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Robo-Advisor Methodologies

dc.contributor.author Wong, Eugene Lu Xian
dc.date.accessioned 2021-03-07T05:16:59Z
dc.date.available 2021-03-07T05:16:59Z
dc.date.issued 2021-02-26
dc.identifier.uri https://hdl.handle.net/10161/22428
dc.description.abstract The takeover of robo advisors in the classic field of investment management is an emerging trend across the industry. Today, most robo-advisors are build on the fundamental principles of the modern portfolio theory, with the objective in obtaining the optimal portfolio that provides the highest expected returns given the risk. Although robo-advisors are already widely known, the inner workings of each robo-advisor remains obscured. This paper will provide a deep insight in the methodologies behind the three major robo-advisors in the market, namely, Betterment, Schwab Intelligent Portfolio and Wealthfront, and will compare and contrast the robo-advisors through three factors, that is, asset allocation, portfolio rebalancing and monitoring.
dc.subject robo-advisor
dc.subject wealthfront
dc.subject betterment
dc.subject Schwab
dc.subject portfolio allocation
dc.subject Portfolio rebalancing
dc.subject Portfolio monitoring
dc.title Robo-Advisor Methodologies
dc.type Report
duke.contributor.id Wong, Eugene Lu Xian|1027773
dc.date.updated 2021-03-07T05:16:58Z
pubs.organisational-group Student
pubs.organisational-group Duke
duke.contributor.orcid Wong, Eugene Lu Xian|0000-0003-2074-7374


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