Application of spectral and ARIMA analysis to combined‐ratio patterns
Emilio C. Venezian and
Chao‐Chun Leng
Journal of Risk Finance, 2006, vol. 7, issue 2, 189-214
Abstract:
Purpose - This paper seeks to use spectral analysis as an alternative method to analyze whether underwriting results exhibit a cyclical behavior for the property‐liability insurance industry and by lines of business. In addition, aims to use the AR(2) process to obtain information about cyclical behavior and cycle lengths. Then, the results from the two methods are to be closely examined and compared. Design/methodology/approach - Spectral analysis and ARIMA are used to obtain cycle lengths, then to compare them to check the consistency of the two methods. Findings - The AR(2) produced more significant results than spectral analysis. Originality/value - This is the first article in insurance using significant levels for spectral analysis to decide appropriate cycle lengths. In addition, the consideration of multiple comparisons to get critical values for significance levels reduces false positive and produces more reliable results.
Keywords: Underwriting; Data analysis; Property insurance (search for similar items in EconPapers)
Date: 2006
References: Add references at CitEc
Citations:
Downloads: (external link)
https://www.emerald.com/insight/content/doi/10.110 ... d&utm_campaign=repec (text/html)
https://www.emerald.com/insight/content/doi/10.110 ... d&utm_campaign=repec (application/pdf)
Access to full text is restricted to subscribers
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eme:jrfpps:15265940610648625
DOI: 10.1108/15265940610648625
Access Statistics for this article
Journal of Risk Finance is currently edited by Nawazish Mirza
More articles in Journal of Risk Finance from Emerald Group Publishing Limited
Bibliographic data for series maintained by Emerald Support ().