Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/186040
Authors: 
Grossmass, Lidan
Year of Publication: 
2014
Citation: 
[Journal:] Swiss Journal of Economics and Statistics [ISSN:] 2235-6282 [Volume:] 150 [Year:] 2014 [Issue:] 3 [Pages:] 191-226
Abstract: 
This paper argues that the inherent data problems make precise point identification of realized correlation difficult but identification bounds in the spirit of Manski (1995) can be derived. These identification bounds allow for a more robust approach to inference especially when the realized correlation is used for estimating other risk measures. We forecast the identification bounds using the HAR model of Corsi (2003) using data during the year of onset of the credit crisis and find that the bounds provide good predictive coverage of the realized correlation for both 1- and 10-step forecasts even in volatile periods.
Subjects: 
High frequency data
realized covariance
partial identification
Bounds
JEL: 
C14
C18
C58
G17
Persistent Identifier of the first edition: 
Creative Commons License: 
https://creativecommons.org/licenses/by/4.0/
Document Type: 
Article

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