I'm Michael Carlo, a Statistics & Data Science student working at the intersection of Machine Learning, NLP, and Quantitative Finance. I enjoy building models, simulations, and tools that link communication, markets, and decision-making.
🚀 tiny_pricing_utils is a lightweight Python package for option pricing and stochastic volatility modeling.
🔹 Implemented Models:
- Black-Scholes Model – Call/Put option pricing & implied volatility calibration.
- Heston Model – A class-based implementation with FFT pricing methods.
- Monte Carlo Simulations – Stock path generation & option valuation.
- Characteristic Functions – This module contains functions for calculating the characteristic functions of the log-stock price under the Black-Scholes and Heston models for Fourier-based pricing techniques.
🔹 Installation:
pip install tiny_pricing_utils
A web-based tool for pricing financial options using Black-Scholes and Heston models. Includes interactive visualizations and Monte Carlo simulations for stock price paths.
🛠️ Repository
An exploratory data analysis (EDA) project on World War 1 propaganda posters. Uses computer vision and machine learning to analyze themes, color patterns, and sentiment in historical war posters.
🛠️ Repository
A dynamic website that visualizes the impact of learning rates in deep learning. Features interactive plots demonstrating convergence behavior in neural network training.
Check out my repositories below to dive deeper into the world of finance and tech ⬇️