This project is a personal exploration and implementation of exotic option products, aimed at deepening practical understanding of structured derivatives as used on trading desks.
Rather than focusing on abstract quant models, this repo reflects the type of work an exotic structurer would do, linking product payoffs, market views, and risk considerations through simulation, visualization, and pricing tools.
Structured products are widely used in equity and FX markets to tailor yield, manage risk, or reflect investor views.
This project simulates and prices these products using:
- Realistic stochastic models (GBM, Heston),
- Custom payoff engines per product,
- and Monte Carlo simulation to price and visualize payoff behavior.
It's designed to help answer questions like:
- How does a Phoenix autocall perform under different vol regimes?
- What happens to a knock-in barrier with high skew?
- How do different model assumptions affect hedging risk?
To follow this repo, you should be comfortable with:
- General finance concepts (equity, fixed income, FX, and basic derivative instruments)
- Vanilla option pricing and the Black-Scholes framework
- Basic stochastic calculus (GBM, volatility surfaces)
- Python and Jupyter
.
├── 01_products/ # Product-specific payoff definitions
├── 02_models/ # Underlying model engines (GBM, Heston, etc.)
├── 03_simulations/ # Monte Carlo pricing engine
├── 04_greeks/ # Risk sensitivities
├── 05_notebooks/ # Interactive notebooks for analysis & visualization