Stochastics-An International Journal of Probability and Stochastic Processes

Scope & Guideline

Charting New Territories in Statistical Analysis

Introduction

Immerse yourself in the scholarly insights of Stochastics-An International Journal of Probability and Stochastic Processes with our comprehensive guidelines detailing its aims and scope. This page is your resource for understanding the journal's thematic priorities. Stay abreast of trending topics currently drawing significant attention and explore declining topics for a full picture of evolving interests. Our selection of highly cited topics and recent high-impact papers is curated within these guidelines to enhance your research impact.
LanguageEnglish
ISSN1744-2508
PublisherTAYLOR & FRANCIS LTD
Support Open AccessNo
CountrySwitzerland
TypeJournal
Converge1975, from 1979 to 1984, from 2007 to 2024
AbbreviationSTOCHASTICS / Stochastics
Frequency8 issues/year
Time To First Decision-
Time To Acceptance-
Acceptance Rate-
Home Page-
Address2-4 PARK SQUARE, MILTON PARK, ABINGDON OR14 4RN, OXON, ENGLAND

Aims and Scopes

The journal 'Stochastics: An International Journal of Probability and Stochastic Processes' focuses on advancing the theoretical and applied aspects of probability and stochastic processes. It serves as a platform for disseminating significant research findings that contribute to the understanding of stochastic phenomena in various fields.
  1. Probability Theory:
    The journal publishes research that explores foundational aspects of probability, including limit theorems, convergence properties, and stochastic calculus.
  2. Stochastic Processes:
    It covers a wide array of stochastic processes, including Markov processes, Lévy processes, and branching processes, focusing on their theoretical properties and applications.
  3. Stochastic Differential Equations (SDEs):
    Research related to the existence, uniqueness, and stability of solutions to SDEs, as well as their applications in various domains like finance and biology, is a core focus.
  4. Control Theory and Optimization:
    The journal features studies that integrate stochastic processes with control theory, particularly in optimizing decisions under uncertainty, such as in finance and risk management.
  5. Statistical Applications:
    Articles often explore statistical methodologies applied to stochastic models, including estimation techniques and asymptotic properties, enhancing the practical applicability of stochastic theory.
  6. Applications in Finance and Insurance:
    There is a consistent emphasis on financial mathematics and actuarial science, particularly in the context of option pricing, risk assessment, and insurance models.
The journal has seen a dynamic shift in its thematic focus, with several emerging topics gaining traction in the recent publications. These trends reflect the evolving landscape of research in probability and stochastic processes.
  1. Risk-sensitive Stochastic Control:
    An increasing number of articles are addressing risk-sensitive approaches in stochastic control, particularly in financial applications and health models, reflecting a growing interest in managing risk under uncertainty.
  2. Stochastic Modeling in Epidemiology:
    There is a marked rise in research applying stochastic models to epidemiological studies, especially in the context of infectious diseases like COVID-19, highlighting the relevance of stochastic processes in public health.
  3. Advanced SDE Techniques:
    Recent trends show a surge in the application of advanced techniques for solving stochastic differential equations, including those driven by Lévy processes and fractional Brownian motion.
  4. Mean-Field and Nonlocal Stochastic Models:
    Emerging themes include mean-field games and nonlocal interactions in stochastic models, which are gaining attention for their applications in various fields such as finance and population dynamics.
  5. Asymptotic Analysis and Large Deviations:
    Research focusing on asymptotic behaviors and large deviation principles is increasingly prominent, reflecting a deeper exploration of tail behaviors and extreme events in stochastic processes.

Declining or Waning

While the journal continuously evolves, certain themes have shown signs of declining prominence in recent years. The following areas appear to be waning in focus based on the publication trends.
  1. Classical Statistical Methods:
    There has been a noticeable decline in papers focusing on traditional statistical methods applied to stochastic processes, as newer methodologies gain traction.
  2. Non-stochastic Models:
    Research that does not incorporate stochastic elements, such as purely deterministic models, has become less frequent, indicating a shift towards more complex stochastic analyses.
  3. Discrete-time Models:
    There is a reduction in publications centered on discrete-time stochastic models, with a greater emphasis on continuous-time processes and their applications.
  4. Linear Stochastic Systems:
    Research focused exclusively on linear stochastic systems has decreased as interest grows in nonlinear dynamics and more complex system behaviors.

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