FabienCarmagnac / volatility-surface-yfinance

This Python script creates a volatility surface plot using historical data and the Black-Scholes-Merton model. It calculates implied volatility for call and put options, visualizing volatility against strike price and time to expiration. Includes a tkinter GUI for parameter input. Requires yfinance, pandas, scipy, matplotlib, and tkinter.

Volatility Surface Generator

This Python script generates a volatility surface for a given underlying asset using option prices retrieved from Yahoo Finance. It employs the Black-Scholes-Merton (BSM) model for implied volatility calculation.

Requirements

• Python 3.x
• yfinance
• pandas
• numpy
• scipy
• matplotlib
• tkinter

Installation

1. Clone the repository:

   git clone https://github.com/Gologoye/volatility-surface-yfinance.git

2. Install the required dependencies:

   pip install -r requirements.txt

Usage

1. Run the script:

   python volatility_surface.py

2. Enter the required parameters in the GUI window:

   • Underlying Asset: Enter the ticker symbol of the underlying asset, to find the right ticker, look on finance.yahoo.com..
   • Risk-Free Rate: Enter the risk-free rate (decimal).
   • Option Type (CALL/PUT): Enter the type of option to analyze (CALL or PUT).
   • Sigma: Enter the initial guess for volatility (decimal).
   • Tolerance (xtol): Enter the tolerance for the solver.
   • Maximum Number of Iterations (maxfev): Enter the maximum number of iterations for the solver.

3. Click the "Generate" button to generate the volatility surface plot.

Example

Note

• The script retrieves historical stock data and option chain data from Yahoo Finance.
• It filters option contracts based on strike price proximity to the current stock price.
• The BSM model is used to calculate implied volatility.
• The GUI is implemented using Tkinter.