Statistical Tools for Finance and Insurance

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Rank − 1 / 2: A Simple Way to Improve the OLS Estimation of Tail Exponents (2007, neutral): “…Littauer Center, 1805 Cambridge St., Cambridge, MA 02138 (ribragim@fas.harvard.edu) Despite the availability of more sophisticated methods, a popular way to estimate a Pareto exponent is still to run an OLS regression: log(Rank) = a − b log(Size), and take b as an estimate of the Pareto exponent.”
Skew mixture models for loss distributions: a Bayesian approach (2012, methodology): “Robert and Casella (2004), Celeux et al. (2000) and Marin et al. (2005). Moreover, when dealing with non Gaussian mixtures we face the problem of simulating from intractable full conditional densities. Recently, Frühwirth-Schnatter and Pyne (2010) proposed an equivalent stochastic representation of ”
A survey of functional principal component analysis (2014, positive): “( 2003 ) and Benko & Härdle ( 2005 ) applied the common functional principal component to model implied volatility surface dynamics .”
An empirical comparison of alternate regime-switching models or electricity spot prices (2010, methodology): “Probably using the integral-type W2 statistic of Cramér-von Mises (see e.g. Čižek et al., 2005) instead of the extremum-based Kolmogorov-Smirnov statistic would result in more convergent behavior of the two goodness-of-fit measures.”