mastfi

Department of Finance

  • Center for Statistics
Mads
Stehr
Assistant professor


Room: SOL/A4.19
Tel:
+4538153647
E-mail: mast.fi@cbs.dk
PIC_Mads Stehr
Presentation

Mads Stehr is an Assistant Professor in Statistics at the Department of Finance, and he holds a PhD in Statistics and Probability Theory from Aarhus University. His research lies mainly within applied probability theory including Lévy-based modeling and extreme value theory. 

Primary research areas
Applied probability theory
Lévy-based spatio-temporal modeling
Extreme value theory
Numerical integration based on stationary sampling
Link to this homepage
www.cbs.dk/en/staff/mastfi
Courses

Stokastiske processer og deres statistiske analyse

Publications sorted by:
2021
Mads Stehr; Anders Rønn-Nielsen / Extreme Value Theory for Spatial Random Fields – With Application to a Lévy-Driven Field
In: Extremes, 7.5.2021
Journal article > peer review
Mads Stehr; Anders Rønn-Nielsen / Tail Asymptotics of an Infinitely Divisible Space-time Model with Convolution Equivalent Lévy Measure
In: Journal of Applied Probability, Vol. 58, No. 1, 3.2021, p. 42-67
Journal article > peer review
2020
Mads Stehr; Markus Kiderlen / Asymptotic Variance of Newton–Cotes Quadratures Based on Randomized Sampling Points
In: Advances in Applied Probability, Vol. 52, No. 4, 12.2020, p. 1284-1307
Journal article > peer review
Mads Stehr; Markus Kiderlen / Improving the Cavalieri Estimator under Non-Equidistant Sampling and Dropouts
In: Image Analysis and Stereology, Vol. 39, No. 3, 2020, p. 197-212
Journal article > peer review
Mads Stehr / Stereology and Spatio-temporal Models : Numerical Integration Methods for Volume Estimation and Extremes for Lévy-based Models.
Aarhus : Aarhus University. Department of Mathematics 2020, 145 p.
Ph.D. thesis
2019
Mads Stehr; Markus Kiderlen / Asymptotic Variance of Newton-Cotes Quadratures based on Randomized Sampling Points
Aarhus : Centre for Stochastic Geometry and Advanced Bioimaging (CSGB), Aarhus University 2019, 33 p. (CSGB Research Reports, No. 2)
Working paper
Mads Stehr; Anders Rønn-Nielsen / Tail Asymptotics of an Infinitely Divisible Space-Time Model with Convolution Equivalent Lévy Measure
Aarhus : Centre for Stochastic Geometry and Advanced Bioimaging (CSGB), Aarhus University 2019, 34 p. (CSGB Research Reports, No. 9)
Working paper