The returns of many financial assets show significant skewness, but in the literature this issue is only marginally dealt with. Our conjecture is that this distributional asymmetry may be due to two different dynamics in positive and negative returns. In this paper we propose a process that allows the simultaneous modelling of skewed conditional returns and different dynamics in their conditional second moments. The main stochastic properties of the model are analyzed and necessary and sufficient conditions for weak and strict stationarity are derived. An application to the daily returns on the principal index of the London Stock Exchange supports our model when compared to other frequently used GARCH-type models, which are nested into ours.

Pelagatti, M. (2009). Modelling Good and Bad Volatility. STUDIES IN NONLINEAR DYNAMICS AND ECONOMETRICS, 13(1).

Modelling good and bad volatility

PELAGATTI, MATTEO MARIA
2009

Abstract

The returns of many financial assets show significant skewness, but in the literature this issue is only marginally dealt with. Our conjecture is that this distributional asymmetry may be due to two different dynamics in positive and negative returns. In this paper we propose a process that allows the simultaneous modelling of skewed conditional returns and different dynamics in their conditional second moments. The main stochastic properties of the model are analyzed and necessary and sufficient conditions for weak and strict stationarity are derived. An application to the daily returns on the principal index of the London Stock Exchange supports our model when compared to other frequently used GARCH-type models, which are nested into ours.
Articolo in rivista - Articolo scientifico
Volatility, GARCH, conditional skewness, conditional second moments, asymmetry
English
Article 2
Pelagatti, M. (2009). Modelling Good and Bad Volatility. STUDIES IN NONLINEAR DYNAMICS AND ECONOMETRICS, 13(1).
Pelagatti, M
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/10281/5071
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