Covariance extension and spectral estimation form a foundational framework in the analysis and synthesis of stochastic processes. At its core, covariance extension refers to the problem of ...

In high-dimensional settings where the number of variables approaches or exceeds the sample size, classical sample covariance matrices become unstable and singular. Covariance matrix estimation ...

Many problems in quantitative finance involve both predictive forecasting and decision-based optimization. Traditionally, covariance forecasting models are optimized with unique prediction-based ...

The estimation of portfolio value-at-risk (VaR) requires a good estimate of the covariance matrix. As it is well known that a sample covariance matrix based on some historical rolling window is noisy ...

X ij = [x ij1, ... , x ijp]' The Generalized Estimating Equation of Liang and Zeger (1986) for estimating the p ×1 vector of regression parameters is an extension of the independence estimating ...

Froot, K. A. "Consistent Covariance Matrix Estimation with Cross-Sectional Dependence and Heteroskedasticity in Cross-Sectional Financial Data." Journal of Financial and Quantitative Analysis 24, no.