Separating Information Maximum Likelihood Method for High-Frequency Financial Data

✍ Scribed by Naoto Kunitomo, Seisho Sato, Daisuke Kurisu

• Publisher: Springer Japan
• Year: 2018
• Tongue: English
• Leaves: 118
• Series: SpringerBriefs in Statistics
• Edition: 1st ed.
• Category: Library

✦ 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.

✦ Table of Contents

Front Matter ....Pages i-viii
Introduction (Naoto Kunitomo, Seisho Sato, Daisuke Kurisu)....Pages 1-3
Continuous-Time Models and Discrete Observations for Financial Data (Naoto Kunitomo, Seisho Sato, Daisuke Kurisu)....Pages 5-15
The SIML Estimation of Volatility and Covariance with Micro-market Noise (Naoto Kunitomo, Seisho Sato, Daisuke Kurisu)....Pages 17-28
An Application to Nikkei-225 Futures and Some Simulation (Naoto Kunitomo, Seisho Sato, Daisuke Kurisu)....Pages 29-37
Mathematical Derivations (Naoto Kunitomo, Seisho Sato, Daisuke Kurisu)....Pages 39-58
Extensions and Robust Estimation (1) (Naoto Kunitomo, Seisho Sato, Daisuke Kurisu)....Pages 59-78
Extensions and Robust Estimation (2) (Naoto Kunitomo, Seisho Sato, Daisuke Kurisu)....Pages 79-96
Local SIML Estimation of Brownian Functionals (Naoto Kunitomo, Seisho Sato, Daisuke Kurisu)....Pages 97-101
Estimating Quadratic Variation Under Jumps and Micro-market Noise (Naoto Kunitomo, Seisho Sato, Daisuke Kurisu)....Pages 103-109
Concluding Remarks (Naoto Kunitomo, Seisho Sato, Daisuke Kurisu)....Pages 111-112
Back Matter ....Pages 113-114

✦ Subjects

Statistics; Statistical Theory and Methods; Statistics for Business/Economics/Mathematical Finance/Insurance; Statistics and Computing/Statistics Programs; Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences