What is he best known for?
The fields of study he is best known for:
- Statistics
- Mathematical analysis
- Normal distribution
Ludger Rüschendorf spends much of his time researching Mathematical optimization, Random variable, Applied mathematics, Combinatorics and Marginal distribution.
His Mathematical optimization research includes themes of Spectral risk measure, Expected shortfall, Dynamic risk measure and Stochastic differential equation.
The various areas that Ludger Rüschendorf examines in his Random variable study include Characterization and Multivariate statistics.
His biological study spans a wide range of topics, including Martingale and Quantile, Econometrics.
He combines subjects such as Contingency table, Kullback–Leibler divergence, Iterative method, Iterative proportional fitting and Bivariate analysis with his study of Applied mathematics.
His work in the fields of Combinatorics, such as Quotient, intersects with other areas such as Distribution function.
His most cited work include:
- Mass transportation problems (511 citations)
- Model uncertainty and VaR aggregation (187 citations)
- An Academic Response to Basel 3.5 (178 citations)
What are the main themes of his work throughout his whole career to date?
Ludger Rüschendorf focuses on Applied mathematics, Mathematical optimization, Portfolio, Combinatorics and Discrete mathematics.
Ludger Rüschendorf works mostly in the field of Applied mathematics, limiting it down to concerns involving Random variable and, occasionally, Expected value.
His study looks at the relationship between Mathematical optimization and topics such as Spectral risk measure, which overlap with Dynamic risk measure and Coherent risk measure.
His Portfolio study incorporates themes from Value at risk, Stochastic ordering and Econometrics.
His Combinatorics research is multidisciplinary, relying on both Class, Upper and lower bounds, Type and Moment.
His Discrete mathematics research includes elements of Pure mathematics, Multivariate random variable, Asymptotic distribution, Limit and Markov chain.
He most often published in these fields:
- Applied mathematics (24.89%)
- Mathematical optimization (19.31%)
- Portfolio (15.88%)
What were the highlights of his more recent work (between 2015-2021)?
- Portfolio (15.88%)
- Applied mathematics (24.89%)
- Econometrics (12.02%)
In recent papers he was focusing on the following fields of study:
The scientist’s investigation covers issues in Portfolio, Applied mathematics, Econometrics, Mathematical optimization and Marginal distribution.
His Portfolio research is multidisciplinary, incorporating perspectives in Series and Domain.
His study in the field of Martingale is also linked to topics like Comparison results.
His Econometrics research is multidisciplinary, incorporating elements of Model risk, Statistics, Stochastic ordering, Extension and Function.
His research combines Stochastic game and Mathematical optimization.
His Marginal distribution study integrates concerns from other disciplines, such as Value at risk, Dual, Upper and lower bounds, No-arbitrage bounds and Relaxation.
Between 2015 and 2021, his most popular works were:
- Value-at-Risk Bounds with Variance Constraints (47 citations)
- How robust is the value-at-risk of credit risk portfolios? (24 citations)
- Risk bounds for factor models (21 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Normal distribution
- Mathematical analysis
Ludger Rüschendorf mostly deals with Econometrics, Portfolio, Upper and lower bounds, Marginal distribution and Copula.
The study incorporates disciplines such as Minimum-variance unbiased estimator, Model risk and Feature, Statistics in addition to Econometrics.
His work carried out in the field of Portfolio brings together such families of science as Distribution, Series, Function, Monotonic function and Domain.
His research in Upper and lower bounds focuses on subjects like Combinatorics, which are connected to Factor analysis, Range, Coherent risk measure, Moment and Standard deviation.
His Marginal distribution study combines topics in areas such as Systematic risk, No-arbitrage bounds and Extension.
In Discrete mathematics, Ludger Rüschendorf works on issues like Multivariate statistics, which are connected to Applied mathematics.
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