JR Concepcion

MS Financial Engineering

Concentration: Quant Risk

BS in Finance, BA in Economics, Minors in Mathematics & Statistics

Concentration: Fintech, Research & Data Analysis

• Built a live Greeks monitoring tool with Python, VBA, xbbg/Bloomberg, and an in-house Python package, giving traders realtime exposure across the derivatives book.
• Back-tested a forwards-based carry trade strategy to hedge repo rate across differing tenors within the derivatives book.
• Worked to replace legacy VBA Greeks functions with xlwings-based Python UDFs, integrating the in-house Python package directly into Excel for faster, more maintainable Greeks calculations.

• Built Excel trackers and interactive dashboards to centralize account data, allowing account managers to monitor reinsurance positions and report deadlines at a glance.
• Collaborated with a manager to automate monthly and quarterly reports utilizing VBA and Salesforce.

• Developed a Python-based desktop app to scrape and display up to 2000 SEC filings with automated data retrieval and filtering for a team of traders.
• Packaged the app as a standalone executable with Py2Exe, integrating financial data from a live database.

• Implemented a Crank-Nicolson finite difference pricer with PSOR for American options, enforcing the early exercise constraint, and built rebalancing simulations modeling delta-gamma hedging strategies to quantify hedge effectiveness.
• Transitioned the project from simulated to live minute-level data, engineering the data pipeline and re-architecting Greeks/volatility calculations with GPU computing (CUDA, CuPy, Numba, Polars).
• Presented findings at the Quaint Quant Conference, SMU Cox School of Business.

• Rebalance the index with an updated registry of Pennsylvania companies, an updated divisor, and adjusted market caps utilizing CBOE market data.
• Automated the daily index value calculation and visualizations utilizing Streamlit, an SQL Database, and GitHub Cron Jobs.
• Lead transition to storing all values in a SQL database to optimize data management and storage for future groups.

• Developed greeks-package, a library for pricing first, second, and third-order Greeks for European and American options.
• Created interactive 3D visualization tools with Plotly for Greeks surfaces, implied volatility, and open interest, optimized for performance with vectorized operations.

• Developed fin-eda, a Python library delivering a full quantitative tear sheet for any stock ticker, price series, or portfolio, computing 50+ metrics across returns, risk, drawdowns, volatility, and liquidity using Pandas, NumPy, and SciPy.
• Designed for accessibility, enabling non-technical users to generate quantitative results with a single function call.

• Built exotics, a library covering three of the most common path-dependent option types: barrier, Asian, and cliquet options, each priced with the specific numerical method.
• Implement strict validation and error handling, ensuring bad inputs and edge cases are caught early and handled properly.