9 research outputs found
Aggregation of Dependent Risks Using the Koehler–Symanowski Copula Function
No full textThis study examines the Koehler and Symanovski copula function with specific marginals, such as the skew Student-t, the skew generalized secant hyperbolic, and the skew generalized exponential power distributions, in modelling financial returns and measuring dependent risks. The copula function can be specified by adding interaction terms to the cumulative distribution function for the case of independence. It can also be derived using a particular transformation of independent gamma functions. The advantage of using this distribution relative to others lies in its ability to model complex dependence structures among subsets of marginals, as we show for aggregate dependent risks of some market indices. Copyright Springer Science + Business Media, Inc. 2005asset returns, IFM method, measures of dependence, minimum distance estimation, skew distributions,
Effect of feeding fermented milk on the incidence of chemically induced colon tumors in rats
No full textIn vivo demonstration of enhanced probiotic effect of co-immobilized Lactobacillus acidophilus and Bifidobacterium bifidum
No full textDetermination of antimutagenic properties of acetone extracted fermented milks and changes in their total fatty acid profiles including conjugated linoleic acids
No full textBetulinol and wood sterols in sediments contaminated by pulp and paper mill effluents: dissolution and spatial distribution
No full textExposure methodology and findings for dietary nitrate exposures in children of Transylvania, Romania
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