Financial Econometrics and Machine Learning

Dear Colleagues,

The primary objective of this Special Issue is to showcase the latest developments in the field of financial econometrics and machine learning and provide a platform for researchers to share their insights, methodologies, and findings. We invite contributions that bridge the gap between econometric theory and machine learning applications, shedding light on the challenges, opportunities, and implications of this integration.

This Special Issue covers a wide range of pertinent topics that are suitable for exploration. These topics encompass, but are not limited to, asset pricing models incorporating machine learning techniques, portfolio optimization and asset allocation using advanced data analytics, volatility modeling and forecasting with machine learning algorithms, high-frequency trading and market microstructure analysis, risk management and credit scoring models utilizing machine learning, financial forecasting and macroeconomic modeling with machine learning, the interpretability and explainability of machine learning models in finance, model validation, and the robustness of machine learning applications in financial econometrics. Both theoretical and empirical contributions that provide novel insights, methodologies, and practical applications in this evolving field are also welcome. 

We look forward to receiving your submissions and to compiling an exceptional collection of articles that will advance our understanding of financial econometrics and machine learning. The ultimate aim is to explore the frontiers of this exciting field and uncover new avenues for knowledge and innovation.

Prof. Dr. Chihwa Kao
Dr. Zhonghui Zhang
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.

• machine learning
• financial econometrics
• asset pricing models
• portfolio optimization
• volatility modeling
• investment decision-making
• derivatives
• risk management
• credit analysis
• financial forecasting
• model validation
• robustness
• random matrix theory