I'm an Applied Mathematics and Physical Sciences graduate from NTUA, currently working as a Power Trading Trainee in the energy markets sector.
My GitHub focuses on Python-based financial modeling, data analysis, interactive dashboards, and quantitative tools. I’m especially interested in projects that connect mathematical modeling, market behavior, risk, and practical decision-making.
- Repository: Deep Hedging for Options
A TensorFlow project that trains a GRU-based neural network to dynamically hedge European call options under realistic simulated market conditions, including volatility spikes, jumps, regime shifts, and combined Heston/Merton jump-diffusion dynamics.
The project includes a full simulation environment, a CVaR-based loss function, backtesting, benchmark comparisons, and diagnostic plots. Results showed significant CVaR90 and VaR90 reduction compared to an unhedged baseline.
- Repository: Volatility Surface Visualization
- Streamlit App: Live Demo
An interactive Streamlit tool for visualizing implied volatility surfaces across strike prices and time-to-maturity for a selected ticker.
The app helps explore how implied volatility changes across the option chain and can support interpretation of market expectations, skew, term structure, and option-pricing behavior.
- Repository: Black-Scholes Interactive Heatmap
- Streamlit App: Live Demo
An interactive option-pricing app based on the Black-Scholes model.
Users can adjust parameters such as volatility, risk-free rate, strike price, and time-to-maturity to generate option price heatmaps and explore how pricing changes under different market assumptions.
- Repository: Airbnb Listings Analysis Dashboard
- Streamlit App: Live Demo
An interactive dashboard for exploring Airbnb listings by city.
The app includes filters for room type, price, availability, and superhost status, along with automatic visual insights through boxplots, scatter plots, histograms, and summary metrics.
- Languages: Python, SQL, Fortran
- Libraries: Pandas, NumPy, Streamlit, scikit-learn, Matplotlib, Seaborn, HDBSCAN, UMAP, PyTorch, TensorFlow
- Tools: Git, JupyterLab, LaTeX
- Currently exploring: energy markets, power trading workflows, financial modeling, reinforcement learning, and lightweight APIs
- Energy markets and power trading
- Quantitative finance and risk modeling
- Financial data analysis
- Interactive analytical tools
- Python-based modeling and simulation
Feel free to explore the repositories, fork anything useful, or reach out via my LinkedIn profile.