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Activity Number:
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270
- Advanced Multivariate Time Series Modeling
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Type:
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Topic Contributed
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Date/Time:
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Tuesday, August 9, 2022 : 10:30 AM to 12:20 PM
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Sponsor:
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International Chinese Statistical Association
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Abstract #322254
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Title:
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Tail Adversarial Stability for Linear Processes
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Author(s):
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Shuyang Bai* and Ting Zhang
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Companies:
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University of Georgia and University of Georgia
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Keywords:
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Time Series;
Extreme Value ;
Moving Average;
Linear Process;
Tail Dependence;
Tail Adversarial Stability
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Abstract:
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Tail adversarial stability is a recently introduced notion for measuring extremal dependence in time series. It has been proven useful in establishing asymptotic statistical theories for extreme value analysis of dependent data. In this talk, we discuss the verification of the tail adversarial stability condition for regularly varying linear processes, a class of processes commonly used for modeling time series extreme values.
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Authors who are presenting talks have a * after their name.
