We address the determination of bitcoin prices and decentralized security. Users forecast the transactional and resale values of holdings, pricing the risk of systemic attacks. Miners contribute resources to protect against attackers and compete for block rewards. Bitcoin’s design leads to multiple equilibria: the same blockchain technology is consistent with sharply different price and security levels. Bitcoin’s monetary policy can lead to welfare losses and deviations from quantity theory. Price-security feedback amplifies fundamental shocks’ volatility impact and leads to boom and busts unconnected to fundamentals. We characterize how viability versus fiat currency depends on bitcoin’s relative acceptability and inflation protection.

[Using over 5,000 trades unequivocally based on nonpublic information about firm fundamentals, we find that asymmetric information proxies display abnormal values on days with informed trading. Volatility and volume are abnormally high, whereas illiquidity is low, in equity and option markets. Daily returns reflect the sign of private signals, but bidask spreads are lower when informed investors trade. Market makers’ learning under event uncertainty and limit orders help explain these findings. The cross-section of information duration indicates that traders select days with high uninformed volume. Evidence from the U.S. SEC Whistleblower Reward Program and the FINRA involvement addresses selection concerns.]

We analyze trading speed and fragmentation in asset markets. In our model, trading venues make technological investments and compete for investors who choose where and how much to trade. Faster venues charge higher fees and attract speed-sensitive investors. Competition among venues increases investor participation, trading volume, and allocative e ffi ciency, but entry and fragmentation can be excessive, and speeds are generically ine ffi cient. Regulations that protect transaction prices (e.g., Securities and Exchange Commission trade-through rule) lead to greater fragmentation. Our model sheds light on the experience of European and U.S. markets since the implementation of Markets in Financial Instruments Directive and Regulation National Markets System.

Using over 5,000 trades unequivocally based on nonpublic information about firm fundamentals, we find that asymmetric information proxies display abnormal values on days with informed trading. Volatility and volume are abnormally high, whereas illiquidity is low, in equity and option markets. Daily returns reflect the sign of private signals, but bid-ask spreads are lower when informed investors trade. Market makers’ learning under event uncertainty and limit orders help explain these findings. The cross-section of information duration indicates that traders select days with high uninformed volume. Evidence from the U.S. SEC Whistleblower Reward Program and the FINRA involvement addresses selection concerns. Received January 11, 2017; editorial decision December 17, 2018 by Editor Andrew Karolyi.

Do illegal insiders internalize legal risk? We address this question with hand‐collected data from 530 SEC (the U.S. Securities and Exchange Commission) investigations. Using two plausibly exogenous shocks to expected penalties, we show that insiders trade less aggressively and earlier and concentrate on tips of greater value when facing a higher risk. The results match the predictions of a model where an insider internalizes the impact of trades on prices and the likelihood of prosecution and anticipates penalties in proportion to trade profits. Our findings lend support to the effectiveness of U.S. regulations' deterrence and the long‐standing hypothesis that insider trading enforcement can hamper price informativeness.