mid · quantitative trading & research

Yadnyeya Vairat

I build the whole stack behind a trading idea. Data pipeline, signal, pricing, execution, then the diagnostics that tell me whether any of it actually worked.

Rutgers MQF · Dec 2027 Newark, NJ Open to Summer 2027 internship
Yadnyeya Vairat
education
Dec 2027

Newark, NJ

Rutgers Business School

Master of Quantitative Finance

Algorithmic Trading & Portfolio Management · Derivatives · Fixed Income · Econometrics · Quantitative Methods

Selected to represent Rutgers at the Rotman International Trading Competition (RITC), Toronto, Feb 2027

Dec 2025

Chico, CA

California State University, Chico

B.S. Management Information Systems, Minor in Computer Science

about

That happened backwards. I did MIS with a CS minor at Chico State, not finance.

Markets came later: first my own book in 2021, then Senior Equity Analyst at Chico Creek Capital, a student-run fund where I covered names, pitched them, and ended up automating P&L and risk monitoring for a 40-stock book because doing it by hand was miserable.

Now I'm in the Rutgers MQF, and I'll be representing Rutgers at the Rotman International Trading Competition in Toronto this February.

Most of what I know came from building things that were allowed to fail. Of 40 futures spreads I researched, 8 survived multiple-testing correction and 3 were still profitable out of sample after costs. Most didn't work, which was the useful part.

Day job right now is AI/ML engineering at Vibe Logics, building Airflow pipelines and training models for conversion scoring and budget allocation. Different domain, same muscle.

what i build

A trading idea has five stages. I've built every one.

Most people specialize in a slice. I wanted to know where an edge actually dies, so I built each stage end to end and measured what the next one gave back.

01

Data

Ingestion across 9 providers, Airflow-orchestrated ETL, survivorship and liquidity filters.

02

Signal

Cointegration tests, Ornstein-Uhlenbeck half-lives, order-flow imbalance, microprice.

03

Pricing

Black-Scholes, binomial trees, Monte Carlo, implied-vol surfaces and the Greeks.

04

Execution

Limit order book simulation, inventory-aware quoting, broker-connected routing.

05

Diagnostics

Markouts, inventory variance, walk-forward validation, transaction costs and slippage.

contact

Always up for talking microstructure, vol, or why your backtest is lying to you.