nep-ias New Economics Papers
on Insurance Economics
Issue of 2015‒03‒27
two papers chosen by
Soumitra K. Mallick
Indian Institute of Social Welfare and Business Management

  1. Claims reserving with HGLM By Alicja Wolny-Dominiak
  2. Should a skeptical portfolio insurer use an optimal or a risk-based multiplier? By Maxime Bonelli; Daniel Mantilla-Garcia

  1. By: Alicja Wolny-Dominiak (University of Economics in Katowice)
    Abstract: We consider the problem of estimating IBNR (Incurred But Not Reported) loss reserves in non-life insurance. The literature proposes a wide variety of methods to estimate IBNR reserves, mostly based on the chain-ladder approach (Mack, 1993). In this paper we focus on two methods, in which unobservable risk parameters U=(U1,...,Uk)' are taken into account. Firstly, we propose HGLM model based in GLM loss reserving (Wüthrich and Mertz, 2008), where conditional inceremental payments (resonse variables) taken form loss triangle follow the distribution of an exponential dispersion family. Secondly, we modify the CapeCode method which uses the grow curve modelling (Clark, 2003). This method is based on two-stage estimation of the expected amount of loss to emerge: the estimation of the ultimate loss by year and the estimation of the pattern of loss emergence. As the pattern of loss to emerge, log-logistic and Weilbull growth curves are assumed. We imply another form of the growth curve and we add random effect yield the hierarchical model like in (Guszcza, 2008). Treating the ultimate losses in accident years as repeated measurements allows us to model parameters that determine the pattern of loss emergence in separately sub-models.
    Keywords: loss reserving, random effect, HGLM, growth curve, R
    JEL: C13 C21 C49
    Date: 2014–12
  2. By: Maxime Bonelli (Inria research centre Sophia Antipolis / Koris International); Daniel Mantilla-Garcia (Edhec-Risk / Koris International)
    Abstract: Following recent evidence of out-of-sample stock market return predictability, the authors aim to evaluate whether the potential benefits suggested by asset allocation theory can actually be captured in the real world using expected return estimates from a predictive system. The question is addressed in the context of an investor maximizing the long-term growth rate of wealth under a maximum drawdown constraint, and compare the optimal strategy using the predictive system with a similar risk-based allocation strategy independent of expected return estimates. The authors find that the risk-based strategy implies nonetheless very variable and relatively high expected returns, and report important potential benefits in using the expected return estimates of the predictive system they used.
    Keywords: financial econometrics, return predictability, asset allocation, portfolio insurance.
    JEL: C58 G17 G11
    Date: 2014–10

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