Advances in Economics, Management and Political Sciences
- The Open Access Proceedings Series for Conferences
Proceedings of the 2nd International Conference on Business and Policy Studies
Series Vol. 13 , 13 September 2023
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Option Pricing and Risk Hedging in the Current Financial Market: A Case for Google
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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.
Keywords
Google, BS, option pricing
References
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Data Availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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- Volume Title
- Proceedings of the 2nd International Conference on Business and Policy Studies
- ISBN (Print)
- 978-1-915371-69-0
- ISBN (Online)
- 978-1-915371-70-6
- Published Date
- 13 September 2023
- Series
- Advances in Economics, Management and Political Sciences
- ISSN (Print)
- 2754-1169
- ISSN (Online)
- 2754-1177
- DOI
- 10.54254/2754-1169/13/20230684
- Copyright
- 13 September 2023
- Open Access
- This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited