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Nonlinear shrinkage estimation of large-dimensional covariance matrices

Ledoit, Olivier; Wolf, Michael - 2010

Persistent link: https://www.econbiz.de/10008988598

Fractional integration and fat tails for realized covariance kernels and returns

Lucas, André; Opschoor, Anne - 2016 - This version: September 1, 2016

We introduce a new fractionally integrated model for covariance matrix dynamics based on the long-memory behavior of daily realized covariance matrix kernels and daily return observations. We account for fat tails in both types of data by appropriate distributional assumptions. The covariance...

Persistent link: https://www.econbiz.de/10011531139

Estimation of a multiplicative covariance structure in the large dimensional case

Hafner, Christian M.; Linton, Oliver; Tang, Haihan - 2016

Persistent link: https://www.econbiz.de/10011565160

Estimation and forecasting of large realized covariance matrices and portfolio choice

Callot, Laurent; Kock, Anders B.; Medeiros, Marcelo C. - 2014

In this paper we consider modeling and forecasting of large realized covariance matrices by penalized vector autoregressive models. We propose using Lasso-type estimators to reduce the dimensionality to a manageable one and provide strong theoretical performance guarantees on the forecast...

Persistent link: https://www.econbiz.de/10010433899

Eigen-Adjusted Covariance Matrices

Menchero, Jose - 2011

The Markowitz mean-variance framework is the foundation of modern portfolio theory. One problem with this approach, however, is how sample covariance matrices tend to underestimate risk. Since the biases of optimized portfolios are closely related to eigenfactor portfolios, we present a...

Persistent link: https://www.econbiz.de/10013121223

Testing Covariates in High Dimensional Regression

Lan, Wei - 2013

In a high dimensional linear regression model, we propose a new procedure for testing statistical significance of a subset of regression coefficients. Specifically, we employ the partial covariances between the response variable and the tested covariates to obtain a test statistic. The resulting...

Persistent link: https://www.econbiz.de/10013082410

The Empirical Properties of Large Covariance Matrices

Zumbach, Gilles O. - 2009

datasets, Gilles turns to the joint problem of volatility and correlation. Certainly, one challenge in the study is to define …, where we concentrate on a small number of stable directions for correlation or covariance. Gilles's deeper investigation … where correlation and volatility are both dynamic quantities …

Persistent link: https://www.econbiz.de/10013155918

High-dimensional Realized Covariance Estimation : a Parametric Approach

Buccheri, Giuseppe - 2020

The estimation of the covariances of high-frequency asset prices is problematic because of asynchronous trading and market microstructure noise. In the last years, both parametric and non-parametric methods have been proposed in order to handle these effects. Little attention has instead been...

Persistent link: https://www.econbiz.de/10012841029

Multiplicative Conditional Correlation Models for Realized Covariance Matrices

Bauwens, Luc - 2020

akin to the consistent dynamic conditional correlation model of the multivariate GARCH literature, and estimation is …

Persistent link: https://www.econbiz.de/10012842834

Regularized Semiparametric Estimation of High Dimensional Dynamic Conditional Covariance Matrices

Morana, Claudio - 2019

This paper proposes a three-step estimation strategy for dynamic conditional correlation models. In the first step … usual normalization. In the third step, the two-step conditional covariance and correlation matrices are regularized by … model. This yields the final, third step smoothed estimate of the conditional covariance and correlation matrices. Due to …

Persistent link: https://www.econbiz.de/10012899132

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