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Abstract Details
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Activity Number:
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617
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Type:
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Contributed
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Date/Time:
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Thursday, August 2, 2012 : 8:30 AM to 10:20 AM
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Sponsor:
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Business and Economic Statistics Section
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| Abstract - #306165 |
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Title:
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Multifractal Processes for Count Data, with an Application in Car Insurance
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Author(s):
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Jean-Philippe Boucher*+
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Companies:
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Université du Québec à Montréal
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Address:
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201, Avenue Du Président-Kennedy, Montréal, QC, H2X 3Y7, Canada
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Keywords:
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Seasonality ;
Time Series ;
Count Data ;
Multifractal process ;
Maximum Likelihood ;
Poisson
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Abstract:
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This work generalizes the multifractal process of Calvet and Fisher (2008), initially used to model the volatility component of autoregressive data, to counting processes. We show that this kind of model easily allows specification of a high-dimension state space, with only a small number of parameters. We illustrate our work with Canadian insurance data related to car claims policies. In particular, we show that this method allows duplication of peaks of daily claims number, such as those observed in Canada. We also show that the model can be generalized to include seasonal effects and covariates.
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Authors who are presenting talks have a * after their name.
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