Research on Asset Allocation of Multivariate GARCH Models Based on Market Data

本文采用多元GARCH模型对资产配置中的风险管理进行了研究。研究旨在通过多元GARCH模型对不同资产间的波动率及其相关性进行分析，以此优化资产组合，达到分散风险、提高投资收益的目的。本文首先介绍了GARCH模型的基本原理和多元GARCH模型的扩展形式，接着利用实际市场数据进行实证分析，验证多元GARCH模型在资产配置中的有效性。结果表明，多元GARCH模型能够较好地捕捉资产间的动态相关性，对风险管理具有重要意义。最后，本文讨论了多元GARCH模型在实际应用中的优势和局限性，并提出了未来的研究方向。This paper investigates the application of the multivariate GARCH model in risk management for asset allocation. The study aims to optimize asset portfolios by analyzing the volatility and correlations between different assets using the multivariate GARCH model, thereby achieving risk diversification and improving investment returns. The paper begins with an introduction to the basic principles of the GARCH model and its multivariate extensions, followed by an empirical analysis using real market data to validate the effectiveness of the multivariate GARCH model in asset allocation. The results indicate that the multivariate GARCH model can effectively capture the dynamic correlations between assets, making it a valuable tool for risk management. Finally, the paper discusses the advantages and limitations of the multivariate GARCH model in practical applications and suggests future research directions.