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Long memory dynamics for multivariate dependence under heavy tails

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

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

Score driven exponentially weighted moving averages and value-at-risk forecasting

Lucas, André; Zhang, Xin - 2015

volatility of individual stock returns and exchange rate returns. …

Persistent link: https://www.econbiz.de/10011332948

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...

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

Intraday stochastic volatility in discrete price changes : the dynamic Skellam model

Koopman, Siem Jan; Lit, Rutger; Lucas, André - 2015

We introduce a dynamic Skellam model that measures stochastic volatility from high-frequency tick-by-tick discrete … series per day varies from 1000 to 10,000. Complexities in the intraday dynamics of volatility and in the frequency of trades … intraday volatility shows that the dynamic modified Skellam model provides accurate forecasts compared to alternative modeling …

Persistent link: https://www.econbiz.de/10011295740

Stationarity and ergodicity regions for score driven dynamic correlation models

Blasques, Francisco; Lucas, André; Silde, Erkki - 2013

Persistent link: https://www.econbiz.de/10010191374

Joint independent metropolis-hastings methods for nonlinear non-Gaussian state space models

Barra, Istvan; Hoogerheide, Lennart; Koopman, Siem Jan; … - 2013

Persistent link: https://www.econbiz.de/10010191411

The dynamic Skellam model with applications

Koopman, Siem Jan; Lit, Rutger; Lucas, André - 2014

We introduce a dynamic statistical model for Skellam distributed random variables. The Skellam distribution can be obtained by taking differences between two Poisson distributed random variables. We treat cases where observations are measured over time and where possible serial correlation is...

Persistent link: https://www.econbiz.de/10010253460

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

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

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

We propose a new class of observation-driven time-varying parameter models for dynamic volatilities and correlations to handle time series from heavy-tailed distributions. The model adopts generalized autoregressive score dynamics to obtain a time-varying covariance matrix of the multivariate...

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

Numerically accelerated importance sampling for nonlinear non-Gaussian state-space models

Koopman, Siem Jan; Lucas, André; Scharth, Marcel - In: Journal of business & economic statistics : JBES ; a … 33 (2015) 1, pp. 114-127

Persistent link: https://www.econbiz.de/10011389921

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