Separating Information Maximum Likelihood Method for High-Frequency Financial Data - Couverture souple
Synopsis
This book presents a systematic explanation of the SIML (Separating Information Maximum Likelihood) method, a new approach to financial econometrics.
Considerable interest has been given to the estimation problem of integrated volatility and covariance by using high-frequency financial data. Although several new statistical estimation procedures have been proposed, each method has some desirable properties along with some shortcomings that call for improvement. For estimating integrated volatility, covariance, and the related statistics by using high-frequency financial data, the SIML method has been developed by Kunitomo and Sato to deal with possible micro-market noises.
The authors show that the SIML estimator has reasonable finite sample properties as well as asymptotic properties in the standard cases. It is also shown that the SIML estimator has robust properties in the sense that it is consistent and asymptotically normal in the stable convergence sense when there are micro-market noises, micro-market (non-linear) adjustments, and round-off errors with the underlying (continuous time) stochastic process. Simulation results are reported in a systematic way as are some applications of the SIML method to the Nikkei-225 index, derived from the major stock index in Japan and the Japanese financial sector.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
À propos de l?auteur
Naoto Kunitomo, Meiji University
Seisho Sato, The University of Tokyo Daisuke Kurisu, Tokyo Institute of TechnologyLes informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Separating Information Maximum Likelihood Method for High-Frequency Financial Data (eng)
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Separating Information Maximum Likelihood Method for High-Frequency Financial Data
Edité par
SPRINGER NATURE Jul 2018, 2018
ISBN 10 : 4431559280
ISBN 13 : 9784431559283
Neuf
Taschenbuch
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book presents a systematic explanation of the SIML (Separating Information Maximum Likelihood) method, a new approach to financial econometrics.Considerable interest has been given to the estimation problem of integrated volatility and covariance by using high-frequency financial data. Although several new statistical estimation procedures have been proposed, each method has some desirable properties along with some shortcomings that call for improvement. For estimating integrated volatility, covariance, and the related statistics by using high-frequency financial data, the SIML method has been developed by Kunitomo and Sato to deal with possible micro-market noises.The authors show that the SIML estimator has reasonable finite sample properties as well as asymptotic properties in the standard cases. It is also shown that the SIML estimator has robust properties in the sense that it is consistent and asymptotically normal in the stable convergence sense when there are micro-market noises, micro-market (non-linear) adjustments, and round-off errors with the underlying (continuous time) stochastic process. Simulation results are reported in a systematic way as are some applications of the SIML method to the Nikkei-225 index, derived from the major stock index in Japan and the Japanese financial sector. 114 pp. Englisch. N° de réf. du vendeur 9784431559283
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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Gives a systematic treatment of SIML (Separating Information Maximum Likelihood) method in financial econometricsDiscusses a robust estimation method for integrated volatility, covariance, and hedging coefficient by using high-frequency financial . N° de réf. du vendeur 84907772
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The Siml Estimation for High-frequency Financial Data With Micro-market Noise
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Paperback. Etat : Brand New. 124 pages. 9.25x6.10x0.32 inches. In Stock. N° de réf. du vendeur zk4431559280
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Separating Information Maximum Likelihood Method for High-Frequency Financial Data
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Taschenbuch. Etat : Neu. Separating Information Maximum Likelihood Method for High-Frequency Financial Data | Naoto Kunitomo (u. a.) | Taschenbuch | viii | Englisch | 2018 | Springer Japan | EAN 9784431559283 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. N° de réf. du vendeur 111092163
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Separating Information Maximum Likelihood Method for High-Frequency Financial Data
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
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Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - This book presents a systematic explanation of the SIML (Separating Information Maximum Likelihood) method, a new approach to financial econometrics.Considerable interest has been given to the estimation problem of integrated volatility and covariance by using high-frequency financial data. Although several new statistical estimation procedures have been proposed, each method has some desirable properties along with some shortcomings that call for improvement. For estimating integrated volatility, covariance, and the related statistics by using high-frequency financial data, the SIML method has been developed by Kunitomo and Sato to deal with possible micro-market noises.The authors show that the SIML estimator has reasonable finite sample properties as well as asymptotic properties in the standard cases. It is also shown that the SIML estimator has robust properties in the sense that it is consistent and asymptotically normal in the stable convergence sense when there are micro-market noises, micro-market (non-linear) adjustments, and round-off errors with the underlying (continuous time) stochastic process. Simulation results are reported in a systematic way as are some applications of the SIML method to the Nikkei-225 index, derived from the major stock index in Japan and the Japanese financial sector. N° de réf. du vendeur 9784431559283
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