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Financial modeling, machine learning, and data-driven research

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
quantFeaturedComing Soon

Advanced Option Pricing Model

A pricing suite covering Black-Scholes-Merton, Heston stochastic volatility (via Fourier transforms), and Monte Carlo simulation with antithetic variates. Includes full Greeks surfaces and 3D volatility visualization. Built as a Streamlit dashboard.

BSM pricing with full Greeks surface
Heston model via Fourier transforms
3D volatility surface visualization
DerivativesPythonStochastic Volatility
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
valuationFeaturedComing 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
valuationComing Soon

Eli Lilly DCF Valuation

DCF valuation incorporating pharmaceutical pipeline analysis. Revenue projections are probability-weighted by drug approval stage. Includes comparable company analysis.

Pipeline-adjusted revenue projections
Probability-weighted drug approval scenarios
Comparable company analysis
DCFPharmaValuation
data-scienceFeatured

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

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
data-scienceFeatured

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-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-science

Customer Segmentation Clustering

K-Means and hierarchical clustering on mall customer data. Identifies 5 spending behavior segments with ARI = 0.942 agreement between methods.

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
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
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