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Quantifying heteroskedasticity metrics

HASSAN, MARWA HASSAN ALY 2016, Quantifying heteroskedasticity metrics, PhD. thesis, GTP Research, Deakin University.

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Title Quantifying heteroskedasticity metrics
Author HASSAN, MARWA HASSAN ALY
Institution Deakin University
School GTP Research
Faculty Institute for Intelligent Systems Research and Innovation
Degree type Research doctorate
Degree name PhD.
Thesis advisor Nahavandi Saeid
Creighton Douglas
Hossny MohammedORCID iD for Hossny Mohammed orcid.org/0000-0002-1593-6296
Date submitted 2016-11
Keyword(s) heteroskedasticity
Statistics
Mathematics
Financial forecasting
Summary This study proposes a quantification measure for heteroskedasticity in the time series. Two methods are introduced for quantifying heteroskedasticity: Slope of Local Variance Index (SoLVI) and a statistical divergence method using Bhattacharys coefficient. Both measures show reliability in measuring and quantifying heteroskedasticity in comparison to numerical and hypothesis heteroskedasticity tests.
Language eng
Field of Research 010406 - Stochastic Analysis and Modelling 50%
080110 - Simulation and Modelling 50%
Socio Economic Objective 970109 - Expanding Knowledge in Engineering 100%
Description of original xi, 95 pages : figures, some coloured.
Copyright notice ┬ęThe Author. All Rights Reserved
Free to Read? Yes
Persistent URL http://hdl.handle.net/10536/DRO/DU:30089384

Document type: Thesis
Collections: Higher degree theses (full text)
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Created: Fri, 25 Nov 2016, 12:51:48 EST by Deb Gray

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.