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ESTIMATION PROBLEMS IN MODELS WITH SPATIAL WEIGHTING MATRICES WHICH HAVE BLOCKS OF EQUAL ELEMENTS
SPATIAL WEIGHTING MATRICES HAVE BLOCKS EQUAL ELEMENTS
2015/9/24
Spatial models whose weighting matrices have blocks of equal elements might be considered if units are viewed as equally distant within certain neighborhoods, but unrelated between neighborhoods. We g...
Forecasting credit migration matrices with business cycle effects—a model comparison
credit risk credit VaR forecasting transition matrices
2011/8/23
Migration matrices are considered a major determinant for credit risk management. They are widely used for credit value-at-risk determination, portfolio management or derivative pricing. It is well kn...
Asymmetric random matrices: What do we need them for?
Asymmetric random matrices standard correlation matrices Complex systems
2011/7/4
Complex systems are typically represented by large ensembles of observations.
Correlation matrices provide an efficient formal framework
to extract information from such multivariate ensembles and i...
The fine structure of spectral properties for random correlation matrices: an application to financial markets
financial correlation matrices eigenvalue factor models
2011/3/23
We study some properties of eigenvalue spectra of financial correlation matrices. In particular, we investigate the nature of the large eigenvalue bulks which are observed empirically, and which have ...
A non-Hermitean extension of paradigmatic Wishart random matrices is introduced to set up a theoretical framework for statistical analysis of (real, complex and real quaternion) stochastic time serie...
Toy Model for Large Non-Symmetric Random Matrices
Singular Values Rectangular RandomMatrices Free Random Matrix Theory
2010/10/20
Non-symmetric rectangular correlation matrices occur in many problems in economics. We test the method of extracting statistically meaningful correlations between input and output variables of large ...
Estimating correlation and covariance matrices by weighting of market similarity
Weighted Correlation Estimation Covariance Estimation Time-dynamic Dependence
2010/10/20
We discuss a weighted estimation of correlation and covariance matrices from historical financial data. To this end, we introduce a weighting scheme that accounts for similarity of previous market co...
On the Estimation of Integrated Covariance Matrices of High Dimensional Diffusion Processes
High dimension high frequency integrated covariance matrix
2010/10/20
We consider the estimation of integrated covariance matrices of high dimensional diffusion processes by using high frequency data. We start by studying the most commonly used estimator, the realized ...
The rigidity of a matrix A for target rank r is the minimum number of entries of A that must be changed to ensure that the rank of the altered matrix is at most r.
Affine processes on positive semidefinite matrices
affine processes Wishart processes stochastic volatility stochastic invariance
2010/11/2
The article provides the mathematical foundation for stochastically continuous affine processes on the cone of positive semidefinite symmetric matrices. This analysis has been motivated by a large and...
Spectral densities of Wishart-Levy free stable random matrices: Analytical results and Monte Carlo validation
Spectral densities Analytical results Monte Carlo validation
2010/10/29
Random matrix theory is used to assess the significance of weak correlations and is well established for Gaussian statistics. However, many complex systems, with stock markets as a prominent example, ...
Universal Correlations and Power-Law Tails in Financial Covariance Matrices
Universal Correlations Power-Law Tails Financial Covariance Matrices
2010/11/1
Signatures of universality are detected by comparing individual eigenvalue distributions and level spacings from financial covariance matrices to random matrix predictions. A chopping procedure is dev...
The empirical properties of large covariance matrices
Covariance matrix spectrum spectral density
2010/10/29
The salient properties of large empirical covariance and correlation matrices are studied for
three datasets of size 54, 55 and 330. The covariance is defined as a simple cross product of the returns...