عنوان

Separating information maximum likelihood method for high-frequency financial data /

(Number (ISBN

4431559280

(Number (ISBN

4431559299

(Number (ISBN

4431559302

(Number (ISBN

9784431559283

(Number (ISBN

9784431559290

(Number (ISBN

9784431559306

Erroneous ISBN

9784431559283

Title Proper

Separating information maximum likelihood method for high-frequency financial data /

General Material Designation

[Book]

First Statement of Responsibility

Naoto Kunitomo, Seisho Sato, Daisuke Kurisu.

Place of Publication, Distribution, etc.

Tokyo :

Name of Publisher, Distributor, etc.

Springer,

Date of Publication, Distribution, etc.

2018.

Specific Material Designation and Extent of Item

1 online resource

Series Title

SpringerBriefs in Statistics,

ISSN of Series

2191-544X

Text of 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.

0

Text of 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.

Source for Acquisition/Subscription Address

Springer Nature

Stock Number

com.springer.onix.9784431559306

International Standard Book Number

9784431559283

Commercial statistics.

Stochastic processes.

Commercial statistics.

MATHEMATICS-- Applied.

MATHEMATICS-- Probability & Statistics-- General.

Stochastic processes.

MAT-- 003000

MAT-- 029000

PBT

PBT

Number

Edition

Class number

Kunitomo, Naoto

Kurisu, Daisuke

Sato, Seisho

Date of Transaction

20200823200109.0

Cataloguing Rules (Descriptive Conventions))

pn

Electronic name

[Book]

Y