About
The Short Version
The Decay Lab is a quantitative trading research platform. We build options and futures strategies with the same rigor you'd apply to a physics experiment — hypothesis, test, validate, deploy. Every strategy is backtested against years of data, validated with Monte Carlo simulation and walk-forward testing, and only goes live when the statistical evidence is clear.
The Founder
I'm a physicist by training — B.S. in Physics, B.A. in Natural & Applied Sciences, and a Master's in Physics. I was in a PhD program funded by the Department of Energy, working on deep inelastic scattering experiments at a particle physics lab. The work involved measuring the internal structure of protons and neutrons by firing high-energy electrons at them and analyzing what comes out.
In particle physics, your code is your eyes. You can't watch a parton get knocked out of a proton and recombine into a shower of particles in 10-23 seconds. You build mathematical models, write the analysis code, and that's how you see what happened. I got very good at one thing: extracting real signals from noisy data and knowing exactly how confident to be in the result.
"My very first meeting with my PhD advisor, he explained how valued physicists were in finance. He talked about people he knew who had gone on to start hedge funds and brokerages."
He wasn't wrong. Jim Simons, a mathematician and theoretical physicist, founded Renaissance Technologies and its Medallion Fund — widely considered the most successful hedge fund in history. David Shaw, a computational scientist, founded D.E. Shaw & Co. Emanuel Derman went from particle physics at Columbia to becoming head of quantitative strategies at Goldman Sachs. The pattern is consistent: people trained to find real signals in overwhelming noise tend to do well when the noise is market data instead of particle collisions.
I built this platform because the problem is the same. Extract a real signal from noisy data, model the uncertainties honestly, and only act when the evidence meets a rigorous threshold. No gut feelings, no chart patterns, no "trust me" — just math and data.
How We Work
- Hypothesis-driven, not curve-fit. Every strategy follows the scientific method. We never optimize to fit historical data and call it edge.
- Confidence intervals, not just win rates. A 70% win rate means nothing without knowing the uncertainty. We bootstrap thousands of resamples to compute the probability of genuine positive edge — the same standard you'd need to publish a physics result.
- Full cost transparency. Most signal services show mid-price fills and ignore fees. We model slippage using the 66% bid-ask spread model, compute commissions, and report net P&L after all expenses.
- Everything is verifiable. Every trade is published. Every backtest can be reproduced. No cherry-picking, no hidden losses, no black boxes.