YIYANG HUANG
+1-984-***-**** ad4jz5@r.postjobfree.com LinkedIn
EDUCATION
Duke University North Carolina, USA
Master of Engineering in Financial Technology GPA: 3.8/4.0 08/2022-12/2023
Coursework: Programming for Fintech (Python, C++), Sys Trading (Python), Machine Learning (Python), Asset Pricing Sichuan University Chengdu, China
Bachelor of Economics in Financial Engineering GPA: 3.8/4.0 09/2018-06/2022
Coursework: Stochastic Calculus, Linear Algebra, Probability, Statistics, Risk Management, Econometrics, Game Theory, Big Data SKILLS
Skills: Python(Pandas, NumPy, Sklearn, Flask, PyTorch), C/C++, SQL, MATLAB, Stata, JavaScript, HTML, CSS, Jira, AWS PROFESSIONAL EXPERIENCE
The Depository Trust & Clearing Corporation (DTCC) Generation AI Project Researcher 06/2023-08/2023
Established an evaluation framework for Generation AI of researched 35 assessment themes subdivided into 7 dimensions with team
Designed prompts for the AI tool Copilot to automatically generate Java unit test codes for user balance management, evaluated the generated code utilizing a heatmap-based assessment framework in 3 days Arc Capital Quantitative Research Intern Sheng Zheng (China) 09/2021-01/2022
Conducted statistical analysis of 10+ futures products employing Stata to generate a 5 year performance report of intraday returns and volatility based on min bars; analyzed product correlations, and proposed production launching plan
Researched and optimized exponential-moving-average (EMA) strategies for precious metal futures through simulations, back-testing in 10+ years, and parameter tuning; implemented intraday and daily trading strategies for precious metal futures in Python
Managed the source code of VN.PY quantitative trading platform, updating the 150k+ backend transaction data and pricing of futures and supporting the daily usage of asset management modules Chengdu Zefu Institution of Financial Engineering Quantitative Research Intern 07/2020-08/2020
Developed a dual-moving-average trading strategy for commodities with Python and back-tested using 5 years historical data of Rebar futures; evaluated PnL and drawdown with various parameter combinations to tune the strategy
Employed financial data analysis and on-site investigation to perform due diligence of target investment company
Explored technical analysis techniques of the futures market; performed simulated trading employing signals like MACD SELECTED PROJECTS
BigBucks Trading Platform Duke FinTech Course Project 03/2023-05/2023
Created a robust trading platform website via Flask, incorporating a user-friendly UI/UX; enabled administrators to manage the platform and users to trade stocks, futures, and cryptos backed by SQLite database and Alpha Vantage API integration
Implemented data storage for 5 years of target equity and SPY index data, providing users with interactive financial charts and advanced analytical tools, including efficient frontier, portfolio position, and diverse data visualizations Design and Testing of Algorithmic Trading Systems Duke FinTech Course Project 01/2023-12/2023
Constructed a trading website using Python, leveraging DASH packages and the Refinitiv API; designed and implemented the "Gap Up Buy" trading strategy, allowing users to execute trades based on their chosen parameters
Analyzed 10 independent variables like VIX Index, employing heatmap visualization and PCA dimensionality reduction techniques; optimized the accuracy of 7 machine learning models within Sklearn for executing trades in conjunction with the strategy National Statistical Modeling Contest Team Leader 05/2021-06/2021
Built machine learning models such as Ridge Regression, Support Vector Machine, and Random Forest to predict GDP Growth with data in 20+ years at Risk (GaR) using financial indices and economic indicators
Implemented machine learning models in Python and used grid-search methodology to tune parameters; identified the best model based on validation dataset; achieved out-of-sample results with R-square of 99.67% and RMSE of 0.016