option-trading-algorithm-with-garch-and-general-additive-binomial-pricing's Introduction

Option Trading Algorithm with GARCH and General Additive Binomial Pricing

Scott Griffin, The University of Iowa, 2023

The Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model is a statistical model used to analyze and forecast volatility in financial time series data.

The General Additive Binomial Pricing Model is a financial model used to value options. It's an extension of the classic binomial option pricing model, incorporating additional factors and complexities to provide more accurate option pricing.

In this notebook I'll build an option trading algorithm that implements these two models, then backtest it with historical option prices. The algorithm will look at four different underlying assets, chosen intentionally: AAPL (high volatility), KO (low volatility), SP500 (market), and BBBY (meme stock). All option prices were downloaded from Bloomberg with contract sizes of 100, and a time-to-expiry of one month.

The general idea of the trading algorithm's strategy is to:
(1) Look at a given market option quote.
(2) Generate a price for that option using the General Additive Binomial Pricing model with a volatility predicted from a fitted GARCH model.
(3) If the market price is some degree lower than our calculated price, buy the option and excercise if in the money during its term.

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