Usage
  • 38 views
  • 29 downloads

Estimation of extreme value dependence: application to Australian spot electricity prices

  • Author / Creator
    Frolova, Nadezda
  • There is an increasing interest in extreme value analysis for financial and climate data. Various statistical methods have been developed for estimating extreme value dependence in time series data sets and the field continues to grow. In this work we consider four statistical methods for estimating extreme value dependence: the extremogram and cross extremogram, quantile regression, the cross-quantilogram and the upper tail dependence coefficient estimated using Gumbel copulas. We consider within series dependence but also cross serial dependence which may be of more interest. We compare the four methods using a data set of spot electricity prices from Australian states included in the National Electricity Market. In addition we discuss the advantages and disadvantages of each method. Finally, a freeware R package, "extremogram", is made available that implements the extremogram methods.

  • Subjects / Keywords
  • Graduation date
    2016-06
  • Type of Item
    Thesis
  • Degree
    Master of Science
  • DOI
    https://doi.org/10.7939/R34J0B53F
  • License
    This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for non-commercial purposes. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.
  • Language
    English
  • Institution
    University of Alberta
  • Degree level
    Master's
  • Department
    • Department of Mathematical and Statistical Sciences
  • Specialization
    • Statistics
  • Supervisor / co-supervisor and their department(s)
    • Cribben, Ivor (Alberta School of Business)
    • Wiens, Douglas (Mathematical and Statistical Sciences)
  • Examining committee members and their departments
    • Cribben, Ivor (Alberta School of Business)
    • Kong, Linglong (Mathematical and Statistical Sciences)
    • Jiang, Bei (Mathematical and Statistical Sciences)
    • Wiens, Douglas (Mathematical and Statistical Sciences)
    • Heo, Geseon (School of Dentistry)