construct 11 strategy portfolios with a peak Sharpe ratio of 10.83. Dynamically adjusted factor parameters and weights based on performance and market feedback, continually enhancing robustness and risk–return profile.

Proposed multi-metric backtesting and visualization upgrades, simplifying parameter inputs and improving data displays to accelerate strategy development. Delivered substantial workflow optimizations that improved team efficiency and user experience in data analysis and strategy research.

Abelian Private Fund, Quantitative Intern

Built an end-to-end data pipeline—from log collection and cleaning to tabular formatting—and performed multi-dimensional visualization of trading data to generate insights for strategy refinement and business operations.

Developed machine-learning-based risk models (e.g., Random Forest) to model and forecast large-scale trading behavior, outputting tiered alerts. Enabled rapid risk assessment under extreme market conditions, improving decision robustness.

Optimized backtest metrics for key strategies, reducing maximum drawdown by over 30% and significantly enhancing stability and risk resilience.

TokenInsight Inc., Quantitative Intern

Developed multi-factor quantitative strategies: retrieved high-frequency data via exchange API, stored it in MongoDB, and built data-cleaning, factor-extraction, and evaluation pipelines. Processed ~50 instruments and tens of millions of records, constructing 191 multi-horizon alpha factors based on price and volume features.

Selected and validated factors: tested 15 core factors in a backtest framework; achieved overall IC stability and Sharpe ratios exceeding 5% and 4.5, respectively.

Conducted high-frequency trading strategy experiments: built a preliminary HFT framework based on the Avellaneda–Stoikov model focused on Ethereum, capturing intraday spread opportunities through dynamic order placement and signal generation.

Founder Securities Co., Ltd., Investment Banking Intern

Participated in a follow‐up phase of a directional equity issuance for a new energy company, strictly adhering to regulatory and compliance procedures. Used Excel functions and pivot tables to consolidate and compare key metrics—revenue, cost, and cash flow—to support project documentation.

Coordinated communications and document archiving: revised confirmation letters and liaised with related firms and banks, organized receipt results for compliance, and synchronized updates with project leads and the compliance department to ensure data integrity and accuracy.

WorldQuant Commences 2023 International Quant Championship--Golden Prize

Quantitative Factor Development & Backtesting: Based on historical U.S. equity data, developed and submitted 14 stock-picking factors on the BRAIN platform. By leveraging a multidimensional factor-construction approach and BRAIN’s backtesting framework, achieved an average Sharpe ratio > 2 and annualized return > 13%, demonstrating robust alpha performance.

Competition Ranking & Recognition: Ranked first in cumulative score within the university and placed in the top 1% globally, leading to a contract as a BRAIN Consultant.

All for Asteroid and Equity for All--2022 MCM/ICM COMAP

Multi-Factor Quantitative Research: Applied the Entropy Weight Method and TOPSIS to construct a Country Development Opportunity Index, integrating Gini and Theil measures to comprehensively quantify “global equity.” Grouped countries by HDI, and cleaned, merged, and visualized data from multiple nations to investigate disparities in equity indices across regions.

Market Structure & Resource Allocation: Employed a two-dimensional K-means model to analyze the asteroid-mining industry landscape, identifying “pioneers” and “leading companies” in emerging markets. Explored the potential impact of resource deployment on global economic equity, providing insights for resource allocation and investment strategy.

Regression Analysis & Return Forecasting: Used OLS to analyze the impact of asteroid resources on global equity, and utilized the GM(1,1) model for trend forecasting. Evaluated short- and long-term shocks of new resource injections on global resource allocation and financial market balance, delivering a systematic study of resource dividends, potential returns, and risk exposures.