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Relative idiosyncratic volatility and the timing of corporate insider trading
This paper investigates whether corporate insiders trade when asymmetric information is high, using data on U.S. corporate insider transactions between 1986 and 2012. We generalize the literature focusing on insider trading around the announcement of different categories of corporate events. The key innovation of this paper is our asymmetric information proxy relivol, which measures deviations of idiosyncratic volatility from a firm's normal level. Our findings suggest that relivol positively predicts insider purchases, indicating that insiders buy shares when their informational advantage is high. However, insiders appear to sell less when relivol is high, which is consistent with existing evidence on sales being driven by alternative, non-information-related trading motives such as liquidity or diversification needs. Furthermore, we find that profits are significantly higher when insiders buy during periods of high relivol but not when they sell shares.
Broker colocation and the execution costs of customer and proprietary orders
Colocation services offered by stock exchanges enable market participants to achieve execution costs for large orders that are substantially lower and less sensitive to transacting against high-frequency traders. However, these benefits manifest only for orders executed on the colocated brokers' own behalf, whereas customers' order execution costs are substantially higher. Analyses of individual order executions indicate that customer orders originating from colocated brokers are less actively monitored and achieve inferior execution quality. This suggests that brokers do not make effective use of their technology, possibly due to agency frictions or poor algorithm selection and parameter choice by customers.
Corporate insider trading and return skewness
Corporate insider trades predict idiosyncratic return skewness. CEO purchases are followed by an increase and CEO sales by a decrease in idiosyncratic skewness. The evidence suggests that this effect is driven by personal preferences rather than behavioral biases such as overconfidence. Our findings are consistent with the interpretation that CEOs, who are generally considered to be underdiversified, optimize their holdings by taking their preference for positive return skewness into account. We observe particularly robust results for CEO sales, which substantiates the less common notion that insider sales can be informative for investors.
Spoilt for choice: Determinants of market shares in fragmented equity markets
Trader Competition in Fragmented Markets: Liquidity Supply Versus Picking-Off Risk
By employing a dynamic model with two limit order books, we show that fragmentation is associated with reduced competition among liquidity suppliers and lower picking-off risk of limit orders. Due to these countervailing channels, the impact of fragmentation on liquidity and welfare differs with asset volatility: When volatility is high (low), liquidity and aggregate welfare in a fragmented market are higher (lower) than in a single market. However, fragmentation always shifts welfare away from agents with exogenous trading motives and toward intermediaries. We empirically corroborate our model’s predictions about liquidity. Our model reconciles the mixed results in the empirical literature.
Nonstandard Errors
In statistics, samples are drawn from a population in a data‐generating process (DGP). Standard errors measure the uncertainty in estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence‐generating process (EGP). We claim that EGP variation across researchers adds uncertainty—nonstandard errors (NSEs). We study NSEs by letting 164 teams test the same hypotheses on the same data. NSEs turn out to be sizable, but smaller for more reproducible or higher rated research. Adding peer‐review stages reduces NSEs. We further find that this type of uncertainty is underestimated by participants.