Entrepreneurs typically seek financing in decentralized markets, where they approach investors sequentially. We develop a model of sequential capital markets with privately informed investors. The sequential market creates a dynamic adverse selection externality that leads to overinvestment and excessive rents to intermediaries, even as the number of competing investors becomes arbitrary large. The resulting rents lead to excessive entry of investors and insufficient entry of entrepreneurs. Moving to a centralized market structure or reducing transparency restores competitiveness but may harm efficiency. The model also explains how even a small skill advantage for an investor can lead to preferential deal flow and outsized returns.

Cryptocurrency markets exhibit periods of large, recurrent arbitrage opportunities across exchanges. These price deviations are much larger across than within countries, and smaller between cryptocurrencies, highlighting the importance of capital controls for the movement of arbitrage capital. Price deviations across countries co-move and open up in times of large bitcoin appreciation. Countries with higher bitcoin premia over the US bitcoin price see widening arbitrage deviations when bitcoin appreciates. Finally, we decompose signed volume on each exchange into a common and an idiosyncratic component. The common component explains 80% of bitcoin returns. The idiosyncratic components help explain arbitrage spreads between exchanges.

We examine the dramatic collapse of the Terra blockchain in May 2022. Using granular blockchain data, we show that the run resulted from the interaction of three economic forces: subsidized money creation, real-time observability of transactions, and investor concentration. The early success of Terra’s algorithmic stablecoin, UST, was fueled by highly subsidized deposit rates, which attracted many investors but failed to engage them meaningfully with other services. Blockchain transparency allowed investors to observe Terra’s worsening fundamentals and monitor each other’s exits in real time. Larger and sophisticated investors reacted faster to adverse signals and served as catalysts for the run. These findings challenge the idea that blockchain transparency levels the playing field and highlight how greater observability and concentration can amplify financial fragility. Our results contribute to the understanding of the limits of private money creation and the dynamics of runs in fully digital financial systems.

The returns to hedge funds and other alternative investments are often highly serially correlated. In this paper, we explore several sources of such serial correlation and show that the most likely explanation is illiquidity exposure and smoothed returns. We propose an econometric model of return smoothing and develop estimators for the smoothing profile as well as a smoothing-adjusted Sharpe ratio. For a sample of 908 hedge funds drawn from the TASS database, we show that our estimated smoothing coefficients vary considerably across hedge-fund style categories and may be a useful proxy for quantifying illiquidity exposure.

Trading in cryptocurrencies grew rapidly over the last decade, dominated by retail investors. Using data from eToro, we show that retail traders are contrarian in stocks and gold, yet the same traders follow a momentum-like strategy in cryptocurrencies. The differences are not explained by individual characteristics, investor composition, inattention, differences in fees, or preference for lottery-like assets. We conjecture that retail investors have a model where cryptocurrency price changes affect the likelihood of future widespread adoption, which leads them to further update their price expectations in the same direction.