Separating Information Maximum Likelihood Method for High-Frequency Financial Data

• Κύριοι συγγραφείς: Kunitomo, Naoto (Συγγραφέας, 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)
• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Tokyo : Springer Japan : Imprint: Springer, 2018.
• Έκδοση: 1st ed. 2018.
• Σειρά: JSS Research Series in Statistics,
• Θέματα: 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...