journal: Random Operators and Stochastic Equations

Impact Factor: 0.4

Published since January 1, 1993

Random Operators and Stochastic Equations

ISSN: 1569-397X

Editor-in-chief: Vyacheslav Girko

Managing Editor: S. Molchanov

Editorial Board: L. Accardi, Sergio Albeverio, R. Carmona, G. Casati, N. Christopeit, C. Domanski, I. Ibragimov, Werner Kirsch, A. Klein, N. Leonenko, Philippe Loubaton, E. Orsingher, L. Pastur, Albert Shiryaev, A.F. Turbin, Alexandre Veretennikov

About this journal

Objective
Random Operators and Stochastic Equations is devoted to the theory of random operators and stochastic analysis. Contributions on theoretical aspects, as well as on physical and technical applications are considered for publication.

Topics

general theory of linear random operators,
theory of random matrices, chaos in classical and quantum mechanics,
stochastic differential equations,
Brownian motion theory,
neural networks theory,
regression analysis,
multivariate statistical analysis,
systems of linear algebraic equations with random coefficients,
spectral decomposition of the solutions of operator stochastic equations,
pattern recognition,
discriminant analysi
stochastic control theory.

Article formats
Research articles

Information on submission process

Your Benefits

Your benefits:

Leading experts in the field of random operators and stochastic equations from all over the world
Cutting-edge research results within theoretical and applied approaches
High-quality peer review

Abstracting and Indexing

Random Operators and Stochastic Equations is covered by the following services:

Baidu Scholar
CNKI Scholar (China National Knowledge Infrastructure)
CNPIEC - cnpLINKer
Dimensions
EBSCO (relevant databases)
EBSCO Discovery Service
Engineering Village
Genamics JournalSeek
Google Scholar
Inspec
Japan Science and Technology Agency (JST)
J-Gate
JournalGuide
JournalTOCs
KESLI-NDSL (Korean National Discovery for Science Leaders)
Mathematical Reviews (MathSciNet)
MyScienceWork
Naver Academic
Naviga (Softweco)
Primo Central (ExLibris)
ProQuest (relevant databases)
Publons
QOAM (Quality Open Access Market)
ReadCube
Scilit
SCImago (SJR)
SCOPUS
Semantic Scholar
Sherpa/RoMEO
Summon (ProQuest)
TDNet
Ulrich's Periodicals Directory/ulrichsweb
WanFang Data
Web of Science - Emerging Sources Citation Index
WorldCat (OCLC)
X-MOL
Yewno Discover
zbMATH Open

Supplementary Materials

Topics

Volume 32 Issue 1

March 2024

Publicly Available March 1, 2024

Frontmatter

Page range: i-iv

Download PDF

January 11, 2024

On a reaction diffusion problem with a moving impulse on boundary

Alioune Coulibaly

Page range: 1-12

Abstract

We study an asymptotic problem of a semilinear partial differential equation (PDE) with Neumann boundary condition, periodic coefficients and highly oscillating drift and nonlinear terms. Our analysis focuses on the double limiting behavior of the PDE-solution perturbed by ε (viscosity parameter) and δ (scaling coefficient) both tending to zero. To do so, we state basic properties of the large deviations principle (LDP) and we express the logarithmic asymptotic of the PDE-solution. Particularly, we provide it for the case when ε converges more quickly than δ.

January 11, 2024

Backward doubly stochastic differential equations driven by fractional Brownian motion with stochastic integral-Lipschitz coefficients

Assane Ndiaye, Sadibou Aidara, Ahmadou Bamba Sow

Page range: 13-25

Abstract

This paper deals with a class of backward doubly stochastic differential equations driven by fractional Brownian motion with Hurst parameter H greater than 1 2 {\frac{1}{2}} . We essentially establish the existence and uniqueness of a solution in the case of stochastic Lipschitz coefficients and stochastic integral-Lipschitz coefficients. The stochastic integral used throughout the paper is the divergence-type integral.

February 1, 2024

Stochastic controls of fractional Brownian motion

Ikram Hamed, Adel Chala

Page range: 27-39

Abstract

We consider a stochastic control problem for a non-linear forward-backward stochastic differential equation driven by fractional Brownian motion, with Hurst parameter H ∈ ( 0 , 1 ) {H\in(0,1)} , in the case where the set of the control domain is convex. We provide an estimation of the solution and establish the necessary and sufficient optimality conditions in the form of the stochastic maximum principle. We apply the theory to solve a linear quadratic stochastic control problem.

February 1, 2024

QMLE for periodic absolute value GARCH models

Walid Slimani, Ines Lescheb, Mouloud Cherfaoui

Page range: 41-61

Abstract

Periodic generalized autoregressive conditionally heteroscedastic (PGARCH) models were introduced by Bollerslev and Ghysels [T. Bollerslev and E. Ghysels, Periodic autoregressive conditional heteroscedasticity, J. Bus. Econom. Statist. 14 1996, 2, 139–151]; these models have gained considerable interest and continued to attract the attention of researchers. This paper is devoted to extensions of the standard absolute value GARCH (AVGARCH) model to the periodically time-varying coefficients (PAVGARCH) one. In this class of models, the parameters are allowed to switch between different regimes. Moreover, these models allow to integrate asymmetric effects in the volatility, Firstly, we give necessary and sufficient conditions ensuring the existence of stationary solutions (in the periodic sense). Secondary, a quasi-maximum likelihood (QML) estimation approach for estimating the PAVGARCH model is developed. The strong consistency and the asymptotic normality of the estimator are studied given mild regularity conditions, requiring strict stationarity and the finiteness of moments of some order for the errors term. Next, we present a set of numerical experiments illustrating the practical relevance of our theoretical results. Finally, we apply our model to two foreign exchange rates: of Algerian Dinar to the European currency Euro (Euro/Dinar) and the American currency Dollar (Dollar/Dinar). This empirical work shows that our approach also outperforms and fits the data well.

February 20, 2024

The generalized canonical equations K ₁, K ₇, K ₁₆, K ₂₇. The REFORM method, the invariance principal method, the matrix expansion method and G-transform. The main stochastic canonical equations K ₁₀₀,...,K ₁₀₆ and the estimators G ₅₅,...,G ₅₈ of the MAGIC (Mathematical Analysis of General Invisible Components)

Vyacheslav L. Girko

Page range: 63-106

Abstract

The generalized version of the stochastic canonical equations K 1 , K 7 , K 16 {K_{1},K_{7},K_{16}} and K 27 {K_{27}} are founded under the generalized Lindeberg condition with the help of which the main MAGIC estimators G 55 , G 56 , G 57 , G 58 {G_{55},G_{56},G_{57},G_{58}} are found.

Ahead of Print / Just Accepted

Ahead of Print / Just Accepted

Volume 32 (2024)

Issue 1

Volume 31 (2023)

Volume 30 (2022)

Volume 29 (2021)

Volume 28 (2020)

Volume 27 (2019)

Volume 26 (2018)

Volume 25 (2017)

Volume 24 (2016)

Volume 23 (2015)

Volume 22 (2014)

Volume 21 (2013)

Volume 20 (2012)

Volume 19 (2011)

Volume 18 (2010)

Volume 17 (2009)

Volume 16 (2008)

Volume 15 (2007)

Volume 14 (2006)

Volume 13 (2005)

Volume 12 (2004)

Volume 11 (2003)

Volume 10 (2002)

Volume 9 (2001)

Volume 8 (2000)

Volume 7 (1999)

Volume 6 (1998)

Volume 5 (1997)

Volume 4 (1996)

Volume 3 (1995)

Volume 2 (1994)

Volume 1 (1993)

Journal Impact Factor	0.4	2022, Journal Citation Reports (Clarivate, 2023)
5-year Journal Impact Factor	0.3	2022, Journal Citation Reports (Clarivate, 2023)
Journal Citation Indicator	0.19	2022, Journal Citation Reports (Clarivate, 2023)
CiteScore	0.6	2022, Scopus (Elsevier B.V., 2023)
SCImago Journal Rank	0.234	2022, SJR (Scimago Lab, 2023; Data Source: Scopus)
Source Normalized Impact per Paper	0.415	2022, CWTS Journal Indicators (CWTS B.V., 2023; Data Source: Scopus)
Mathematical Citation Quotient	0.12

More information about journal rankings

Submit

Submission
.. is done electronically by emailing both a PDF file and the source files (LaTeX) to one of the Editors-in-Chief or to any member of the Editorial Board. See the Editorial Information for names and e-mail addresses.

Your benefits of publishing with us

Rapid online publication ahead-of-print with short turnaround times
Optional open access publication
Accepted papers will be published online first as DOI-citable, forward-linked articles for quickest possible visibility for the scientific community
Every article easily discoverable because of SEO and comprehensive abstracting and indexing services
Convenient citation tracking via e-mail alert
Secure archiving by De Gruyter and the independent archiving service Portico
Professional sales and marketing support

Submission process

Submission of your paper
Peer review process (you will be guided through every step)
Decision on your paper
If accepted: you have the option to publish it open access
Publication online and in print

Please note

Manuscripts must be written in clear and concise English
The authors can provide the names and e-mail addresses of up to four potential reviewers
Only unpublished material can be accepted, and authors may not republish their paper in the same or similar form. The decision on the acceptance is taken after a peer-reviewing procedure
Before submitting your article please have a look at our Instruction for Authors, Ethical Guidelines and our Copyright Transfer Agreement
Once your article is accepted you have the option to publish it open access
Our Repository Policy allows you to distribute 30 PDF copies of your published article to colleagues (the PDF has to include the information that it is an author's copy). Please also feel free to distribute the link to the online abstract
If you have any general questions please visit our FAQ page for authors

We look forward to receiving your manuscript!

Hybrid Open Access

Please note that authors from institutions with which we have a transformative agreement can publish open access without paying an article processing charge (APC). More information on the eligible institutions and articles can be found under the "Funding and Support" tab here.

Editorial

Editor-in-Chief
Vyacheslav Girko
Institute of Mathematics
Ukrainian National Academy of Sciences
Tereshchenkivska St. 3
01601 Kiev, Ukraine
E-mail: vgirko1946@gmail.com

Managing Editor
Stanislav Molchanov
Department of Mathematics and Statistics
University of North Carolina at Charlotte
9201 University City Blvd.
Charlotte, NC 28223-0001, USA
E-mail: smolchan@uncc.edu

Executive Secretary
Ganna Vladimirova
avladimirova1954@gmail.com

Editorial Board
Luigi Accardi
Department of Mathematics
Università degli Studi di Roma Tor Vergata
Via della Ricerca Scientifica
00133 Rome, Italy
E-mail: accardi@volterra.mat.uniroma2.it

Sergio Albeverio 
Institut für Angewandte Mathematik
Universität Bonn
Wegelerstr. 6
53115 Bonn, Germany
E-mail: albeverio@uni-bonn.de

Rene Carmona 
Department of Operations Research & Financial Engineering
Princeton University
Princeton, NJ 08544-5263, USA
E-mail: rcarmona@princeton.edu

Giulio Casati 
Department of Physics and Mathematics
University of Insubria
Via Valleggio 11
22100 Como, Italy
E-mail: giulio.casati@uninsubria.it

Norbert Christopeit 
Department of Economics
University of Bonn
Adenauerallee 24–42
53113 Bonn, Germany
E-mail: christopeit@uni-bonn.de

Czeslaw Domanski 
Institute of Econometrics and Statistics
University of Lódz
Ul. Revolucii 1905p, N41
90214 Lódz, Poland
E-mail: czedoman@uni.lodz.pl

Ildar Ibragimov 
Laboratory of Statistical Methods
Petersburg Department of Steklov Institute of Mathematics
Fontanka 27
191023 St. Petersburg, Russia
E-mail: ibr32@pdmi.ras.ru

Werner Kirsch 
Lehrgebiet Stochastik Fakultät für Mathematik und Informatik
FernUniversität Hagen
58084 Hagen, Germany
E-mail: werner.kirsch@fernuni-hagen.de

Abel Klein 
Department of Mathematics
University of California, Irvine
241 Multipurpose Science & Technology Building
Irvine, CA 92697-3875, USA
E-mail: aklein@math.uci.edu

Nikolai Leonenko 
School of Mathematics
Cardiff University
Senghennydd Road
Cardiff CF24 4AG, UK
E-mail: leonenkon@Cardiff.ac.uk

Philippe Loubaton
IGM LabInfo, UMR8049
Institut Gaspard Monge/Electronique
Université de Marne la Vallée
5 Boulevard Descartes
Cité Descartes, Champs sur Marne
77454 Marne la Vallée Cedex 2, France
E-mail: loubaton@univ-mlv.fr

Stanislav Molchanov 
Department of Mathematics and Statistics
University of North Carolina at Charlotte
9201 University City Blvd.
Charlotte, NC 28223-0001, USA
E-mail: smolchan@uncc.edu

Enzo Orsingher 
Dipartimento di Statistica, Probabilità e Statistiche Applicate
Università di Roma La Sapienza
Piazzale Aldo Moro 5
00185 Rome, Italy
E-mail: orsinghe@pow2.sta.uniroma1.it

Leonid Pastur 
B. Verkin Institute for Low Temperature Physics and Engineering
National Academy of Sciences of Ukraine
Lenin St. 47
Kharkov 61103, Ukraine
E-mail: lpastur@ilt.kharkov.ua

Mykola Portenko 
Institute of Mathematics
Ukrainian National Academy of Sciences
Tereshchenkivska St. 3
01601 Kiev, Ukraine
E-mail: portenko@imath.kiev.ua

Albert Shiryaev 
Department of Probability Theory and Mathematical Statistics
Steklov Mathematical Institute
Russian Academy of Sciences
Gubkina St. 8
119991 Moscow, Russia
E-mail: albertsh@mi.ras.ru

Anatoly F. Turbin 
Institute of Mathematics
Ukrainian National Acaemy of Sciences
Tereshchenkivska St. 3
01601 Kiev-4, Ukraine
E-mail: turbin@imath.kiev.ua

Alexandre Veretennikov 
School of Mathematics
University of Leeds
LS2 9JT Leeds
UK
E-mail: a.veretennikov@leeds.ac.uk

(Deutsch)

Online ISSN: 1569-397X
Type: Journal
Language: English
Publisher: De Gruyter
First published: January 1, 1993
Publication Frequency: 4 Issues per Year
Audience: researchers in the field of the theory of random operators and stochastic analysis