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Aggregation, Heterogeneous Autoregression and Volatility of Daily International Tourist Arrivals and Exchange Rates

Chang, C-L.; McAleer, M.J. - Erasmus University Rotterdam, Econometric Institute - 2010

conditional mean specifications. The QMLE for the GARCH(1,1), GJR(1,1) and EGARCH(1,1) models for world, US and Japanese tourist …

Persistent link: https://www.econbiz.de/10008584742

Option Pricing using Realized Volatility

Stentoft, Lars - School of Economics and Management, University of Aarhus - 2008

In the present paper we suggest to model Realized Volatility, an estimate of daily volatility based on high frequency data, as an Inverse Gaussian distributed variable with time varying mean, and we examine the joint properties of Realized Volatility and asset returns. We derive the appropriate...

Persistent link: https://www.econbiz.de/10005440036

Volatility Components, Affine Restrictions and Non-Normal Innovations

Christoffersen, Peter; Dorion, Kris; Wang, Yintian - School of Economics and Management, University of Aarhus - 2008

Recent work by Engle and Lee (1999) shows that allowing for long-run and short-run components greatly enhances a GARCH … valuation performance of the Engle-Lee model and compare it to the standard one-component GARCH(1,1) model. We also compare … these non-affine GARCH models to one- and two- component models from the class of affine GARCH models developed in Heston …

Persistent link: https://www.econbiz.de/10005440037

Option Valuation with Long-run and Short-run Volatility Components

Christoffersen, Peter; Jacobs, Kris; Ornthanalai, Chayawat - School of Economics and Management, University of Aarhus - 2008

This paper presents a new model for the valuation of European options, in which the volatility of returns consists of two components. One of these components is a long-run component, and it can be modeled as fully persistent. The other component is short-run and has a zero mean. Our model can be...

Persistent link: https://www.econbiz.de/10005440047

Parameterizing unconditional skewness in models for financial time series

He, Changli; Silvennoinen, Annastiina; Teräsvirta, Timo - School of Economics and Management, University of Aarhus - 2008

In this paper we consider the third-moment structure of a class of time series models. It is often argued that the marginal distribution of financial time series such as returns is skewed. Therefore it is of importance to know what properties a model should possess if it is to accommodate...

Persistent link: https://www.econbiz.de/10005440080

Decomposing European Bond and Equity Volatility

Christiansen, Charlotte - School of Economics and Management, University of Aarhus - 2007

The paper investigates volatility spillover from US and aggregate European asset markets into European national asset markets. A main contribution is that bond and equity volatility spillover is analyzed simultaneously. A new model belonging to the "volatility-spillover" class is suggested: The...

Persistent link: https://www.econbiz.de/10005209092

On IGARCH and convergence of the QMLE for misspecified GARCH models

Jensen, Anders Tolver; Lange, Theis - School of Economics and Management, University of Aarhus - 2009

We address the IGARCH puzzle by which we understand the fact that a GARCH(1,1) model fitted by quasi maximum likelihood … data is generated by certain types of continuous time stochastic volatility models, but fitted to a GARCH(1,1) model one …

Persistent link: https://www.econbiz.de/10005198859

Testing for Expected Return and Market Price of Risk in Chinese A-B Share Market: A Geometric Brownian Motion and Multivariate GARCH Model Approach

Zhu, Jie - School of Economics and Management, University of Aarhus - 2008

. Models with dynamic of Geometric Brownian Motion are adopted, multivariate GARCH models are also introduced to capture the … risk is insignificant for both markets if GARCH models are adopted. …

Persistent link: https://www.econbiz.de/10005198860

How Volatile is ENSO?

Chu, L.F.; McAleer, M.J.; Chen, C-C. - Erasmus University Rotterdam, Econometric Institute - 2009

both the ARMA(1,1)-GARCH(1,1) and ARMA(3,2)-GJR(1,1) models are suitable for modelling ENSO volatility. Moreover, 1998 is a …

Persistent link: https://www.econbiz.de/10005034225

Long Memory in Stock Market Volatility and the Volatility-in-Mean Effect: The FIEGARCH-M Model

Christensen, Bent Jesper; Nielsen, Morten Ørregaard; … - School of Economics and Management, University of Aarhus - 2007

We extend the fractionally integrated exponential GARCH (FIEGARCH) model for daily stock return data with long memory …-in-mean effect is significant, and the FIEGARCH-M model outperforms the original FIEGARCH model and alternative GARCH …

Persistent link: https://www.econbiz.de/10005034729