Future trends and models for managing risk and return

M. Tony Via

Chapter 12 in Understanding Investment Risk and Return, 2025, pp 262-285 from Edward Elgar Publishing

Abstract: This chapter discusses emerging trends and research methodologies related to risk and return. Improvements in sensor technology in recent years and the ability to store data in digital formats have created a vast proliferation of machine-readable data worldwide. Coupled with the rapid increase in computing power in recent decades, the abundance of data is leading to the dominance of artificial intelligence and machine learning methods over traditional factor modeling in financial research. These nascent developments have introduced a greater potential for unforeseen risks, especially as humans become more connected and behavioral science trends make more of an impact. New areas such as “explainable AI” and prompt engineering have risen to improve understanding of these systems. These innovations have expanded the need for certified experts in emerging subfields of financial risk, and the chapter closes with a discussion of risk-based financial certification agencies and programs.

Keywords: Factor modeling; Machine learning; AI; Behavioral science; Explainable AI; Prompt engineering (search for similar items in EconPapers)
Date: 2025
ISBN: 9781035339716
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.elgaronline.com/doi/10.4337/9781035339723.00025 (application/pdf)
Our link check indicates that this URL is bad, the error code is: 403 Forbidden

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:elg:eechap:23600_12

Ordering information: This item can be ordered from
http://www.e-elgar.com

Access Statistics for this chapter

More chapters in Chapters from Edward Elgar Publishing
Bibliographic data for series maintained by Jack Sweeney ().