Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/3924
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dc.contributor.authorLux, Thomasen_US
dc.contributor.authorKaizoji, Taiseien_US
dc.date.accessioned2009-01-28T14:15:10Z-
dc.date.available2009-01-28T14:15:10Z-
dc.date.issued2006en_US
dc.identifier.urihttp://hdl.handle.net/10419/3924-
dc.description.abstractWe investigate the predictability of both volatility and volume for a large sample ofJapanese stocks. The particular emphasis of this paper is on assessing the performance of longmemory time series models in comparison to their short-memory counterparts. Since long memorymodels should have a particular advantage over long forecasting horizons, we consider predictions ofup to 100 days ahead. In most respects, the long memory models (ARFIMA, FIGARCH and therecently introduced multifractal model) dominate over GARCH and ARMA models. However, whileFIGARCH and ARFIMA also have quite a number of cases with dramatic failures of their forecasts,the multifractal model does not suffer from this shortcoming and its performance practically alwaysimproves upon the na?ve forecast provided by historical volatility. As a somewhat surprising result, wealso find that, for FIGARCH and ARFIMA models, pooled estimates (i.e. averages of parameterestimates from a sample of time series) give much better results than individually estimated models.en_US
dc.language.isoengen_US
dc.publisher|aInstitut für Volkswirtschaftslehre, Kiel-
dc.relation.ispartofseries|aEconomics Working Paper / Christian-Albrechts-Universität Kiel, Department of Economics |x2006,13en_US
dc.subject.jelC53en_US
dc.subject.jelG12en_US
dc.subject.jelC22en_US
dc.subject.ddc330-
dc.subject.keywordForecastingen_US
dc.subject.keywordLong memory models-
dc.subject.keywordVolume-
dc.subject.keywordVolatility-
dc.subject.stwBörsenkursen_US
dc.subject.stwVolatilitäten_US
dc.subject.stwBörsenumsatzen_US
dc.subject.stwPrognoseverfahrenen_US
dc.subject.stwZeitreihenanalyseen_US
dc.subject.stwSchätzungen_US
dc.subject.stwAktienmarkten_US
dc.subject.stwJapanen_US
dc.titleForecasting volatility and volume in the Tokyo stock market: Long memory, fractality and regime switchingen_US
dc.typeWorking Paperen_US
dc.identifier.ppn520839978en_US
dc.rightshttp://www.econstor.eu/dspace/Nutzungsbedingungen-
dc.identifier.repecRePEc:zbw:cauewp:5160-

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