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The Power of (Non-)Linear Shrinking : A Review and Guide to Covariance Matrix Estimation

Ledoit, Olivier - 2020

Many econometric and data-science applications require a reliable estimate of the covariance matrix, such as Markowitz portfolio selection. When the number of variables is of the same magnitude as the number of observations, this constitutes a difficult estimation problem; the sample covariance...

Persistent link: https://www.econbiz.de/10012849284

A Machine Learning Approach to Estimating Large Positive Definite Covariance Matrix of High Frequency Data

Cui, Liyuan - 2019

This paper proposes a novel covariance estimator via a machine learning approach when both the sampling frequency and covariance dimension are large. Assuming that a large covariance matrix can be decomposed into low rank and sparse components, our method simultaneously provides a consistent...

Persistent link: https://www.econbiz.de/10012867396

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

Large dynamic covariance matrices: enhancements based on intraday data

De Nard, Gianluca; Engle, Robert F.; Ledoit, Olivier; … - 2021 - This version: June 2021

unconditional correlation matrix. In this paper, we show how performance can be increased further by using open/high/low/close (OHLC …

Persistent link: https://www.econbiz.de/10012584099

Beta observation-driven models with exogenous regressors : a joint analysis of realized correlation and leverage effects

Gorgi, Paolo; Koopman, Siem Jan - 2020

impact of past values of realized correlation on future values is at least 10% higher when stock returns are negative rather … than positive. This finding supports the conjecture that correlation between stock returns tends to be higher when stock …

Persistent link: https://www.econbiz.de/10012161059

The power of (non-)linear shrinking : a review and guide to covariance matrix estimation

Ledoit, Olivier; Wolf, Michael - 2020 - This version: February 2020

Persistent link: https://www.econbiz.de/10012165719

Large dynamic covariance matrices: enhancements based on intraday data

De Nard, Gianluca; Engle, Robert F.; Ledoit, Olivier; … - 2020

. (2019) is able to overcome this curse via nonlinear shrinkage estimation of the unconditional correlation matrix. In this …

Persistent link: https://www.econbiz.de/10012253083

The power of (non-)linear shrinking : a review and guide to covariance matrix estimation

Ledoit, Olivier; Wolf, Michael - 2019

Persistent link: https://www.econbiz.de/10012018920

Large Scale Covariance Estimates for Portfolio Selection

Lautizi, Francesco - 2015

We propose an estimator of the Covariance Matrix (SWSE) of a large number of assets. This estimator improves the Similarity Weighted Estimator (SWE) introduced in Munnix et al. (2014), by combining it with the shrinkage estimator of the sample covariance matrix towards the market factor...

Persistent link: https://www.econbiz.de/10013018002

A parsimonious test of constancy of a positive definite correlation matrix in a multivariate time-varying GARCH model

Kang, Jian; Jakobsen, Johan Stax; Silvennoinen, Annastiina - In: Econometrics : open access journal 10 (2022) 3, pp. 1-41

We construct a parsimonious test of constancy of the correlation matrix in the multivariate conditional correlation … deterministically as a function of time. The alternative is a covariance matrix, not a correlation matrix, so the test may be viewed as … a general test of stability of a constant correlation matrix. The size of the test in finite samples is studied by …

Persistent link: https://www.econbiz.de/10013459316