基于Copula-Kernel模型的投资组合La-VaR分析研究

Jianhui Yang, Bin Yang
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引用次数: 0

摘要

传统的VaR方法在衡量投资组合风险方面存在诸多缺陷,本文对BDSS模型进行了修正,得到了基于相对价格的修正BDSS模型- La-VaR模型。为了拟合收益率和相对价格序列,本文采用光滑性较好的高斯核函数和copula核模型来描绘边际分布和相关结构。随后通过蒙特卡罗模拟得到经验分布序列。实证结果表明,Copula-kernel模型对收益率和相对价格序列的拟合具有较高的精度。随着置信度c的降低,La-VaR模型的流动性风险越来越显著,但回归检验表明,VaR和La-VaR模型都高估了风险。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Study on Portfolio La-VaR Analysis Based on Copula-Kernel Model
Traditional VaR method has many defects in measuring portfolio risk, this paper modifies BDSS model and gets revised BDSS model - La-VaR model based on relative price. For fitting the sequences of the rate of return and relative price, this paper adopts Gaussian-kernel function with good smoothness and Copula-kernel model to portray marginal distribution and correlation structure. Afterwards sequence of empirical distribution is produced through Monte Carlo simulation. The empirical results show that Copula-kernel model has a high accuracy in fitting sequences of the rate of return and relative price. Liquidity risk in La-VaR model is getting significant as the decrease of confidence c, but back testing shows that both VaR and La-VaR model overestimate the risk.
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