Can asset management firms really benefit from AI and machine learning?

This paper will look at techniques from both an academic2 and industry machine learning perspective. Machine learning. When you hear those terms, what comes to mind is a science fiction movie where machines achieve consciousness—and trouble ensues.

Asset management can be broken into the following tasks: (1) portfolio construction, (2) risk management, (3) capital management, (4) infrastructure and deployment, and (5) sales and marketing. AI and Machine Learning: Practical Applications for Asset Management Firms (Part 1 of a 3-Part Series) AI. This is the second in a series of articles dealing with machine learning in asset management. Human involvement will still be critical for risk management and framework selection, but increasingly the strategy innovation process will be automated. Raghav Bharadwaj Last updated on April 3, 2020. This article focuses on portfolio construction using machine learning. The Journal of Financial Data Science, Spring 2020, 2 (1) 10-23. AI and Machine Learning for Asset Management Firms: Part 3 – Trip Planning .

To order reprints of this article, please contact David Rowe at d.rowe{at}pageantmedia.com or 646-891-2157. This is the second in a series of articles dealing with machine learning in asset management. Raghav is serves as Analyst at Emerj, covering AI trends across major industry updates, and conducting qualitative and quantitative research. 1. Introductory Thoughts Machine learning (ML) in finance can take on an (1) academic, (2) front office, (3) and a back-office form. AI and machine learning are real and relevant—even for tasks like asset management trip planning. (d.snow{at}firmai.org) 1. Machine Learning in Asset Management—Part 2: Portfolio Construction—Weight Optimization.

Machine learning will become increasingly important for asset management and most firms will be utilizing either machine learning tools or data within the next few years. Machine Learning in Investment Management and Asset Management – Current Applications . Derek Snow 1. is a doctoral candidate of finance at the University of Auckland in Auckland, New Zealand. This article focuses on portfolio weighting using machine learning. The techniques used in the front and back office falls within financial industry machine learning1.

Last updated on April 3, 2020, published by Raghav Bharadwaj. While it sounds improbable, it’s not. At best, you might dismiss the concepts as hype or the buzz word of the day.