Results 61 to 70 of about 51,902 (192)
Optimal Portfolio Choice With Cross‐Impact Propagators
Mathematical Finance, EarlyView.ABSTRACT We consider a class of optimal portfolio choice problems in continuous time where the agent's transactions create both transient cross‐impact driven by a matrix‐valued Volterra propagator, as well as temporary price impact. We formulate this problem as the maximization of a revenue‐risk functional, where the agent also exploits available ...
Eduardo Abi Jaber +2 more
wiley +1 more source
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
wiley +1 more source
A Model of Strategic Sustainable Investment
Mathematical Finance, EarlyView.ABSTRACT We study a problem of optimal irreversible investment and emission reduction formulated as a nonzero‐sum dynamic game between an investor with environmental preferences and a firm. The game is set in continuous‐time on an infinite‐time horizon.
Tiziano De Angelis +2 more
wiley +1 more source
Likelihood Estimation for Stochastic Differential Equations with Mixed Effects
Scandinavian Journal of Statistics, EarlyView.ABSTRACT Stochastic differential equations provide a powerful tool for modelling dynamic phenomena affected by random noise. When time series are observed for several experimental units, it is often the case that some of the parameters vary between the individual experimental units.
Fernando Baltazar‐Larios +2 more
wiley +1 more source
On fractional deviation operators
Le Matematiche, 1997 The so called fractional deviation operators are introduced. This class of integral transforms appears naturally from the study of iteration of fractional integrals of Riemann-Liouville type. Since B.
Carlos C. Peña
doaj
Repelled Point Processes With Application to Numerical Integration
Scandinavian Journal of Statistics, EarlyView.ABSTRACT We look at Monte Carlo numerical integration from a stochastic geometry point of view. While crude Monte Carlo estimators relate to linear statistics of a homogeneous Poisson point process (PPP), linear statistics of more regularly spread point processes can yield unbiased estimators with faster‐decaying variance, and thus lower integration ...
Diala Hawat +3 more
wiley +1 more source
Coupled Clustering in Hierarchical Matrices for the Oseen Problem
International Journal for Numerical Methods in Fluids, Volume 98, Issue 6, Page 751-765, June 2026.Fluid flow problems can be modelled by the Navier‐Stokes or, after linearization, by the Oseen equations. Their discretization results in linear systems in saddle point form which are typically very large and need to be solved iteratively. We propose a novel block structure for hierarchical matrices which is then used to build preconditioners for the ...
Jonas Grams, Sabine Le Borne
wiley +1 more source
A Novel Mixed‐Hybrid, Higher‐Order Accurate Formulation for Kirchhoff–Love Shells
Proceedings in Applied Mathematics and Mechanics, Volume 26, Issue 2, June 2026.ABSTRACT This paper presents a novel mixed‐hybrid finite element formulation for Kirchhoff–Love shells, designed to enable the use of standard C0$C^0$‐continuous higher‐order Lagrange elements. This is possible by introducing the components of the moment tensor as a primary unknown alongside the displacement vector, circumventing the need for C1$C^1 ...
Jonas Neumeyer, Thomas‐Peter Fries
wiley +1 more source
On MAP Estimates and Source Conditions for Drift Identification in SDEs
Proceedings in Applied Mathematics and Mechanics, Volume 26, Issue 2, June 2026.ABSTRACT We consider the inverse problem of identifying the drift in an stochastic differential equation (SDE) from n$n$ observations of its solution at M+1$M+1$ distinct time points. We derive a corresponding maximum a posteriori (MAP) estimate, we prove differentiability properties as well as a so‐called tangential cone condition for the forward ...
Daniel Tenbrinck +3 more
wiley +1 more source
International Journal of Robust and Nonlinear Control, Volume 36, Issue 9, Page 4957-4970, June 2026.ABSTRACT Data‐based learning of system dynamics allows model‐based control approaches to be applied to systems with partially unknown dynamics. Gaussian process regression is a preferred approach that outputs not only the learned system model but also the variance of the model, which can be seen as a measure of uncertainty.
Daniel Landgraf +2 more
wiley +1 more source