Option-Visualizer

This project's goal is to investigate the performance of various option strategies. It is divided into three main parts:

1. Option Calculator: Calculate the basic return profile for individual options (e.g., calls or puts) given specific parameters.
2. Strategy Analyzer: Analyze the return profiles of simple strategies like covered calls, cash-secured puts, bull call spreads, and seagulls.
3. Backtest Analyzer: Evaluate the performance of strategies over longer time periods using historical data.

Project Structure

/web

Contains the web application built with Flask. This folder includes templates, static assets, and the main application logic.

• /web/templates: HTML templates for the web interface.

  • index.html: The homepage with navigation to different tools.
  • option_calculator.html: Interface for calculating individual option prices and payoffs.
  • strategy_analyzer.html: Interface for analyzing option strategies.
  • backtest_analyzer.html: Interface for backtesting strategies over historical data.

• /web/static: Static assets such as CSS and JavaScript files.

  • css/style.css: Styles for the web application.

• /web/app.py: The main Flask application file. Defines routes for the web interface and API endpoints for calculations and backtesting.

/core

Core logic and utilities for option pricing, strategy creation, and calculations.

• /core/strategies: Contains strategy definitions and a factory for creating strategies.

  • strategy_base.py: Base classes for option and stock positions, and the trading strategy framework.
  • strategy_factory.py: Factory for creating predefined strategies like covered calls and cash-secured puts.

• /core/pricing: Implements pricing models for options.

  • black_scholes.py: Black-Scholes model for option pricing and greeks calculation.

• /core/utils: Utility functions for date calculations and other helpers.

  • date_utils.py: Functions for calculating time-to-maturity and other date-related utilities.

/analytics

Modules for analyzing and backtesting strategies.

• /analytics/backtest_engine.py: Engine for running backtests on strategies, including buy-and-hold and cash-secured put comparisons.
• /analytics/returns.py: Functions for calculating returns and performance metrics.

/tests

Contains unit tests for the application. (Currently not included but recommended for future development.)

/data

(Optional) Placeholder for storing any data files, such as historical price data or backtest results.

/config

(Optional) Placeholder for configuration files, such as environment variables or settings.

/README.md

This file. Provides an overview of the project and its structure.

/pyproject.toml

Defines the project metadata and dependencies for Python.

/requirements.txt

(Optional) Placeholder for listing Python dependencies if not using pyproject.toml.

/static

(Optional) Placeholder for additional static assets if needed.

How to Run

I use uv to manage the package dependency.

uv run -m web.app

3. Open the application in your browser at http://localhost:8080.

Future Improvements