NBER Reporter: Winter 2000/2001
Barclay, Hendershott, and McCormick compare the execution quality of trades with market makers to trades on Electronic Communications Networks (ECNs). Average realized and effective spreads are smaller for ECN trades than for market-maker trades. The lower effective spreads for ECN trades are generated by lower quoted spreads at the time of the trade, and because market makers give more price improvement to small trades than ECNs do. ECN trades are also more informative than trades with market makers. The authors show that increased trading on ECNs improves most measures of overall market quality. In the cross section, more ECN trading is associated with lower quoted, effective, and realized spreads, both overall and on trades with market makers. More ECN trading is also associated with less quoted depth.
Parlour and Rajan develop a dynamic model of price competition in broker and dealer markets. Competing market makers quote bid-ask spreads, and competing brokers choose a commission to be paid by an investor. Brokers also choose a routing strategy across market makers. Then, to minimize their total transaction costs, investors choose a broker. This environment changes the order mix and can make retail investors worse off. It leads to lower brokerage commissions but higher market-maker spreads, thereby increasing the total transactions cost for investors.
Jones assembles an annual time series of bid-ask spreads on Dow Jones stocks from 1898-1998, along with an annual estimate of the weighted-average commission rate for trading New York Stock Exchange stocks since 1925. Spreads gradually declined over the course of the century but are punctuated by sharp rises during periods of market turmoil. Proportional one-way commissions rise dramatically to a peak of nearly one percent in the late 1960s and early 1970s, and fall sharply following commission deregulation in 1975. The sum of half-spreads and one-way commissions, multiplied by annual turnover, is an estimate of the annual proportional cost of aggregate equity trading. This cost drives a wedge between aggregate gross equity returns and net equity returns. This wedge accounts for only a small part of the observed equity premium, though. All else equal, the gross equity premium is perhaps one percent lower today than it was early in the 1900s. Finally, Jones shows that these measures of liquidity -- spreads and turnover -- predict stock returns up to one year ahead. High spreads predict high stock returns; high turnover predicts low stock returns. This suggests that liquidity is an important determinant of conditional expected returns.
After studying spreads, depths, and trading activity for U.S. equities over an extended time sample, Chordia, Roll, and Subrahmanyam find that daily changes in market averages of liquidity and trading activity are highly volatile, negatively serially dependent, and influenced by a variety of factors. Liquidity plummets significantly in down markets but increases weakly in up markets. Trading activity increases in either up or down markets. Recent market volatility induces less trading activity and reduces spreads. There are strong day-of-the-week effects; Fridays are relatively sluggish and illiquid while Tuesdays are the opposite. Long- and short-term interest rates influence liquidity and trading activity. Depth and trading activity increase just prior to major macroeconomic announcements.
Peterson and Sirri compare the execution costs of market orders and marketable limit orders (that is, limit orders with the same trading priority as market orders) to provide empirical evidence on the order submission strategy of investors with similar commitments to trade. The results indicate that the unconditional trading costs of marketable limit orders are significantly greater than those of market orders. The authors attribute the difference in costs to a selection bias and show that the order submission strategy decision is based on prevailing market conditions, stock characteristics, and the type of investor. After correcting for the selection bias, their results suggest that the average trader chooses the order type with lower conditional trading costs.