We introduce systematic tests exploiting robust statistical and behavioral patterns in trading to detect fake transactions on 29 cryptocurrency exchanges. Regulated exchanges feature patterns consistently observed in financial markets and nature; abnormal first-significant-digit distributions,...

Web3 and DeFi are widely advocated as innovations for greater financial inclusion and democratization. We assemble the most comprehensive dataset to date on the largest Web3 ecosystem and use large-scale computing to conduct an initial investigation. We describe Ethereum's network structure,...

Web3 and DeFi are widely advocated as innovations for greater financial inclusion and democratization. We conduct an initial investigation using data from the Ethereum network. We describe its network structure and distributions of transactions, mining, and ownership. Mining and ownership of...

We introduce systematic tests exploiting robust statistical and behavioral patterns in trading to detect fake transactions on 29 cryptocurrency exchanges. Regulated exchanges feature patterns consistently observed in financial markets and nature; abnormal first-significant-digit distributions,...

We directly optimize the objectives of portfolio management via reinforcement learning---an alternative to conventional supervised-learning-based paradigms that entail first-step estimations of return distributions, pricing kernels, or risk premia. Building upon breakthroughs in AI, we develop...

Using data on 988 peer-to-peer lending platforms in China, we examine cross-side network effects (CNEs)---arguably the most important factor for multi-sided marketplaces---throughout platforms’ lifecycle in a dynamic industry characterized by entries, exits, and network externalities. We find...

We predict asset returns and measure risk premia using a prominent technique from artificial intelligence -- deep sequence modeling. Because asset returns often exhibit sequential dependence that may not be effectively captured by conventional time series models, sequence modeling offers a...

We document characteristics-based return anomalies in a large cross-section (4,000) of crypto assets. Cryptocurrency returns exhibit momentum in the largest-cap group, reversals in other size groups, and strong crypto value and network adoption premia, from which we derive two novel factors to...