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Modeling Dynamic Volatilities and Correlations under Skewness and Fat Tails

Zhang, Xin; Creal, Drew; Koopman, Siem Jan; Lucas, Andre - Tinbergen Instituut - 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/10011257612

Efficient Bayesian Estimation and Combination of GARCH-Type Models

Ardia, David; Hoogerheide, Lennart F. - Tinbergen Instituut - 2010

estimation strategies available for the Bayesian inference of GARCH-type models. The emphasis is put on a novel efficient …-nested GARCH-type models are estimated and combined to predict the distribution of next-day ahead log-returns. …

Persistent link: https://www.econbiz.de/10011255484

Adaptive Polar Sampling with an Application to a Bayes Measure of Value-at-Risk

Bauwens, Luc; Bos, Charles S.; Dijk, Herman K. van - Tinbergen Instituut - 1999

applied within a Bayesian analysisof a GARCH-mixture model which is used for the evaluation of theValue-at-Risk of the return …

Persistent link: https://www.econbiz.de/10011256462

Daily Exchange Rate Behaviour and Hedging of Currency Risk

Bos, Charles S.; Mahieu, Ronald J.; Dijk, Herman K. van - Tinbergen Instituut - 2001

ofseveral modelcharacteristics (unit roots, GARCH, stochastic volatility, heavy taileddisturbance densities) areinvestigated in …

Persistent link: https://www.econbiz.de/10011256653

Stock Index Returns' Density Prediction using GARCH Models: Frequentist or Bayesian Estimation?

Hoogerheide, Lennart F.; Ardia, David; Corre, Nienke - Tinbergen Instituut - 2011

-known GARCH models for density prediction of daily S&P 500 and Nikkei 225 index returns, a comparison is provided between …

Persistent link: https://www.econbiz.de/10011256766

Herding, A-synchronous Updating and Heterogeneity in Memory in a CBS

Diks, Cees; Weide, Roy van der - Tinbergen Instituut - 2003

predicts MA(1) structure with a negative coeffient. Asynchronous updating leads to an MA(1) model for returns with GARCH($1 …,1$) innovations, and predicts a relation between the ARCH and GARCH coefficients. Heterogeneity in memory leads to long … coefficient and the relation between the ARCH and GARCH coefficients for exchange rate data. …

Persistent link: https://www.econbiz.de/10011256802

Stock Index Volatility Forecasting with High Frequency Data

Hol, Eugenie; Koopman, Siem Jan - Tinbergen Instituut - 2002

Volatility (SV) and Generalised Autoregressive Conditional Heteroskedasticity (GARCH) models which are both extended to include … outperforms the GARCH model. …

Persistent link: https://www.econbiz.de/10011256816

Bayesian Estimation of the GARCH(1,1) Model with Student-t Innovations

Ardia, David; Hoogerheide, Lennart F. - Tinbergen Instituut - 2010

parsimonious and effective GARCH(1,1) model with Student-<I>t</I> innovations. The estimation procedure is fully automatic and thus …

Persistent link: https://www.econbiz.de/10011256998

The Stochastic Volatility in Mean Model

Koopman, Siem Jan; Uspensky, Eugenie Hol - Tinbergen Instituut - 2000

In this paper we present an exact maximum likelihood treatment forthe estimation of a Stochastic Volatility in Mean(SVM) model based on Monte Carlo simulation methods. The SVM modelincorporates the unobserved volatility as anexplanatory variable in the mean equation. The same extension...

Persistent link: https://www.econbiz.de/10011257033

A New Bootstrap Test for the Validity of a Set of Marginal Models for Multiple Dependent Time Series: An Application to Risk Analysis

Ardia, David; Gatarek, Lukasz; Hoogerheide, Lennart F. - Tinbergen Instituut - 2014

over a small time frame (e.g., a crisis period). We apply our method to test GARCH model specifications for a large panel …

Persistent link: https://www.econbiz.de/10011257126