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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
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A dynamic multivariate heavy-tailed model for time-varying volatilities and correlations
Creal, Drew; Koopman, Siem Jan; Lucas, André - 2010
the weighting of lagged squared innovations for the estimation of future correlations and volatilities. When we account … representation as a time-varying heavy-tailed copula which is particularly useful if the interest focuses on dependence structures …
Persistent link: https://www.econbiz.de/10011380135
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Forecasting volatility with Copula-based time series models
Sokolinskiy, Oleg; Dijk, Dick van - 2011
Persistent link: https://www.econbiz.de/10009720755
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Mixed density based copula likelihood
Azam, Kazim; Lucas, André - 2015 - This version: January 7, 2015
methods in the literature, we use maximum likelihood estimation based on closed-form copula functions. We show with a …We consider a new copula method for mixed marginals of discrete and continuous random variables. Unlike the Bayesian … using data from the 2013 Household Finance Survey, we show how the copula dependence between income (continuous) and …
Persistent link: https://www.econbiz.de/10010464789
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Nonstationarity in GARCH models : a Bayesian analysis
Kleibergen, Frank; Dijk, Herman K. van - 1993
Persistent link: https://www.econbiz.de/10000122477
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Idiosyncratic labour income risk and aggregate consumption : an unobserved component approach
Pozzi, Lorenzo - 2007
We investigate the importance of aggregate and consumer-specific or idiosyncratic labour income risk for aggregate consumption changes in the US over the period 1952-2001. Theoretically, the effect of labour income risk on consumption changes is decomposed into an aggregate and into an...
Persistent link: https://www.econbiz.de/10011372981
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Modeling and forecasting S&P 500 volatility : long memory, structural breaks and nonlinearity
Martens, Martin; Dijk, Dick van; Pooter, Michiel de - 2004
The sum of squared intraday returns provides an unbiased and almost error-free measure of ex-post volatility. In this paper we develop a nonlinear Autoregressive Fractionally Integrated Moving Average (ARFIMA) model for realized volatility, which accommodates level shifts, day-of-the-week...
Persistent link: https://www.econbiz.de/10011335205
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Realized Wishart-GARCH : a score-driven multi-Asset volatility model
Hansen, Peter Reinhard; Janus, Paweł; Koopman, Siem Jan - 2016
the variance matrix. Monte Carlo evidence for parameter estimation based on different small sample sizes is provided. We …
Persistent link: https://www.econbiz.de/10011520881
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Common and idiosyncratic conditional volatility factors : theory and empirical evidence
Blasques, Francisco; D'Innocenzo, Enzo; Koopman, Siem Jan - 2021 - This version: June 21, 2021
dimensionality. The relatively simple structure of the model leads to simple computations for the estimation of parameters and signal …
Persistent link: https://www.econbiz.de/10012591559
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In-sample bounds for time-varying parameters of observation driven models
Blasques, Francisco; Koopman, Siem Jan; Łasak, Katarzyna; … - 2015
. They are applicable to the complete class of observation driven models and are valid for a wide range of estimation …
Persistent link: https://www.econbiz.de/10010484891