Ordinary and Markov-Switching Autoregressive Models for Firm-Level Underwriting Data
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Frank Y. Feng
Abstract
For many decades, the analysis of underwriting-profitability regimes (i. e. successive “hard” and “soft” markets) has formed an important topic in insurance research. In the present article, we study the characteristics of firm-level underwriting results by applying both ordinary and Markov-switching autoregressive models to data from individual U.S. property-liability companies. The research employs both univariate and multivariate methods. Our analysis argues against the existence of distinct, firm-level underwriting regimes in the U.S. property-liability market, but offers evidence of cross-company interactions over time.
Acknowledgements
The authors would like to thank Gary Venter, Morton Lane, and other participants in the 2018 joint conference of NTU-IRFRC and APRIA (Singapore) for their insightful comments on a previous version of this research.
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Articles in the same Issue
- Editorial
- Guest Editors’ Note on the Summer 2019 Special Issue – New Solutions in Risk Management
- Featured Articles
- Regularized Regression for Reserving and Mortality Models
- Estimating the Recovery Rates for Unsecured Loans to Small Sized Firms
- Factors Widening the Gap between Hypothetical and Actual choices—Empirical Evidence from the Japanese Medical Insurance Market—
- Ordinary and Markov-Switching Autoregressive Models for Firm-Level Underwriting Data
Articles in the same Issue
- Editorial
- Guest Editors’ Note on the Summer 2019 Special Issue – New Solutions in Risk Management
- Featured Articles
- Regularized Regression for Reserving and Mortality Models
- Estimating the Recovery Rates for Unsecured Loans to Small Sized Firms
- Factors Widening the Gap between Hypothetical and Actual choices—Empirical Evidence from the Japanese Medical Insurance Market—
- Ordinary and Markov-Switching Autoregressive Models for Firm-Level Underwriting Data
