Background

I am a researcher and systems builder exploring investment analysis in the AI era.

With two decades of work in asset valuation and value investing, I have been invited to teach valuation courses at universities. Quantitative Intelligence Laboratory is my ongoing practice of combining AI methods with fundamental valuation to study decision-support systems across market cycles.

I believe that in increasingly complex markets, an independent and disciplined analytical system is a foundation for clearer research judgment.

Credentials

  • Certified Asset Appraiser / Senior Accountant
  • CPA Australia
  • Core translator of International Valuation Standards

Research interests

Topics that guide the laboratory roadmap.

AI-assisted financial analysis

Using machine learning to structure and interpret public financial disclosures.

Quantitative valuation models

Model-based market-cap and price estimates with industry comparison.

Automated knowledge systems

Data pipelines that keep research indicators updated and auditable.

LLM applications

Large language models for research workflows and knowledge organization.

Systems in production

Public research interfaces currently available on this platform.

A-share Quantitative Valuation System

Live system combining market-wide financial data, financial–market-cap relationships, and model-based valuation estimates for research comparison.

Open Valuation Engine →

A-share Financial Quality Assessment System

Automated processing of financial statements with multi-dimensional scores, radar views, and historical quality/risk trends.

Open Quality Assessment →