Swati Nayak
MS in Fin Mathematics @ UC San Diego
I'm a 2nd Year PhD student in Quant at the University of Massachusetts Amherst. Before coming to UMass, I earned my MS in Financial Mathematics from UC San Diego. I spent a few years working in quantitative finance and analytical consulting — experiences that shaped how I think about problems and keep my research grounded in the real world.
My research sits at the intersection of computational finance and statistical learning, specifically in interest rate derivative pricing, structured credit modelling, and the application of stochastic methods and deep learning to fixed-income markets. I work across quantitative modelling, high-dimensional inference, and applied AI, with a focus on building frameworks that bridge financial theory with modern computational tools.
I care about research that doesn't just sit in journals; I want it to matter. Whether it's a conversation about markets, models, or the messy space where math meets money, I'm always up for it. Let's connect :)
Research
Mortgage-Backed Securities
Currently exploring machine learning applications in MBS — prepayment modeling, credit risk, and the dynamics underneath securitized markets.
Horizon Dependence and Global Spillovers of Liberation Day Shock in Swaptions
I study how swaption-implied volatility was repriced around the April 2, 2025 'Liberation Day' tariff announcement across eight major economies. Using model-free variance extraction from both Bachelier and Black-Scholes option pricing frameworks, I document clear horizon dependence: short-expiry volatilities rose sharply while medium and long-term volatilities fell. The adjustment arrived with a 5-day lag and persisted. Cross-border spillovers were amplified through yield correlations and dampened by trade openness — in the most exposed economies, the yield channel dominates.
Impact of COVID-19 on FDI Inflows into India
An empirical study examining how the pandemic disrupted foreign direct investment flows into India, analyzing sector-level impacts and recovery patterns across major investing economies. View on ResearchGate →
Publications
Working papers and published research.
Visit my Google Scholar for updates.
Conferences
UMass Amherst Finance Conference
University of Massachusetts Amherst
UMass Amherst Finance Conference
University of Massachusetts Amherst
NYU Stern Market Microstructure Conference
New York University, Stern School of Business
Curriculum Vitae
Track: Data Science and Machine Learning
Minor: Finance, Mathematics & Statistics
Contact
I'm always happy to connect — whether it's about research, opportunities, or a conversation over coffee.