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.date.updated

2021-03-07T05:16:58Z

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.identifier.uri

https://hdl.handle.net/10161/22428

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robo-advisor

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wealthfront

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betterment

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Schwab

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portfolio allocation

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Portfolio rebalancing

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Portfolio monitoring

dc.title

Robo-Advisor Methodologies

dc.type

Report

duke.contributor.orcid

Wong, Eugene Lu Xian|0000-0003-2074-7374

pubs.organisational-group

Student

pubs.organisational-group

Duke

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