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Working paper

Fitting vast dimensional time-varying covariance models.

Abstract:

Building models for high dimensional portfolios is important in risk management and asset allocation. Here we propose a novel and fast way of estimating models of time-varying covariances that overcome an undiagnosed incidental parameter problem which has troubled existing methods when applied to hundreds or even thousands of assets. Indeed we can handle the case where the cross-sectional dimension is larger than the time series one. The theory of this new strategy is developed in some detail...

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Publisher:
Oxford-Man Institute of Quantitative Finance
Series:
Working Papers
Publication date:
2008-09-24
Language:
English
UUID:
uuid:85565326-c877-42ae-9b20-a2a3b35b03b1
Local pid:
oai:economics.ouls.ox.ac.uk:12175
Deposit date:
2011-08-15

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