Skip to main content

Articles

Page 1 of 1

  1. We study fully nonlinear second-order (forward) stochastic PDEs. They can also be viewed as forward path-dependent PDEs and will be treated as rough PDEs under a unified framework. For the most general fully n...

    Authors: Rainer Buckdahn, Christian Keller, Jin Ma and Jianfeng Zhang
    Citation: Probability, Uncertainty and Quantitative Risk 2020 5:7
  2. It is well known that the minimal superhedging price of a contingent claim is too high for practical use. In a continuous-time model uncertainty framework, we consider a relaxed hedging criterion based on acce...

    Authors: Ludovic Tangpi
    Citation: Probability, Uncertainty and Quantitative Risk 2020 5:6
  3. The recently proposed numerical algorithm, deep BSDE method, has shown remarkable performance in solving high-dimensional forward-backward stochastic differential equations (FBSDEs) and parabolic partial diffe...

    Authors: Jiequn Han and Jihao Long
    Citation: Probability, Uncertainty and Quantitative Risk 2020 5:5
  4. In this paper, we consider a class of nonlinear regression problems without the assumption of being independent and identically distributed. We propose a correspondent mini-max problem for nonlinear regression...

    Authors: Qing Xu and Xiaohua (Michael) Xuan
    Citation: Probability, Uncertainty and Quantitative Risk 2019 4:8
  5. An error occurred during the publication of an article in Probability, Uncertainty and Quantitative Risk. The article was published in volume 4 with a duplicate citation number.

    Authors:
    Citation: Probability, Uncertainty and Quantitative Risk 2019 4:7

    The original article was published in Probability, Uncertainty and Quantitative Risk 2019 4:5

  6. We develop a one-dimensional notion of affine processes under parameter uncertainty, which we call nonlinear affine processes. This is done as follows: given a set Θ of parameters for the process, we construct a ...

    Authors: Tolulope Fadina, Ariel Neufeld and Thorsten Schmidt
    Citation: Probability, Uncertainty and Quantitative Risk 2019 4:5

    The Publisher Correction to this article has been published in Probability, Uncertainty and Quantitative Risk 2019 4:7

  7. Conditional expectations (like, e.g., discounted prices in financial applications) are martingales under an appropriate filtration and probability measure. When the information flow arrives in a punctual way, ...

    Authors: Christophe Profeta and Frédéric Vrins
    Citation: Probability, Uncertainty and Quantitative Risk 2019 4:2
  8. We show that the comparison results for a backward SDE with jumps established in Royer (Stoch. Process. Appl 116: 1358–1376, 2006) and Yin and Mao (J. Math. Anal. Appl 346: 345–358, 2008) hold under more simpl...

    Authors: Christel Geiss and Alexander Steinicke
    Citation: Probability, Uncertainty and Quantitative Risk 2018 3:9

    The Correction to this article has been published in Probability, Uncertainty and Quantitative Risk 2019 4:6

  9. In this paper, we study strongly robust optimal control problems under volatility uncertainty. In the G-framework, we adapt the stochastic maximum principle to find necessary and sufficient conditions for the exi...

    Authors: Francesca Biagini, Thilo Meyer-Brandis, Bernt Øksendal and Krzysztof Paczka
    Citation: Probability, Uncertainty and Quantitative Risk 2018 3:8
  10. In this paper, we provide a valuation formula for different classes of actuarial and financial contracts which depend on a general loss process by using Malliavin calculus. Similar to the celebrated Black–Scho...

    Authors: Caroline Hillairet, Ying Jiao and Anthony Réveillac
    Citation: Probability, Uncertainty and Quantitative Risk 2018 3:7
  11. The main aim of this paper is to introduce the notion of risk excess measure, to analyze its properties, and to describe some basic construction methods. To compare the risk excess of one distribution Q w.r.t. a ...

    Authors: Olivier P. Faugeras and Ludger Rüschendorf
    Citation: Probability, Uncertainty and Quantitative Risk 2018 3:6
  12. Asset returns are modeled by locally bilateral gamma processes with zero covariations. Covariances are then observed to be consequences of randomness in variations. Support vector machine regressions on prices...

    Authors: Dilip B. Madan and Wim Schoutens
    Citation: Probability, Uncertainty and Quantitative Risk 2018 3:5
  13. We study the existence and uniqueness of a solution to path-dependent backward stochastic Volterra integral equations (BSVIEs) with jumps, where path-dependence means the dependence of the free term and genera...

    Authors: Ludger Overbeck and Jasmin A. L. Röder
    Citation: Probability, Uncertainty and Quantitative Risk 2018 3:4
  14. The objective of this paper is to provide a comprehensive study of the no-arbitrage pricing of financial derivatives in the presence of funding costs, the counterparty credit risk and market frictions affectin...

    Authors: Tomasz R. Bielecki, Igor Cialenco and Marek Rutkowski
    Citation: Probability, Uncertainty and Quantitative Risk 2018 3:2
  15. We consider the class of affine LIBOR models with multiple curves, which is an analytically tractable class of discrete tenor models that easily accommodates positive or negative interest rates and positive sp...

    Authors: Antonis Papapantoleon and Robert Wardenga
    Citation: Probability, Uncertainty and Quantitative Risk 2018 3:1
  16. We develop a dynamic optimization framework to assess the impact of funding costs on credit swap investments. A defaultable investor can purchase CDS upfronts, borrow at a rate depending on her credit quality,...

    Authors: Lijun Bo
    Citation: Probability, Uncertainty and Quantitative Risk 2017 2:12
  17. This paper provides sufficient conditions for the time of bankruptcy (of a company or a state) for being a totally inaccessible stopping time and provides the explicit computation of its compensator in a frame...

    Authors: Matteo Ludovico Bedini, Rainer Buckdahn and Hans-Jürgen Engelbert
    Citation: Probability, Uncertainty and Quantitative Risk 2017 2:10
  18. The paper presents a comprehensive model of a banking system that integrates network effects, bankruptcy costs, fire sales, and cross-holdings. For the integrated financial market we prove the existence of a p...

    Authors: Stefan Weber and Kerstin Weske
    Citation: Probability, Uncertainty and Quantitative Risk 2017 2:9
  19. Risks embedded in asset price dynamics are taken to be accumulations of surprise jumps. A Markov pure jump model is formulated on making variance gamma parameters deterministic functions of the price level. Es...

    Authors: Dilip B. Madan
    Citation: Probability, Uncertainty and Quantitative Risk 2017 2:8
  20. We apply to the concrete setup of a bank engaged into bilateral trade portfolios the XVA theoretical framework of (Albanese and Crépey2017), whereby so-called contra-liabilities and cost of capital are charged b...

    Authors: Claudio Albanese, Simone Caenazzo and Stéphane Crépey
    Citation: Probability, Uncertainty and Quantitative Risk 2017 2:7
  21. In this introductory paper to the issue, I will travel through the history of how quantitative finance has developed and reached its current status, what problems it is called to address, and how they differ f...

    Authors: Mauro Cesa
    Citation: Probability, Uncertainty and Quantitative Risk 2017 2:6
  22. We show the well-posedness of backward stochastic differential equations containing an additional drift driven by a path of finite q-variation with q∈[1,2). In contrast to previous work, we apply a direct fixpoin...

    Authors: Joscha Diehl and Jianfeng Zhang
    Citation: Probability, Uncertainty and Quantitative Risk 2017 2:5
  23. G-Brownian motion has a very rich and interesting new structure that nontrivially generalizes the classical Brownian motion. Its quadratic variation process is also a continuous process with independent and st...

    Authors: Zhengyan Lin and Li-Xin Zhang
    Citation: Probability, Uncertainty and Quantitative Risk 2017 2:4
  24. In this work we give a comprehensive overview of the time consistency property of dynamic risk and performance measures, focusing on a the discrete time setup. The two key operational concepts used throughout ...

    Authors: Tomasz R. Bielecki, Igor Cialenco and Marcin Pitera
    Citation: Probability, Uncertainty and Quantitative Risk 2017 2:3
  25. Default probability distributions are often defined in terms of their conditional default probability distribution, or their hazard rate. By their definition, they imply a unique probability density function. ...

    Authors: Charles S. Tapiero and Pierre Vallois
    Citation: Probability, Uncertainty and Quantitative Risk 2017 2:2
  26. In this paper, a new numerical scheme for a class of coupled forward-backward stochastic differential equations (FBSDEs) is proposed by using branching particle systems in a random environment. First, by the f...

    Authors: Dejian Chang, Huili Liu and Jie Xiong
    Citation: Probability, Uncertainty and Quantitative Risk 2016 1:9
  27. Authors: Shige Peng, Rainer Buckdahn and Juan Li
    Citation: Probability, Uncertainty and Quantitative Risk 2016 1:5
  28. We consider the problem of approximation of the solution of the backward stochastic differential equations in Markovian case. We suppose that the forward equation depends on some unknown finite-dimensional par...

    Authors: Yu A. Kutoyants
    Citation: Probability, Uncertainty and Quantitative Risk 2016 1:4
  29. We consider a strictly pathwise setting for Delta hedging exotic options, based on Föllmer’s pathwise Itô calculus. Price trajectories are d-dimensional continuous functions whose pathwise quadratic variations an...

    Authors: Alexander Schied and Iryna Voloshchenko
    Citation: Probability, Uncertainty and Quantitative Risk 2016 1:3
  30. Allowing for correlated squared returns across two consecutive periods, portfolio theory for two periods is developed. This correlation makes it necessary to work with non-Gaussian models. The two-period conic...

    Authors: Ernst Eberlein and Dilip B. Madan
    Citation: Probability, Uncertainty and Quantitative Risk 2016 1:1