Results 131 to 140 of about 8,616 (247)
International Journal of Analysis and Applications, 2019 Considering Lipschitz functions which are not necessarily Fr´echet differentiable, we obtain a non-smooth version of Lakshmikantham’s theorem in finite dimensional ordered Banach spaces . We also present an application of the obtained result in dynamical
-- Zohari, -- Mardanbeigi
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Pathwise uniqueness for a SDE with non-Lipschitz coefficients
Stochastic Processes and their Applications, 2002 Let \(B\subseteq \mathbb R^ {n}\) be the closed unit ball, \(W\) a standard \(n\)-dimensional Wiener process. The stochastic differential equation \[ dX = -cX\,dt + \{2(1-\| X\| ^ 2)\}^ {1/2} \,dW\tag{1} \] is studied. From a well-known result by \textit{T.\ Yamada} and \textit{S.\ Watanabe} [J.\ Math.\ Kyoto Univ.\ 11, 155--167 (1971; Zbl 0236.60037)]
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Measure‐valued processes for energy markets
Mathematical Finance, Volume 35, Issue 2, Page 520-566, April 2025.Abstract We introduce a framework that allows to employ (non‐negative) measure‐valued processes for energy market modeling, in particular for electricity and gas futures. Interpreting the process' spatial structure as time to maturity, we show how the Heath–Jarrow–Morton approach can be translated to this framework, thus guaranteeing arbitrage free ...
Christa Cuchiero +3 more
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Robust Bernoulli Mixture Models for Credit Portfolio Risk
Mathematical Finance, EarlyView.ABSTRACT This paper presents comparison results and establishes risk bounds for credit portfolios within classes of Bernoulli mixture models, assuming conditionally independent defaults that are stochastically increasing in a common risk factor. We provide simple and interpretable conditions on conditional default probabilities that imply a comparison ...
Jonathan Ansari, Eva Lütkebohmert
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Reinforcement Learning for Jump‐Diffusions, With Financial Applications
Mathematical Finance, EarlyView.ABSTRACT We study continuous‐time reinforcement learning (RL) for stochastic control in which system dynamics are governed by jump‐diffusion processes. We formulate an entropy‐regularized exploratory control problem with stochastic policies to capture the exploration–exploitation balance essential for RL.
Xuefeng Gao, Lingfei Li, Xun Yu Zhou
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Generalized Newton’s method for solving nonlinear and nondifferentiable algebraic systems
Journal of Numerical Analysis and Approximation Theory, 2015 In this paper a model based on non-smooth equations is proposed for solving a non-linear and non-differential equation obtained by discretization of a quasi-variational inequality that models the frictional contact problem. The main aim of this paper is
Nicolae Pop
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Never, Ever Getting Started: On Prospect Theory Without Commitment
Mathematical Finance, EarlyView.ABSTRACT Prospect theory is arguably the most prominent alternative to expected utility theory. We study the investment or gambling behavior of a prospect theory decision maker who is aware of his time‐inconsistency but lacks commitment. For the empirically relevant prospect theory specifications, we obtain the extreme prediction that such a decision ...
Sebastian Ebert, Philipp Strack
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Mathematical Finance, EarlyView.ABSTRACT This study develops a novel multivariate stochastic framework for assessing systemic risks, such as climate and nature‐related shocks, within production or financial networks. By embedding a linear stochastic fluid network, interpretable as a generalized vector Ornstein–Uhlenbeck process, into the production network of interdependent ...
Giovanni Amici +3 more
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Random Carbon Tax Policy and Investment Into Emission Abatement Technologies
Mathematical Finance, EarlyView.ABSTRACT We analyze the problem of a profit‐maximizing electricity producer, subject to carbon taxes, who decides on investments into CO2$\rm CO_2$ abatement technologies. We assume that the carbon tax policy is random and that the investment in the abatement technology is divisible, irreversible, and subject to transaction costs.
Katia Colaneri +2 more
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Sensitivity analysis for generalized estimating equation with non‐ignorable missing data
Scandinavian Journal of Statistics, EarlyView.Abstract Many incomplete‐data statistical inference procedures are developed under the missing at random (MAR) assumption. However, the MAR assumption has been criticized as being overly strong for real‐data problems, and is unverifiable by using observed data. To handle data that are missing not at random (MNAR), sensitivity analysis has been proposed
Hui Gong, Kin Wai Chan
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