Abstract: The NYSE Trade and Quote (TAQ) dataset, used throughout finance research and securities regulation, is generated by a Securities Information Processor (SIP), which aggregates quotes and trades from all U.S. stock exchanges at a central location. We show that the SIP systematically reports events out of sequential order: quote changes that occur after a trade are frequently reported as occurring before the trade. The source of the issue is that trades and quotes are recorded with variable latency (due to, e.g., geography) and are extremely clustered in time. The result is a look-ahead bias: the prevailing SIP quotes, ubiquitous in signing trades and measuring spreads, incorporate price impact from the trade itself. We document that the look-ahead bias leads to incorrect trade signing and downward-biased effective spreads and price impact. The errors are extreme for the large fraction of trades with high reporting latency: approximately 20% of trades are incorrectly signed, and effective spreads and price impact are understated by more than 40%. We propose a signing methodology based on exchange rules that yields 100% accuracy for a significant majority of volume and, over all trades, outperforms the current standard. We also introduce a new benchmark to measure effective spreads and price impact that is free from bias.
Discussant: Stacey Jacobsen, Southern Methodist University
Abstract: In a dynamic model of large traders, we show that some length of daily market closure is welfare-improving relative to 24/7 trade. Market closure coordinates liquidity, since traders are willing to incur price impact at the end of the day to limit the expected cost of holding excess inventory overnight. A long closure is optimal in markets with few traders or infrequent shocks, while traders in large and active markets would benefit from extending trading hours to near 24/7. The equilibrium for competing volume-maximizing exchanges is 24/7 trade, suggesting a potential conflict with traders.
Discussant: Sophie Moinas, Toulouse School of Economics
Dmitriy Muravyev, University of Illinois-Urbana-Champaign
Abstract: Internalization mechanisms – like price improvement auctions in options – let market makers trade without displaying quotes. Studies in equities find little evidence that internalization reduces quote competition. Options offer a better setting because the same market makers set the best quotes and internalize retail orders. We find that market makers use auctions to match best prices when their quotes are uncompetitive: when an exchange is not posting the best price, auction trades are 31 percentage points more likely to occur, but significantly less likely to receive price improvement. Exchanges that offer auctions are less likely to compete on quotes. A market-wide change restricting auctions increased quote competition from auction exchanges and narrowed overall quoted spreads by 23%. Effective spreads declined less, as narrower quotes reduce price improvement opportunities. Long-term trends are consistent. As auction use rose sharply in 2014, quoted spreads also increased and diverged from effective spreads. While internalization may benefit individual retail orders, it reduces quote competition and widens quoted spreads.
