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Methods to Analyse Agricultural Commodity Price Volatility Read chapter Read first chapter

2011 | OriginalPaper | Chapter

8. Approaches to Assess Higher Dimensional Price Volatility Co-movements

Authors : Jochen Schmitz, Oliver von Ledebur

Published in: Methods to Analyse Agricultural Commodity Price Volatility

Publisher: Springer New York

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Abstract

In this chapter two different multivariate GARCH models are used to analyse how volatility changes over time and markets. Multiple time series properties for agricultural commodities futures are analysed and non-linearity in the variance of each series is taken into account. Both implemented models are discussed in light of viability of estimation of higher dimensional time series systems. We identified patterns in volatility transmission that are of particular importance for volatility analysis and for market participants.

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previous chapter Using Futures Prices to Forecast US Corn Prices: Model Performance with Increased Price Volatility
next chapter Price Co-movements in International Markets and Their Impacts on Price Dynamics
Footnotes
1
This way of modelling is chosen as a standard approach. For a discussion and analysis of the variability of trends of prices and volatility, see Gilbert (2006) and Gilbert and Morgan (2010).
 
2
These restrictions are the same as in the univariate GARCH model, see Bollerslev (1986).
 
3
See footnote 2 for the restrictions of the variances to be positive.
 
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Metadata
Title
Approaches to Assess Higher Dimensional Price Volatility Co-movements
Authors
Jochen Schmitz
Oliver von Ledebur
Copyright Year
2011
Publisher
Springer New York
Book
Methods to Analyse Agricultural Commodity Price Volatility

Print ISBN: 978-1-4419-7633-8

Electronic ISBN: 978-1-4419-7634-5

Copyright Year: 2011

DOI
https://doi.org/10.1007/978-1-4419-7634-5_8