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Decomposing Portfolio Value-at-Risk: A General Analysis
Hallerbach, Winfried G. - Tinbergen Institute - 1999
distribution specifications or historical and Monte Carlo simulation methods. Although these approaches to overall VaR estimation …, component VaR and incremental VaR readily follow. The proposed estimation approach pairs intuitive appeal with computational … efficiency. We evaluate various alternative estimation methods in an application example and conclude that the proposed approach …
Persistent link: https://www.econbiz.de/10005144576
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Decomposing Portfolio Value-at-Risk: A General Analysis
Hallerbach, Winfried G. - Tinbergen Instituut - 1999
orhistorical and Monte Carlo simulation methods. Although these approaches to overall VaR estimation have receivedsubstantial … proposed estimation approach pairs intuitiveappeal with computational efficiency. We evaluate various alternative estimation …
Persistent link: https://www.econbiz.de/10011256282
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A General Framework for Observation Driven Time-Varying Parameter Models
Creal, Drew; Koopman, Siem Jan; Lucas, André - Tinbergen Instituut - 2008
We propose a new class of observation driven time series models referred to as Generalized Autoregressive Score (GAS) models. The driving mechanism of the GAS model is the scaled score of the likelihood function. This approach provides a unified and consistent framework for introducing...
Persistent link: https://www.econbiz.de/10011255643
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A General Framework for Observation Driven Time-Varying Parameter Models
Creal, Drew; Koopman, Siem Jan; Lucas, André - Tinbergen Institute - 2008
We propose a new class of observation driven time series models referred to as Generalized Autoregressive Score (GAS) models. The driving mechanism of the GAS model is the scaled score of the likelihood function. This approach provides a unified and consistent framework for introducing...
Persistent link: https://www.econbiz.de/10005209514
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Econometric Analysis of Financial Derivatives: An Overview
Chang, Chia-Lin; McAleer, Michael - Tinbergen Instituut - 2014
, including market-based estimation of stochastic volatility models, the fine structure of equity-index option dynamics, leverage …
Persistent link: https://www.econbiz.de/10011256249
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Monte Carlo Maximum Likelihood Estimation for Generalized Long-Memory Time Series Models
Mesters, Geert; Koopman, Siem Jan; Ooms, Marius - Tinbergen Instituut - 2011
An exact maximum likelihood method is developed for the estimation of parameters in a non-Gaussian nonlinear log …
Persistent link: https://www.econbiz.de/10011261933
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Long Memory and Level Shifts: Re-Analyzing Inflation Rates
Bos, Charles S.; Franses, Philip Hans; Ooms, Marius - Tinbergen Institute - 1998
<p>A key application of long memory time series models concerns inflation. Long memory implies that shocks have a long-lasting effect. It may however be that empirical evidence for long memory is caused by neglecting one or more level shifts. Since such level shifts are not unlikely for inflation,...</p>
Persistent link: https://www.econbiz.de/10005209483
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Long Memory Modelling of Inflation with Stochastic Variance and Structural Breaks
Bos, C.S.; Koopman, S.J.; Ooms, M. - Tinbergen Institute - 2007
varying size. Based on the new modelling framework and the associated estimation technique, we find remarkable changes in the …
Persistent link: https://www.econbiz.de/10005209535
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Long Memory Dynamics for Multivariate Dependence under Heavy Tails
Janus, Pawel; Koopman, Siem Jan; Lucas, André - Tinbergen Institute - 2011
We develop a new simultaneous time series model for volatility and dependence with long memory (fractionally integrated) dynamics and heavy-tailed densities. Our new multivariate model accounts for typical empirical features in financial time series while being robust to outliers or jumps in the...
Persistent link: https://www.econbiz.de/10009386532
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Monte Carlo Maximum Likelihood Estimation for Generalized Long-Memory Time Series Models
Mesters, Geert; Koopman, Siem Jan; Ooms, Marius - Tinbergen Institute - 2011
An exact maximum likelihood method is developed for the estimation of parameters in a non-Gaussian nonlinear log …
Persistent link: https://www.econbiz.de/10009144743