Does trader leverage drive equity market liquidity? We use the unique features of the margin trading system in India to identify a causal relationship between traders' ability to borrow and a stock's market liquidity. To quantify the impact of trader leverage, we employ a regression discontinuity design that exploits threshold rules that determine a stock's margin trading eligibility. We find that liquidity is higher when stocks become eligible for margin trading and that this liquidity enhancement is driven by margin traders' contrarian strategies. Consistent with downward liquidity spirals due to deleveraging, we also find that this effect reverses during crises.HOW DOES TRADER LEVERAGE impact equity market liquidity? The recent financial crisis has increased interest in the idea that variation in traders' ability to use leverage (that is, the ability of traders to borrow in order to invest in risky assets) can cause sharp changes in market liquidity. In fact, the assumption that capital constraints drive market liquidity is central to several influential theoretical models (see, for example, Gromb and Vayanos

We provide evidence that open-end structures undermine asset managers' incentives to attack long-term mispricing. First, we compare open-end funds with closed-end funds. Closed-end funds purchase more underpriced stocks than open-end funds, especially if the stocks involve high arbitrage risk. We then show that hedge funds with high share restrictions, having a lower degree of open-ending, also trade against long-term mispricing to a larger extent than other hedge funds. Our analysis suggests that open-end organizational structures are not conducive to long-term risky arbitrage.

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We study capital allocations to managers with two mutual funds, and show that investors learn about managers from their performance records. Flows into a fund are predicted by the manager's performance in his other fund, especially when he outperforms and when signals from the other fund are more useful. In equilibrium, capital should be allocated such that there is no cross-fund predictability. However, we find positive predictability, particularly among underperforming funds. Our results are consistent with incomplete learning: while investors move capital in the right direction, they do not withdraw enough capital when the manager underperforms in his other fund. * Darwin Choi and Abhiroop Mukherjee are at Hong Kong University of Science and Technology, and Bige Kahraman is at Saïd Business School, University of Oxford. We thank Kenneth Singleton (the Editor), an Associate Editor, and two anonymous referees for many helpful suggestions. We are also grateful for comments received from