Probability, Uncertainty and Quantitative Risk

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Content type: Research
| 16 April 2019

Law of large numbers and central limit theorem under nonlinear expectations

Authors: Shige Peng
Content type: Research
| 30 March 2019

The Cauchy problem of Backward Stochastic Super-Parabolic Equations with Quadratic Growth

Authors: Renzhi Qiu and Shanjian Tang
Content type: Research
| 11 February 2019

Piecewise constant martingales and lazy clocks

Authors: Christophe Profeta and Frédéric Vrins
Content type: Research
| 4 January 2019

Mixed deterministic and random optimal control of linear stochastic systems with quadratic costs

Authors: Ying Hu and Shanjian Tang
Content type: Research
| 28 December 2018

Existence, uniqueness and comparison results for BSDEs with Lévy jumps in an extended monotonic generator setting

Authors: Christel Geiss and Alexander Steinicke

Content type: Commentary
| 5 June 2017

A brief history of quantitative finance

Authors: Mauro Cesa
Content type: Research
| 26 June 2017

Credit, funding, margin, and capital valuation adjustments for bilateral portfolios

Authors: Claudio Albanese, Simone Caenazzo and Stéphane Crépey
Content type: Research
| 1 March 2017

Stochastic global maximum principle for optimization with recursive utilities

Authors: Mingshang Hu
Content type: Research
| 26 June 2017

The joint impact of bankruptcy costs, fire sales and cross-holdings on systemic risk in financial networks

Authors: Stefan Weber and Kerstin Weske
Content type: Research
| 1 December 2016

Backward-forward linear-quadratic mean-field games with major and minor agents

Authors: Jianhui Huang, Shujun Wang and Zhen Wu

Aims and scope

Probability, Uncertainty and Quantitative Risk is a high-quality, peer-reviewed, open-access journal reporting significant developments in modern probability theory, its relation to stochastic analysis and statistics, stochastic processes, their dynamics and control, as well as applications in domains such as finance, economics, biology, computer science, and the corresponding data analysis.

Aims and scope

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