Projects

Selected projects across markets, data infrastructure, and systematic research.

Practical work spanning financial tooling, market infrastructure, developer workflows, and quantitative research.

Python package

Developer tooling · CLI · distribution

pkgwhy

A Python package and CLI concept focused on improving how reusable code, utilities, and agent-ready functionality are packaged, discovered, and executed across environments.

  • Designed as a reusable package and CLI workflow for distributing practical Python functionality.
  • Explores cleaner developer ergonomics for running packaged tools and capabilities.
  • Being developed as a structured, extensible project with packaging and public distribution in mind.

Research infrastructure

Market data · data engineering · backtesting

Point-in-Time Database & Market Data Infrastructure

A local-first market data and research infrastructure project designed to store clean point-in-time data for backtesting, signal research, and quantitative workflow development.

  • Focused on building a robust point-in-time data layer for cleaner historical analysis.
  • Intended to support research across market, macroeconomic, and other financial datasets.
  • Built to improve repeatability, reduce data quality issues, and support backtesting workflows.

Market microstructure

Order book research · derivatives data

Locally Reconstructed Hyperliquid Level 2 Order Book & Deribit Options Skew Data

A market microstructure project focused on locally reconstructing Hyperliquid Level 2 order book data and pairing it with Deribit options skew data for research, monitoring, and trading infrastructure development.

  • Locally reconstructed Hyperliquid Level 2 order book data at approximately 250ms refresh intervals.
  • Integrated with Deribit options skew data for additional derivatives and sentiment context.
  • Designed for market monitoring, microstructure research, and future quantitative workflow development.

Competition research

Quantitative research · systematic strategy

2026 SIG Algothon Competition

A competition-focused quantitative research project built around the 2026 SIG Algothon, exploring systematic strategy design, validation, and risk-aware decision-making under competitive constraints.

  • Focused on systematic trading strategy development for the 2026 competition.
  • Involves research around validation, robustness, and risk-aware performance evaluation.
  • Used as a practical framework for applying quantitative thinking under real constraints.