Advances in Statistical Methods for Time Series Analysis

Dear Colleagues,

Time series analysis constitutes a cornerstone in understanding the dynamics of the key phenomena we observe. The intersection of statistics, mathematics, and econometrics plays a crucial role in understanding and analyzing such phenomena, enabling researchers to uncover patterns, forecast trends, and make informed decisions addressing contemporary challenges in fields such as economics and finance, among others. As such, we are pleased to announce a Special Issue dedicated to "Advances in Statistical Methods for Time Series Analysis", aiming to explore the latest developments and applications in this critical area of research.

This Special Issue invites contributions that advance the theoretical foundations, methodological innovations, and practical applications of statistical methods for analyzing time series data.

We welcome submissions of original research articles that contribute to the advancement of knowledge in statistical methods for time series analysis. Both theoretical developments and empirical studies are encouraged. Additionally, interdisciplinary studies that bridge the gaps between statistics, mathematics, and econometrics are highly valued.

We look forward to receiving your submissions and fostering fruitful discussions in this rapidly evolving field.

Dr. Paolo Pagnottoni
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Mathematics is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

• statistics for time series analysis
• mathematical methods for time series analysis
• time series analysis in economics, finance, engineering, healthcare, and medicine
• econometric methods for time series
• time series forecasting
• multivariate methods for economics and finance
• risk management
• machine learning methods for time series analysis and forecasting
• artificial intelligence methods for time series analysis and forecasting
• network and neural network models
• alternative time series data analysis and forecasting
• financial time series analysis and digital finance
• cryptocurrency data analysis and forecasting
• time series methods of climate change impacts on population, economics, and finance