Copula estimation for nonsynchronous financial data

Fuente: arXiv
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Autores principales: Chakrabarti, Arnab, Sen, Rituparna
Formato: Preprint
Publicado: 2019
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author Chakrabarti, Arnab
Sen, Rituparna
author_facet Chakrabarti, Arnab
Sen, Rituparna
contents Copula is a powerful tool to model multivariate data. We propose the modelling of intraday financial returns of multiple assets through copula. The problem originates due to the asynchronous nature of intraday financial data. We propose a consistent estimator of the correlation coefficient in case of Elliptical copula and show that the plug-in copula estimator is uniformly convergent. For non-elliptical copulas, we capture the dependence through Kendall's Tau. We demonstrate underestimation of the copula parameter and use a quadratic model to propose an improved estimator. In simulations, the proposed estimator reduces the bias significantly for a general class of copulas. We apply the proposed methods to real data of several stock prices.
format Preprint
id arxiv_https___arxiv_org_abs_1904_10182
institution arXiv
publishDate 2019
record_format arxiv
spellingShingle Copula estimation for nonsynchronous financial data
Chakrabarti, Arnab
Sen, Rituparna
Statistical Finance
Applications
Copula is a powerful tool to model multivariate data. We propose the modelling of intraday financial returns of multiple assets through copula. The problem originates due to the asynchronous nature of intraday financial data. We propose a consistent estimator of the correlation coefficient in case of Elliptical copula and show that the plug-in copula estimator is uniformly convergent. For non-elliptical copulas, we capture the dependence through Kendall's Tau. We demonstrate underestimation of the copula parameter and use a quadratic model to propose an improved estimator. In simulations, the proposed estimator reduces the bias significantly for a general class of copulas. We apply the proposed methods to real data of several stock prices.
title Copula estimation for nonsynchronous financial data
topic Statistical Finance
Applications
url https://arxiv.org/abs/1904.10182