《Statistical Risk Models》
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作者:
Zura Kakushadze and Willie Yu
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最新提交年份:
2017
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英文摘要:
We give complete algorithms and source code for constructing statistical risk models, including methods for fixing the number of risk factors. One such method is based on eRank (effective rank) and yields results similar to (and further validates) the method set forth in an earlier paper by one of us. We also give a complete algorithm and source code for computing eigenvectors and eigenvalues of a sample covariance matrix which requires i) no costly iterations and ii) the number of operations linear in the number of returns. The presentation is intended to be pedagogical and oriented toward practical applications.
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中文摘要:
我们给出了构建统计风险模型的完整算法和源代码,包括确定风险因素数量的方法。其中一种方法基于eRank(有效秩),产生的结果类似于(并进一步验证)我们其中一人在早期论文中提出的方法。我们还给出了一个完整的算法和源代码,用于计算样本协方差矩阵的特征向量和特征值,它需要i)无代价的迭代,ii)在返回数中线性运算的次数。本演示旨在进行教学,并面向实际应用。
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分类信息:
一级分类:Quantitative Finance 数量金融学
二级分类:Portfolio Management 项目组合管理
分类描述:Security selection and optimization, capital allocation, investment strategies and performance measurement
证券选择与优化、资本配置、投资策略与绩效评价
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一级分类:Quantitative Finance 数量金融学
二级分类:Risk Management 风险管理
分类描述:Measurement and management of financial risks in trading, banking, insurance, corporate and other applications
衡量和管理贸易、银行、保险、企业和其他应用中的金融风险
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