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Level-slope-curvature : fact or artefact?
Lord, Roger; Pelsser, Antoon André Jean - 2005
conditions have the nice interpretation of restricting the level, slope and curvature of the correlation surface. It is proven … that the Schoenmakers-Coffey correlation matrix also brings along such factors. Finally, we formulate and corroborate our … conjecture that the order present in correlation matrices causes slope. …
Persistent link: https://www.econbiz.de/10011346478
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Tail heterogeneity for dynamic covariance-matrix-valued random variables : the F-Riesz distribution
Blasques, Francisco; Lucas, André; Opschoor, Anne; … - 2021
We introduce the new F-Riesz distribution to model tail-heterogeneity in fat-tailed covariance matrix observations. In contrast to the typical matrix-valued distributions from the econometric literature, the F-Riesz distribution allows for di↵erent tail behavior across all variables in the...
Persistent link: https://www.econbiz.de/10012421038
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Spillover dynamics for systemic risk measurement using spatial financial time series models
Blasques, Francisco; Koopman, Siem Jan; Lucas, André; … - 2014
We introduce a new model for time-varying spatial dependence. The model extends the well-known static spatial lag model. All parameters can be estimated conveniently by maximum likelihood. We establish the theoretical properties of the model and show that the maximum likelihood estimator for the...
Persistent link: https://www.econbiz.de/10010391531
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Spillover dynamics for systemic risk measurement using spatial financial time series models : conference paper
Blasques, Francisco; Koopman, Siem Jan; Lucas, André; … - 2014
A new model for time-varying spatial dependencies is introduced. It forms an extension to the popular spatial lag model and can be estimated conveniently by maximum likelihood. The spatial dependence parameter is assumed to follow a generalized autoregressive score (GAS) process. The theoretical...
Persistent link: https://www.econbiz.de/10010491085
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Tail distribution of the maximum of correlated Gaussian random variables
Botev, Zdravko I.; Mandjes, Michel; Ridder, Ad - 2015
In this article we consider the efficient estimation of the tail distribution of the maximum of correlated normal random variables. We show that the currently recommended Monte Carlo estimator has difficulties in quantifying its precision, because its sample variance estimator is an inefficient...
Persistent link: https://www.econbiz.de/10011431354
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Realized Wishart-GARCH : a score-driven multi-Asset volatility model
Hansen, Peter Reinhard; Janus, Paweł; Koopman, Siem Jan - 2016
We propose a novel multivariate GARCH model that incorporates realized measures for the variance matrix of returns. The key novelty is the joint formulation of a multivariate dynamic model for outer-products of returns, realized variances and realized covariances. The updating of the variance...
Persistent link: https://www.econbiz.de/10011520881
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Realized matrix-exponential stochastic volatility with asymmetry, long memory and spillovers
Asai, Manabu; Chang, Chia-Lin; McAleer, Michael - 2016
The paper develops a novel realized matrix-exponential stochastic volatility model of multivariate returns and realized covariances that incorporates asymmetry and long memory (hereafter the RMESV-ALM model). The matrix exponential transformation guarantees the positivedefiniteness of the...
Persistent link: https://www.econbiz.de/10011536626
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The comovement between real activity and prices in the G7
Den Haan, Wouter J. - 2002
robust across countries and time periods. Typically, the correlation coefficients at long-run horizons are significantly … negative and the correlation coefficients at short-run horizons are substantially higher. Additionally, there is evidence of … positive correlation at short-run forecast horizons for some countries. …
Persistent link: https://www.econbiz.de/10011327530
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Detecting serial dependence in tail events
Diks, Cees G. H. - 2002
A test for serial independence is proposed which is related to the BDS test but focuses on tail event probabilities rather than probabilities near the center of the distribution. The motivation behind this approach is to obtain a test more suitable for detecting structure in the tails, such as...
Persistent link: https://www.econbiz.de/10011327543
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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