We study intraday market intermediation in an electronic market before and during a period of large and temporary selling pressure. On May 6, 2010, U.S. financial markets experienced a systemic ...intraday event—the Flash Crash—where a large automated selling program was rapidly executed in the E-mini S&P 500 stock index futures market. Using audit trail transaction-level data for the E-mini on May 6 and the previous three days, we find that the trading pattern of the most active nondesignated intraday intermediaries (classified as High-Frequency Traders) did not change when prices fell during the Flash Crash.
We examine invariance relationships in tick-by-tick transaction data in the U.S. stock market. Over the period 1993–2001, monthly regression coefficients of the log of the trade arrival rate on the ...log of trading activity have an almost constant value of 0.666, close to the value of two-thirds predicted by market microstructure invariance. Over the 2001–2014 period, after decimalization and the increasing use of electronic order matching systems and algorithmic trading, the coefficients increase to about 0.79. The evidence suggests that changes in coefficients are due to increasing importance of minimum lots size in a world where algorithmic traders split orders into tiny pieces.
•This paper studies invariance relationships in tick-by-tick transaction data in the U.S. stock market.•From 1993 to 2001, the regression coefficient of trade rate on trading activity is 2/3, as predicted by invariance.•A breakdown in the relationship after tick size was reduced in 2001 suggests minimum lot size limits order splitting.•An invariance-implied measure of effective price volatility increases explanatory power.
In electronic, liquid markets traders frequently change their positions. We posit that the asymmetry in the distribution of these position changes carries important information about portfolio demand ...in the market. We use skewness to capture the asymmetry in position changes and from this distribution, we construct a market-wide measure for portfolio demand. Using a rich regulatory data set on S&P 500 E-mini futures, we show that this portfolio demand measure has a positive impact on prices. Decomposing our measure of portfolio demand into aggressive, passive and mixed components, we show that a one standard deviation increase in passive liquidity demand is associated with a 0.5 tick rise in prices for S&P 500 E-mini futures. Finally, we show that the distribution of position changes is crucial for explaining the execution cost of large traders.
Market liquidity is expected to facilitate arbitrage, which in turn should affect the liquidity of the assets traded by arbitrageurs. We study this relationship using a unique dataset of equity and ...bond ETFs compiled from big trade-level data. We find that liquidity is an important determinant of the efficacy of the ETF arbitrage. For less liquid bond ETFs, Granger-causality tests and impulse responses suggest that this relationship is stronger and more persistent, and liquidity spillovers are observed from portfolio constituents to ETF shares. Our results inform the design of synthetic securities, especially when derived from less liquid instruments.
We study the price pressure and price discovery effects in the U.S. Treasury market by using a term structure model. Our model decomposes yield curve shifts into two components: a virtually permanent ...change related to order flow and a transitory, price pressure effect due to dealer inventories. We find strong evidence that net dealer Treasury inventories has impact on the yield curve. Cash Treasury instruments in inventory have a larger impact on yields than futures contracts, suggesting that cash and futures inventories are not perfect substitutes. Price discovery in the level of interest rates is most strongly linked to non-dealer order flow in the 10-year futures contract, while price discovery in the slope of the curve is linked to order flow in the 10-year futures and the 5-year cash market.
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