We provide a model that links a security’s market liquidity — i.e., the ease of trading it — and traders ’ funding liquidity — i.e., their availability of funds. Traders provide market liquidity and their ability to do so depends on their funding, that is, their capital and the margins charged by their financiers. In times of crisis, reductions in market liquidity and funding liquidity are mutually reinforcing, leading to a liquidity spiral. The model explains the empirically documented features that market liquidity (i) can suddenly dry up (i.e. is fragile), (ii) has commonality across securities, (iii) is related to volatility, (iv) experiences “flight to liquidity ” events, and (v) comoves with the market. Finally, the model shows how the Fed can improve current market liquidity by committing to improve funding in a potential future crisis.

Given the cross-sectional and temporal variation in their liquidity, emerging equity markets provide an ideal setting to examine the impact of liquidity on expected returns. Our main liquidity measure is a transformation of the proportion of zero daily firm returns, averaged over the month. We find that it significantly predicts future returns, whereas alternative measures such as turnover do not. Consistent with liquidity being a priced factor, unexpected liquidity shocks are positively correlated with contemporaneous return shocks and negatively correlated with shocks to the dividend yield. We consider a simple asset pricing model with liquidity and the market portfolio as risk factors and transaction costs that are proportional to liquidity. The model differentiates between integrated and segmented countries and time periods. Our results suggest that local market liquidity is an important driver of expected returns in emerging markets, and that the liberalization process has not fully eliminated its impact.

The effective cost of trading is usually estimated from transaction-level data. This study proposes a Gibbs estimate that is based on daily closing prices. In a validation sample, the daily Gibbs estimate achieves a correlation of 0.965 with the transactionlevel estimate. When the Gibbs estimates are incorporated into asset pricing specifications over a long historical sample (1926 to 2006), the results suggest that effective cost (as a characteristic) is positively related to stock returns. The relation is strongest in January, but it appears to be distinct from size effects. INVESTIGATIONS INTO THE ROLE of liquidity and transaction costs in asset pricing must generally confront the fact that while many asset pricing tests make use of U.S. equity returns from 1926 onward, the high-frequency data used to estimate trading costs are usually not available prior to 1983. Accordingly, most studies either limit the sample to the post-1983 period of common coverage or use the longer historical sample with liquidity proxies estimated from daily data. This paper falls into the latter group. Specifically, I propose a new approach to estimating the effective cost of trading and the common variation in this cost. These estimates are then used in conventional asset pricing specifications with a view to ascertaining the role of trading costs as a characteristic in explaining expected returns. 1

This paper studies predatory trading: trading that induces and/or exploits other investors ’ need to reduce their positions. We show that if one trader needs to sell, others also sell and subsequently buy back the asset. This leads to price overshooting, and a reduced liquidation value for the distressed trader. Hence, the market is illiquid when liquidity is most needed. Further, a trader profits from triggering another trader’s crisis, and the crisis can spill over across traders and across assets.

Do bond investors demand credit quality or liquidity? The answer is both, but at different times and for different reasons. Using data on the Euro-area government bond market, which features a unique negative correlation between credit quality and liquidity across countries, we show that the bulk of sovereign yield spreads is explained by differences in credit quality, though liquidity plays a nontrivial role, especially for low credit risk countries and during times of heightened market uncertainty. In contrast, the destination of large flows into the bond market is determined almost exclusively by liquidity. We conclude that credit quality matters for bond valuation but that, in times of market stress, investors chase liquidity, not credit quality. (JEL G10, G12) In times of economic distress, we often observe investors rebalance their portfolios toward less risky and more liquid securities, especially in fixed-income markets. This phenomenon is commonly referred to as a flight-to-quality and a flight-to-liquidity, respectively. While the economic motives of these two phenomena are clearly distinct from each other, empirically disentangling a flight-to-quality from a flight-to-liquidity is difficult because, as Ericsson and

In a model with multiple agents with different risk aversions facing margin constraints, we show how securities’ required returns are characterized both by their beta and their margins. Negative shocks to fundamentals make margin constraints bind, lowering risk free rates and raising Sharpe ratios of risky securities, especially for high-margin securities. Such a funding liquidity crisis gives rise to a “basis,” that is, a price gap between securities with identical cash-flows but different margins. In the time series, the basis depends on the shadow cost of capital which can be captured through the interest-rate spread between collateralized and uncollateralized loans, and, in the cross section, it depends on relative margins. We apply the model empirically to the CDS-bond basis and other deviations from the Law of One Price, and to evaluate the effects of unconventional monetary policy and lending facilities.

We describe how episodic illiquidity arises from a breakdown in cooperation between market participants. We first solve a one-period trading game in continuous-time, using an asset pricing equation that accounts for the price impact of trading. Then, in a multi-period framework, we describe an equilibrium in which traders cooperate most of the time through repeated interaction, providing apparent liquidity to one another. Cooperation breaks down when the stakes are high, leading to predatory trading and episodic illiquidity. Equilibrium strategies that involve cooperation across markets lead to less frequent episodic illiquidity, but cause contagion when cooperation breaks down.

We present a theory of excess stock market volatility, in which market movements are due to trades by very large institutional investors in relatively illiquid markets. Such trades generate significant spikes in returns and volume, even in the absence of important news about fundamentals. We derive the optimal trading behavior of these investors, which allows us to provide a unified explanation for apparently disconnected empirical regularities in returns, trading volume and investor size. I.

We provide the impact on asset prices of search-and-bargaining frictions in over-the-counter markets. Under certain conditions, illiquidity discounts are higher when counterparties are harder to find, when sellers have less bargaining power, when the fraction of qualified owners is smaller, or when risk aversion, volatility, or hedging demand are larger. Supply shocks cause prices to jump, and then “recover” over time, with a time signature that is exaggerated by search frictions. We discuss a variety of empirical implications.

Unlike textbook arbitrageurs who instantaneously trade when prices deviate from fundamental values, real world arbitrageurs must overcome various frictions. For example, they often invest other peoples ’ money, resulting in a principal/agent problem that is exacerbated in market downturns. Rather than increasing investment levels when prices dip below fundamental values, arbitrageurs may, in the face of investor redemptions, sell cheap securities causing prices to decline further. As a result, mispricings can be large and can extend for long periods of time. We first study the convertible bond market in 2005 when convertible hedge funds faced large redemptions of capital from investors. These redemptions led to binding capital constraints for many funds, resulting in massive bond sales, and in many cases, fund liquidations. These sales reduced prices of convertibles relative to fundamental values, especially around redemption dates. Even some multi-strategy hedge funds and large Wall Street banks who were not capital constrained acted as net sellers, consistent with the view that information barriers within a firm (not just relative to outside investors) can lead to capital constraints for trading desks with mark-to-market losses. We document similar patterns in the convertible bond market around the collapse of Long Term Capital Management (LTCM) in 1998. When LTCM incurred large losses on its macroeconomic bets, the firm was forced to liquidate large convertible bond positions. These sales led to depressed valuations of convertible bonds despite the fact there was