对数协方差到算术协方差矩阵函数?
是否有一个函数可以将使用对数返回构建的协方差矩阵转换为基于简单算术返回的协方差矩阵?
动机:我们希望使用均值-方差效用函数,其中预期收益和方差以算术术语指定。然而,由于对数回报的可加性,通常使用对数回报来估计回报和协方差,并且我们假设资产价格遵循对数正态随机过程。
Meucci 描述了一种为 上对数正态收益的通用/任意分布生成基于算术收益的协方差矩阵的过程附录第 5 页。
Is there a function that can convert a covariance matrix built using log-returns into a covariance matrix based on simple arithmetic returns?
Motivation: We'd like to use a mean-variance utility function where expected returns and variance is specified in arithmetic terms. However, estimating returns and covariances is often performed with log-returns because of the additivity property of log returns, and we assume asset prices follow a lognormal stochastic process.
Meucci describes a process to generate a arithmetic-returns based covariance matrix for a generic/arbitrary distribution of lognormal returns on Appendix page 5.
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这是我对公式的翻译:
编辑:根据评论修复了
-1
问题。尝试一个示例:
生成多元对数正态回报:
与公式的预期结果进行比较:
Here's my translation of the formulae:
edit: fixed
-1
issue based on comments.Try an example:
Generate multivariate log-normal returns:
Compare with expected results from formulae: