Risk Analysis for Electric Vehicle Investments: Beta Trends and Monte Carlo Insights

2024-24-0027

09/18/2024

Features
Event
Conference on Sustainable Mobility
Authors Abstract
Content
The electric vehicle (EV) industry is seeing a significant increase in global investments. However, it faces major challenges, especially the shortage and rising costs of key raw materials needed for battery production. This situation creates higher economic risks for investors.
This paper evaluates the risks of investing in the EV industry, considering current supply chain issues related to finding raw materials, manufacturing, and selling. The evaluation uses the beta coefficient, which measures how much an individual stock’s price is expected to fluctuate compared to the overall stock market. To examine the beta coefficient’s variability, a Monte Carlo simulation is used to calculate its changes, providing insights into the volatility of assets in the EV industry relative to market conditions. The simulation is repeated multiple times until consistent results are obtained. The main goal of this study is to offer a forward-looking tool to help with investment decisions in the production of electric vehicles. This method goes beyond traditional profitability measures by including considerations of uncertainty, risk factors, and variables. These factors, though inherently uncertain and unable to be assigned specific values, are defined within a range of probabilities. The simulation results, expressed in terms of probability, show that the beta coefficient for the EV automotive sector is riskier than the reference value. By providing a detailed perspective on risk assessment, this study aims to help investors make informed and well-grounded decisions, enhancing their understanding of the challenges and opportunities in the evolving EV investment landscape.
Meta TagsDetails
DOI
https://doi.org/10.4271/2024-24-0027
Pages
12
Citation
Gutierrez, M., and Taco, D., "Risk Analysis for Electric Vehicle Investments: Beta Trends and Monte Carlo Insights," SAE Technical Paper 2024-24-0027, 2024, https://doi.org/10.4271/2024-24-0027.
Additional Details
Publisher
Published
Sep 18
Product Code
2024-24-0027
Content Type
Technical Paper
Language
English