# 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.