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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

Forecasting value-at-risk under temporal and portfolio aggregation

Kole, Erik; Markwat, Thijs; Opschoor, Anne; Dijk, Dick van - 2015

We examine the impact of temporal and portfolio aggregation on the quality of Value-at-Risk (VaR) forecasts over a horizon of ten trading days for a well-diversified portfolio of stocks, bonds and alternative investments. The VaR forecasts are constructed based on daily, weekly or biweekly...

Persistent link: https://www.econbiz.de/10011431503

Out-of-sample comparison of copula specifications in multivariate density forecasts

Diks, Cees G. H.; Panchenko, Valentyn; Dijk, Dick van - 2008

multivariate density forecasts, based on the Kullback-Leibler Information Criterion (KLIC). The test is valid under general …

Persistent link: https://www.econbiz.de/10011377261

Measuring and predicting heterogeneous recessions

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

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

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

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

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

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