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).
• Configurable Inputs:
  • Risk-Free Rate: User-defined (for scenario testing / current market assumptions).
  • Dividend Yield: User-defined (scenario testing).
  • Strike Range Filter: Choose a strike range as a percentage of spot price.
  • Y-Axis Selection:
    • Strike Price, or
    • Log-moneyness: (\ln(K/F)), where (F = S \cdot e^{(r-q)T})
• 3D Volatility Surface Plot:
  • X-axis: Time to expiration (years)
  • Y-axis: Strike price or log-moneyness
  • Z-axis: Implied volatility (%)

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Visualization

Example output from the app:

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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 option chain data (calls), expirations, strikes, and market prices via yfinance.

2. Filtering: Filters options by strike range and removes very short-dated expirations.

3. Implied Volatility Calculation: Computes implied volatility by solving for σ in the Black–Scholes model (with dividend yield q) using a root-finder.

4. Surface Construction: Interpolates the IV points onto a grid and plots a 3D surface with Plotly.

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Notes / Limitations

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

• Surfaces can look noisy for illiquid options (wide bid/ask spreads, stale last prices).

• Current implementation focuses on calls.

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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

• Add puts and put/call parity checks.

• Liquidity filters (volume/open interest/spread) as UI controls.

• Surface export (CSV + image).

• Alternative smoothing/interpolation methods or model fits (e.g., SVI).

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License

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

Created by Georgios Drosogiannis