I'm an incoming UC Berkeley MFE student (Class of 2027). This is my space for quant projects, notes, and write-ups—
focused on clean data, careful validation, and realistic backtests (costs, slippage, and regime behavior).
Note: I'm actively uploading more work—additional systematic research pipelines are being finalized.
Links go live as each repo is published.
NIFTY Smallcap 100 pairs trading — testing faster mean reversion on Indian small-cap equities, extending the NIFTY 50 research pipeline.
Clean experimentation, honest results, and turning ideas into shipping-quality code.
Hi, I'm Venkata Sreenivaas Lingam. I'm an incoming UC Berkeley Master of Financial Engineering student (Class of 2027). I completed my undergraduate degree in Finance with a minor in Mathematics at Rutgers University.
Since graduating, I've been working at a technology-driven healthcare staffing marketplace, where I've taken on responsibilities across revenue and credit analytics. I like building lean, low-cost systems that move the needle—turning messy operational data into forecasts, risk monitors, and decision tools that teams actually use. My default mode is pattern-hunting: understand the structure of the data, pressure-test assumptions, and convert insights into actionable outputs.
I've been drawn to financial markets since high school and spend my free time researching and testing systematic ideas—especially in statistical arbitrage, volatility, and market microstructure. This site is where I share projects, write-ups, and notes: what worked, what didn't, and what I learned along the way.
Outside markets, I enjoy reading (see my book list—recommendations welcome), weightlifting, go-karting, poker, and horology. Feel free to connect via the links below.
I'm currently seeking Quant Research or Quant Trader internships for Summer 2026.
Research pipelines, backtests, and systems. Each links to code + write-up when available.
Additional research projects (commodities spreads, NIFTY Smallcap 100) are being finalized. Links go live as each repo is published.
A systematic cointegration-based pairs trading pipeline on the NIFTY 50 universe (46 stocks, 1,035 pairs scanned).
Uses rolling OLS hedge ratio, z-score entry/exit signals, and beta stability filters.
Best pair: EICHERMOT / SHRIRAMFIN — Sharpe 0.40 · Sortino 0.92 · CAGR 14% · Total Return 2.95× (net of 10bps/leg costs, 2018–2026).
A reproducible FX pairs-trading research pipeline: data ingestion → systematic pair screening → diagnostics →
leak-safe backtests → cost & robustness sweeps.
Main focus: USDCNH–USDCNY (onshore vs offshore RMB) — the strongest candidate by
cointegration + residual stationarity, with fast mean-reversion (≈ 2-day half-life).
Includes benchmark on AUDUSD–NZDUSD and sensitivity across transaction-cost scenarios.
Streamlit-based Texas Hold'em equity calculator using Monte Carlo simulation (via treys).
v1 models opponents as random hands and returns equity + a basic pot-odds/EV call/fold recommendation.
Gold-Silver / Brent-WTI experiments: mean reversion, half-life, regime stability. Testing cointegration durability across market stress periods and validating spread behavior under transaction costs.
A lightweight research framework with configs, saved metrics, plots, and reproducible runs. Designed for rapid iteration with version-controlled experiments and artifact logging.
Short write-ups on cointegration, half-life estimation, purging leakage, cost sensitivity, and regime detection. Each note pairs math with working code examples.
Previous Reads
If you think I'd like something in markets, probability, macro, or decision-making under uncertainty—send it my way.