Coding Projects
Investment tools, analytical platforms, and interactive research — designed, coded, and deployed from scratch using Python and TypeScript.
Stochastic financial statement builder running 10,000 Monte Carlo simulations per company. Fits growth and margin distributions from 5–15 years of historical data, generates P5–P95 fair value ranges, and decomposes which drivers contribute most to valuation variance.
Institutional-grade emerging markets equity research suite. Eight integrated modules — stock screening, valuation heatmap, correlation matrix, portfolio construction, country risk dashboard, base rate analysis, and geopolitical risk monitoring — built end-to-end and deployed live for daily use by an EM value strategy.
Multi-factor correlation analysis platform. Pairwise and rolling correlations between equity factors and individual stocks, with dendrogram clustering, time-series decomposition, and regime detection.
This website. 18+ research articles blending quantitative and qualitative thinking, with 15+ custom interactive D3 widgets including Monte Carlo simulators, probability heatmaps, network graphs, Bayesian updaters, and base rate quizzes. Built end-to-end as a static Next.js site.
Risk scenario modelling for mapping geopolitical events to portfolio exposures. Probability-weighted impact analysis with tail distribution visualisation and Monte Carlo simulation across multiple risk scenarios.
Which sports produce the most dramatic, unpredictable matches? Interactive analytics platform ranking sports by a custom jeopardy index derived from lead changes, scoring entropy, and comeback frequency.
Screen the full EM equity universe across valuation, profitability, financial health, and through-the-cycle metrics. Multi-region filtering, percentile-based valuation filters, and customisable metric weighting.
Country × sector heatmap of valuation metrics across 1,272 emerging-market equities. Layer your portfolio over the market view to spot exposure gaps and find cheap pockets the portfolio is missing.
Portfolio correlation analysis with hierarchical clustering dendrogram. Computes pairwise correlations across the entire holdings list and visually groups stocks by similarity to surface concentration risk.
Build and modify portfolios with real-time impact analysis. Side-by-side current vs. new weights with delta tracking, pro-rata rebalancing, and CSV import for portfolio editing workflows.
24 emerging-market countries scored across 5 risk pillars — macro, political, market, external, structural — with customisable pillar weights. Sortable cards with composite scores and risk-band classification.
Historical peer comparison for the “outside view” — pulls company metrics into their sector base rate distribution, percentile-rank, and probability scenarios. A direct application of Mauboussin’s base-rate book to live data.
End-to-end investment research pipeline. Screens ~2,200 large-cap equities globally, triages them down to a shortlist using a 9-section quantitative brief, then runs full deep-dive analysis on each — 7 Red Questions (hidden liabilities, earnings distortions, balance sheet risk, etc.), Monte Carlo valuation, DCF, and a final publication-quality investment memo. The attached screenshot shows a real deep-dive output on Diageo.
Educational stock market simulator with virtual trading, real market data from EODHD, portfolio tracking, and a competitive leaderboard system.
3D city visualisation where buildings represent countries — height mapped to CAPE yield, width to market cap. Interactive WebGL fly-through experience with real-time valuation data.
Python analysis suite examining the accuracy of historical valuation models with the benefit of hindsight. Back-tests valuation assumptions against actual outcomes across thousands of stocks.
Frontend
React, Next.js, TypeScript, Tailwind CSS
Visualisation
D3.js, Recharts, Three.js
Backend
FastAPI, Flask, Python, Uvicorn
Data & Infrastructure
SQLite, PostgreSQL, Pandas, Vercel, Tauri
Every project is self-directed and built end-to-end — from data ingestion and backend API design to interactive frontend visualisation. The tools encode specific ways of thinking about investment problems; collectively they represent a process infrastructure that would be difficult to replicate.