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variability. By doing so, we introduce bias, but reduce variance. In this paper, we give details on feasible optimal shrinkage …
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Shrinkage estimation of the covariance matrix of asset returns was introduced to the finance profession several years … paper presents, from a pedagogic perspective, an introduction to shrinkage estimation and uses Microsoft ExcelTM for its …
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stock data are used to demonstrate the relative robustness of BFGMRES to illiquidity when compared to the “shrinkage to … ratios and standard deviations for filtered data. In a simulation study, we show that BFGMRES is more robust than shrinkage … to market in the presence of data irregularities. Indeed, when there is an illiquid stock shrinkage to market allocates …
Persistent link: https://www.econbiz.de/10011051937
Let X=[Xij]p×n be a p×n random matrix whose entries are i.i.d real random variables satisfying the moment condition EX114∞. Let T be a p×p deterministic nonnegative definite matrix. It is assumed that the empirical distribution of the eigenvalues of T converges weakly to a probability...
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We study the joint limit distribution of the k largest eigenvalues of a p×p sample covariance matrix XXT based on a large p×n matrix X. The rows of X are given by independent copies of a linear process, Xit=∑jcjZi,t−j, with regularly varying noise (Zit) with tail index α∈(0,4). It is...
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