Option Pricing and Risk Hedging in the Current Financial Market: A Case for Google

Abstract

In the past few decades, financial derivative securities have been developing rapidly around the world, and the issue of options and investment consumption has attracted more and more attention from mathematicians and financiers at home and abroad. In this paper, option pricing models are constructed and calibrated based on the Black Scholes Merton model, binomial tree model, historical data model and Monte Carlo diffusion model. The differences between different option pricing models for options and stock hedging of the same company in a short period of time are discussed and analyzed. In this article, the Monte Carlo model outperforms the traditional Black Scholes Merton model, while the binomial tree model and the historical data model do not perform well. The results of this paper are beneficial for investors to use the optimal model to predict option prices, weaken the aggregate risk, and improve the aggregate return level.