Return attribution analysis of the UK insurance portfolios
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- 作者：G. A. Christodoulakis (1)
E. C. Mamatzakis (2) - 关键词：Insurance premiums ; Monte Carlo integration ; Non ; negativity constraints ; Return attribution ; Sharpe style analysis ; C1 ; C3 ; C5 ; E3 ; G2 ; G22
- 刊名：Annals of Finance
- 出版年：2010
- 出版时间：July 2010
- 年：2010
- 卷：6
- 期：3
- 页码：405-420
- 全文大小：315KB
- 参考文献：1. Association of British Insurers (ABI): Sources of premium income (various issues), London (2006a)
2. Association of British Insurers (ABI): Insurance statistics, London (2006b)
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E. C. Mamatzakis (2)
1. Manchester Business School, Crawford House, Booth Street West, Manchester, M15 6PB, UK
2. Department of Economics, University of Piraeus, Karaoli & Dimitriou 80, 18534, Piraeus, Greece - ISSN：1614-2454
文摘
We examine the attribution of premium growth rates for the five main insurance sectors of the United Kingdom for the period 1969-005; in particular, Property, Motor, Pecuniary, Health and Accident, and Liability. In each sector, the growth rates of aggregate insurance premiums are viewed as portfolio returns which we attribute to a number of factors such as realized and expected losses and expenses, their uncertainty and market power, using the Sharpe (Determining the Fund’s Effective Asset Mix. Investment Management Review, November–December, pp. 59-9, 1988; J. Portfolio Manag. 18:7-9, 1992) Style Analysis. Our estimation method differs from the standard least squares practice which does not provide confidence intervals for style betas and adopts a Bayesian approach, resulting in a robust estimate of the entire empirical distribution of each beta coefficients for the full sample. We also perform a rolling analysis of robust estimation for a window of seven overlapping samples. Our empirical findings show that there are some main differences across industries as far as the weights attributed to the underlying factors. Rolling regressions assist us to identify the variability of these weights over time, but also across industries.