Portfolio Design and Optimization Based on the CAPM Model

Boxiong Xing

2024

Abstract

In the evolving landscape of global financial markets, traditional portfolio management approaches face challenges due to the rise of new asset classes and increasingly complex investment environments. This study examines the optimization of portfolio returns and risks by integrating traditional assets with emerging ones. This paper explores the optimization of portfolio returns and risks by combining traditional and emerging assets. The research uses data from assets (e.g., Apple, crude oil, Bitcoin, and SPY options), employing models including CAPM, the mean-variance model, and CVaR to determine the most efficient asset allocation. The results reveal that a portfolio consisting of 50% Apple, 10% crude oil, 30% SPY, and 10% Bitcoin achieves an expected annualized return of 8.32% with an annualized volatility of 8.46%. This allocation achieves a strong balance between risk and return, offering a solid foundation for optimizing portfolio strategies. This research highlights the significance of strategic asset allocation and sophisticated risk management, offering key insights for investors aiming for stable, long-term growth. Future research could further improve portfolio performance by incorporating real-time data and machine learning models, allowing for more adaptive and responsive investment strategies in the face of market uncertainties.

Paper Citation

in Harvard Style

Xing B. (2024). Portfolio Design and Optimization Based on the CAPM Model. In Proceedings of the 1st International Conference on E-commerce and Artificial Intelligence - Volume 1: ECAI; ISBN 978-989-758-726-9, SciTePress, pages 469-475. DOI: 10.5220/0013268900004568

in Bibtex Style

@conference{ecai24,
author={Boxiong Xing},
title={Portfolio Design and Optimization Based on the CAPM Model},
booktitle={Proceedings of the 1st International Conference on E-commerce and Artificial Intelligence - Volume 1: ECAI},
year={2024},
pages={469-475},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013268900004568},
isbn={978-989-758-726-9},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on E-commerce and Artificial Intelligence - Volume 1: ECAI
TI - Portfolio Design and Optimization Based on the CAPM Model
SN - 978-989-758-726-9
AU - Xing B.
PY - 2024
SP - 469
EP - 475
DO - 10.5220/0013268900004568
PB - SciTePress