Spreads, depths, and quote clustering on the nyse and Nasdaq: Evidence after the 1997 sec rule changes Kee H. Chung,a,* Bonnie F. Van Ness,b Robert A. Van Nessb

Table 4 Comparision of depths between Nasdaq stocks and NYSE stocks We calculate the time-weighted average depth using all the time-series observations during the three-month study period. We report the results of paired comparison t-tests for the equality of depths between Nasdaq and NYSE stocks. We measure share price by the mean value of the midpoints of quoted bid and ask prices, and trade size by the average dollar transaction during the study period. The number of trades is the total number of transactions during the study period. We measure return volatility by the standard deviation of daily returns calculated from the daily closing midpoints of bid and ask prices.
		Depths
Quartile Based on	Quartile	Nasdaq Quote	NYSE Quote	Nasdaq-NYSE	t-stat
Share Price	Q1 Q2 Q3 Q4	8231 4366 3715 3602	18945 11499 8380 7901	-10714 -7133 -4665 -4299	-3.011** -8.474** -9.340** -7.231**
Number of Trades	Q1 Q2 Q3 Q4	6289 3785 4241 5610	6552 9825 12583 17833	-263 -6040 -8341 -12223	-0.091 -4.863** -5.787** -9.939**
Trade Size	Q1 Q2 Q3 Q4	7945 4412 3904 3654	17430 11737 9175 8388	-9485 -7325 -5271 -4734	-2.678** -8.124** -9.101** -7.743**
Return Volatility	Q1 Q2 Q3 Q4	6757 4049 4467 4647	8263 9657 12223 16639	-1506 -5608 -7756 -11993	-0.515 -6.265** -8.868** -6.285**
Whole Sample		4983	11698	-6707	-7.120*
^**Significant at the 1% level

Table 5 Proportion of trades inside the quote This table shows the proportion of trades that occur at prices inside the posted bid and ask quotes. The results are reported for the whole sample and for each quartile based on share price, number of trades, trade size, and return volatility.
	Proportion of trades inside the quote
Quartile based on	Quartile	Nasdaq Trade	NYSE Trade
Share Price	Q1 Q2 Q3 Q4	0.2145 0.2511 0.2889 0.2993	0.2647 0.3066 0.358 0.3567
Number of Trades	Q1 Q2 Q3 Q4	0.3215 0.2899 0.2496 0.1922	0.3565 0.3255 0.3141 0.2896
Trade Size	Q1 Q2 Q3 Q4	0.2196 0.2504 0.2759 0.3079	0.271 0.3123 0.3356 0.3673
Return Volatility	Q1 Q2 Q3 Q4	0.2928 0.2741 0.2499 0.2366	0.3395 0.3392 0.3135 0.2937
Whole Sample		0.2634	0.3215

Table 6 Price impact of trades on Nasdaq and the NYSE Price impact measures the average information content of trades or the market maker's losses to better informed traders. Price impact is calculated by subtracting the realized spread from the effective spread. We report the results of paired comparison t-tests for the equality of price impact between Nasdaq and NYSE stocks. We measure share price by the mean value of the midpoints of quoted bid and ask prices, and trade size by the average dollar transaction during the study period. The number of trades is the total number of transactions during the study period. We measure return volatility by the standard deviation of daily returns calculated from the daily closing midpoints of bid and ask prices.
		Price Impact
Quartile based on	Quartile	NASDAQ Trade	NYSE Trade	Nasdaq-NYSE	t-stat
Share Price	Q1 Q2 Q3 Q4	0.0495 0.0179 0.0147 0.0171	0.173 0.1087 0.0797 0.0713	-0.1235 -0.0908 -0.065 -0.0542	-11.222** -11.085** -13.252** -8.203**
Number of Trades	Q1 Q2 Q3 Q4	0.039 0.0191 0.0229 0.0183	0.1364 0.1072 0.1035 0.0856	-0.0974 -0.0882 -0.0806 -0.0673	-8.667** -14.724** -10.105** -9.583**
Trade Size	Q1 Q2 Q3 Q4	0.0537 0.0211 0.0134 0.0109	0.1774 0.0985 0.0791 0.0776	-0.1236 -0.0774 -0.0657 -0.0666	-10.610** -14.954** -14.491** -7.566**
Return Volatility	Q1 Q2 Q3 Q4	0.014 0.0178 0.027 0.0406	0.0677 0.0938 0.1168 0.1549	-0.0536 -0.0761 -0.0898 -0.1143	-14.070** -9.798** -11.531** -10.048**
Whole Sample		0.0248	0.1082	-0.0834	-19.996**
^**Significant at the 1% level.

Table 7 Distribution of Nasdaq and NYSE quotes by even- and odd-quotes Panel A reports the percentage of Nasdaq and NYSE quotes in each quote increment. Panel B reports the proportion of even-quotes within each price grid. Panel A. Proportion of quotes in each quote increment
	Nasdaq Quotes			NYSE Quotes
Quote	Bid	Ask	Total	Bid	Ask	Total
0/16 1/16 2/16 3/16 4/16 5/16 6/16 7/16 8/16 9/16 10/16 11/16 12/16 13/16 14/16 15/16	0.1117 0.0405 0.0797 0.0324 0.0886 0.0342 0.0773 0.0337 0.0957 0.0351 0.0785 0.0347 0.0938 0.0363 0.0865 0.0413	0.1185 0.0387 0.0839 0.0342 0.094 0.0308 0.0788 0.0352 0.0995 0.0326 0.0751 0.0339 0.093 0.0315 0.0804 0.0399	0.1151 0.0396 0.0818 0.0333 0.0913 0.0325 0.0781 0.0345 0.0976 0.0338 0.0768 0.0343 0.0934 0.034 0.0835 0.0406	0.0878 0.0524 0.0686 0.0449 0.0737 0.0487 0.0691 0.045 0.0799 0.052 0.0729 0.0475 0.0785 0.05 0.077 0.052	0.0908 0.0506 0.069 0.051 0.0726 0.0482 0.0675 0.0519 0.0743 0.0488 0.0686 0.0517 0.0744 0.0491 0.07 0.0616	0.0893 0.0515 0.0688 0.0479 0.0732 0.0484 0.0683 0.0485 0.0771 0.0504 0.0708 0.0496 0.0765 0.0496 0.0735 0.0568
Panel B. Proportion of even-quotes within each price grid
Proportion of Even-16ths Among 16^ths Proportion of Even-8^ths Among 8ths Proportion of Even-4^ths Among Quarters Proportion of Whole Numbers Among Halves	0.7118 0.542 0.5292 0.536	0.7233 0.5543 0.5339 0.5416	0.7175 0.5484 0.5318 0.5387	0.6074 0.5242 0.523 0.519	0.5872 0.5289 0.527 0.5455	0.5973 0.5267 0.5247 0.5332

Table 8 The impact of quote clustering on spreads The first column shows the results when we regress the quoted spread of Nasdaq stocks against the four stock attributes and the extent of quote clustering. The second column shows the results of the same regression for NYSE stocks. To examine whether the differential extent of clustering between NASDAQ and NYSE quotes can explain the difference between NYSE and Nasdaq spreads, we estimate the following regression model: Spread^N - Spread^Y = 0 + i(Xi^N - Xi^Y) + 5(QC^N - QC^Y) + ; where Xi (i = 1 to 4) represents one of the four stock attributes, N and Y refer to Nasdaq and NYSE, respectively,  denotes the summation over i = 1 to 4, QC represents the extent of quote clustering, and  is an error term. We expect 5 to be positive if the differential degree of clustering between Nasdaq and NYSE quotes can account for the difference between Nasdaq and NYSE spreads. We repeat the above regression analysis with the effective and realized spreads. Absolute values of White's (1980) t-statistics are reported in parentheses.
	Quoted Spread			Effective Spread			Realized Spread
Independent Variable	Nasdaq	NYSE	Nasdaq - NYSE	Nasdaq	NYSE	Nasdaq - NYSE	Nasdaq	NYSE	Nasdaq – NYSE
Intercept 1/(Share Price) 1/(Number of Trades) 1/(Trade Size) Return Volatility Clustering Adjusted R^2 F-value	-0.0006 -1.18 0.0484 (6.17**) 5.2621 (6.39**) 48.4500 (4.07**) 0.0503 (3.97**) 0.0560 (9.96**) 0.6464 176.88**	-0.0007 (2.71**) 0.0533 (19.81**) 3.9750 (9.67**) 64.8947 (14.19**) 0.0415 (5.39**) 0.0200 (5.17**) 0.9140 1023.30**	0.0010 (4.51**) -0.0001 (3.05**) -0.0001 -0.89 0.0001 -0.56 -0.0114 -0.4800 0.0574 (11.37**) 0.2139 27.17**	-0.0001 -0.33 0.0329 (6.39**) 2.8352 (5.23**) 54.7216 (6.99**) 0.0301 (3.61**) 0.0371 (10.04**) 0.7376 271.36**	-0.0008 (5.54**) 0.0461 (30.84**) 2.2533 (9.85**) 35.6243 (14.01**) 0.0481 (11.25**) 0.0133 (6.19**) 0.9504 1842.59**	0.0012 (7.88**) -0.0001 (3.60**) -0.0001 -0.14 0.0001 -1.27 -0.0063 -0.4 0.0381 (11.25**) 0.2106 26.67**	-0.0001 (0.03) 0.0340 (6.86**) 2.7970 (5.37**) 46.2509 (6.15**) 0.0297 (3.70**) 0.0362 (10.18**) 0.7283 258.86**	-0.0006 (5.85*) 0.0464 (41.43**) 1.3184 (7.70**) 27.1569 (14.26**) 0.0212 (6.62**) 0.0125 (7.76**) 0.9649 2645.62**	0.0021 (14.09**) -0.0001 (3.07**) -0.0001 (0.25) 0.0001 (1.45) -0.0023 (0.15) 0.0340 (10.02**) 0.1742 21.29**
^*Significant at the 5% level. ^**Significant at the 1% level.

Table 9 Determinants of quote clustering on Nasdaq and the NYSE To examine whether quote clustering is related to stock attributes, we regress our measure of quote clustering against the four stock attributes using our sample of Nasdaq stocks and the matched sample of NYSE stocks. To examine whether differences in the extent of clustering between Nasdaq and NYSE quotes are due to differences in the attributes between Nasdaq and NYSE stocks, we run the following regression: QC^N - QC^Y = 0 + i(Xi^N - Xi^Y) + ; where QC represents the extent of quote clustering, Xi (i = 1 to 4) represents one of the four stock attributes, N and Y refer to Nasdaq and NYSE, respectively,  denotes the summation over i = 1 to 4, and  is an error term. Absolute values of White's (1980) t-statistics are reported in parentheses.
Independent Variables	Regression results based on level variables Nasdaq Quotes NYSE Quotes		Regression results based on differences between Nasdaq and NYSE
Intercept Share Price Number of Trades Trade Size Return Volatility Adjusted-R^2 F-value	0.0309 (6.78**) 0.0010 (9.63**) -0.0001 (11.50**) 0.0001 (0.46) 0.1055 (1.10) 0.3897 77.79**	0.0216 (5.79**) 0.0003 (3.25**) -0.0001 (6.33**) 0.0001 (0.73) 0.0768 (0.83) 0.1057 15.21**	0.0255 (15.38**) 0.0008 (3.09**) -0.0001 (2.23*) 0.0001 (0.11) 0.2646 (1.24) 0.0238 3.93**
^*Significant at the 5% level. ^**Significant at the 1% level.

1 ^These lawsuits were later consolidated into a single class-action in the Southern District of New York.

2 ^These new rules were phased-in for all Nasdaq National Market System (NMS) issues by October 13, 1997.

3 ^ECNs are proprietary trading systems such as Instinet that are used exclusively by market makers and large institutions.

4 ^See, for example, the market quality monitoring report posted on the NASD website.

5    ^Demsetz (1997) suggests that the excess of Nasdaq spreads over NYSE spreads reported in Christie and Schultz (1994) may not necessarily be an indication of collusion among Nasdaq dealers. Demsetz suggests that Nasdaq spreads are likely to be larger than NYSE spreads even in the absence of the alleged collusion because spreads on the Nasdaq were set exclusively by dealers, while NYSE spreads were set by both specialists and limit order traders. Because Nasdaq spreads reflect the interest of both market makers and limit order traders in our post-reform data, our study is not subject to the same criticism.

6    ^The dates on which the new SEC rules became effective for 13 batches of 50 stocks are: January 20, February 10, February 24, April 21, April 28, May 5, May 12, May 19, May 27, June 2, June 9, June 23, and June 30.

7    ^The discrepancy (26 stocks) may be due to some Nasdaq stocks moving to other exchanges or going bankrupt after being subject to the new SEC rules.

8    ^See, for example, Demsetz (1968), Benston and Hagerman (1974), Stoll (1978), McInish and Wood (1992), and Huang and Stoll (1996).

9    ^Nasdaq uses the same volume counting rules as the NYSE. Every time a trade occurs, either between two market makers, a market maker and a customer, or two customers, it is counted as one trade. The factor that makes it difficult to compare volumes of the two markets is the inter-dealer trading on Nasdaq.