Economics | Research & Data Analysis
After earning my Economics degree from CSUN and working in institutional wealth management, I founded Explo Holdings to pursue equity research, portfolio management, and real estate development. I am preparing for graduate studies in economics with a long-term focus on economic consulting and policy research. In my free time I enjoy playing poker, enough to call it a hobby, but not enough to call me a degenerate (hopefully).
Current Work
Explo Holdings is a family investment and real estate holding company I founded in 2026. My work there is mostly research and bookkeeping: building and maintaining the financial database described below, writing due-diligence reports on public companies, and keeping unit-level accounting reconciled against bank and brokerage records. It also holds a residential construction project in Lancaster, CA.
Research Platform
A quantitative research platform I built in Python, SQL (DuckDB) and Streamlit. It covers 9,000+ U.S.-listed companies and ADRs over 30 years, joining daily prices, quarterly financial statements, FX rates, analyst estimates and insider trades, and runs a screening model that flags companies worth a deeper look.
The screening model scores every company in the database across four factors. Hard gates filter out companies that fail basic quality thresholds before scoring begins, and the model was tested with a 20-year historical backtest. Its output is a ranked list that feeds into deeper due-diligence research.
The platform has a Streamlit frontend, a SQL computation layer running inside DuckDB, and a local database holding tens of millions of rows of prices and financial metrics. Data is sourced from the Financial Modeling Prep API and refreshed daily.
Professional Experience
Investment Associate | March 2025 – November 2025
At Vance Wealth, a registered investment advisory firm, I worked across the full scope of portfolio management operations for a book of approximately $700 million in client assets. The role combined daily trading execution with quantitative research and process automation, giving me hands-on experience with institutional-grade investment workflows.
Designed a direct indexing exclusion model that ranked S&P 500 companies on leverage and distress risk (Debt/EBITDA, Debt/Market Cap, Altman Z-score) and backtested 99 exclusion thresholds over ten years; the selected threshold outperformed by 72 basis points a year on average, in nine of ten years. The study found that highly leveraged firms outperform in rate-hiking cycles and underperform in rate-cutting cycles. I presented the findings to the full firm, and leadership adopted the expanded screen.
Built a Python model that ranked 401(k) plan fund options within each Morningstar category on 19 weighted metrics, including expense ratio, Sharpe ratio, alpha, downside capture, category-relative returns and manager tenure across 3- to 15-year horizons, for client plan due-diligence reviews.
Managed daily trading operations for the firm's approximately $700 million book of business. Responsibilities included pre- and post-trade compliance checks, portfolio rebalancing across client accounts, wash sale rule monitoring, and execution of equity and fixed income trades through institutional platforms.
Conducted equity research and due diligence on alternative investments including private credit, real estate, venture capital, and private equity. Executed tax loss harvesting strategies across client portfolios to optimize after-tax returns while maintaining target asset allocations.
Independent Research
An independent research paper investigating the relationship between corporate leverage and economic cycles. This work builds on research begun during my time at Vance Wealth, where I found statistical evidence that leveraged firms outperform in rising rate environments.
The study uses 30 years of fundamental data from the Terminal platform, overlaid with Federal Funds Rate data from FRED, to examine how capital structure decisions interact with monetary policy regimes. The goal is to produce a publishable analysis that contributes to the corporate finance literature on leverage and macroeconomic sensitivity.
Background
Bachelor of Arts in Economics, Cum Laude
Mathematics Coursework (non-degree)
Investigated the relationship between macroeconomic indicators and U.S. automotive sales using OLS regression. Built automated data collection pipelines with Selenium and BeautifulSoup, implemented ARIMA time series forecasting, and conducted statistical analysis with statsmodels.
Developed a logistic regression model using scikit-learn to predict customer churn. Focused on feature engineering, model evaluation via F1-score optimization, and translating model outputs into actionable business recommendations.
IBM via Coursera
IBM via Coursera
University of Michigan via Coursera
Data analysis and machine learning tracks
Overview
Built a quantitative research platform covering 9,000+ companies and audited it for data errors. Write due-diligence research on public companies and maintain unit-level partnership accounting.
Trading operations for ~$700M book. Designed a direct indexing exclusion model (72 bps average outperformance) and presented the leverage findings to the full firm. Built a 401(k) fund scoring model. Equity research, tax loss harvesting, alternative investment due diligence.
GPA 3.7, Finance minor, Dean's List (6 semesters), Certificate of Excellence. V.P. of Python Coding in Economics Club. Coursework in econometrics, business analytics, quantitative methods, and risk management.
Get in Touch
I am always open to conversations about economics, research, or economic consulting. Feel free to reach out through any of the channels below.