Comparison of Option Pricing Based on Black-Scholes and Binomial Tree: Evidence from Moutai’s Share Price
- DOI
- 10.2991/978-94-6463-408-2_39How to use a DOI?
- Keywords
- Black-Scholes Model; Binomial Tree Model; Chinese Capital Market; Kweichow Moutai Company
- Abstract
As a matter of fact, option pricing is a vital area in mathematical finance, and various academic pricing methods has shed light on specific option types’ pricing, among which Black-Scholes model and Binomial Tree model are the most widely-used measures. However, recent debates have been concentrated on the utility and efficiency of those two measures. Moreover, the newly developed Chinese capital market have been developing its option transaction mechanisms to a more mature level. Based on those two models’ theoretical framework, this study acquired real time data of Moutai from Shanghai Stock Market Exchange (SSE) and use Python code to simulate the option price in the next period based on two different models respectively. According to the analysis, though share price from SSE might not reflect the overall Chinese capital market’s condition, these results would contribute to mend the research gap of empirical application of option pricing models in the Chinese market.
- Copyright
- © 2024 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Jiale Li PY - 2024 DA - 2024/05/07 TI - Comparison of Option Pricing Based on Black-Scholes and Binomial Tree: Evidence from Moutai’s Share Price BT - Proceedings of the 9th International Conference on Financial Innovation and Economic Development (ICFIED 2024) PB - Atlantis Press SP - 342 EP - 351 SN - 2352-5428 UR - https://doi.org/10.2991/978-94-6463-408-2_39 DO - 10.2991/978-94-6463-408-2_39 ID - Li2024 ER -