Using live trade execution data from an institutional money manager, we measure the real-world costs and challenges a trader faces when demanding significant liquidity of Bitcoin. We provide a novel characterization of the market to purchase digital assets across exchanges and over-the-counter...

In this study, we analyze factors influencing the intention to invest in mutual funds in e-commerce or online marketplace. We built a model based on the trust transfer theory to examine whether perceived similarity with other digital products – such as mobile payment products- affects...

Using the unique dataset on web analytics and exploiting institutional features of search engine technology, I study the relationship between an ETF’s visibility on the Internet and its fund flows. I consider three channels of online visibility: Organic or “free” search, paid search, and...

This paper investigates whether Tether, a digital currency pegged to the U.S. dollar, influenced Bitcoin and other cryptocurrency prices during the 2017 boom. Using algorithms to analyze blockchain data, we find that purchases with Tether are timed following market downturns and result in...

The peer-to-peer loan market was designed to bring together borrowers and lenders without banks as middlemen. Yet over time P2P lending platforms have evolved into new intermediaries, performing essentially all tasks related to loan evaluation. By contrast, lenders are overwhelmingly passive and...

We examine both displayed and non-displayed orders sent by all investors to the electronic central limit order book of the Italian stock exchange Borsa Italiana (BI). Extant literature relies on trades as basic level of observation for the lack of data. Our unique dataset enables us to...

This paper uses order-level data of all investors of the Italian stock exchange Borsa Italiana (BI) to resolve three issues that remained unsettled in the extant microstructure literature: the interaction between the exchange and a parallel market for large blocks; the asymmetry between the...

This study analyzes more than 28 million recent loan listings on LendingClub, one of the world's largest online marketplace lending platform. Using tree-based machine learning, we develop robust predictive representations of funding decisions on this fintech peer-to-peer lending platform. We...

We report the results of a longitudinal intervention with students across five universities in China designed to reduce online consumer debt. Our research design allocates individuals to either a financial literacy treatment, a self-control training program, or a zero-touch control group. The...