The story behind Vaelor
I wanted to know whether a disciplined, automated strategy could genuinely beat the market — not in theory, but proven and running live. So I built the whole thing myself: a machine-learning research pipeline that ranks the market, a strategy validated with walk-forward backtesting across nine years and every market regime, and an autonomous agent that trades and protects a portfolio with no human in the loop. Then I deployed it for real and started a public track record. Vaelor is the result — honest, transparent, and live.
Built & deployed
End-to-end, solo
Strategy validated
9 yrs · 5/5 regimes
Status
Live · forward-testing
What I bring
Finance
- DCF & 3-Statement Modeling
- LBO / Comps / Precedent Txns
- Equity Research
- Scenario & Variance Analysis
Engineering
- Python (pandas, scikit-learn)
- TypeScript / React / Next.js
- SQL / PostgreSQL
- Git, Vercel, cloud deploy
Quant / ML
- Cross-sectional factor models
- Walk-forward backtesting
- Risk modeling & sizing
- NLP sentiment (VADER)
Education
Arizona State University
W. P. Carey School of Business
B.S. Economics & Finance (Dual Major)
GPA 3.47·Dean's List·Grad March 2028
SIE Exam — in progress
Experience
2026
Founder — Vaelor
Designed, built, and deployed an autonomous AI investing platform end-to-end: ML research pipeline, live auto-rebalancing, risk controls. Live at vaelor.dev.
2024
Office Aide — ESSE Trading Impex LLP
Operations support at an international trading firm.
2023
Finance Intern — InnoLearn Solutions
Financial analysis and modeling support.
Let's talk.
Open to feedback, partnership, and early support as Vaelor grows.