Probability, Uncertainty and Quantitative Risk

ISSN: 2367-0126 (Online)

Description

Considering the recent and very dynamical development of the theory of backward stochastic differential equations which, thanks to its vast field of applications in stochastic control, games, finance, PDEs and SPDEs has attracted many researchers, but which also has opened the development of other new research subjects as those of nonlinear expectation and path-dependent PDEs, it is important to accompany and to stimulate the future development with a journal which, on one side, is dedicated to these topics, but forms on the other side also a bridge to new approaches in probability theory in a larger sense and is open for new developments.

The journal Probability, Uncertainty and Quantitative Risk emerges as the times require. The objective of the journal is to publish works of high standard in the cutting-edge topics of

1. Ambiguity and Knightian Uncertainty, mathematical modelling under uncertainty,  

2. Backward stochastic differential equations, non-linear expectation and  path-dependent PDEs,

3. Dynamic risk measures,

4. Mathematical modelling in finance and economics,

5. Quantitative risks,

6. Recursive Utility,

7. Stochastic dynamical systems under model uncertainty,

8. Uncertainty quantification,

9. Computational aspects and numerical methods related with the above topics,

10. Related topics, among them namely also related statistics and data science,

11. Opening to new approaches and high quality manuscripts in Theoretical and Applied Probability Theory.

The related topics can be understood in a rather large sense, going from mathematical approaches, where the above topics play a key role or constitute an important tool, like backward SDE methods in stochastic control problems, differential games in the context of uncertainty which may be, e.g., related with asymmetric information, to a vast field of applications as, for instance, mean-field approaches in finance or in modelling systematic risk, but concerning also new approaches and developments in stochastic analysis and probability theory.

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