option-wiz 0.0.1

Package for option calculations

Derivatives_Pricing_Library

Future Ideas:

Strategy Performance: https://medium.com/@rgaveiga/optionlab-a-python-library-for-evaluating-option-trading-strategies-50551ba7e578

• FIX MONTE CARLO THETA

• Customization and Extensibility: Design the library to be modular and customizable, allowing users to extend its functionality to suit their specific needs.

• Optimization: Potential optimization technique at http://www.jaeckel.org/LetsBeRational.pdf

• Option Contract Representation: Define a class or data structure to represent option contracts, including attributes like underlying asset, expiration date, strike price, option type (call/put), etc.

• Pricing Models: Implement common options pricing models like Black-Scholes, Binomial, and Monte Carlo simulations. Allow users to calculate option prices, Greeks (Delta, Gamma, Theta, Vega, Rho), and implied volatility.

• Volatility Analysis: Provide tools to analyze historical and implied volatility. Offer functions to compute volatility smile, volatility skews, term structures, and volatility cones.

• Volatility Forecasting: Implement features to forecast future implied or historical volatility using different models, such as GARCH

• Risk Management: Offer tools for risk assessment and portfolio management involving options positions. Calculate portfolio Greeks, value-at-risk (VaR), and stress testing scenarios.

• Visualization: Include visualization capabilities to plot option-related data, such as payoff diagrams, volatility charts, and strategy performance graphs.

• Strategy Analysis: Enable users to analyze option strategies like covered calls, protective puts, straddles, strangles, iron condors, and more. Calculate potential profit/loss, risk-reward ratios, break-even points, and visualize payoff diagrams.

• Historical Data and Market Analysis: Integrate with financial data providers to retrieve historical and real-time market data. Allow users to analyze and visualize option chains, historical price trends, and volume/open interest data.

• Backtesting and Simulation:Provide the ability to backtest option strategies using historical data.Simulate various market conditions and assess strategy performance over time.

• Option Chains and Expirations: Implement methods to retrieve and display available option contracts for a given underlying asset.

• Error Handling and Documentation: Include comprehensive documentation for each function and class. Implement proper error handling with meaningful error messages to assist users in troubleshooting.

• Educational Resources: Document the library with clear explanations and examples of its functionalities. Provide educational resources on options trading and analysis concepts for users who are new to options.