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<article xsi:noNamespaceSchemaLocation="http://jats.nlm.nih.gov/publishing/1.1/xsd/JATS-journalpublishing1-mathml3.xsd" dtd-version="1.1" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"><front><journal-meta><journal-id journal-id-type="publisher-id">ASDS</journal-id><journal-title-group><journal-title>Applied Statistics and Data Science</journal-title></journal-title-group><issn>3066-8433</issn><eissn>3066-8441</eissn><publisher><publisher-name>Art and Design</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.61369/ASDS.2025070019</article-id><article-categories><subj-group subj-group-type="heading"><subject>Article</subject></subj-group></article-categories><title>基于高维协方差矩阵估计的投资组合优化策略比较与分析</title><url>https://artdesignp.com/journal/ASDS/1/7/10.61369/ASDS.2025070019</url><author>孙章爽,张婷,万宇雷,王国强</author><pub-date pub-type="publication-year"><year>2025</year></pub-date><volume>1</volume><issue>7</issue><history><date date-type="pub"><published-time>2025-09-20</published-time></date></history><abstract>在金融领域，协方差矩阵的精确估计对于优化投资组合至关重要。研究旨在综合比较无条件协方差矩阵估计和条件协方差矩阵估计在投资组合优化中的表现，并基于不同维度的股票和商品两种大类资产的数据进行投资组合优化的实证分析。结果显示：对于低维情形，无条件协方差矩阵估计在组合收益和组合风险偏差方面均具有突出表现；对于高维情形，条件协方差矩阵估计的表现更为有效。</abstract><keywords>协方差矩阵估计,条件协方差,压缩估计,稀疏估计,投资组合优化</keywords></article-meta></front><body/><back><ref-list><ref id="B1" content-type="article"><label>1</label><element-citation publication-type="journal"><p>[1]ENGEL J，BUYDENS L，BLANCHET L. 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