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George-Dros/README.md

Hi, I'm George!

Welcome to my GitHub profile! I'm an Applied Mathematics graduate with a focus on Python-based data analysis, modeling, and interactive tools. I enjoy building clear, purposeful applications—especially those that make complex ideas easier to explore.

Featured Projects

1. Deep Hedging Neural Network for Derivatives Pricing

A PyTorch project that trains a GRU-based neural network to dynamically hedge European call options under realistic market conditions (volatility spikes, jumps, regime shifts).
Includes CVaR-based loss function, full simulation environment, and backtesting with benchmark metrics and plots.

2. Volatility Surface Visualization

Interactive tool for visualizing implied volatility surfaces across strike prices and time-to-maturity for any given ticker. Useful for traders and analysts interpreting market expectations and option behaviors.

3. Black Scholes Interactive Heatmap

This app generates option price heatmaps using the Black-Scholes model. Customize inputs like volatility and risk-free rate to explore pricing behavior and market mispricing signals.

4. Airbnb Data Analysis Dashboard

An interactive dashboard for exploring Airbnb listings in any city. Includes filters for room type, price, availability, and superhost status. Provides automatic visual insights through boxplots, scatter plots, histograms, and a summary panel.

Tech Stack

  • Languages: Python, SQL, Fortran
  • Libraries: Pandas, NumPy, Streamlit, scikit-learn, Matplotlib, Seaborn, HDBSCAN, UMAP, Pytorch
  • Tools: Git, JupyterLab, LaTeX
  • Currently exploring: reinforcement learning, financial modeling workflows, and lightweight APIs

Let's Connect!

  • Feel free to explore the repos, fork anything useful, or reach out via LinkedIn Profile.

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  1. Black-Scholes-Interactive-heatmap Black-Scholes-Interactive-heatmap Public

    An interactive Black-Scholes Option Pricing app built with Streamlit. Features include pricing heatmaps, P&L analysis, and mispricing visualization using market data. Users can explore how spot pri…

    Python 4 1

  2. Volatility_Surface Volatility_Surface Public

    A Python project that visualizes a 3D implied volatility surface for options on any ticker symbol. Configurable inputs include risk-free rate, dividend yield, and strike price range. Ideal for anal…

    Python 11 4

  3. Portfolio_Optimization Portfolio_Optimization Public

    This project showcases portfolio optimization in Python, calculating and visualizing the Efficient Frontier, Max Sharpe Ratio (MSR), and Global Minimum Variance (GMV) portfolios, along with the Cap…

    Jupyter Notebook 1

  4. Pair_trading Pair_trading Public

    A pair-trading algorithm using cointegration, linear regression, and Z-score-based entry/exit rules. The strategy, applied to validated stock pairs, achieved consistent portfolio growth from $24,05…

    Jupyter Notebook

  5. airbnb-data-analysis airbnb-data-analysis Public

    Interactive Streamlit app for visualizing and analyzing Airbnb listings by price, location, room type, and more.

    Jupyter Notebook

  6. Deep-Hedging-Neural-Network-for-Derivatives-Pricing Deep-Hedging-Neural-Network-for-Derivatives-Pricing Public

    Deep Hedging neural network for dynamically pricing and managing derivatives risk under realistic market frictions

    Jupyter Notebook