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- W4313646656 abstract "Abstract Pearson's system is a rich class of models that includes many classical univariate distributions. It comprises all continuous densities whose logarithmic derivative can be expressed as a ratio of quadratic polynomials governed by a vector of coefficients. The estimation of a Pearson density is challenging, as small variations in can induce wild changes in the shape of the corresponding density . The authors show how to estimate and effectively through a penalized likelihood procedure involving differential regularization. The approach combines a penalized regression method and a profiled estimation technique. Simulations and an illustration with S&P 500 data suggest that the proposed method can improve market risk assessment substantially through value‐at‐risk and expected shortfall estimates that outperform those currently used by financial institutions and regulators." @default.
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- W4313646656 date "2023-01-06" @default.
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- W4313646656 title "Sparse estimation within Pearson's system, with an application to financial market risk" @default.
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- W4313646656 doi "https://doi.org/10.1002/cjs.11754" @default.
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