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The effects of an increase in equity tick size on stock and option transaction costs
We examine the impact of the 2016 U.S. SEC Tick Size Pilot Program on transaction costs in both the equity and options markets. We find that an increase in the tick size from one-cent to five-cents increases percent bid-ask spreads for test stocks vis-à-vis control stocks; however, this increase is substantially reduced when the test stocks have actively traded options. We also find a spillover effect in transaction costs from the underlying stock market to the options market, as both percent bid-ask spreads and implied volatility spreads widen in options for test stocks versus control stocks. Lastly, we find reversal effects at the conclusion of the pilot program, as percent spreads in both the equity and options markets narrow when the tick size is reduced.
Making cents of tick sizes: The effect of the 2016 U.S. SEC tick size pilot on limit order book liquidity
We use the 2016 U.S. SEC tick size pilot to examine the effects of an increase in the minimum price variation on limit order book liquidity in NASDAQ-listed stocks on the NASDAQ exchange. For treatment stocks with an average pre-pilot quoted spread less than 0.05, the tick size increase is binding and leads to a significant decrease in liquidity in the limit order book. Specifically, the implied cost to trade at and away from the best bid and offer prices increases and the limit order book becomes less resilient – the amount of time required for a deviation in liquidity to return to its long-run mean. For treatment stocks with an average pre-pilot quoted spread of at least 0.05, the tick size increase is non-binding and leads to either a slight decrease, or no change in limit order book liquidity.
A new leadership share measure for price discovery
We propose a new measure of price discovery, New Leadership Share (NLS), that attributes permanent information flow to individual markets using a uniquely identified structural moving average model. NLS quantifies each market’s contribution to permanent price innovations as a proportion of total informational leadership and offers key technical advantages, including uniqueness and adherence to standard statistical asymptotics. We derive closed-form solutions and analytical standard errors for bivariate markets and provide a framework that extends naturally to multiple markets without the variable ordering problem. Simulation results show that NLS consistently outperforms three widely used benchmarks. Empirical analysis of 2023 data finds that exchange-traded funds and front-month futures markets share equal leadership relative to the S&P 500 spot index.
1-share orders and trades
1-share trades are the most common odd lot trade size, accounting for 9.62% of all odd lot transactions and 3.65% of all trades on NASDAQ in 2012. While 50.41% of 1-share trades result from broken orders, 34.89% of 1-share trades are intentional. We provide substantial evidence that traders use 1-share trades to “ping” for hidden liquidity. In particular, our results indicate that 1-share trades are disproportionately aggressive and also execute against hidden liquidity more than any other odd lot trade size. We also find a relative increase in trading immediately following a 1-share trade. Our results are in line with Clark-Joseph (2014), who suggests that traders may use small, unprofitable trades to detect information from other traders. Specifically, 1-share trades represent the minimum cash outlay necessary to trade, while simultaneously producing the smallest possible effects on a market maker's inventory, and in turn, a security's price.
Retail option traders and the implied volatility surface
Retail trader sophistication and stock market quality: Evidence from brokerage outages
We study brokerage platform outages to examine the impact of retail investors on financial markets. We contrast outages at Robinhood, which caters to inexperienced investors, with outages at traditional retail brokers. For stocks with high retail interest, we find that negative shocks to Robinhood investor participation are associated with reduced market order imbalances, increased market liquidity, and lower return volatility, whereas the opposite relations hold following outages at traditional retail brokerages. The findings suggest that herding by inexperienced investors can create inventory risks that harm liquidity in stocks with high retail interest, while other retail trading improves market quality.
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.