Quasi-maximum likelihood estimation of GARCH models in the presence of missing values

2018 ◽  
Vol 89 (2) ◽  
pp. 292-314
Author(s):  
Marcos H. Cascone ◽  
Luiz K. Hotta
Keyword(s):  
Maximum Likelihood ◽  
Maximum Likelihood Estimation ◽  
Missing Values ◽  
Likelihood Estimation ◽  
Garch Models ◽  
Quasi Maximum Likelihood

QUASI-MAXIMUM LIKELIHOOD ESTIMATION OF SEMI-STRONG GARCH MODELS

2009 ◽  
Vol 25 (2) ◽  
pp. 561-570 ◽  
Author(s):  
Juan Carlos Escanciano
Keyword(s):  
Maximum Likelihood ◽  
Maximum Likelihood Estimation ◽  
Likelihood Estimation ◽  
Garch Models ◽  
Martingale Difference ◽  
Likelihood Estimator ◽  
Conditional Mean ◽  
Mild Conditions ◽  
Consistency And Asymptotic Normality ◽  
Quasi Maximum Likelihood

This note proves the consistency and asymptotic normality of the quasi–maximum likelihood estimator (QMLE) of the parameters of a generalized autoregressive conditional heteroskedastic (GARCH) model with martingale difference centered squared innovations. The results are obtained under mild conditions and generalize and improve those in Lee and Hansen (1994,Econometric Theory10, 29–52) for the local QMLE in semistrong GARCH(1,1) models. In particular, no restrictions on the conditional mean are imposed. Our proofs closely follow those in Francq and Zakoïan (2004,Bernoulli10, 605–637) for independent and identically distributed innovations.

scholarly journals Identifying Stabilising Effects on Survey Based Life Satisfaction Using Quasi-maximum Likelihood Estimation

2021 ◽  
Author(s):  
Johannes Klement
Keyword(s):  
Life Satisfaction ◽  
Maximum Likelihood ◽  
Maximum Likelihood Estimation ◽  
Negative Binomial ◽  
Measurement Instrument ◽  
Likelihood Estimation ◽  
Satisfaction Scale ◽  
Quasi Maximum Likelihood ◽  
The Stability

AbstractTo which extent do happiness correlates contribute to the stability of life satisfaction? Which method is appropriate to provide a conclusive answer to this question? Based on life satisfaction data of the German SOEP, we show that by Negative Binomial quasi-maximum likelihood estimation statements can be made as to how far correlates of happiness contribute to the stabilisation of life satisfaction. The results show that happiness correlates which are generally associated with a positive change in life satisfaction, also stabilise life satisfaction and destabilise dissatisfaction with life. In such as they lower the probability of leaving positive states of life satisfaction and increase the probability of leaving dissatisfied states. This in particular applies to regular exercise, volunteering and living in a marriage. We further conclude that both patterns in response behaviour and the quality of the measurement instrument, the life satisfaction scale, have a significant effect on the variation and stability of reported life satisfaction.

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