Full metadata record
DC Field | Value | Language |
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dc.contributor.author | Deo, Rohit S. | - |
dc.contributor.author | Hurvich, C. M. | - |
dc.date.accessioned | 2006-06-22T18:01:08Z | - |
dc.date.available | 2006-06-22T18:01:08Z | - |
dc.date.issued | 2000 | - |
dc.identifier.uri | http://hdl.handle.net/2451/14797 | - |
dc.description.abstract | We discuss some of the issues pertaining to modelling and estimating long memory in volatility. The main focus is on semi parametric estimation of the memory parameter in the long memory stochastic volatility model. We present the asymptotic properties of the log periodogram regression estimator of the memory parameter in this model. A modest simulation study of the estimator is also presented to study its behaviour when the volatility possesses only short memory. We conclude with a discussion of the appropriate choice of transformation of returns to measure persistence in volatility. | en |
dc.format.extent | 1263095 bytes | - |
dc.format.mimetype | application/pdf | - |
dc.language | English | EN |
dc.language.iso | en | |
dc.publisher | Stern School of Business, New York University | en |
dc.relation.ispartofseries | SOR-2000-14 | en |
dc.title | Estimation of Long Memory in Volatility | en |
dc.type | Working Paper | en |
dc.description.series | Statistics Working Papers Series | EN |
Appears in Collections: | IOMS: Statistics Working Papers |
Files in This Item:
File | Description | Size | Format | |
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SOR-2000-14.pdf | 1.23 MB | Adobe PDF | View/Open |
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