Retail investors often make poor investing decisions due to behavioral factors. In recent years, smartphone apps such as Robinhood that promise to "democratize investing" have risen in popularity. These apps have allowed retail investors to trade stocks, options, and other securities easily and inexpensively, often commission-free. It seems plausible that the design patterns of these new apps may significantly influence trading behaviors of their users. For instance, since underperformance is caused by behavioral, rather than informational, factors, making trading easier or increasing access to information can be counterproductive. But so far, there is little formal design guidance on how such apps should be designed. This thesis starts to fillthis gap in design guidance by making two overarching contributions. First, it introduces a set of design guidelines for trading platforms based on fundamental results from related olds that may encourage healthier investing behaviors. Second, it presents a prototype for Robinhood's Forest, an 'interpassive" trading application based on these principles. The thesis also discusses design implications and opportunities for future design.

45 pages

Thesis Com mittee:
Chinmay Kalkarni (Chair)
Geoff Kaufman

Srinivasan Seshan, Head, Computer Science Department
Martial Hebert, Dean, School of Computer Science

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