Volatility Surface

An interactive Streamlit app that visualizes a 3D implied volatility surface for options on a chosen stock ticker.
Explore how implied volatility varies across time to expiration and either strike or moneyness.

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Features

• Flexible Ticker Symbol: Analyze options for any supported ticker (via Yahoo Finance / yfinance).
• OTM put/call blend: The surface is built from out-of-the-money options on each side (OTM puts below spot, OTM calls above) — the liquid, informative quotes — instead of calls only.
• Configurable Inputs:
  • Risk-Free Rate and Dividend Yield: User-defined (scenario testing).
  • Strike Range Filter: Choose a strike range as a percentage of spot price.
  • Liquidity Filters: Minimum volume, minimum open interest, and maximum bid-ask spread (%).
  • Y-Axis Selection: Strike Price or Log-moneyness (\ln(K/F)), where (F = S \cdot e^{(r-q)T}).
• Two surface methods:
  • Raw (interpolated) — grid interpolation of the observed IV points.
  • SVI fit — an arbitrage-free Gatheral SVI smile fit per expiry for a smooth surface.
• Smile / Skew viewer: 2D implied-vol-vs-strike plot for a chosen expiry, with the SVI fit overlaid.
• Export: Download the IV points as CSV and the surface as an interactive HTML file.
• Fast & cached: Network fetches and IV solves are cached and run in parallel, so moving the sliders is instant.

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Visualization

3D implied volatility surface (put/call blended):

Volatility smile / skew for a single expiry, with the arbitrage-free SVI fit overlaid:

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Setup Instructions

1. Clone the Repository:

    git clone https://github.com/George-Dros/Volatility_Surface
    cd Volatility_Surface

2. Create and activate a virtual environment

   py -3.12 -m venv .venv
    .\.venv\Scripts\Activate.ps1

3. Install requirements

   pip install -r requirements.txt

4. Run the Streamlit app

   streamlit run app.py

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How it works

1. Data Collection: Fetches call and put option chains, expirations, strikes, and market prices via yfinance (chains fetched in parallel and cached).

2. OTM blend & filtering: Keeps the out-of-the-money side per strike (puts ≤ spot, calls > spot), drops very short-dated expirations, and applies strike/liquidity filters.

3. Implied Volatility Calculation: Solves for σ in the Black–Scholes model (with dividend yield q) using Brent's method, on the mid price (falling back to last price).

4. Surface Construction: Either interpolates the IV points onto a grid, or fits an arbitrage-free SVI smile per expiry, then plots a 3D surface with Plotly.

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Testing

pip install -r requirements-dev.txt
pytest

The suite covers the Black–Scholes/IV round-trip, time-to-expiry determinism, the OTM-blend + liquidity pipeline, and the SVI fit. It runs in CI (GitHub Actions) on every push and pull request.

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Notes / Limitations

• Data quality depends on Yahoo Finance quotes; some tickers/expirations may return sparse or missing data.

• The SVI fit enforces no butterfly (per-expiry) arbitrage via parameter bounds, but does not enforce calendar arbitrage across expiries.

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Use Cases

1. Volatility Smile / Skew Inspection: Visualize skew patterns across maturities and strikes/moneyness.

2. Scenario Testing: Change r and q to see how assumptions affect the surface.

3. Learning Tool: A quick way to connect option market prices to implied vol behavior.

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Future Enhancements

• Calendar-arbitrage-free surface fitting (currently only per-expiry butterfly arbitrage is constrained).

• Greeks display and a term-structure (ATM vol vs. expiry) view.

• PNG/static image export (currently CSV + interactive HTML).

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License

This project is open-source and available under the MIT License.

Created by Georgios Drosogiannis