This short paper demonstrates how a covariance matrix estimated using log returns of multiple assets in their respective base currencies can be converted directly into a covariance matrix in a single ...
Covariance matrix forecasts of financial asset returns are an important component of current practice in financial risk management. A wide variety of models are available for generating such forecasts ...
High dimensionality comparable to the sample size is a common feature in portfolio allocation, risk management, genetic network and climatology. In this talk, we first use a multi-factor model to ...
Download PDF More Formats on IMF eLibrary Order a Print Copy Create Citation This paper proposes a novel shrinkage estimator for high-dimensional covariance matrices by extending the Oracle ...
The COV= option must be specified to compute an approximate covariance matrix for the parameter estimates under asymptotic theory for least-squares, maximum-likelihood, or Bayesian estimation, with or ...
Journal of Applied Probability, Vol. 27, No. 1 (Mar., 1990), pp. 156-170 (15 pages) Let Xt be a discrete-time multivariate stationary process possessing an infinite autoregressive representation and ...
Procedures for calculating the additive genetic variance-covariance matrix and its inverse are adapted to accommodate the occurrence of mutations in the genome. The inverse matrix can be used in mixed ...
Given the drawbacks of implementing multivariate analysis for mapping multiple traits in genome-wide association study (GWAS), principal component analysis (PCA) has been widely used to generate ...
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