Nov 29th 2023
Hi there! Hope this finds you well.
I'm currently pursuing a Master's Degree in Financial Mathematics, at Miami Herbert Business School, University of Miami in Miami, Florida.
I’m a results-oriented quantitative analyst with a strong foundation in time series analysis and quantitative finance. I have hands-on experience conducting real-time simulated backtesting of various trading strategies using Alpaca API and Python, and further optimizing algorithmic trading practices by integrating machine learning techniques based on backtesting results. Through extensive industry research, I have developed a solid understanding of agricultural and precious metals markets. I am proficient in multiple programming languages and databases, enabling efficient data mining, analysis, and visualization using Excel and Excel VBA. Additionally, I have contributed to multiple investment projects, gaining valuable hands-on experience in the field.
Aug. 2024 - May 2025 (expected)
Miami, Florida, United States
Main Classes: Real Estate Finance | Mathematics of Financial Derivatives | Behavioral Finance | Quantitative Finance and Market Microstructure | Fixed Income | Financial Modeling | Advanced Financial Modeling | PE & VC | Wealth Management
Sep. 2020 – Jun. 2024
Guangzhou, Guangdong, China
huangdapao@huangdapao.com
xxh497@miami.edu
Python, Excel VBA, Stata, Matlab, Tableau, Commodities...
Aug 2024 - Present
Miami, Florida, United States · On-site
1. Present as an analyst in Finance & Real Estate Sector, evaluate stocks in the sector and generate reports.
2. Authored valuation reports on an individual stock, with recommended stock successfully included in the initial live portfolio.
Skills: Pricing Analysis, Financial Concepts, Market Pricing, Macroeconomics Analysis, P/E P/B Ratio Evaluation, DCF, DDM
Freelance
Jul 2024 - Present
Remote
1. Developed an automated quantitative monitoring system integrated with Lark bot, enabling real-time stock price and quantitative indicator alerts for multiple China Mainland listed companies, along with scheduled market data distribution and global market brief report.
2. Built a multi-term bond yield analysis system based on partial data from Chinese and U.S. bond markets, integrating Nelson-Siegel fitting and forward rate calculations to identify arbitrage opportunities and optimize fixed-income strategies.
3. Developed and tested a machine learning-based S&P 500 return forecasting system, incorporating multi-term lag features, PCA for dimensionality reduction, and genetic algorithm optimization. Evaluated linear regression, FFNN, and LSTM models through backtesting and visualized PCA insights using Excel and matplotlib to support stock market analysis.
4. Constructed a Python-based Dow 30 portfolio optimization system, integrating Markowitz optimization and a genetic algorithm to optimize the Sharpe ratio under weight constraints. Evaluated performance on training and test data using annualized return, volatility, and Sharpe ratio metrics.
5. Assisted in maintaining quantitative analysis modules, information systems, and subscription systems, addressing unexpected issues and improving system stability.
6. Participated in the development and maintenance of the company's website and email system.
7. Continuously optimized the company’s quantitative analysis system, adding market data processing and factor analysis modules.
Skills: Python, Financial Concepts, HTML, JavaScript, Raspberry Pi, HTML, C++, Website Development, CSS, Quantitative Finance
Internship
Dec 2023 - Jul 2024
Guangzhou, Guangdong, China · On-site
1. Built a model using Python to update, cross-verify, and analyze data.
2. Used PCA to predict trends in Southeast Asian markets.
3. Completed commodity analysis on gold and eggs.
4. Developed a quantitative analysis system, a mail subscription & bot push system, and a stock recommendation system.
Skills: Python, Data Analysis, SQL, VBA Excel, Financial Concepts, Quantitative Analytics, Commodity Pricing, Tableau, Industry Analysis, Quantitative Research
Click on the pictures below to see details:
Nov 29th 2023
Dec 27th 2023
Freelance
May 2024 - Present
Remote
1. Monitor multi-platforms’ reviews for the game Stellaris using semantic analysis to gather player feedback and produce weekly reports to support game optimization and market strategies.
2. Liaise between the Stellaris development team and Chinese players to ensure accurate information delivery.
3. Plan engagement activities to boost player participation and satisfaction and manage community relations.
4. Successfully managed a PR crisis by providing decision-makers with comprehensive information and well-founded recommendations to support effective decision-making.
Skills: Community Management, Data Crawling & Analysis, Translation, Technical Writing
Internship
Jul 2023 - Nov 2023
On-site · Guangzhou, Guangdong, China
1. Refined hedging models and analyzed data for the hog farming department.
2. Used Python and VBA for daily automatic updates of reports.
3. Conducted on-site research on hog farming enterprises.
Skills: Commodity Markets, Python, Data Analysis, VBA Excel, Financial Concepts, Pricing Strategy, Commodity Pricing, Industry Analysis
Internship
Mar 2023 - May 2023
On-site · Guangdong, China
1. Extracted 3000+ negative information pieces from government websites using Requests and Selenium.
2. Conducted correlation analysis among companies using Python and Apriori algorithm.
Skills: Web Crawling, Python, Data Analysis
Internship
Oct 2022 - Apr 2023
Remote · Guangzhou, Guangdong, China
1. Expanded industry database categories and improved data for six databases.
2. Used Python to collect, organize, and normalize 169,700 index entries.
Skills: Data Mining, Python, Data Analysis, SQL
Book Contribution
Publisher: Tsinghua University Press
Expected Publication: February 2025
Authored Chapter 7, titled “Principal Component Analysis (PCA),” which explores PCA as a dimensionality reduction technique for extracting essential information from high-dimensional datasets. The chapter includes the theoretical foundation, practical implementation, and applications in financial data processing, such as data cleaning, standardization, feature extraction, risk management, and portfolio construction. Python code examples and visual aids are provided to enhance understanding and practical application.
Jul 2022 - Sep 2022
Selected Prompt: Compositional Analysis and Identification of Glass Artifacts
Jun 2022 - Jun 2022
Ranked 4th out of 20 teams.
Jun 2021 - Jun 2021
Ranked 2nd out of 136 teams.
Jun 2021 - Sep 2021
Ranked within the top 50 out of 277 teams.
Jun 2021 - Sep 2021
Ranked 3rd out of 246 teams.
Sep 2024 - Present
The system selects the top 30 stocks in each sector using multiple risk assessment indicators and various scoring methods to build portfolios. Data is updated every third weekend of each month, portfolio performance is evaluated, new portfolios are constructed, and continuous improvements are made.
Jan 2024 - Present
This Python-based system leverages real-time data ingestion, feature engineering, and machine learning models to generate personalized stock recommendations. It processes market trends, historical data, and user profiles, delivering daily global market reports and recommendations via automated email.
Dec 2023 - Jun 2024
Utilized deep learning models such as LSTM, RNN, and Transformer for ensemble learning to optimize quantitative investment strategies with enhanced accuracy and efficiency.
Dec 2023 - May 2024
Selected appropriate variables and constructed a VAR model based on collected weekly average data. Employed cointegration tests, Granger causality tests, and impulse response analysis to investigate the short-term volatility patterns of hog futures on spot hog prices in China, and conducted risk measurement.