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Field name	Details
Dewey Class	519.5
Title	Separating Information Maximum Likelihood Method for High-Frequency Financial Data ([EBook]) / by Naoto Kunitomo, Seisho Sato, Daisuke Kurisu.
Author	Kunitomo, Naoto
Added Personal Name	Sato, Seisho author.
Added Personal Name	Kurisu, Daisuke author.
Other name(s)	SpringerLink (Online service)
Publication	Tokyo : : Springer Japan : : Imprint: Springer, , 2018.
Physical Details	VIII, 114 p. 8 illus. : online resource.
Series	SpringerBriefs in Statistics 2191-544X
ISBN	9784431559306
Summary Note	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.:
Contents note	1. Introduction -- 2. High-Frequency Financial Data and Statistical Problems -- 3. The SIML method -- 4. Asymptotic Properties -- 5. Simulation and Finite Sample Properties -- 6. Asymptotic Robustness -- 7. Two Dimension Applications -- 8. Concluding Remarks -- 9. References.
System details note	Online access to this digital book is restricted to subscription institutions through IP address (only for SISSA internal users)
Internet Site	http://dx.doi.org/10.1007/978-4-431-55930-6
Links to Related Works	Subject References: Statistical Theory and Methods . Statistics . Statistics and Computing/Statistics Programs . Statistics for Business/Economics/Mathematical Finance/Insurance . Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences . Authors: Kunitomo, Naoto . Kurisu, Daisuke . Sato, Seisho . Corporate Authors: SpringerLink (Online service) . Series: SpringerBriefs in Statistics . Classification: 519.5 .

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Separating Information Maximum Likelihood Method for High-Frequency Financial Data

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