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All Outputs (18)

Design litigation in the EU Member States: Are overlaps with other intellectual property rights and unfair competition problematic and are SMEs benefitting from the EU design legal framework? (2021)
Journal Article
Church, O., Derclaye, E., & Stupfler, G. (2021). Design litigation in the EU Member States: Are overlaps with other intellectual property rights and unfair competition problematic and are SMEs benefitting from the EU design legal framework?. European Law Review, 2021(1),

Genuine overlaps (several intellectual property rights (IPR) applying to the same intellectual effort) create overprotection. There is hardly any empirical legal research done on how claimants have litigated at national level not only on their design... Read More about Design litigation in the EU Member States: Are overlaps with other intellectual property rights and unfair competition problematic and are SMEs benefitting from the EU design legal framework?.

Operating at the extreme: Estimating the upper yield boundary of winter wheat production in commercial practice (2020)
Journal Article
Mitchell, E. G., Crout, N. M., Wilson, P., Wood, A. T., & Stupfler, G. (2020). Operating at the extreme: Estimating the upper yield boundary of winter wheat production in commercial practice. Royal Society Open Science, 7(4), https://doi.org/10.1098/rsos.191919

© 2020 The Authors. Wheat farming provides 28.5% of global cereal production. After steady growth in average crop yield from 1950 to 1990, wheat yields have generally stagnated, which prompts the question of whether further improvements are possible.... Read More about Operating at the extreme: Estimating the upper yield boundary of winter wheat production in commercial practice.

Tail expectile process and risk assessment (2019)
Journal Article
Daouia, A., Girard, S., & Stupfler, G. (2020). Tail expectile process and risk assessment. Bernoulli, 26(1), 531-556. https://doi.org/10.3150/19-BEJ1137

Expectiles define a least squares analogue of quantiles. They are determined by tail expectations rather than tail probabilities. For this reason and many other theoretical and practical merits, expectiles have recently received a lot of attention, e... Read More about Tail expectile process and risk assessment.

Beyond tail median and conditional tail expectation: extreme risk estimation using tail Lp-optimisation (2019)
Journal Article
Gardes, L., Girard, S., & Stupfler, G. (2020). Beyond tail median and conditional tail expectation: extreme risk estimation using tail Lp-optimisation. Scandinavian Journal of Statistics, 47(3), 922-949. https://doi.org/10.1111/sjos.12433

The Conditional Tail Expectation is an indicator of tail behaviour that, contrary to the quantile or Value-at-Risk, takes into account the frequency of a tail event together with the probabilistic behaviour of the variable of interest on this event.... Read More about Beyond tail median and conditional tail expectation: extreme risk estimation using tail Lp-optimisation.

On a relationship between randomly and non-randomly thresholded empirical average excesses for heavy tails (2019)
Journal Article
Stupfler, G. (2019). On a relationship between randomly and non-randomly thresholded empirical average excesses for heavy tails. Extremes, 22(4), 749–769. https://doi.org/10.1007/s10687-019-00351-5

Motivated by theoretical similarities between the classical Hill estimator of the tail index of a heavy-tailed distribution and one of its pseudo-estimator versions featuring a non-random threshold, we show a novel asymptotic representation of a clas... Read More about On a relationship between randomly and non-randomly thresholded empirical average excesses for heavy tails.

An Empirical Analysis of the Design Case Law of the EU Member States (2019)
Journal Article
Church, O., Derclaye, E., & Stupfler, G. (2019). An Empirical Analysis of the Design Case Law of the EU Member States. International Review of Intellectual Property and Competition Law, 50(6), 685-719. https://doi.org/10.1007/s40319-019-00813-0

This article empirically examines the substantive decisions on all types of design rights from the courts of the 28 Member States since the entry into force of the Design Directive and the Design Regulation, up to and including August 2017. The artic... Read More about An Empirical Analysis of the Design Case Law of the EU Member States.

On a class of norms generated by nonnegative integrable distributions (2019)
Journal Article
Falk, M., & Stupfler, G. (2019). On a class of norms generated by nonnegative integrable distributions. Dependence Modeling, 7(1), 259-278. https://doi.org/10.1515/demo-2019-0014

We show that any distribution function on R d with nonnegative, nonzero and integrable marginal distributions can be characterized by a norm on R d+1 , called F-norm. We characterize the set of F-norms and prove that pointwise convergence of a sequen... Read More about On a class of norms generated by nonnegative integrable distributions.

An integrated functional Weissman estimator for conditionalextreme quantiles (2019)
Journal Article
Gardes, L., & Stupfler, G. (2019). An integrated functional Weissman estimator for conditionalextreme quantiles. Revstat Statistical Journal, 17(1), 109-144

It is well-known that estimating extreme quantiles, namely, quantiles lying beyond the range of the available data, is a nontrivial problem that involves the analysis of tail behavior through the estimation of the extreme-value index. For heavy-taile... Read More about An integrated functional Weissman estimator for conditionalextreme quantiles.

Extreme M-quantiles as risk measures: from L1 to Lp optimization (2018)
Journal Article
Daouia, A., Girard, S., & Stupfler, G. (2019). Extreme M-quantiles as risk measures: from L1 to Lp optimization. Bernoulli, 25(1), 264-309

The class of quantiles lies at the heart of extreme-value theory and is one of the basic tools in risk management. The alternative family of expectiles is based on squared rather than absolute error loss minimization. It has recently been receiving a... Read More about Extreme M-quantiles as risk measures: from L1 to Lp optimization.

Extremiles: A New Perspective on Asymmetric Least Squares (2018)
Journal Article
Daouia, A., Gijbels, I., & Stupfler, G. (2019). Extremiles: A New Perspective on Asymmetric Least Squares. Journal of the American Statistical Association, 114(527), 1366-1381. https://doi.org/10.1080/01621459.2018.1498348

Quantiles and expectiles of a distribution are found to be useful descriptors of its tail in the same way as the median and mean are related to its central behavior. This paper considers a valuable alternative class to expectiles, called extremiles,... Read More about Extremiles: A New Perspective on Asymmetric Least Squares.

On the study of extremes with dependent random right-censoring (2018)
Journal Article
Stupfler, G. (2019). On the study of extremes with dependent random right-censoring. Extremes, 22(1), 97–129. https://doi.org/10.1007/s10687-018-0328-6

The study of extremes in missing data frameworks is a recent developing field. In particular, the randomly right-censored case has been receiving a fair amount of attention in the last decade. All studies on this topic, however, essentially work unde... Read More about On the study of extremes with dependent random right-censoring.

Analyzing and predicting cat bond premiums: a financial loss premium principle and extreme value modeling (2017)
Journal Article
Stupfler, G., & Yang, F. (2018). Analyzing and predicting cat bond premiums: a financial loss premium principle and extreme value modeling. ASTIN Bulletin, 48(1), https://doi.org/10.1017/asb.2017.32

CAT bonds play an important role in transferring insurance risks to the capital market. It has been observed that typical CAT bond premiums have changed since the recent financial crisis, which has been attributed to market participants being increa... Read More about Analyzing and predicting cat bond premiums: a financial loss premium principle and extreme value modeling.

Estimation of tail risk based on extreme expectiles (2017)
Journal Article
Daouia, A., Girard, S., & Stupfler, G. (in press). Estimation of tail risk based on extreme expectiles. Journal of the Royal Statistical Society: Series B, 80(2), https://doi.org/10.1111/rssb.12254

We use tail expectiles to estimate alternative measures to the Value at Risk (VaR) and Marginal Expected Shortfall (MES), two instruments of risk protection of utmost importance in actuarial science and statistical _nance. The concept of expectiles i... Read More about Estimation of tail risk based on extreme expectiles.

Improved estimators of extreme Wang distortion risk measures for very heavy-tailed distributions (2017)
Journal Article
El Methni, J., & Stupfler, G. (2018). Improved estimators of extreme Wang distortion risk measures for very heavy-tailed distributions. Econometrics and Statistics, 6, https://doi.org/10.1016/j.ecosta.2017.03.002

A general way to study the extremes of a random variable is to consider the family of its Wang distortion risk measures. This class of risk measures encompasses several indicators such as the classical quantile/Value-at-Risk, the Tail-Value-at-Risk a... Read More about Improved estimators of extreme Wang distortion risk measures for very heavy-tailed distributions.

An offspring of multivariate extreme value theory: the max-characteristic function (2016)
Journal Article
Falk, M., & Stupfler, G. (2017). An offspring of multivariate extreme value theory: the max-characteristic function. Journal of Multivariate Analysis, 154, https://doi.org/10.1016/j.jmva.2016.10.007

This paper introduces max-characteristic functions (max-CFs), which are an offspring of multivariate extreme-value theory. A max-CF characterizes the distribution of a random vector in Rd, whose components are nonnegative and have finite expectation.... Read More about An offspring of multivariate extreme value theory: the max-characteristic function.

Uniform asymptotic properties of a nonparametric regression estimator of conditional tails (2015)
Journal Article
Goegebeur, Y., Guillou, A., & Stupfler, G. (2015). Uniform asymptotic properties of a nonparametric regression estimator of conditional tails. Annales de l'Institut Henri Poincaré (B) Probabilités et Statistiques, 51(3), 1190-1213. https://doi.org/10.1214/14-AIHP624

We consider a nonparametric regression estimator of conditional tails introduced by Goegebeur, Y., Guillou, A., Schorgen, G. (2013). Nonparametric regression estimation of conditional tails – the random covariate case. It is shown that this estimator... Read More about Uniform asymptotic properties of a nonparametric regression estimator of conditional tails.

Estimating extreme quantiles under random truncation (2014)
Journal Article
Gardes, L., & Stupfler, G. (2015). Estimating extreme quantiles under random truncation. TEST, 24(2), 207–227. https://doi.org/10.1007/s11749-014-0403-5

The goal of this paper is to provide estimators of the tail index and extreme quantiles of a heavy-tailed random variable when it is right truncated. The weak consistency and asymptotic normality of the estimators are established. The finite sample p... Read More about Estimating extreme quantiles under random truncation.