Skip to main navigation
Skip to search
Skip to main content
EdUHK Research Repository Home
About the Repository
Home
Researchers
Research Units
Projects
Research Outputs
Prizes and Awards
KT Activities
Search by expertise, name or affiliation
A new Pearson-Type QMLE for conditionally heteroscedastic models
Ke ZHU,
Wai Keung LI
Department of Mathematics and Information Technology (MIT)
Research output
:
Contribution to journal
›
Articles
›
peer-review
16
Citations (Scopus)
Overview
Fingerprint
Fingerprint
Dive into the research topics of 'A new Pearson-Type QMLE for conditionally heteroscedastic models'. Together they form a unique fingerprint.
Sort by
Weight
Alphabetically
Mathematics
Heteroscedastic Model
90%
Quasi-maximum Likelihood
89%
Maximum Likelihood Estimator
59%
Innovation
28%
Stock Index
20%
Major Index
19%
Exchange rate
18%
GARCH
17%
Moment Conditions
15%
Strong Consistency
15%
Asymptotic Normality
12%
Simulation Study
9%
Estimator
8%
Performance
7%
Model
4%
Business & Economics
Quasi-maximum Likelihood Estimator
100%
Strong Consistency
21%
Innovation
20%
Exchange Rates
19%
Moment Conditions
18%
Asymptotic Normality
17%
Stationarity
14%
GARCH
13%
Stock Index
13%
Simulation Study
12%
Estimator
10%
Performance
5%
Social Sciences
innovation
43%
normality
39%
simulation
26%
performance
15%