Advances in Financial Mathematics and Risk Management

Dear Colleagues,

Financial mathematics and risk management are two key areas in economics and in finance that heavily use mathematical modeling, statistical analysis, and computational techniques. In recent years, there has been a growing interest in incorporating artificial intelligence (AI) and machine learning (ML) into these fields to improve the accuracy, efficiency, and decision-making capabilities.

One significant advantage of AI and ML is their ability to analyze large datasets quickly and accurately. Financial institutions can use AI algorithms to identify patterns and trends in market data and make better-informed decisions about investments, portfolio management, and risk management. AI can also help identify potential risks and opportunities by analyzing data from multiple sources, such as news articles, social media, and financial reports, which can inform financial modeling and risk management strategies.

In financial mathematics, AI can help improve predictive models by identifying patterns and trends that may be difficult to identify through traditional statistical methods. This can lead to more accurate forecasting of market trends, asset prices, and other financial indicators. AI can also help identify optimal investment strategies and portfolio allocations based on risk tolerance, performance objectives, and other factors.

Risk management, on the other hand, can benefit from AI in several ways. For example, AI algorithms can analyze financial data in real-time, detect potential risks and market anomalies, and alert risk managers to take appropriate action. AI can also help with credit risk analysis, fraud detection, and compliance monitoring, among other areas. Furthermore, AI can provide a more comprehensive analysis of risk factors by incorporating non-financial data, such as geopolitical events and macroeconomic indicators, into risk models.

While there are significant benefits to incorporating AI into financial mathematics and risk management, there are also potential challenges and risks to consider. For example, AI algorithms may be subject to bias, which can lead to inaccurate or unfair decisions. Additionally, AI models may be difficult to interpret, which can cause it to be challenging to understand how decisions are made and to assess the validity of model outputs.

We welcome original research articles that explore, by using artificial intelligence, theoretical and applied aspects of economic and financial mathematics, risk management, and related fields, including but not limited to:

• Mathematical models of economic and financial markets;
• Risk measurement and management techniques;
• Portfolio optimization and asset allocation;
• Option pricing and derivatives;
• Credit risk analysis and management;
• Behavioral economics and decision making under uncertainty;
• Econometrics and data analysis;
• Regulation policy.

We welcome papers that use a range of methodologies, including empirical studies, theoretical models, and computational techniques. Submissions should be of high quality, original, and significantly contribute to the field of economic and financial mathematics and risk management.

Prof. Domenico Marino
Prof. Dr. Piluso Fabio
Prof. Dr. Jaime Gil Lafuente
Prof. Dr. Hussein A. Abdou
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. 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.

• artificial intelligence
• risk management
• portfolio optimization
• machine learning
• decision making