Who Benefits from Robo-advising?

UNIVERSITY OF TECHNOLOGY SYDNEY
Finance Department
Research Seminars in Finance

Alberto Rossi

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.

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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.

Seminar protocols:

  • 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

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Acknowledgement of Country

UTS acknowledges the Gadigal people of the Eora Nation, the Boorooberongal people of the Dharug Nation, the Bidiagal people and the Gamaygal people, upon whose ancestral lands our university stands. We would also like to pay respect to the Elders both past and present, acknowledging them as the traditional custodians of knowledge for these lands.