Front running

Abstract: We study the behavior of short sellers as informed market participants and examine potential sources of their information. Using a newly available dataset with high-frequency short sales data, we find evidence of significant increases in short sales immediately prior to large insider sales, but not prior to small insider sales. We examine a number of explanations that the increase in short sales is driven by public information, either about the firm or about the impending insider sale. The evidence is inconsistent with these explanations, but is consistent with front-running facilitated by leaked information.

Abstract: We build a linear-quadratic model to analyze trading in a market with private information and heterogeneous agents. Agents receive private taste/inventory shocks and trade continuously. Agents differ in their need for trade as well as the cost to hold excessive inventory. In equilibrium, trade is gradual. Trading speed depends on the number and market power of participants, and trade among large market participants is slower than that among small ones. Price has momentum due to the actions of large traders: it drifts down if the sellers have greater market power than buyers, and vice versa. The model can also answer welfare questions, for example about the social costs and benefits of market consolidation. It can also be extended to allow private information about common value.

Abstract: Markets face a new and daunting mode of manipulation. With this new mode of market manipulation, millions of dollars can vanish in seconds, rogue actors can halt the trading of billion-dollar companies, and trillion-dollar financial markets can be distorted with a simple click or a few lines of code. Every investor and institution is at risk. This is the new precarious reality of our financial markets. This Article is about our ominous financial reality, this dangerous new mode of market manipulation, and the need for pragmatic policies to better address the rising threats to manipulate our financial markets. To start, the Article offers an overview about the recent rise and regulation of new financial technology. It begins with a close examination of The Flash Crash of 2010 and the publication of Flash Boys by Michael Lewis. Next, the Article surveys the changing landscape of market manipulation. It identifies traditional manipulation methods like cornering, front running, and pumping-and-dumping, as well as new manipulation methods like spoofing, pinging, and mass misinformation. It explains how new cybernetic market manipulation schemes that leverage modern technologies like electronic networks, social media, and artificial intelligence are more harmful than traditional schemes. The Article then grapples with why this new mode of market manipulation will present critical challenges for regulators. Finally, it recommends three pragmatic proposals for combating the new threats of cybernetic market manipulation by improving intermediary integrity, enhancing financial cybersecurity, and simplifying investment strategies. Ultimately, this Article provides an original and improved framework for thinking and acting anew about market regulation, market operations, and market manipulation.

Abstract: Employing comprehensive limit-order data which identify investor types, this paper examines the clustering pattern of limit-order prices. First, limit orders, particularly those submitted by individual investors (IIs), tend to cluster at integer and even prices. Second, nonmarketable limit-order prices cluster more than marketable limit-order prices, indicating that aggressive limit orders generally embed more information. Third, investors choosing even-priced limit orders are not penalized by lower execution ratios. Fourth, investors (particularly IIs) strategically exhibit front-running behavior. Fifth, price clustering indeed creates price barriers. Finally, the degree of price clustering using trade data is significantly underestimated, compared to that using limit-order data.