Results 51 to 60 of about 265 (178)

Asymptotics of Time‐Varying Processes in Continuous‐Time Using Locally Stationary Approximations

Journal of Time Series Analysis, EarlyView.
ABSTRACT We introduce a general theory on stationary approximations for locally stationary continuous‐time processes. Based on the stationary approximation, we use θ$$ \theta $$‐weak dependence to establish laws of large numbers and central limit type results under different observation schemes.
Robert Stelzer, Bennet Ströh
wiley   +1 more source

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, Luca Di Persio, Francesco Guida, Sara Svaluto‐Ferro   +3 more
wiley   +1 more source

A Characterization of Some Class Nonlinear Eigenvalue Problem in VELS

Sakarya Üniversitesi Fen Bilimleri Enstitüsü Dergisi, 2019
Değişken üs Lebesgue uzaylarında lineer olmayan özdeğer problemlerininbazı sınıflarının karakterizasyonunu araştıracağız.
Lütfi Akın
doaj   +1 more source

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, Eyal Neuman, Sturmius Tuschmann   +2 more
wiley   +1 more source

Navigating Supply Shocks: Sector Resilience and Production Prices Through Stochastic Input–Output Modeling

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, Gianluca Fusai, Anna Maria Gambaro, Daniele Marazzina   +3 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, Mogens Bladt, Michael Sørensen   +2 more
wiley   +1 more source

Global W1,p(·) estimate for renormalized solutions of quasilinear equations with measure data on Reifenberg domains

Advances in Nonlinear Analysis, 2018
In this paper, we prove the gradient estimate for renormalized solutions to quasilinear elliptic equations with measure data on variable exponent Lebesgue spaces with BMO coefficients in a Reifenberg flat domain.
Bui The Anh
doaj   +1 more source

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, Gabriel Mastrilli, Rémi Bardenet, Raphaël Lachièze‐Rey   +3 more
wiley   +1 more source

Bayesian Inference for Multivariate Monotone Densities

Scandinavian Journal of Statistics, EarlyView.
ABSTRACT We consider a nonparametric Bayesian approach to estimation and testing for a multivariate monotone density. Instead of following the conventional Bayesian approach of imposing a prior that satisfies the monotonicity restriction, we place a prior on the step heights via binning and a Dirichlet distribution. The resulting posterior distribution
Kang Wang, Subhashis Ghosal
wiley   +1 more source

Some mudular inequalities in Lebesgue spaces with variable exponent

, 2019
9pages
Izuki, Mitsuo, Noi, Takahiro, Sawano, Yoshihiro   +2 more
openaire   +3 more sources