Jesse Blocher

Phantom Liquidity and High Frequency Quoting

This article examines every NASDAQ ITCH feed message for S&P 500 Index stocks for 2012 and identifies clusters of extremely high and extremely low limit-order cancellation activity. The authors find results consistent with the idea that cancel clusters are the result of high-frequency traders jockeying for queue position and reacting to information to establish a new price level. Furthermore, few trades seem to be executed during cancel clusters or even immediately after them. Low cancellation activity seems to be markedly different, with many level changes all caused by executions. The results are consistent with high-frequency trading firms behaving as agents who bring efficiency to the market without the need to have executions at intermediate prices. The authors also discuss the misconception that investors and low-frequency traders are synonymous and its implications for policy given these results.

Network Externalities in Mutual Funds

I measure the effects of capital flow contagion in financial markets by analyzing portfolio managers linked through interconnected asset holdings. My novel, network-based specification provides estimates of shocks to common predictor variables 50-75% higher than existing estimates of manager’s capital flows which ignore network relationships. This additional impact arises because my network specification includes the effect of spillover onto immediate neighbors and beyond, leading to feedback loops. My findings seem to result from crowded trades (popular, short-term investment strategies) since network connections do not show strong persistence and relatively small changes in asset allocation toward more concentrated positions may increase interconnection considerably. ∗Special thanks to Jennifer Conrad, Adam Reed and Joey Engelberg, Greg Brown and Pab Jotikasthira for timely and helpful advice on this project. I am also grateful to Rick Sias (Discussant at FRA conference), Chris Lundblad, Ed VanWesep and Matt Ringgenberg for useful comments. Thanks to Matthew Bothner (ESMT Management/Sociology) and Peter Mucha (UNC Applied Mathematics) for valuable guidance on network measures and computational algorithms, respectively. Ethan Cohen-Cole and Tim Conley provided help and references on identification and econometrics. James Moody and seminar participants at the Duke Network Analysis Center (dnac.ssri.duke.edu) provided useful feedback, as did seminar participants at the SAMSI (www.samsi.info) program on Complex Networks. Blocher is from the University of North Carolina Chapel Hill Kenan-Flagler Business School, Finance Area, Campus Box 3490 McColl Building, Chapel Hill, NC 27599-3490. Contact info: jesse_blocher@unc.edu or www.unc.edu/~jabloche.

Short Constraints are Persistent Constraints

Short selling constraints predict negative stock returns at the monthly frequency, but is it a monthly phenomenon? We show that short selling constraints are persistent, lasting nine months on average, and therefore measured subsequent negative returns cannot be due primarily to an easing of these constraints. Instead, negative returns from short constrained stocks result primarily because stock owners sell the constrained stock. Many common measures of short selling constraints in the literature actually measure persistent short selling constraints. 43.6% of all traded firms experience a persistent short-selling constraint episode lasting at least two months. Because persistent stock overpricing is predictable over long periods of time, CEOs and other insiders may be able to exploit it more easily.

Supply Side Short-Selling Constraints: Who Is Buying When Shorts Are Selling?

The equity lending literature has assumed that equity loan supply is static due to institutional constraints. Instead, we show that reduced stock lending (both at the margin and in levels) causes increased stock loan fees and stock overpricing. We find the strongest effect among stocks with the highest disagreement, as suggested by theory. Investors buy and do not lend for two reasons. First, they prefer positive skewness: loan-supply-constrained stocks exhibit increased lottery-like return distributions. Second, loan supply restrictions cause short-term positive holding period returns, implicating them in stock overpricing.

Risk Shifting or Just Risk-Adjusted Returns

Intuitively, option-like compensation contracts induce risk-shifting behavior, confirmed by numerous empirical studies. However, theoretical work has shown that risk shifting should not happen without a definite expiration date of the option. With a sample of Commodity Trading Advisors (CTAs), we show that increases in risk (interpreted as risk shifting) correspond to even greater increases in return, as shown by increasing Sharpe ratios. Second, controlling for expected returns eliminates measured risk shifting. Finally, measured risk shifting behavior, strong between 1994 and 2003, is substantially lower or missing from 2004 to 2014. Thus, we conclude that CTAs are increasing risk adjusted returns, not risk shifting, confirming the theoretical results.