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Session Overview
Session
APE-9: Leverage Constraints and Liquidity in Equity Markets
Time:
Friday, 23/Aug/2019:
10:30 - 12:00

Session Chair: Naveen Gondhi, INSEAD
Location: D -106

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Presentations

Leveraged Funds and the Shadow Cost of Leverage Constraints

Zhongjin Lu, Zhongling Qin

University of Georgia, United States of America

Discussant: Thummim Cho (London School of Economics)

Using the most comprehensive dataset of leveraged funds, we measure the market-wide shadow cost of leverage constraints and examine its pricing implications. The shadow cost averages 0.51% per annum from 2006 to 2016. It spikes upon quarter-ends when financial intermediaries make mandatory reporting, positively predicts future betting-against-beta (BAB) returns, and negatively correlates with contemporaneous BAB returns. Stocks that underperform when the shadow cost increases earn 0.75% more per month. Our shadow cost measure helps identify supply and demand shifts in the leverage market. Overall, using our shadow cost measure rather than the widely used TED spread uncovers strong support for the predictions of leverage-constraint based theories.

efa2019-APE-9-1967-Leveraged Funds and the Shadow Cost of Leverage Constraints.pdf


Liquidity Risk?

Jeffrey Pontiff

Boston College, United States of America

Discussant: Daniel Schmidt (HEC Paris)

We revisit the role of liquidity risk. We successfully replicate Pastor and Stambaugh’s (2003) gamma liquidity risk index and, within their time period, concur with their risk premium estimate. An out-of-their-time-period analysis finds post-time-period returns that are higher and pre-time-period returns that are lower than in-time-period returns. Modest variations to the index that are intended to improve power—such as value weighting, including zero volume days, including all stock price levels, and a modification intended to reduce estimation error—all cast doubt on whether the gamma premium is compensation for liquidity risk. We create five alternative liquidity risk indices from various popular liquidity proxies. Using time-series that start in either 1932 or 1968, none of the ten specifications produce statistically significant risk premia.

efa2019-APE-9-2063-Liquidity Risk.pdf


Gamma Fragility

Andrea Barbon1, Andrea Buraschi2

1USI Lugano and SFI; 2Imperial College London

Discussant: Bart Yueshen (INSEAD)

We build on a growing literature that studies the impact of market frictions on the dynamics of stock markets, such as momentum, price spirals, excess volatility, and investigate the potential feedback effects of delta-hedging in derivative markets on the underlying market. We document a link between large aggregate dealers' gamma imbalances in illiquid markets and intraday momentum/reversal and market fragility. This link is distinct from information frictions (adverse selection and private information) and funding liquidity frictions (margin requirement shocks). We test our joint hypothesis using a large panel of index and equity options that we use to compute a proxy of aggregate gamma imbalance. We find supporting evidence that intra-day momentum (reversal) is explained by the interaction of negative (positive) aggregate gamma imbalance and market illiquidity. The effect is stronger for the least liquid underlying securities. The result helps to explain both intra-day volatility and autocorrelation of returns.

efa2019-APE-9-1934-Gamma Fragility.pdf


 
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