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| Ramirez, Octavio A.. |
| This paper explores the impact of error-term non-normality on the performance of the normal-error Generalized Autoregressive Conditional Heteroskedastic (GARCH) model under small and moderate sample sizes. A non-normal-, asymmetric-error GARCH model is proposed, and its finite-sample performance is evaluated in comparison to the normal-error GARCH under various underlying error-term distributions. The results suggest that one must be skeptical of using the normal-error GARCH when there is evidence of conditional error-term non-normality. The conditional distribution of the error-term in a previous mainstream application of the normal GARCH is found to be non-normal and asymmetric. The same application is used to illustrate the advantages of the proposed... |
| Tipo: Conference Paper or Presentation |
Palavras-chave: Error- term non-normality; Skewness; Autoregressive conditional heteroskedasticity; Research Methods/ Statistical Methods. |
| Ano: 2001 |
URL: http://purl.umn.edu/20595 |
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| Taing, Siv; Worthington, Andrew. |
| This paper examines return interrelationships between numbers of equity sectors across several European markets. The markets comprise six Member States of the European Union (EU): namely, Belgium, Finland, France, Germany, Ireland and Italy. The five sectors include the consumer discretionary, consumer staples, financial, industrials and materials sectors. Generalised Autoregressive Conditional Heteroskedasticity in Mean (GARCHM) models are used to consider the impact of returns in other European markets on the returns in each market across each sector. The results indicate that there are relatively few significant interrelationships between sectors in different markets, with most of these accounted for by the larger markets in France, Germany and Italy.... |
| Tipo: Journal Article |
Palavras-chave: Risk and return; Volatility; Autoregressive conditional heteroskedasticity; C32; F36; G15. |
| Ano: 2005 |
URL: http://purl.umn.edu/37160 |
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| Moschini, GianCarlo; Myers, Robert J.. |
| We develop a new multivariate GARCH parameterization that is suitable for testing the hypothesis that the optimal futures hedge ratio is constant over time, given that the joint distribution of cash and futures prices is characterized by autoregressive conditional heteroskedasticity. The advantage of the new parameterization is that it allows for a flexible form of time-varying volatility, even under the null of a constant hedge ratio. The model is estimated using weekly corn prices. Statistical tests reject the null hypothesis of a constant hedge ratio and also reject the null that time variation in optimal hedge ratios can be explained solely by deterministic seasonality and time-to-maturity effects. |
| Tipo: Working or Discussion Paper |
Palavras-chave: Autoregressive conditional heteroskedasticity; Futures; Hedging; Marketing. |
| Ano: 2001 |
URL: http://purl.umn.edu/18516 |
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