关联性溢出矩阵:一种分散投资的工具

Connectedness spillover matrices : a tool for diversification

Annals of Operations Research · 2026
被引 0 · 同刊同年前 10%
ABS 3

中文导读

研究2015至2025年全球主要股指与加密货币的关联性,用ConvLSTM算法构建溢出矩阵,发现加密货币因低相关性可改善分散投资,帮助投资者在高波动市场中优化资产配置。

Abstract

Abstract This research analyzes the performance and interconnectedness of major global stock market indices and decentralized finance assets, specifically cryptocurrencies, over the period from 2015 to 2025. The study includes indices such as the S&P 500 and Nasdaq Composite from the United States, the FTSE 100, DAX, and CAC 40 from Europe, and the Nikkei 225 from Japan, and two more indices from China and India representing different economic regions. Additionally, Bitcoin and Ethereum are included to assess the impact of decentralized finance on traditional financial indices and asset allocation strategies. By employing Artificial Intelligence algorithms like ConvLSTM, the research measures the dynamic asset allocation and volatility management through an interconnected spillover matrix. The findings reveal that integrating ConvLSTM enhances the understanding of the interconnectedness between cryptocurrencies and traditional assets, offering improved diversification opportunities due to their low correlation, decentralization, and inflation-hedge characteristics. The study’s results suggest that investors can make more informed decisions regarding dynamic asset allocation in high-volatility portfolios, providing indicators of rising systemic risk and market stress.

金融市场资产配置加密货币波动性人工智能