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Guide: The Interactive Dashboard

The optpricing dashboard provides a rich, interactive user interface for visual analysis and pricing. It is built with Streamlit and is the easiest way to explore the library's features without writing code.

Launching the Dashboard

To start the application, simply run the following command in your terminal:

optpricing dashboard

This will launch the dashboard in a new browser tab. The sidebar on the left is the main navigation hub, allowing you to select a ticker, a data snapshot date (including live data), and a model to analyze.

Dashboard Pages

The dashboard is organized into several specialized pages:

1. Pricer & Greeks

This is an on-demand pricing tool. It allows you to manually set every parameter—from the option's strike and maturity to the specific parameters of the selected financial model. It's an ideal environment for:

  • Building intuition about how different parameters affect option prices and Greeks.
  • Performing sensitivity analysis.
  • Comparing the output of different numerical techniques for the same model.

2. Calibration & IV

This page is the front-end for the model calibration workflow. Here you can:

  • Select one or more models (e.g., BSM, Merton) to calibrate against a chosen market data snapshot.
  • Visualize the results of the calibration, including the final Root Mean-Squared Error (RMSE).
  • Analyze the resulting Implied Volatility (IV) surface of the calibrated model against the market's IV surface.
  • View volatility smiles and error heatmaps to diagnose mispricings and understand model fit.

3. Market Analytics

This page is an exploratory tool for option chain data. It allows you to load a live or historical snapshot and visualize key metrics for a chosen expiry date, including:

  • Total Volume and Open Interest for calls vs. puts.
  • An Open Interest "pyramid" showing concentrations across different strike prices.
  • The statistical distribution of Implied Volatility across the chain.

4. Model Fitting

This page contains tools for quantitative research, allowing you to:

  • Generate a Quantile-Quantile (QQ) plot to visually assess if a stock's historical returns conform to a normal distribution (a key assumption of the BSM model).
  • Fit jump parameters for a Merton-style process directly from historical returns using the method of moments.

5. Term Structure

This page is dedicated to interest rate models. It allows you to price Zero-Coupon Bonds and visualize the resulting yield curve generated by the Vasicek or CIR short-rate models.