Proceedings of the 2019 International Conference on Economic Management and Cultural Industry (ICEMCI 2019)

Comparison of Black–Scholes Model and Monte-Carlo Simulation on Stock Price Modeling

Authors
Qiwu Jiang*
Corresponding Author
Qiwu Jiang*
Available Online 20 December 2019.
DOI
10.2991/aebmr.k.191217.025How to use a DOI?
Keywords
Black-Scholes Option Pricing Model, Monte-Carlo Simulation, Stock Price, European Call Option
Abstract

Option price and its valuation are crucial issues in finance research. In this research we implement Black-Scholes option pricing model and compare it with stochastic modeling, namely the Monte-Carlo Simulation. These two classical models are implemented on newly emerged technology companies like Google and Apple and traditional industry like Esso. The result shows that both option pricing model and numerical simulation are able to yield prices close to actual stock price

Copyright
© 2019, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)

Volume Title
Proceedings of the 2019 International Conference on Economic Management and Cultural Industry (ICEMCI 2019)
Series
Advances in Economics, Business and Management Research
Publication Date
20 December 2019
ISBN
10.2991/aebmr.k.191217.025
ISSN
2352-5428
DOI
10.2991/aebmr.k.191217.025How to use a DOI?
Copyright
© 2019, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Qiwu Jiang*
PY  - 2019
DA  - 2019/12/20
TI  - Comparison of Black–Scholes Model and Monte-Carlo Simulation on Stock Price Modeling
BT  - Proceedings of the 2019 International Conference on Economic Management and Cultural Industry (ICEMCI 2019)
PB  - Atlantis Press
SP  - 135
EP  - 137
SN  - 2352-5428
UR  - https://doi.org/10.2991/aebmr.k.191217.025
DO  - 10.2991/aebmr.k.191217.025
ID  - Jiang*2019
ER  -