Limit order book as a market for liquidity

We develop a dynamic model of an order-driven market populated by discretionary liquidity traders. These traders must trade, yet can choose the type of order and are fully strategic in their decision. Traders differ by their impatience: less patient traders demand liquidity, more patient traders provide it. Three equilibrium types are obtained - the type is determined by three parameters: the degree of impatience of the patient traders, which we interpret as the cost of execution delay in providing liquidity; their proportion in the population, which is the cost of the minimal price improvement. Despite its simplicity, the model generates a rich set empirical predictions on the relation between market parameters, time to execution, and spreads. We argue that the economic intuition of this model is robust, thus its main results will remain in more general models.limit and market orders; time-to-execution; market quality

Liquidity cycles and make/take fees in electronic markets

In this paper, the authors develop a dynamic model of trading with two specialized sides: traders posting quotes (“market makers”) and traders hitting quotes (“market takers”). Traders monitor the market to seize profit opportunities, generating high frequency make/take liquidity cycles. Monitoring decisions by market-makers and market-takers are self-reinforcing, generating multiple equilibria with differing liquidity levels and duration clustering. The trading rate is typically maximized when makers and takers are charged different fees or even paid rebates, as observed in reality. The model yields several empirical implications regarding the determinants of make/take fees, the trading rate, the bid-ask spread, and the effect of algorithmic trading on these variables. Finally, algorithmic trading can improve welfare because it increases the rate at which gains from trade are realized.liquidity; monitoring; make/take fees; duration clustering; algorithmic trading; two-sided markets

The diminishing liquidity premium

Previous evidence suggests that less liquid stocks entail higher average returns. Using NYSE data, we present evidence that both the sensitivity of returns to liquidity and liquidity premia have significantly declined over the past four decades to levels that we cannot statistically distinguish from zero. Furthermore, the profitability of trading strategies based on buying illiquid stocks and selling illiquid stocks has declined over the past four decades, rendering such strategies virtually unprofitable. Our results are robust to several conventional liquidity measures related to volume. When using liquidity measure that is not related to volume, we find just weak evidence of a liquidity premium even in the early periods of our sample. The gradual introduction and proliferation of index funds and exchange traded funds is a possible explanation for these results

Performance Evaluation with High Moments and Disaster Risk

Traditional performance evaluation measures do not account for tail events and rare disasters. To address this issue, we reinterpret the riskiness measures of Aumann and Serrano (2008) and Foster and Hart (2009) as performance indices. We derive the moment properties of these indices and their sensitivity to rare disasters and show that they are consistent with the asset pricing literature. As applications, we show that “anomalous” investment strategies such as “momentum” or investment in private equity lose much of their glamour when accounting for high moments and rare events. Furthermore, using the indices to select mutual funds results in desirable high-moment properties out of sample

Generalized Systematic Risk

We generalize the concept of .systematic risk to a broad class of risk measures potentially accounting for high distribution moments, downside risk, rare disasters, as well as other risk attributes. We offer two different approaches. First is an equilibrium framework generalizing the Capital Asset Pricing Model, two-fund separation, and the security market line. Second is an axiomatic approach resulting in a systematic risk measure as the unique solution to a risk allocation problem. Both approaches lead to similar results extending the traditional beta to capture multiple dimensions of risk. The results lend themselves naturally to empirical investigation

Trading in the Presence of Short-Lived Private Information: Evidence from Analyst Recommendation Changes

We study how short-lived private information affects trading strategies and liquidity provision. Our empirical identification rests on information acquisition before analyst recommendations are publically announced. Consistent with theory, institutional investors who are likely to possess short-lived private information on average “buy the rumor and sell the news,” buying before analyst upgrades and selling when upgrades are announced. When we go beyond existing theory, we find that different classes of informed institutions differ in their profit-taking patterns, reflecting variations in their trading horizons and motives. The returns to holding private information are economically large. Individuals, who are unlikely to be informed early, buy on upgrade announcements but not before. Institutions that are not attentive to firm-specific news appear to suffer from a winner’s curse, emerging as de-facto liquidity providers to better-informed institutions. Placebo tests confirm that these trading patterns are unique to situations in which some investors have a short-lived informational advantage

A Forward-Looking Factor Model for Volatility: Estimation and Implications for Predicting Disasters

We show that any factor structure for stock returns can be naturally translated into a factor structure for return volatility. We use this structure to propose a methodology for estimating forward-looking variances and covariances of both factors and individual assets from option prices at a high frequency. We implement the model empirically and show that our forward-looking volatility estimates provide useful predictions of rare disasters for both factors and individual stocks

Stock Picking, Industry Picking and Market Timing in Sell-Side Research

Also presented at AFA Meeting 2013</p

Industry Recommendations: Characteristics, Investment Value, and Relation to Firm Recommendations

Also presented at 2009 FEA Conference, 2010 AFA Meeting, 2010 FARS Conference, 2010 FIRS Conference</p