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A dynamic multivariate heavy-tailed model for time-varying volatilities and correlations

Creal, Drew; Koopman, Siem Jan; Lucas, André - 2010

time-varying covariance matrix of the multivariate Student's t distribution. The key novelty of our proposed model concerns …

Persistent link: https://www.econbiz.de/10011380135

Long memory dynamics for multivariate dependence under heavy tails

Janus, Paweł; Koopman, Siem Jan; Lucas, André - 2011

Persistent link: https://www.econbiz.de/10009720703

Modeling dynamic volatilities and correlations under skewness and fat tails

Zhang, Xin; Creal, Drew; Koopman, Siem Jan; Lucas, André - 2011

We propose a new model for dynamic volatilities and correlations of skewed and heavy-tailed data. Our model endows the Generalized Hyperbolic distribution with time-varying parameters driven by the score of the observation density function. The key novelty in our approach is the fact that the...

Persistent link: https://www.econbiz.de/10011386468

Generalized autoregressive method of moments

Creal, Drew; Koopman, Siem Jan; Lucas, André; … - 2015

We introduce a new estimation framework which extends the Generalized Method of Moments (GMM) to settings where a subset of the parameters vary over time with unknown dynamics. To filter out the dynamic path of the time-varying parameter, we approximate the dynamics by an autoregressive process...

Persistent link: https://www.econbiz.de/10011431471

Fractional integration and fat tails for realized covariance kernels and returns

Lucas, André; Opschoor, Anne - 2016 - This version: September 1, 2016

We introduce a new fractionally integrated model for covariance matrix dynamics based on the long-memory behavior of … daily realized covariance matrix kernels and daily return observations. We account for fat tails in both types of data by … appropriate distributional assumptions. The covariance matrix dynamics are formulated as a numerically efficient matrix recursion …

Persistent link: https://www.econbiz.de/10011531139

Fractional integration and fat tails for realized covariance kernels

Opschoor, Anne; Lucas, André - In: Journal of financial econometrics 17 (2019) 1, pp. 66-90

Persistent link: https://www.econbiz.de/10012054426

Finite Sample Optimality of Score-Driven Volatility Models

Blasques, Francisco; Lucas, André; van Vlodrop, Andries - 2017

We study optimality properties in finite samples for time-varying volatility models driven by the score of the predictive likelihood function. Available optimality results for this class of models suffer from two drawbacks. First, they are only asymptotically valid when evaluated at the...

Persistent link: https://www.econbiz.de/10011819504

Finite sample optimality of score-driven volatility models

Blasques, Francisco; Lucas, André; Vlodrop, Andries van - 2017

Persistent link: https://www.econbiz.de/10011772958

A General Framework for Observation Driven Time-Varying Parameter Models

Creal, Drew; Koopman, Siem Jan; Lucas, André - 2008

unified and consistent framework for introducing time-varying parameters in a wide class of non-linear models. The GAS model … specification provides a wide range of new observation driven models. Examples include non-linear regression models with time …

Persistent link: https://www.econbiz.de/10010325732

A Dynamic Multivariate Heavy-Tailed Model for Time-Varying Volatilities and Correlations

Creal, Drew; Koopman, Siem Jan; Lucas, André - 2010

time-varying covariance matrix of the multivariate Student's t distribution. The key novelty of our proposed model concerns …

Persistent link: https://www.econbiz.de/10010325845

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