Copula estimation for nonsynchronous financial data

Abstract

Copula is a powerful tool to model multivariate data. Due to its several meritsCopula modelling has become one of the most widely used methods to model financial data.We discuss the problem of modelling intraday financial data through Copula. The problem originates due to the nonsynchronous nature of intraday financial data whereas to estimate the Copula, we need synchronous observations. We show that this problem may lead to serious underestimation of the Copula parameter. We propose a modification to obtain a consistent estimator in case of Elliptical Copula or to reduce the bias significantly in case of general copulas.

Limiting Spectral Distribution of High-dimensional Hayashi-Yoshida Estimator of Integrated Covariance Matrix

“…In this section we show the "closeness" of the Hayashi-Yoshida estimator with a scaled realized estimator which is motivated from the intraday covariance estimator proposed in 36 . We determine the scaling coefficients for the bivariate case.…”

“…on the interval ( 1 −1 ), ( 1) and the return on the is defined on the interval ( 2 −1 ), ( 2) . It can be shown the overlap and nonoverlapping parts of these two intervals play a crucial role in bias of the estimated covariance 36 . To define the overlap we first illustrate four possible configurations of the intervals.…”