This article analyzes the effects of information leakage on trading behavior and market efficiency. A trader who receives a noisy signal about a forthcoming public announcement can exploit it twice. First, when he receives it, and second, after the public announcement since he knows best the extent to which his information is already reflected in the pre-announcement price. Given his information he expects the price to overshoot and intends to partially revert his trade. While information leakage makes the price process more informative in the short-run, it reduces its informative-ness in the long-run. The analysis supports Securities and Exchange Commission’s Regulation Fair Disclosure. In a perfect world, all investors would receive information pertinent to the value of the stock immediately and simultaneously. In reality, however, some agents like corporate insiders and their favored analysts can receive signals about this information before it is disclosed to the general public. The focus of our analysis is to determine (i) the optimal trading strategy of an early-informed agent and (ii) the implications of this trading behavior

We analyze the relationship between asset price bubbles and systemic risk, using bank-level data covering almost 30 years. Banks’ systemic risk already rises during a bubble’s buildup and even more so during its bust. The increase in risk strongly differs across banks and by bubble. It depends on bank characteristics (especially bank size) and bubble characteristics and can become very large: in a median real estate bust, systemic risk increases by almost 70% of the median for banks with unfavorable characteristics. These results emphasize the importance of bank-level factors in the buildup of financial fragility during bubble episodes.

We provide a model that links an asset's market liquidity (i.e., the ease with which it is traded) and traders' funding liquidity (i.e., the ease with which they can obtain funding). Traders provide market liquidity, and their ability to do so depends on their availability of funding. Conversely, traders' funding, i.e., their capital and margin requirements, depends on the assets' market liquidity. We show that, under certain conditions, margins are destabilizing and market liquidity and funding liquidity are mutually reinforcing, leading to liquidity spirals. The model explains the empirically documented features that market liquidity (i) can suddenly dry up, (ii) has commonality across securities, (iii) is related to volatility, (iv) is subject to “flight to quality,” and (v) co-moves with the market. The model provides new testable predictions, including that speculators' capital is a driver of market liquidity and risk premiums.

We study the run on the German banking system in 1931 to understand whether depositors anticipate which banks will fail in a major financial crisis. We find that deposits decline by around 20% during the run. There is an equal outflow of retail and nonfinancial wholesale deposits from both failing and surviving banks. In contrast, we find that interbank deposits almost exclusively decline for failing banks. Our evidence suggests that banks are better informed about which fellow banks will fail. In turn, banks being informed allows the interbank market to continue providing liquidity even during times of severe financial distress.