Continuous record asymptotics for rolling sample variance estimators.
It is widely known that conditional covariances of asset returns change over time. Researchers doing empirical work have adopted many strategies for accommodating conditional heteroskedasticity. Among the popular strategies are: (a) chopping the available data into short blocks of time and assumi...
| Publicado en: | Econometrica Vol. 64; pp. 139 - 175 |
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| Autores principales: | , |
| Formato: | Artículo |
| Publicado: |
Wiley-Blackwell
January 1996
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=512728081&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 512728081 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 00129682 ECN jtl: Econometrica issn: 00129682 maglogo: N pubinfo: dt: January 1996 vid: 64 pid: 480 pub: Wiley-Blackwell artinfo: ui: 512728081 10.2307/2171927 ppf: 139 ppct: 36 formats: tig: atl: Continuous record asymptotics for rolling sample variance estimators. aug: au: Foster, Dean P. Nelson, Daniel B. su: Stochastic processes Statistical sampling Regression analysis Estimation theory Variances Stock price indexes Mathematical models Rate of return on stocks sug: subj: Stochastic processes Statistical sampling Regression analysis Estimation theory Variances Stock price indexes Mathematical models Rate of return on stocks ab: It is widely known that conditional covariances of asset returns change over time. Researchers doing empirical work have adopted many strategies for accommodating conditional heteroskedasticity. Among the popular strategies are: (a) chopping the available data into short blocks of time and assuming homoskedasticity within the blocks, (b) performing one-sided rolling regressions, in which only data from, say, the preceding five year period is used to estimate the conditional covariance of returns at a given date, and (c) performing two-sided rolling regressions, in which covariances are estimated for each date using, say, five years of lags and five years of leads. Another model—GARCH—amounts to a one-sided weighted rolling regression. We develop continuous record asymptotic approximations for the measurement error in conditional variances and covariances when using these methods. We derive asymptotically optimal window lengths for standard rolling regressions and optimal weights for weighted rolling regressions. As an empirical example, we estimate volatility on the S&P 500 stock index using daily data from 1928 to 1990. Reprinted by permission of the Econometric Society. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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