We introduce a novel covariance estimator that exploits the heteroskedastic nature of financial time series by employing exponential weighted moving averages and shrinking the in-sample eigenvalues through cross-validation. Our estimator is model-agnostic in that we make no assumptions on the...

Cross-sectional asset pricing tests with GMM can generate spuriously high explanatory power for factor models when the moment conditions are specified such that they allow the estimated factor means to substantially deviate from the observed sample averages. In fact, by shifting the weights on...

Under rotation-equivariant decision theory, sample covariance matrix eigenvalues can be optimally shrunk by recombining sample eigenvectors with a (potentially nonlinear) function of the unobservable population covariance matrix. The optimal shape of this function reflects the loss/risk that is...

The idiosyncratic (microscopic) and systemic (macroscopic) components of market structure have been shown to be responsible for the departure of the optimal mean-variance allocation from the heuristic 'equally-weighted' portfolio. In this paper, we exploit clustering techniques derived from...

We introduce the new F-Riesz distribution to model tail-heterogeneity in fat-tailed covariance matrix observations. In contrast to the typical matrix-valued distributions from the econometric literature, the F-Riesz distribution allows for di↵erent tail behavior across all variables in the...

This paper discusses the notion of cointegrating space for linear processes integrated of any order. It first shows that the notions of (polynomial) cointegrating vectors and of root functions coincide. Second, it discusses how the cointegrating space can be defined (i) as a vector space of...

Linear algebra is without a doubt a fundamental tool to deal with empirical economic problems. The goal of this paper is to use some of these techniques to treat business cycles. To do that, we present the classic ordinary least square approach to estime the coefficients of a detrended time...

We study the rank of the instantaneous or spot covariance matrix Σ(t) of a multidimensional continuous semi-martingale X(t). Given highfrequency observations X(i=n), i = 0; : : : ;n, we test the null hypothesis rank (Σ(t)) ≤ r for all t against local alternatives where the average (r + 1)st...