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...

We discuss emerging research on digital tokens and cryptocurrencies. Specifically, we (i) provide a comprehensive categorization of crypto-tokens as observed or designed in practice, (ii) discuss major issues concerning the economics of using tokens including platform finance, user adoption,...

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 develop a dynamic asset-pricing model of cryptocurrencies/tokens that allow users to conduct peer-to-peer transactions on digital platforms. The equilibrium value of tokens is determined by aggregating heterogeneous users' transactional demand rather than discounting cashflows as in standard...

We introduce a class of interpretable tree-based models (P-Tree) for analyzing (unbalanced) panel data, with iterative and global (instead of recursive and local) split criteria. We apply P-Tree to split the cross section of asset returns under the no-arbitrage condition, generating a stochastic...