Robust bootstrap procedures for the chain-ladder method

Insurers are faced with the challenge of estimating the future reserves needed to handle historic and outstanding claims that are not fully settled. A well-known and widely used technique is the chain-ladder method, which is a deterministic algorithm. To include a stochastic component one may apply generalized linear models to the run-off triangles based on past claims data. Analytical expressions for the standard deviation of the resulting reserve estimates are typically difficult to derive. A popular alternative approach to obtain inference is to use the bootstrap technique. However, the standard procedures are very sensitive to the possible presence of outliers. These atypical observations, deviating from the pattern of the majority of the data, may both inflate or deflate traditional reserve estimates and corresponding inference such as their standard errors. Even when paired with a robust chain-ladder method, classical bootstrap inference may break down. Therefore, we discuss and implement several robust bootstrap procedures in the claims reserving framework and we investigate and compare their performance on both simulated and real data. We also illustrate their use for obtaining the distribution of one year risk measures.     

Market timing in precious metals is detrimental to value creation

Few number of days accounts for most of the returns delivered by precious metals (gold, silver, platinum and palladium). A passive buy and hold investment strategy in precious metals outperforms market timers who miss the best 5, 10 and 50 days by 51%, 71% and 98%, respectively. Likewise, long-term performance of precious metals is largely determined by the return of few outliers (black swans). Thus, investors should reconsider trying to predict when to be in and out of the precious metals markets and support investing in precious metals ETFs.     

Breaks and outliers when modelling the volatility of the U.S. stock market

This study analyses volatility persistence of the U.S. stock market, after taking into account the role of breaks and outliers. By employing a wavelet-based algorithm, it identifies several outliers which are comfortably associated with major events such as the ‘Black Monday’ and the Asian crisis. There is also evidence of clustering of breaks and a substantial variation in the properties of the identified segments.     

Robust normal reference bandwidth for kernel density estimation

Bandwidth selection is the main problem of kernel density estimation, the most popular method of density estimation. The classical normal reference bandwidth usually oversmoothes the density estimate. The existing hi-tech bandwidths have computational problems (even may not exist) and are not robust against outliers in the sample. A highly robust normal reference bandwidth is proposed, which adapts to different types of densities.     

Skew and heavy‐tail effects on firm performance

Research summary : Most strategic management studies adopt an average‐centered view that uses the central tendency to explain between‐group variation in performance (i.e., performance differences between business units, firms, industries, and countries). In this study, we explain within‐group variation using a variance‐centered view that focuses on the peripheral characteristics of performance distributions as defined by skew and heavy tails (i.e., variance and kurtosis). Drawing on performance feedback theory, we hypothesize that successful firms tend to develop a positive skew in their performance distributions, which we call a “positive skew effect” in this study, and that heavy tails moderate this effect. Our analysis of the performance of a group of foreign affiliates provides general support for our hypotheses at both the firm and segment (industry and country) levels. Managerial summary : Managers of multi‐business firms use various approaches to improve the aggregate performance of their business units. Some expand the range of upper performance outliers (exploration) or reduce the range of lower outliers (downsizing); others improve the performance of current business units (exploitation). We find that firms with superior performance tend to have a balanced mix of the three approaches. We also find that segments (countries and industries) with higher mean performances provide environments that facilitate the entry of productive firms and the exit of unproductive firms and provide environments in which incumbents can further improve their performance by learning from others. We observe that successful firms and segments have a positive skew in their performance distributions, which we call a “positive skew effect.” Copyright © 2016 John Wiley & Sons, Ltd.