Kyong Shik Eom

Microstructure-based manipulation: Strategic behavior and performance of spoofing traders

We examine how investors strategically spoof the stock market by placing orders with little chance of being executed, but which mislead other traders into thinking there is an imbalance in the order book. Using the complete intraday order and trade data of the Korea Exchange (KRX) in a custom data set identifying individual accounts, we find that investors strategically placed spoofing orders which, given the KRX’s order-disclosure rule at the time, created the impression of a substantial order book imbalance, with the intent to manipulate subsequent prices. This manipulation, which made use of specific features of the market microstructure, differs from previously studied forms of manipulation based on information or transactions. Roughly half of the spoofing orders were placed in conjunction with day trading. Stocks targeted for manipulation had higher return volatility, lower market capitalization, lower price level, and lower managerial transparency. We also find that spoofing traders achieved substantial extra profits. The frequency of spoofing orders decreased drastically after the KRX altered its order-disclosure rule. & 2012 Elsevier B.V. All rights reserved. JEL classification: G14

Price Stabilization and Discovery Under a Random-End Trading Mechanism

We study the effects of a contingent random-end (RE) trading mechanism on price stabilization, discovery, and efficiency. Using the real-time order book, we analyzed all RE occurrences on the Korea Exchange (KRX) in 2009 and 2010. The RE trading mechanism promoted price stabilization, but with some reservations. A significant part of this price stabilization effect came from the cancellation or correction of existing orders. The RE trading mechanism improved opening price discovery, but caused overreaction at the close. Policymakers should consider tighter parameters of the RE trading mechanism on the expiration dates of derivatives contracts than on regular trading days.

Idiosyncratic Volatility Under a Price-Limit System Using Gibbs-Sampling

We examine the effects of price limits on the idiosyncratic volatility of individual stocks. When estimating idiosyncratic volatility, we adopt the Gibbs-sampling method to resolve the problem of censored returns caused by price limits. Results show that idiosyncratic volatility is significantly higher than would appear from OLS estimates using the observed censored return data. Tight price limits reduce idiosyncratic volatility, at significant cost; looser price limits have no effect on idiosyncratic volatility. We argue that regulators should substitute volatility-interruption systems in place of price-limit systems for individual stocks.