The SIML estimation of realized volatility of the Nikkei-225 Futures and hedging coefficient with micro-market noise

For the estimation problem of the realized volatility and hedging coefficient by using high-frequency data with possibly micro-market noise, we use the Separating Information Maximum Likelihood (SIML) method, which was recently developed by Kunitomo and Sato [11–13]. By analyzing the Nikkei-225 Futu...

Full description

Saved in:
Bibliographic Details
Published in:Mathematics and computers in simulation 2011-03, Vol.81 (7), p.1272-1289
Main Authors: Kunitomo, Naoto, Sato, Seisho
Format: Article
Language:English
Subjects:
High-frequency data
Micro-market noise
Nikkei-225 Futures
Realized volatility
Separating Information Maximum Likelihood estimation
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:For the estimation problem of the realized volatility and hedging coefficient by using high-frequency data with possibly micro-market noise, we use the Separating Information Maximum Likelihood (SIML) method, which was recently developed by Kunitomo and Sato [11–13]. By analyzing the Nikkei-225 Futures data, we found that the estimates of realized volatility and the hedging coefficients have significant bias by using the traditional historical method which should be corrected. The SIML method can handle the bias problem in the estimation by removing the possible micro-market noise in multivariate high-frequency data. We show that the SIML method has the asymptotic robustness under non-Gaussian cases even when the market noises are autocorrelated and endogenous with the efficient market price or the signal term.
ISSN:0378-4754
1872-7166
DOI:10.1016/j.matcom.2010.08.003