Current work
Research and quantitative analysis
Two current roles connect complex-systems thinking with real-world financial research while retaining clear professional boundaries.
Researcher · Center for Complex Networks
Research in complex systems, complex networks, econophysics and data-driven modelling.
Visit CCNSDQuantitative Research Analyst · Belfortcorp
Buy-side quantitative research for financial markets.
Visit BelfortcorpAcademic workstream
Research, papers and teaching
Formal papers, preprints and research drafts will be added here only from dedicated academic source material. LinkedIn presentations and industry-facing notes are intentionally excluded from this workstream.
Papers and preprints
Future papers and preprints on complex systems, econophysics and quantitative modelling will be indexed with abstracts, dates, citation details and stable links.
Dedicated academic material to followLecture notes
Academic notes will focus on interacting systems, complex networks, statistical mechanics and reproducible quantitative analysis.
Awaiting academic source draftsTeaching materials
Course outlines, exercises and reference material will appear here when an academic teaching collection is ready.
Collection plannedResearch notebook
Short technical notes can document questions, definitions and reproducible experiments without presenting unfinished ideas as formal publications.
Separate from public postsIndustry and public workstream
Selected notes on markets, risk and AI
Public presentations and LinkedIn notes are collected as professional and educational writing—not as academic publications.
Crisis-resilient leverage
Hierarchical allocations, maximum-entropy exposure, risk budgets and a volatility-driven crash governor.
Portfolio risk · 2025Market randomness
Information, noise traders, price efficiency, temporary anomalies and the risk-return trade-off.
Market dynamics · 2024Becoming a quantitative analyst
Problem formulation, physical intuition, backtesting, financial knowledge and risk-aware system design.
Professional education · 2024Physics perspectives on AI
Energy landscapes, symmetry, emergence, Hopfield networks and attention as adaptive coupling.
Interdisciplinary notes · 2024–2025Research discipline
A transparent path from idea to evidence
- State the hypothesis. Define the mechanism and what evidence could contradict it.
- Document the data. Record origin, time range, cleaning choices and known limitations.
- Separate development from evaluation. Protect out-of-sample evidence from repeated tuning.
- Model implementation constraints. Include costs, liquidity, timing and operational assumptions.
- Monitor risk and stability. Treat changing behaviour as a research finding, not something to hide.
- Publish context with results. Distinguish simulation, paper trading and live execution.
Scope: This website presents research and educational material. It does not provide personalized financial advice or promise investment performance.
Follow the work