A New Class of Multivariate Skew Densities, With Application to Generalized Autoregressive Conditional Heteroscedasticity Models

By Luc Bauwens, Sébastien-Yves Laurent. 2005

280 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/845672a842b3c95ea9bda9420cf76bd9c5559bd9

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Citations in the corpus

Beta-t-(E)GARCH (2008, background): “7 Asymmetric t The t -distribution with a location (median) of zero and scale of exp( =2) has pdf as in Laurent (2007, p31) or Bauwens and Laurent (2005): For known degrees of freedom and skewness, , the kernel of the log-likelihood function at time t is”
Gold, Oil, and Stocks: Dynamic Correlations (2016, unknown): “…wavelet decomposition usually provides a broader picturewhen compared to the time domain approach that in fact aggregates all investment is respect, Bauwens and Laurent (2005) show that both the one-step and two-step methods provide very similar estimates. literature is well surveyed by Hansen and…”
Estimation and Forecasting of Dynamic Conditional Covariance: A Semiparametric Multivariate Model (2009, methodology): “Apart from adopting the quantiles of standard normal distribution, Bauwens and Laurent (2005) used a Monte Carlo simulation and HDF (2006) employed the quantiles of the standardized portfolio returns.”
Multivariate stochastic volatility (2009, background): “Other multivariate skew densities have also been proposed, for example, in Arellano-Valle and Azzalini (2006), Bauwens and Laurent (2005) , Dey and Liu (2005) Azzalini (2005), Gupta et al. (2004) and Ferreira and Steel (2004).”
Modelling Volatilities and Conditional Correlations in Futures Markets with a Multivariate t Distribution (2007, background): “In the case of some asset returns, particularly in the cash markets, it might also be important to consider using multivariate asymmetric distributions, such as the multivariate skew-Student density recently proposed by Bauwens and Laurent (2005).”
Skewed distributions in finance and actuarial science: a review (2015, background): “Other papers concerned with skewness in the context of times series include well-known works by Bauwens and Laurent (2005) and Jondeau and Rockinger (2003, 2006b, 2012).”
A Dynamic Multivariate Heavy-Tailed Model for Time-Varying Volatilities and Correlations (2011, methodology): “The same test for evaluating forecast performance was used in a similar context by Bauwens and Laurent (2005) and Chib, Nardari, and Shephard (2006).”
Comparison of semiparametric and parametric methods for estimating copulas (2007, background): “A skew t-distribution (df = , skewness = 0.5) has tails that are of the same order as that for t but the probability masses on either sides of the origin are different, leading to skewness (for example, see Bauwens and Laurent, 2005).”
Forecasting risk with Markov-switching GARCH models:A large-scale performance study (2018, methodology): “GARCH; see, for instance, Bernardi and Catania (2016) and Ardia et al.”
Multivariate Location-Scale Mixtures of Normals and Mean-Variance-Skewness Portfolio Allocation (2009, background): “…root”matrix is not irrelevant except in univariate models, or in multivariate models in which either Σt(θ) is time-invariant or ε ∗ t is spherical (i.e. β = 0), a fact that previous efforts to model multivariate skewness in dynamic models have overlooked (see e.g. Bauwens and Laurent, 2005).”
Lambert W random variables—a new family of generalized skewed distributions with applications to risk estimation (2009, unknown): “Typically, εt ∼N (0,1), but also student tor skew t-distributions are used for more flexibility in the conditional distribution of εt given the information set Ωt−1 available at time t− 1 [Bauwens and Laurent (2005)]. French, Schwert and Stambaugh (1987) also found that”
Distributional Tests in Multivariate Dynamic Models with Normal and Student-t Innovations (2009, methodology): “Our choice also differs from Bauwens and Laurent (2005), who introduce skewness by stretching the multivariate Student-t distribution differently in different orthants.”
Conditional Euro Area Sovereign Default Risk (2014, unknown): “Alternative skewed t distributions have been proposed as well, such as Branco and Dey (2001), Gupta (2003), Azzalini and Capitanio (2003), and Bauwens and Laurent (2005); see also the overview of Aas and Haff (2006).”