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Thesis

Statistical dynamical models of multivariate financial time series

Abstract:

The last few years have witnessed an exponential increase in the availability and use of financial market data, which is sampled at increasingly high frequencies. Extracting useful information about the dependency structure of a system from these multivariate data streams has numerous practical applications and can aid in improving our understanding of the driving forces in the global financial markets. These large and noisy data sets are highly non-Gaussian in nature and require the use o...

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Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Research group:
Machine Learning Research Group
Oxford college:
Exeter College
Role:
Author

Contributors

Division:
MPLS
Department:
Engineering Science
Role:
Supervisor
Publication date:
2013
Type of award:
DPhil
Level of award:
Doctoral
Awarding institution:
University of Oxford
Language:
English
Keywords:
Subjects:
UUID:
uuid:428015e6-8a52-404e-9934-0545c80da4e1
Local pid:
ora:11824
Deposit date:
2015-07-09

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