We analyze the effects of a recent piece of consumer-protection regulation – Dodd-Frank – on mortgage originations. Dodd-Frank aimed at reducing mortgage fees and abuses against vulnerable borrowers, but increased the costs of originating mortgages. We find it triggered a substantial...

We document that, since 2011, mortgage lenders reduced credit to middle-class households by 15% and increased credit to wealthy households by 21%. Credit to low-income households was unaffected. Results hold at the individual-loan level and zip-code level, and at the intensive margin and...

We show that a model featuring an average commodity factor, a carry factor, and a momentum factor is capable of describing the cross-sectional variation of commodity returns. More parsimonious one- and two-factor models that feature only the average and/or carry factors are rejected. To provide...

We study a robo-advising portfolio optimizer that constructs tailored strategies based on in- vestors' holdings and preferences. Adopters are similar to non-adopters in terms of demographics, but have more assets under management, trade more, and have higher risk-adjusted performance. The...

We document five effects of providing individuals with crowdsourced spending information about their peers (individuals with similar characteristics) through a FinTech app. First, users who spend more than their peers reduce their spending significantly, whereas users who spend less keep...

Traditional forms of robo-advice were targeted to help individuals make portfolio allocation decisions. Based on the balance-sheet view of households, the scope for robo-advising has been expanding to many other personal-finance choices, such as households' saving and consumption decisions, debt...

Using unique data from a medium-sized cryptocurrency exchange in Asia, we establish 10 facts about cryptocurrency exchanges and cryptocurrency trading. 1) Individuals hold cryptocurrency portfolios of small value, 2) they trade very few cryptocurrencies, 3) their trading patterns are very...

We use a broad survey to elicit investor needs and their satisfaction in the context of financial advice. We provide evidence that traditionally-advised individuals do not hire financial advisors mainly to maximize portfolio returns. They instead hire financial advisors to satisfy a broader set...

We exploit a leading FinTech peer-to-peer lending platform paired with an automated robo-advising lending tool to test for and quantify the effects of cultural biases in large-stake risky choices for which the scope for statistical discrimination is minimal. Comparing the choices lenders make...

We study a robo-advising portfolio optimizer that constructs tailored strategies based on investors' holdings and preferences. Adopters are similar to non-adopters in terms of demographics, but have more assets under management, trade more, and have higher risk-adjusted performance. The...