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The Variance Gamma (VG) Model with Long Range Dependence

Doctor of Philosophy (PhD) / This thesis mainly builds on the Variance Gamma (VG) model for financial assets over time of Madan & Seneta (1990) and Madan, Carr & Chang (1998), although the model based on the t distribution championed in Heyde & Leonenko (2005) is also given attention. The primary contribution of the thesis is the development of VG models, and the extension of t models, which accommodate a dependence structure in asset price returns. In particular it has become increasingly clear that while returns (log price increments) of historical financial asset time series appear as a reasonable approximation of independent and identically distributed data, squared and absolute returns do not. In fact squared and absolute returns show evidence of being long range dependent through time, with autocorrelation functions that are still significant after 50 to 100 lags. Given this evidence against the assumption of independent returns, it is important that models for financial assets be able to accommodate a dependence structure.

Identiferoai:union.ndltd.org:ADTP/283733
Date January 2009
CreatorsFinlay, Richard
PublisherUniversity of Sydney., School of Mathematics and Statistics
Source SetsAustraliasian Digital Theses Program
Detected LanguageEnglish
RightsThe author retains copyright of this thesis., http://www.library.usyd.edu.au/copyright.html

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