S
Steven Vanduffel
Researcher at Vrije Universiteit Brussel
Publications - 51
Citations - 415
Steven Vanduffel is an academic researcher from Vrije Universiteit Brussel. The author has contributed to research in topics: Portfolio & Multivariate statistics. The author has an hindex of 11, co-authored 51 publications receiving 339 citations.
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Optimal Payoffs under State-dependent Preferences
TL;DR: In this paper, the authors introduce a framework for portfolio selection within which state-dependent preferences can be accommodated, assuming that investors care about the distribution of final wealth and its interaction with some benchmark.
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Financial Bounds for Insurance Claims
TL;DR: In this article, the authors use an indifference pricing principle to derive lower bounds for claims' prices, and these bounds correspond to the market prices of some explicitly known financial payoffs, and have to be corrected by a covariance term which reflects the interaction between the insurance claim and the financial market.
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Financial Bounds for Insurance Claims
Carole Bernard,Steven Vanduffel +1 more
TL;DR: In this paper, the authors show that the discounted expected value is no longer valid as a classical lower bound for insurance prices in general: it has to be corrected by a covariance term that reflects the interaction between the insurance claim and the financial market.
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Correlation Order, Merging and Diversification
TL;DR: In this article, the influence of the dependence between random losses on the shortfall and on the diversification benefit that arises from merging these losses was investigated, and it was shown that increasing dependence between losses, expressed in terms of correlation order, has an increasing effect on the mismatch.
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Some Stein-type inequalities for multivariate elliptical distributions and applications
TL;DR: Brown et al. as discussed by the authors derived a Stein-type inequality for the multivariate Student's t -distribution and generalized their result to the family of generalized hyperbolic distributions and derived a lower bound for the variance of a function of a random variable.