Imperial College London
Alternate

Walter Distaso

Business School

Professor of Financial Econometrics
 
 
 
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Contact

 

+44 (0)20 7594 3293w.distaso Website

 
 
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Location

 

3.0253 Prince's GateSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Abadir:2014:10.1016/j.jeconom.2014.03.010,
author = {Abadir, KM and Distaso, W and ike, F},
doi = {10.1016/j.jeconom.2014.03.010},
journal = {Journal of Econometrics},
pages = {165--180},
title = {Design-free estimation of variance matrices},
url = {http://dx.doi.org/10.1016/j.jeconom.2014.03.010},
volume = {181},
year = {2014}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - This paper introduces a new method for estimating variance matrices. Starting from the orthogonal decomposition of the sample variance matrix, we exploit the fact that orthogonal matrices are never ill-conditioned and therefore focus on improving the estimation of the eigenvalues. We estimate the eigenvectors from just a fraction of the data, then use them to transform the data into approximately orthogonal series that deliver a well-conditioned estimator (by construction), even when there are fewer observations than dimensions. We also show that our estimator has lower error norms than the traditional one. Our estimator is design-free: we make no assumptions on the distribution of the random sample or on any parametric structure the variance matrix may have. Simulations confirm our theoretical results and they also show that our simple estimator does very well in comparison with other existing methods.
AU  - Abadir,KM
AU  - Distaso,W
AU  - ike,F
DO  - 10.1016/j.jeconom.2014.03.010
EP  - 180
PY  - 2014///
SN  - 1872-6895
SP  - 165
TI  - Design-free estimation of variance matrices
T2  - Journal of Econometrics
UR  - http://dx.doi.org/10.1016/j.jeconom.2014.03.010
UR  - http://hdl.handle.net/10044/1/26856
VL  - 181
ER  -
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