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A new Pearson-Type QMLE for conditionally heteroscedastic models
Ke ZHU,
Wai Keung LI
Department of Mathematics and Information Technology (MIT)
Research output
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Contribution to journal
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Articles
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peer-review
16
Citations (Scopus)
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Dive into the research topics of 'A new Pearson-Type QMLE for conditionally heteroscedastic models'. Together they form a unique fingerprint.
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Keyphrases
Quasi-maximum Likelihood Estimation
100%
Heteroscedastic Model
100%
Copyright
16%
Simulation Study
16%
Laplacian
16%
Exchange Rate
16%
Stock Index
16%
American Statistical Association
16%
Generalized Autoregressive Conditional Heteroscedasticity (GARCH)
16%
Strict Stationarity
16%
Strong Consistency
16%
LAD Estimator
16%
Weak Moment Condition
16%
Non-Gaussian
16%
Strong Asymptotics
16%
Asymptotic Normality
16%
Mathematics
Maximum Likelihood Estimator
100%
Gaussian Distribution
33%
Simulation Study
16%
Laplace Operator
16%
Strict Stationarity
16%
Asymptotic Normality
16%
Moment Condition
16%