Journal of Behavioral Finance

Call for Papers
Journal of Behavioural Finance
Statistical and Machine Learning for Investor Modelling

Behavioral finance is the study of how the psychology of investors affects personal investment and market outcomes. Investment dealerships and banks need to develop tools, based on rigorous research about and modelling of investment behaviours, to provide automated support for retail investors and financial advisors in selecting, managing, and evaluating investment portfolios. The historic difficulty in designing these tools lies in specifying the complex mathematical structure that models investor behavior in the presence of market conditions. Machine learning offers a data-driven approach with less specification of the data generating process.

Financial industry has recently started using machine learning in personal finance applications, such as risk modelling, return forecasting, portfolio construction, financial distress prediction, and so forth. Increasingly prevalent is the use of machine learning techniques to analyze retail investor investment behaviors, such as securities trading, insurance, loans, and consumption. Applying machine learning and AI to model investor behaviors is a natural partnership.

This call for papers aims to provide a space for financial researchers in academia and industry to bridge the gap between theory and practice, and share recent research in this new and evolving area. This call for papers will bring together theoretical and industrial machine learners, quantitative finance experts, financial industry practitioners, and fintech entrepreneurs to share their understanding of how AI can be employed to better model investor behaviors, and guide the next steps in the research path of investor modelling and machine learning.

We invite research, tutorials, research papers as well as opinion pieces on machine learning for investor modelling, with scopes and topics broadly defined by:
● The design and implementation of machine learning and statistical models that estimate investor behavior:
○ informed by market events, including news and social media,
○ managed by robo-, financial and hybrid advisors with differing discretionary licenses,
○ guided by financial health, risk tolerance, and investment goals
● Sentiment analysis of investor and financial advisor communications using different datasets (phone calls, textual correspondence, or other alternative data sources).
● The role of AI/Decision Support Systems in Fintech designed to support retail investors in making better financial decisions.
● Investment recommendation systems for portfolio construction and management
Papers are encouraged from financial industry practitioners that introduce domain-specific problems and challenges to academic researchers. These papers should describe problems that can inspire new research directions in academia, and should serve to bridge the information gap between academia and the financial industry. Additionally, tutorials are encouraged from academic researchers that explain current solutions to challenges related to the technical areas previously mentioned. These tutorials will serve as an introduction and enable financial industry practitioners to employ/adapt the latest academic research to their use-cases.

Submission instructions
Submission instructions for papers submitted to Taylor and Francis can be found at: https://www.tandfonline.com/action/authorSubmission?show=instructions&journalCode=hbhf20
Once submitted to Taylor and Francis, please e-mail the manuscript title and that you are submitting to this special issue to Brian Bruce (Editor-in-Chief, [email protected]) and John R.J. Thompson (Special Issue Editor, [email protected])
The special call will be accepting submissions until June 30th 2024. All research articles in Journal of Behavioral Finance will undergo rigorous peer review, based on double blind anonymous refereeing by at least two anonymous referees.

Guest editors
Matt Davison (Western University, Canada), Yongjae Lee (Ulsan National Institute of Science and Technology), Dhagash Mehta (BlackRock, Inc.), Alberto G. Rossi (Georgetown University), John R.J. Thompson (University of British Columbia, Canada)

Keywords
Economics, Finance, Business & Industry
Computer Science
Mathematics & Statistics

Submission instructions
Submission instructions for papers submitted to Taylor and Francis can be found at: https://www.tandfonline.com/action/authorSubmission?show=instructions&journalCode=hbhf20
Once submitted to Taylor and Francis, please e-mail the manuscript title and that you are submitting to this special issue to Brian Bruce (Editor-in-Chief, [email protected]) and John R.J. Thompson (Special Issue Editor, [email protected])
The special call will be accepting submissions until June 30th 2024. All research articles in Journal of Behavioral Finance will undergo rigorous peer review, based on double blind anonymous refereeing by at least two anonymous referees.

Instructions for AuthorsSubmit an Article