Builder
The person and the platform behind statisTracker DerivLab — an open research tool for derivatives pricing and prediction-market analytics.
Mash Zahid
Analytic Finance · Derivatives Analytics · Applied AI
Mash Zahid holds an Analytic Finance MBA from the University of Chicago Booth School of Business, with additional PhD-level coursework in Behavioral Finance and Financial Engineering. He built the statisTracker DerivLab tool as a working demonstration of how listed options and event contracts can be priced on a shared risk-neutral engine — the same instrument class viewed through two market lenses.
Credentials
- Analytic Finance MBA, University of Chicago Booth School of Business
- PhD coursework in Behavioral Finance and Financial Engineering
- Associate Partner, IBM — Fortune 100 generative AI
- Global Director of AI Strategy, KPMG
- Architecture Review Board, Moveworks (pre–ServiceNow acquisition)
- Board Director, Eyecast — production multi-VLM systems at the edge
Technical focus
- Risk-neutral pricing & implied densities
- Volatility surface & SVI calibration
- Cross-market basis (options ↔ event contracts)
- Production AI systems in regulated industries
Every number on this site is produced by an in-repo TypeScript quant engine — BSM Greeks, Leisen–Reimer American lattices, Breeden–Litzenberger densities, raw-SVI smiles — unit-tested against textbook values. See Methodology.
Background
Over two decades in strategy and operations, Mash has spent the last ten years designing and deploying AI systems at enterprise scale across financial services, energy and utilities, telecommunications, healthcare, automotive, and professional services. The through-line is the same one that shows up in DerivLab: models that must be correct under scrutiny, not merely impressive in a demo.
As an Associate Partner at IBM, he led large-scale generative AI engagements for Fortune 100 clients, including a conversation intelligence program that unlocked eight-figure operational value in its first month. As Global Director of AI Strategy at KPMG, he advanced the firm's flagship audit platform into neural network–based deep learning. He served on the Architecture Review Board for Moveworks before its $2.85B acquisition by ServiceNow.
As Board Director at Eyecast, he architects a production multi-VLM hazard-detection platform for utility grid operations (NextEra footprint) — cooperating vision-language models fused via Bayesian weak-signal statistics, deployed on-prem at the edge with no cloud inference. That same instinct — models that cooperate rather than compete, with operator-tunable operating points — shapes how this tool treats options-implied probabilities versus prediction-market quotes.
Why this tool exists
A binary YES contract paying $1 is a cash-or-nothing digital option. Listed single-name options and event markets are therefore the same instrument class under different market microstructure. statisTracker DerivLab prices both off one engine and surfaces the cross-market basis — useful for research, teaching, and as a living portfolio piece for anyone who cares how risk-neutral densities actually get built from a chain.
Educational research platform — delayed data, not investment advice.