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A simple test for causality in volatility

Chang, Chia-Lin; McAleer, Michael - In: Econometrics 5 (2017) 1, pp. 1-5

An early development in testing for causality (technically, Granger non-causality) in the conditional variance (or volatility) associated with financial returns was the portmanteau statistic for non-causality in the variance of Cheng and Ng (1996). A subsequent development was the Lagrange...

Persistent link: https://www.econbiz.de/10011755368

A simple test for causality in volatility

Chang, Chia-Lin; McAleer, Michael - 2016

An early development in testing for causality (technically, Granger non-causality) in the conditional variance (or volatility) associated with financial returns, was the portmanteau statistic for non-causality in variance of Cheng and Ng (1996). A subsequent development was the Lagrange...

Persistent link: https://www.econbiz.de/10011556246

The fiction of Full BEKK

Chang, Chia-Lin; McAleer, Michael - 2017

The purpose of the paper is to show that univariate GARCH is not a special case of multivariate GARCH, specifically the Full BEKK model, except under parametric restrictions on the off-diagonal elements of the random coefficient autoregressive coefficient matrix, provides the regularity...

Persistent link: https://www.econbiz.de/10011587639

Modeling and estimation of synchronization in multistate Markov-switching models

Çakmaklı, Cem; Paap, Richard; Dijk, Dick van - 2010

This paper develops a Markov-Switching vector autoregressive model that allows for imperfect synchronization of cyclical regimes in multiple variables, due to phase shifts of a single common cycle. The model has three key features: (i) the amount of phase shift can be different across regimes...

Persistent link: https://www.econbiz.de/10011382676

Measuring and predicting heterogeneous recessions

Çakmaklı, Cem; Paap, Richard; Dijk, Dick van - 2011

Persistent link: https://www.econbiz.de/10009720726

Profiteering from the dot-com bubble, sub-prime crisis and Asian financial crisis

McAleer, Michael; Suen, John; Wong, Wing Keung - 2013

Persistent link: https://www.econbiz.de/10009767005

Asymmetry and leverage in conditional volatility models

McAleer, Michael - In: Econometrics 2 (2014) 3, pp. 145-150

The three most popular univariate conditional volatility models are the generalized autoregressive conditional heteroskedasticity (GARCH) model of Engle (1982) and Bollerslev (1986), the GJR (or threshold GARCH) model of Glosten, Jagannathan and Runkle (1992), and the exponential GARCH (or...

Persistent link: https://www.econbiz.de/10010421299

A one line derivation of EGARCH

McAleer, Michael; Hafner, Christian M. - In: Econometrics 2 (2014) 2, pp. 92-97

parameters are not available under general conditions, but rather only for special cases under highly restrictive and … unverifiable conditions. It is often argued heuristically that the reason for the lack of general statistical properties arises … (2) the reason for the lack of statistical properties of the estimators of EGARCH under general conditions is that the …

Persistent link: https://www.econbiz.de/10010421302

A multivariate asymmetric long memory conditional volatility model with X, regularity and asymptotics

Asai, Manabu; McAleer, Michael - 2016

The paper derives a Multivariate Asymmetric Long Memory conditional volatility model with Exogenous Variables (X), or the MALMX model, with dynamic conditional correlations, appropriate regularity conditions, and associated asymptotic theory. This enables checking of internal consistency and...

Persistent link: https://www.econbiz.de/10011531101

The correct regularity condition and interpretation of asymmetry in EGARCH

Chang, Chia-Lin; McAleer, Michael - 2017

In the class of univariate conditional volatility models, the three most popular are the generalized autoregressive conditional heteroskedasticity (GARCH) model of Engle (1982) and Bollerslev (1986), the GJR (or threshold GARCH) model of Glosten, Jagannathan and Runkle (1992), and the...

Persistent link: https://www.econbiz.de/10011688332