2010 - INFORMS John von Neumann Theory Prize
The scientist’s investigation covers issues in Combinatorics, Random walk, Markov process, Markov additive process and Applied mathematics. Søren Asmussen interconnects Probability theory, Large deviations theory, Random variable, Distribution and Log-normal distribution in the investigation of issues within Combinatorics. His Random walk research is multidisciplinary, relying on both Discrete mathematics, Queueing theory and Lévy process.
His Markov process study combines topics in areas such as State, Exponential function, Markov chain and First-hitting-time model. He has researched Markov additive process in several fields, including Martingale, Markov renewal process, Mathematical optimization, Queue and Applied probability. His Applied probability research incorporates themes from Renewal theory and Theoretical computer science.
His primary areas of investigation include Applied mathematics, Combinatorics, Markov chain, Queue and Discrete mathematics. His studies deal with areas such as Poisson distribution, Statistics, First-hitting-time model and Mathematical optimization as well as Applied mathematics. Søren Asmussen has included themes like Random variable, Distribution, Type, Limit and Random walk in his Combinatorics study.
Søren Asmussen frequently studies issues relating to Markov process and Markov chain. His Markov process research focuses on Exponential function and how it connects with Lévy process. His Queue research incorporates elements of Distribution, Queueing theory and Stability.
Søren Asmussen spends much of his time researching Life insurance, Applied mathematics, Combinatorics, Queue and Actuarial science. His Applied mathematics study combines topics from a wide range of disciplines, such as Markov process, Series and Extreme value theory. Søren Asmussen combines subjects such as Laplace transform, Transition rate matrix and Orthogonal polynomials with his study of Markov process.
His Combinatorics research includes elements of Plot and Benchmark. In his study, which falls under the umbrella issue of Queue, Mathematical optimization, Branching process and Expected value is strongly linked to Stability. The study incorporates disciplines such as Random walk and Lévy process in addition to Infimum and supremum.
Søren Asmussen focuses on Life insurance, Discrete mathematics, Lévy process, Econometrics and Laplace transform. His research in Life insurance intersects with topics in Competition, Markov process, Differential game, Applied mathematics and Investment. Markov process and Jump diffusion are two areas of study in which he engages in interdisciplinary work.
The concepts of his Applied mathematics study are interwoven with issues in Matrix, Queueing theory and Transition rate matrix. His work deals with themes such as Factorization, Distribution, Infimum and supremum and Exponential function, which intersect with Lévy process. The various areas that Søren Asmussen examines in his Laplace transform study include Random variable, Rare event simulation, Weibull distribution, Statistical physics and Point.
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Applied Probability and Queues
Stochastic Simulation: Algorithms and Analysis
Søren Asmussen;Peter W. Glynn.
Controlled diffusion models for optimal dividend pay-out
Søren Asmussen;Michael Taksar.
Insurance Mathematics & Economics (1997)
Russian and American put options under exponential phase-type Lévy models
Søren Asmussen;Florin Avram;Martijn R. Pistorius.
Stochastic Processes and their Applications (2004)
Approximations of small jumps of Lévy processes with a view towards simulation
Søren Asmussen;Jan Rosiński.
Journal of Applied Probability (2001)
Risk theory in a Markovian environment
Scandinavian Actuarial Journal (1989)
Optimal risk control and dividend distribution policies: example of excess-of loss reinsurance for an insurance corporation
Søren Asmussen;Bjarne Højgaard;Michael Taksar.
Finance and Stochastics (2000)
Marked point processes as limits of Markovian arrival streams
Søren Asmussen;Ger Koole.
Journal of Applied Probability (1993)
Stationary distributions for fluid flow models with or without Brownian noise
Stochastic Models (1995)
Subexponential asymptotics for stochastic processes : extremal behavior, stationary distributions and first passage probabilities
Annals of Applied Probability (1998)
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