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Robust Maximization of Asymptotic Growth under Covariance Uncertainty
Maximization Covariance Uncertainty
2011/7/19
This paper resolves a question proposed in Kardaras and Robertson (2011): how to invest in a robust growth-optimal way in a market where precise knowledge of the covariance structure of the underlying...
Dynamic Large Spatial Covariance Matrix Estimation in Application to Semiparametric Model Construction via Variable Clustering: the SCE approach
Time Series Covariance Estimation Regularization Sparsity Thresholding Semiparametrics Graphical Model Variable Clustering
2011/7/5
To better understand the spatial structure of large panels of economic and nancial time
series and provide a guideline for constructing semiparametric models, this paper rst consid-
ers estimating...
When do improved covariance matrix estimators enhance portfolio optimization? An empirical comparative study of nine estimators
covariance matrix nine estimators portfolio optimization
2010/4/28
The use of improved covariance matrix estimators as an alternative to the sample estimator is considered an important approach for enhancing portfolio optimization. Here we empirically compare the per...
Variance-covariance based risk allocation in credit portfolios: analytical approximation
Variance-covariance risk allocation nalytical approximation
2010/11/1
High precision analytical approximation is proposed for variance-covariance based risk allocation in a portfolio of risky assets. A general case of a single-period multi-factor Merton-type model with ...
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...