DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kim, Donggyu | ko |
dc.date.accessioned | 2017-09-08T06:01:55Z | - |
dc.date.available | 2017-09-08T06:01:55Z | - |
dc.date.created | 2017-09-01 | - |
dc.date.created | 2017-09-01 | - |
dc.date.issued | 2016-07 | - |
dc.identifier.citation | JOURNAL OF TIME SERIES ANALYSIS, v.37, no.4, pp.513 - 532 | - |
dc.identifier.issn | 0143-9782 | - |
dc.identifier.uri | http://hdl.handle.net/10203/225855 | - |
dc.description.abstract | The existing estimation methods for the model parameters of the unified GARCH-Ito model (Kim and Wang, ) require long period observations to obtain the consistency. However, in practice, it is hard to believe that the structure of a stock price is stable during such a long period. In this article, we introduce an estimation method for the model parameters based on the high-frequency financial data with a finite observation period. In particular, we establish a quasi-likelihood function for daily integrated volatilities, and realized volatility estimators are adopted to estimate the integrated volatilities. The model parameters are estimated by maximizing the quasi-likelihood function. We establish asymptotic theories for the proposed estimator. A simulation study is conducted to check the finite sample performance of the proposed estimator. We apply the proposed estimation approach to the Bank of America stock price data. | - |
dc.language | English | - |
dc.publisher | WILEY | - |
dc.subject | MAXIMUM LIKELIHOOD ESTIMATION | - |
dc.subject | REALIZED VOLATILITY | - |
dc.subject | NOISE | - |
dc.title | Statistical Inference for Unified Garch-Ito Models with High-Frequency Financial Data | - |
dc.type | Article | - |
dc.identifier.wosid | 000378512700004 | - |
dc.identifier.scopusid | 2-s2.0-84978952218 | - |
dc.type.rims | ART | - |
dc.citation.volume | 37 | - |
dc.citation.issue | 4 | - |
dc.citation.beginningpage | 513 | - |
dc.citation.endingpage | 532 | - |
dc.citation.publicationname | JOURNAL OF TIME SERIES ANALYSIS | - |
dc.identifier.doi | 10.1111/jtsa.12171 | - |
dc.contributor.localauthor | Kim, Donggyu | - |
dc.description.isOpenAccess | N | - |
dc.type.journalArticle | Article | - |
dc.subject.keywordAuthor | GARCH | - |
dc.subject.keywordAuthor | high-frequency financial data | - |
dc.subject.keywordAuthor | low-frequency financial data | - |
dc.subject.keywordAuthor | Ito process | - |
dc.subject.keywordAuthor | quasi-maximum likelihood estimator | - |
dc.subject.keywordAuthor | realized volatility | - |
dc.subject.keywordPlus | MAXIMUM LIKELIHOOD ESTIMATION | - |
dc.subject.keywordPlus | REALIZED VOLATILITY | - |
dc.subject.keywordPlus | NOISE | - |
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