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I am a December 2023 graduate from the University of Wisconsin–Madison, where I earned my BA in Economics on a full-tuition Chick Evans Scholarship.
My love for trading goes back to 2020, and I have spent the past 3 years devoted to the quantitative side, especially research, given my economics background. I’ve hit every wall and error log imaginable, but each day is a chance to improve, and I am proud to share my journey. Thanks for checking it out!
Economics, UW–MadisonChick Evans Scholar
Relevant Experience
Quantitative Research & Development
Built Python pipelines with REST APIs, WebSockets, and parallel processing to extract, transform, and load millions of rows of historical and real-time OHLCV bars and NBBO quote data for 1,000+ equities.
Designed and managed Azure SQL Server databases, optimizing schema, indexing, and partitioning for fast queries at scale.
Researched and backtested systematic equity strategies using machine learning, including random forest and symbolic regression, to discover and validate alpha signals.
Performed statistical analysis including correlation, least-squares regression, significance testing, and decile analysis, then visualized results in matplotlib, Chart.js, and Power BI through correlation heatmaps, decile-based charts, and time-series event studies.
Conducted macroeconomic research across traditional and alternative datasets, SEC EDGAR filings (10-K, Form 4), ESG disclosures, and a custom-built LLM-based news sentiment model to grade sectors and industries.
Automated paper-trading strategies on AWS to execute signal-driven trades, manage live positions, and control risk through adaptive volatility-based stop-losses and timed position exits.
