Separating Information Maximum Likelihood Method for High-Frequency Financial Data

• Main Authors: Kunitomo, Naoto (Author, http://id.loc.gov/vocabulary/relators/aut), Sato, Seisho (http://id.loc.gov/vocabulary/relators/aut), Kurisu, Daisuke (http://id.loc.gov/vocabulary/relators/aut)
• Corporate Author: SpringerLink (Online service)
• Format: Electronic eBook
• Language: English
• Published: Tokyo : Springer Japan : Imprint: Springer, 2018.
• Edition: 1st ed. 2018.
• Series: JSS Research Series in Statistics,
• Subjects: Statistics .; Statistical Theory and Methods.; Statistics for Business, Management, Economics, Finance, Insurance.; Statistics and Computing/Statistics Programs.; Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences.

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. Althoug...