We use a novel machine learning approach to tackle the problem of limit order management. Applying our framework to data, we show that the most important variable for a trader to consider is the price level of their order, followed by the queue sizes of the order book, volatility and finally...

We investigate competition between traditional stock exchanges and new ‘dark' trading venues using an important difference in regulatory treatment. SEC required minimum pricing increments constrain some stock spreads, causing large limit order queues. Dark pools allow some traders to by-pass...

Dark pools volumes have increased significantly over the last decade. This has raised concerns on the reliability of reference prices used by these pools, and asymmetric participant outcomes via “latency arbitrage”. Using a novel data set provided by the major UK exchanges and dark pools...

We study the mandated introduction of a supervised auction for the primary bond market in China. The regulatory intervention significantly reduced the cost of debt for Chinese issuers. We show that the majority of the benefits flow from reduced agency conflict between underwriters and issuers....

This paper presents empirical estimates of the value of data-feeds from individual marketplaces in the trading of Canadian equities. These estimates are then contrasted with the actual fees charged by the marketplaces and an international comparison is made. We find that some marketplaces charge...