Quantitative researcher building volatility models, derivatives pricing systems, and AI-driven financial infrastructure.
Roshan Shah: Finance and quantitative researcher focused on volatility modeling and AI-driven financial systems. Always building at the intersection of finance, technology, and markets.
UNC Chapel Hill
Kenan-Flagler Business School
B.S. Business Administration + Data Science (GPA 4.0)
Assured Enrollment into KF. Portfolio Management Team (TMT), Quant Finance Association
The Lawrenceville School
High School (GPA 3.92/4.00)
Herman Hollerith Prize, Cum Laude Society, McClellan Society
languages
- Python
- R
- C++
- SQL
skills
- DCF / Comps
- Volatility Models
- Derivatives trading
- Economic modeling
interests
- Poker
- Football
- Traveling
- FOOD (like any)
- Reading
- AI governance
Experience
Black Swan Management
ResearcherNov 2025 – PresentAnalyzing regime changes and market catalysts for public equity investing. Studying volatility dynamics and distributional assumptions to improve risk-adjusted returns.
Kenan-Flagler CDR
Research AssistantSep 2025 – PresentSupporting faculty research on behavioral decision-making in financial contexts. Designing experiments and analyzing participant data for academic publication.
Hitech Corporation
Strategy InternJul – Sep 2025Developed U.S. market entry thesis for a $3.4M cross-border acquisition. Conducted competitive analysis and built financial projections for TAM sizing.
Chakli Capital LLC
Summer AnalystMay – Jul 2025Supported public-equity investing focused on AI and enterprise software. Built valuation models (DCF, comps) and wrote sector memos on AI monetization trends.
DTV.AI
Co-FounderMay 2023 – Feb 2025Built cost-analytics business serving retailers and CPG brands. Identified sourcing inefficiencies and quantified 12–15% margin improvement opportunities.
Projects
Novel hybrid pricing framework for American options integrating Hurst exponent forecasting with regime-switching volatility.
High-performance D2C e-commerce platform with custom subscription management and optimized checkout flows.
Ultra-low latency trading engine (1.8M+ orders/sec). Lock-free concurrency with sharded SPSC queues.
Real-time educational platform for quant finance with client-side Python execution via Pyodide.
Universal Atmospheric Model forecasting exoplanet weather with 94% accuracy.
Automated academic auditing via custom PDF parsing. Used by administration for transcript analysis.