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Financial modeling, machine learning, and data-driven research

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15 projects
quant

Advanced Option Pricing Models

An interactive pricing studio covering Black-Scholes-Merton, Heston stochastic volatility (via the Carr-Madan Fourier transform), and Monte Carlo simulation with antithetic variates. Live Greeks surfaces, 3D implied-volatility skew, and a companion review paper synthesising CQF Module 3.

Closed-form BSM pricing with full Greeks surfaces
Heston model priced via Carr-Madan Fourier inversion
Monte Carlo with antithetic variates (VRF ≈ 2.9 European, 5.6 binary)
DerivativesHestonFourier
quant

Exotic Options Lab

Where the Black-Scholes closed form runs out. This page prices Asian, barrier, lookback, and American-exercise options under GBM using Monte Carlo path-dependence and the Longstaff-Schwartz regression. Includes live path-explorer animations and a copy-pasteable Python pricer.

Arithmetic & geometric Asian options with control-variate variance reduction
Barrier and lookback Monte Carlo with continuity correction
American-exercise pricing via Longstaff-Schwartz least-squares regression
ExoticsMonte CarloLongstaff-Schwartz
quant

Finite Difference Solver

Solving the Black-Scholes PDE directly on a grid. Explicit, implicit, and Crank-Nicolson schemes side by side, with a live stability visualisation showing exactly when the explicit method blows up past the CFL bound, and projected SOR for American early exercise.

BSM PDE reduced to the heat equation and solved on a grid
Explicit, implicit, and Crank-Nicolson convergence side by side
CFL stability visualisation: watch explicit FDM blow up live
PDEFinite DifferenceCrank-Nicolson
quant

Pricing Where GBM Breaks

A catalogue of markets where lognormal equity assumptions fail and the models that replace them: Garman-Kohlhagen for FX with two interest rates, Vasicek and Hull-White for rates, the Merton structural model for credit, and the Schwartz mean-reverting model for commodities.

Garman-Kohlhagen FX option pricing with the two-rate skew
Vasicek and Hull-White short-rate yield-curve simulator
Merton structural model: equity as a call on firm value
FXRatesCredit
quantFeatured

Commodity Risk Lab

Live VaR backtesting (Kupiec POF + Christoffersen independence), stylized-facts diagnostics, and side-by-side Gaussian / Cornish-Fisher / Filtered Historical Simulation method comparison on six commodity tickers. Data pipeline: Supabase + daily GitHub Actions ETL.

Per-asset Kupiec POF + Christoffersen independence VaR backtest
Stylized-facts diagnostic (CQF Module 2.4) on the live returns series
Gaussian vs Cornish-Fisher vs FHS comparison with recommended method per asset
VaRRiskBacktesting
data-scienceFeatured

Spotify Popularity Time-Series Forecasting

Apply the same ARIMA / GARCH stack quants use for asset returns to a non-financial domain: track popularity on Spotify. Built on 586,672 tracks across 72 years (1950-2021). Includes a procedural Web Audio synthesiser that lets you hear what 'high energy, low valence' actually sounds like.

586,672 Spotify tracks, 1950-2021, real Kaggle dataset
auto.arima + EGARCH(1,1) on daily aggregated popularity
Per-genre ARIMA with stationarity testing and risk/reward analysis
RARIMAGARCH
appliedFeatured

Coffee Futures Snowflake Warehouse

A production-style Snowflake data warehouse for coffee futures research. Galaxy schema (fact constellation) with 8 fact tables (~1.2M rows total) and 19 dimension tables stitched together from FMP, FRED, Open-Meteo, and the CFTC COT report. Designed to make a coffee thesis queryable in one join.

Galaxy schema: 8 fact tables, 19 dimension tables, ~1.2M rows
ETL pipeline pulling FMP, FRED, Open-Meteo, and CFTC COT scraping
Date dimension with country-specific harvest seasons baked in
SnowflakeGalaxy SchemaETL
quant

Financial Transmission Rights Pricing

Most option pricing models assume the underlying is a stock or a commodity. This paper takes the Black-Scholes framework and adapts it for Financial Transmission Rights, where the underlying is congestion risk on a power grid. Includes jump-diffusion models, seasonality adjustments, and interactive LMP charts.

Black-Scholes adaptation for non-standard underlying assets
Congestion risk modeling in deregulated electricity markets
Jump-diffusion and seasonality adjustments
DerivativesBlack-ScholesEnergy Markets
valuationFeatured

Eli Lilly DCF Valuation

DCF valuation of Eli Lilly (NYSE: LLY) using FCFF and FCFE with pipeline-adjusted revenue projections. Target price $627 against reference $579 with full scenario analysis and 9-peer relative valuation.

Pipeline-adjusted revenue projections ($33B → $95B, 2023–2027)
WACC = 5.79% via CAPM with 5-year monthly betas
Bull/Base/Bear scenario analysis across 6 drivers
DCFPharmaValuation
data-scienceFeatured

MNIST: MLP vs CNN

Technical comparison of a Multilayer Perceptron and Convolutional Neural Network on MNIST digit classification. Includes 3Blue1Brown-style architecture visualizations, convolution operation animations, and analysis of why spatial awareness matters.

99.29% CNN accuracy vs 97.92% MLP accuracy
Interactive neural network architecture visualizations
Step-by-step convolution operation animation
Deep LearningPythonTensorFlow
data-scienceFeatured

Customer Segmentation Clustering

K-Means and hierarchical clustering on mall customer data. Identifies 5 spending behavior segments with ARI = 0.942 agreement between methods. The unsupervised methodology generalises directly to regime detection and factor-cluster portfolio construction on the quant side.

K-Means and hierarchical clustering comparison (ARI = 0.942)
Interactive elbow method and silhouette analysis
5 customer segment profiles with marketing strategies
Machine LearningK-MeansClustering
data-science

Nike Brand Perception NLP Analysis

Scraped 300K+ reviews from the App Store, Reddit, and Trustpilot for Nike, Adidas, and Under Armour. Ran sentiment analysis (NRC, AFINN, Bing lexicons), LDA topic modeling, TF-IDF, and aspect-based sentiment on price, quality, and sustainability. Built in R.

Multi-platform data collection (App Store, Reddit, Trustpilot)
Comparative brand sentiment analysis
Topic modeling for brand perception drivers
NLPSentiment AnalysisR
data-science

Urban Heat Island ML Explorer

Interactive satellite ML classification explorer covering Rio de Janeiro, Santiago, and Freetown. Classifies urban heat island zones using the features extracted by UHI-Pipe.

Satellite imagery processing pipeline
Multi-city heat island classification
Interactive visualization dashboard
Satellite MLGeospatialPython
data-science

UHI-Pipe: Satellite Data Library

A Python package (published on PyPI) that extracts satellite imagery from Sentinel-2, Landsat-8, and Copernicus DEM, then computes 19 spectral indices including NDVI, NDBI, and land surface temperature. Outputs ML-ready DataFrames with parquet caching.

Published to PyPI as installable package
Spectral indices extraction (NDVI, NDBI, LST)
Microsoft Planetary Computer integration
Python PackageGeospatialSentinel-2
applied

Neon Survivor

Arena survival game in a single HTML file. All visuals drawn with Canvas, all audio synthesized with Web Audio API. 6 weapons, 6 passives, 6 evolutions, 7 enemy types, boss fights. Zero dependencies, instant load.

6 weapons, 6 passive upgrades, 6 weapon evolutions
All visuals and audio procedurally generated
Single ~50KB HTML file, no dependencies
HTML5 CanvasWeb Audio APIJavaScript

In Progress · Coming Soon

4 projects
quantComing Soon

Advanced ML Trading System

Implementation of methods from Lopez de Prado's Advances in Financial Machine Learning. CUSUM filters for event detection, triple barrier labeling, meta-labeling for signal confidence, purged K-fold cross-validation, and Kelly criterion for position sizing. Built in Python with XGBoost.

Triple barrier labeling and meta-labeling
Sequential bootstrap and purged K-fold CV
Kelly criterion dynamic bet sizing
Quantitative FinanceMLPython
valuationComing Soon

Amazon Comprehensive Financial Analysis

Full financial analysis of Amazon: income statement forecasting, balance sheet projection, DuPont decomposition, WACC estimation, and DCF modeling with Monte Carlo simulation on terminal value.

5-year revenue and margin forecasting
DuPont decomposition of ROE drivers
WACC estimation and sensitivity analysis
DCFValuationFinancial Modeling
appliedComing Soon

ResolvAI

AI-powered IT ticket resolution system built for BNP Paribas ServiceNow. Template-based with 10 pre-configured incident types and automated resolution note generation.

10 pre-configured incident resolution templates
Automated resolution note generation
Enterprise ServiceNow integration
AIServiceNowPython
appliedComing Soon

RH-BI-Pipeline

Automated data pipeline: SharePoint ingestion, Python cleaning and geocoding, GitHub Actions CI/CD, Supabase PostgreSQL storage, Power BI dashboards. Runs unattended.

End-to-end automated ETL pipeline
GitHub Actions CI/CD orchestration
Power BI dashboard output
Data EngineeringPythonSupabase