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Performance of information criteria for selection of Hawkes process models of financial data
journal contribution
posted on 2023-06-09, 08:38 authored by J M Chen, A G Hawkes, Enrico Scalas, M TrinhWe test three common information criteria (IC) for selecting the order of a Hawkes process with an intensity kernel that can be expressed as a mixture of exponential terms. These processes find application in high-frequency financial data modelling. The information criteria are Akaike's information criterion (AIC), the Bayesian information criterion (BIC) and the Hannan-Quinn criterion (HQ). Since we work with simulated data, we are able to measure the performance of model selection by the success rate of the IC in selecting the model that was used to generate the data. In particular, we are interested in the relation between correct model selection and underlying sample size. The analysis includes realistic sample sizes and parameter sets from recent literature where parameters were estimated using empirical financial intra-day data. We compare our results to theoretical predictions and similar empirical findings on the asymptotic distribution of model selection for consistent and inconsistent IC.
History
Publication status
- Published
File Version
- Accepted version
Journal
Quantitative FinanceISSN
1469-7688Publisher
Taylor & FrancisExternal DOI
Issue
2Volume
18Page range
225-235Department affiliated with
- Mathematics Publications
Research groups affiliated with
- Probability and Statistics Research Group Publications
Full text available
- Yes
Peer reviewed?
- Yes
Legacy Posted Date
2017-11-06First Open Access (FOA) Date
2019-06-19First Compliant Deposit (FCD) Date
2017-11-06Usage metrics
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