Arbeitspapier

Modeling Dynamic Volatilities and Correlations under Skewness and Fat Tails

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 skewed and fat-tailed shape of the distribution directly affects the dynamic behavior of the time-varying parameters. It distinguishes our approach from familiar alternatives such as the generalized autoregressive conditional heteroskedasticity model and the dynamic conditional correlation model where distributional assumptions affect the likelihood but not the parameter dynamics. We present a modified expectation-maximization algorithm to estimate the model. Simulated and empirical evidence shows that the model outperforms its close competitors if skewness and kurtosis are relevant features of the data.

Sprache
Englisch

Erschienen in
Series: Tinbergen Institute Discussion Paper ; No. 11-078/2/DSF22

Klassifikation
Wirtschaft
Econometric and Statistical Methods and Methodology: General
Single Equation Models; Single Variables: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
Multiple or Simultaneous Equation Models: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
Thema
Dynamic conditional correlations
Generalized Hyperbolic distributions
Observation driven models
Volatilität
Statistische Verteilung
Korrelation
Statistische Methode
Theorie

Ereignis
Geistige Schöpfung
(wer)
Zhang, Xin
Creal, Drew
Koopman, Siem Jan
Lucas, Andre
Ereignis
Veröffentlichung
(wer)
Tinbergen Institute
(wo)
Amsterdam and Rotterdam
(wann)
2011

Handle
Letzte Aktualisierung
10.03.2025, 11:41 MEZ

Datenpartner

Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.

Objekttyp

  • Arbeitspapier

Beteiligte

  • Zhang, Xin
  • Creal, Drew
  • Koopman, Siem Jan
  • Lucas, Andre
  • Tinbergen Institute

Entstanden

  • 2011

Ähnliche Objekte (12)