Abstract
The distribution of the innovations is the second most important component in a process. With a good understanding of the heteroskedasticity, the distribution of the empirical innovations can be studied. A normal distribution can be clearly rejected, regardless of the model used for the heteroskedasticity. A Student distribution with a number of degrees of freedom around 5 gives a simple and good characterization of the empirical distributions. This shows that the fat tail observed in the return distributions is mostly generated by the innovations, while the volatility feed-back mechanism plays a small role.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Zumbach, G.: The riskmetrics 2006 methodology. Technical report, RiskMetrics Group (2006). Available at: www.riskmetrics.com and www.ssrn.com
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Zumbach, G. (2013). The Innovation Distributions. In: Discrete Time Series, Processes, and Applications in Finance. Springer Finance. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31742-2_13
Download citation
DOI: https://doi.org/10.1007/978-3-642-31742-2_13
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-31741-5
Online ISBN: 978-3-642-31742-2
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)