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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
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...
Persistent link: https://www.econbiz.de/10011065005
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...
Persistent link: https://www.econbiz.de/10011039768
We consider sample covariance matrices constructed from real or complex i.i.d. variates with finite 12th moment. We assume that the population covariance matrix is positive definite and its spectral measure almost surely converges to some limiting probability distribution as the number of...
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