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Erschienen in: Financial Markets and Portfolio Management 1/2015

01.02.2015

Covariance averaging for improved estimation and portfolio allocation

verfasst von: Fotis Papailias, Dimitrios D. Thomakos

Erschienen in: Financial Markets and Portfolio Management | Ausgabe 1/2015

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Abstract

We propose a new method for estimating the covariance matrix of a multivariate time series of financial returns. The method is based on estimating sample covariances from overlapping windows of observations which are then appropriately weighted to obtain the final covariance estimate. We extend the idea of (model) covariance averaging offered in the covariance shrinkage approach by means of greater ease of use, flexibility and robustness in averaging information over different data segments. The suggested approach does not suffer from the curse of dimensionality and can be used without problems of either approximation or any demand for numerical optimization.

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Fußnoten
1
Note that the \(\displaystyle \widehat{\alpha }_{1}\) estimate of the smoothing parameter is, by construction, less than 1 and positive.
 
2
This is the average cost that one of the major online brokerage houses charges the individual investor.
 
3
We perform a standard estimation and test for zero mean differences using a GMM-based approach and standard errors. Details of the calculations and many other statistics beyond those presented are available on request.
 
4
The maximum drawdown is defined as the largest peak-to-trough drop in the portfolio value during the underlying evaluation period.
 
5
Counting the number of times that a table entry is greater than 50 %.
 
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Metadaten
Titel
Covariance averaging for improved estimation and portfolio allocation
verfasst von
Fotis Papailias
Dimitrios D. Thomakos
Publikationsdatum
01.02.2015
Verlag
Springer US
Erschienen in
Financial Markets and Portfolio Management / Ausgabe 1/2015
Print ISSN: 1934-4554
Elektronische ISSN: 2373-8529
DOI
https://doi.org/10.1007/s11408-014-0242-0

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