Who Benefits from Robo-advising?
UNIVERSITY OF TECHNOLOGY SYDNEY
Research Seminars in Finance
Topic: Who Benefits from Robo-advising? Evidence from Machine Learning
Speaker: Alberto Rossi, Georgetown University
Abstract: We study the effects of a large U.S. hybrid robo-adviser on the portfolios of previously self-directed investors. Across all investors, robo-advising reduces idiosyncratic risk by lowering the holdings of individual stocks and active mutual funds and raising exposure to low-cost indexed mutual funds. It further eliminates investors' home bias and increases investors' overall risk-adjusted performance, mainly by lowering investors' portfolio risk. We use a machine learning algorithm, known as Boosted Regression Trees (BRT), to explain the cross-sectional variation in the effects of advice on portfolio allocations and performance. Finally, we study the determinants of investors' sign-up and attrition.
Moderator: Thomas Matthys, University of Technology Sydney
Date: Wednesday, 26th August 2020
Time: 9.00 – 10.00 a.m. (Australian Eastern Standard Time)
Venue: This is on online Zoom webinar.
After registering, you will receive a confirmation email containing information on how to join the meeting, including an access link.
- The webinar will run for 45 minutes, followed by a 15 minute Q&A session.
- There will be a moderator for each seminar event, who will facilitate communication and resolve any technical issues.
- Participants can use the Q&A facility to ask questions during the presentation. The moderator will then alert the speaker and ask the questions raised.
Co-ordinator: Harry Scheule
Enquiries: Duncan Ford