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Option Pricing Series

Interactive Streamlit Application for Option Payoffs and Strategies

Try it live: Option Pricing Series Interactive App

Author: Mark Bogorad

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Summary

The Option Pricing Series is a dynamic Streamlit application designed to visualize option payoffs and explore trading strategies. It integrates Black-Scholes pricing models, visual heatmaps, and optimal hedging calculations with a real-time input storage mechanism powered by KDB+.

The app provides traders and financial engineers with tools to analyze how varying spot prices and volatilities affect option payoffs, helping users make informed decisions.

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Features

• Heatmaps: Visualize how option profits vary with spot prices and volatilities.
• Trade Strategies: Explore predefined strategies like covered calls, protective puts, and strangles.
• Greeks Calculation: Compute Delta, Gamma, Vega, Rho, and Theta for hedging decisions.
• KDB+ Integration: Store and retrieve user inputs for enhanced data tracking.
• Interactive UI: Real-time adjustments to parameters via Streamlit sliders and inputs.

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Relevance

Option pricing and risk management are critical in financial engineering. Traditional static calculations are enhanced here with:

• Real-time interactivity for exploring multiple scenarios.
• Integration with KDB+ for efficient data storage and retrieval.
• A focus on visual and intuitive analysis, ideal for both novice and professional users.

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Methodology

Core Functionality

• Black-Scholes Model: Computes call and put prices, profits, and option Greeks.
• Heatmap Visualization: Plots profit for various spot prices and volatilities.
• Optimal Hedges: Calculates hedge ratios for risk management.

Tools and Libraries

• Streamlit: Builds the user interface.
• KDB+: Stores user inputs.
• Pandas, NumPy, SciPy: Enables data manipulation and statistical calculations.
• Matplotlib, Seaborn: For visualizations.

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Installation

1. Clone the repository:

   git clone https://github.com/markbogorad/option-pricing-series.git
   cd option-pricing-series

2. Install dependencies:

   pip install -r requirements.txt

3. Run the Streamlit application:

   streamlit run main.py

4. (Optional) Start the KDB+ server for input storage:

   q -p 5001

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Usage

1. Set Parameters: Input current asset price, strike price, volatility, etc., in the sidebar.
2. Visualize Payoffs: Navigate between tabs to explore heatmaps, strategies, and hedges.
3. Analyze Results: View and download stored inputs or utilize KDB+ for advanced data tracking.

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Example

Call and Put Option Profit Heatmaps

Heatmaps display profits for call and put options based on:

• Spot Price (X-axis)
• Volatility (Y-axis)

Optimal Hedges

Greeks such as Delta and Vega are calculated to provide actionable hedging insights:

• Example Delta Hedge:

  "To delta hedge, trade 0.34 units of the underlying asset."

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License

This project is licensed under the MIT License. See the LICENSE file for details.

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