Dear Colleagues,

In recent years, the fields of finance and statistics have witnessed tremendous growth in the volume and complexity of data. This has led to the emergence of big data analytics as a powerful tool for extracting insights, improving decision-making, and enhancing risk management in finance. Big data analytics is the process of collecting, processing, and analyzing large and complex datasets to reveal hidden patterns and relationships. As such, it has the potential to transform the way finance is conducted, from improving the accuracy of financial forecasts to detecting fraudulent activities. 

The aim of this Special Issue is to explore emerging trends and opportunities in the application of statistics and big data to finance. We seek to publish original research papers, reviews, and case studies that demonstrate the potential of big data analytics to drive innovation and transformation in finance. The subject matter will be aligned with the scope of the journal, which focuses on applied statistics, data science, and computational methods for solving real-world problems.

We invite submissions on the following themes, but not limited to:

• Risk management and regulatory compliance using big data;
• Financial forecasting and prediction using machine learning;
• High-frequency trading and algorithmic trading using big data;
• Sentiment analysis and social media analytics for financial markets;
• Big data analytics for fraud detection and prevention in finance;
• Portfolio optimization and asset allocation using big data;
• Natural language processing and text mining for financial analysis;
• Visualization and communication of big data insights in finance;
• Ethical and social implications of big data analytics in finance.

This Special Issue aims to showcase the latest advancements and innovations in the field of applied statistics and big data for finance. We look forward to receiving high-quality contributions from researchers, practitioners, and academics in this exciting and rapidly evolving area. 

Prof. Dr. Hossein Hassani
Dr. Xu Huang
Dr. Nadejda Komendantova
Guest Editors

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. Journal of Risk and Financial Management is an international peer-reviewed open access monthly 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 1400 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.

• applied statistics
• big data
• data analytics
• data science
• computational methods
• risk management
• regulatory compliance
• financial forecasting
• machine learning
• high-frequency trading
• algorithmic trading
• sentiment analysis
• social media analytics
• fraud detection
• fraud prevention
• portfolio optimization
• asset allocation
• natural language processing
• text mining
• visualization
• communication
• ethical implications
• social implications
• finance
• financial analysis
• financial markets