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Activity Number:
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346
- Time Series: Stationarity, Non-Stationarity, Cointegration, ARCH Models, and GARCH Models
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Type:
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Contributed
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Date/Time:
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Wednesday, August 5, 2020 : 10:00 AM to 2:00 PM
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Sponsor:
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Business and Economic Statistics Section
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Abstract #309601
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Title:
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On Order Selection for ARFIMA and GARCH Processes
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Author(s):
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Hsueh-Han Huang* and Ngai Hang Chan and Ching-Kang Ing and Kun Chen
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Companies:
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National Tsing Hua University and Chinese University of Hong Kong and National Tsing Hua University and Southwestern University of Finance and Economics
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Keywords:
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Order selection;
Nonstationary time series;
Information criterion;
ARFIMA;
GARCH
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Abstract:
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In this paper, we establish order selection consistency for autoregressive fractionally integrated moving average (ARFIMA) processes without constraints on the memory parameter, and for generalized autoregressive conditional heteroskedasticity (GARCH) processes. To the best of our knowledge, these are the first selection consistency results obtained for both classes of models. Numerical analysis is conducted to illustrate our theoretical findings.
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Authors who are presenting talks have a * after their name.
