Centralised Order Books versus Hybrid Order Books:

Jean-François GajewskiUniversité de Paris XII Val de Marne, IRG

Carole Gresse Université Paris Dauphine, CEREG

A Paired Comparison of Trading Costson NSC (Euronext)

and SETS (London Stock Exchange)

Topic of the paper

Differences in trading mechanisms may imply differences in execution costs and spread components

Harris(1997), Domowitz et al. (2001), Jain (2001) …

Many papers order-driven markets vs. quote-driven marketsMadhavan(1992), Pagano and Roëll (1992,1996), De Jong, Nijman and Roëll (1996),Huang and Stoll (1996) …

But few compare different types of order booksVenkataraman (2001), Kasch-Haroutounian and Theissen (2003)

Two order-driven market designsSETS (London Stock Exchange) Large caps (FTSE-100…), order book + multiple dealers

NSC (Euronext) almost pure centralised order-driven market

Common features / Organisational differences

Organisational feature NSC (Euronext Paris) SETS (LSE)

Trading mechanism Automated order-driven continuous market for most liquid stocks

Automated order-driven continuous market for Blue Chips

Trading day schedule Opening call auction: 9.00 amContinuous auction: 9.00-17.30Closing call auction: 17.35 pm

Opening call auction: 8.00 amContinuous auction: 8.00- 16.30Closing call auction at 16.35

Liquidity providers Patient investors (limit orders) Patient investors (limit orders)RSPs for retail ordersBroker-dealers outside the book

Priority rules Price Time

Price Time

Trading mechanism for ordinary trades

Matching of orders in the electronic order bookApplications

Matching of orders in the order bookBilateral negotiations with dealers off the order book Retail orders processed by RSPs, generally at a price at least as favourable as the order book best limit

Organisational feature NSC (Euronext Paris) SETS (LSE)

Block market Procédure de bloc Working Principal Agreement

VWAP trades Not practicable Processed by broker-dealers outside the order book

Tick size Price < 50 € : 0,01 € Price >50 and <100 € : 0,05 € Price >100 and <500 € : 0,1 € Price >500 € : 0,5 €

Price < 5£: 0,25 p Price>5 and <10£: 0,5 p Price >10£: 1 p

Organisational differences

Matching of all orders in the NSC electronic order book on Euronext

Bilateral negotiations with dealers outside the order book at the LSE

Processing of retail orders by Retail Service Providers at the LSE

Testable hypothesesSuperiority of mixed structures (Jain (2001), Gresse (2002), Swan and Westerholm (2004))

Fragmentation effects (Mendelson (19987), Chowdry and Nanda (1991), Easley, Kiefer & O’Hara (1996))

VolatilityH1. Prices are less volatile in the HOM (SETS) than in the COM (NSC).

Spreads and trade sizeH2. The internalisation of a substantial part of the order flow by dealers in the HOM fragments the market and enlarges quoted and effective spreads.

H3. Additional depth provided by dealers out the OB in the HOMincreases trade size (H3a)lower trading costs on large transactions (H3b)

Spread componentsH4. Order-processing costs are greater in the HOM than in the COM.

H5. Inventory costs are greater in the HOM than in the COM.

H6. Higher pre-trade transparency in the COM higher adverse selection costs

H7. ASC inside the order book of a HOM are greater than those incurred in a COM.

Data and methodology

Data selection

Trading data and quotes during the first six months of 2001211 securities continuously traded on Euronext Paris157 securities listed on SETS at the LSE

Sample matching

The Dow Jones economic sectorThe free float capitalisation on January 2001The total trading volume (€) during the first semester of 2001

2

2

1pLSEjp

Euronextip

LSEjp

Euronextip

j 2XX

XXMin

55 pairs of stocks

Measurement of volatility,trading costs and spread components

Quoted spreads

Mid

limitbuyingBestlimitsellingBestspreadQuoted

Mid

MidpriceTrading2spreadEffective

€ in sizeTradeMid

MidpriceTrading

costmarginalEffective

Effective spreads

Effective marginal costs (empirical estimation of the Kyle’s coefficient)

Spread components : Huang and Stoll’s methodology

Short-term volatility

2pricenimumiMpriceaximumM

pricenimumiMpriceaximumMrangericeP

volatilityreturncloseDaily

rangepricedailyAverageratioVolatility

Analysis of execution costs on SETS and NSC

Trading mechanism NSC

SETS

In the order book

Off the order book

Total trading volume (thousand €) 453,696,215160,735,063

(44.42%)201,153,419

(55.58%)

Volatility ratio 1.4865 2.3186

Quoted spread 0.2585% 0.7048%

Average number of quotes per day 1,802.22 423.29

Effective spread 0.2503% 0.4024% 0.4859%

Effective marginal cost 0.0703% 0.2238% 0.2613%

Average number of trades per day 145,547 34,413 35,055

Average trade size (€) 45,944 63,705 135,192

Share in trading volume by transaction class

0.00%

5.00%

10.00%

15.00%

20.00%

25.00%

Class 1 Class 2 Class 3 Class 4 Class 5 Class 6 Class 7 Class 8 Class 9

NSC

Sets

1.28%

5.03%

11.62%

10.15%

22.26%

16..7%

10.99%

7.27%

14.71%

0.76%

3.39% 3.39%

5.37%

15.97% 16.34%

14.52% 15.69%

21.73%

Effective spreads by transaction class

0.00%

0.10%

0.20%

0.30%

0.40%

0.50%

0.60%

0.70%

0.80%

0.90%

1.00%

Class 1 Class 2 Class 3 Class 4 Class 5 Class 6 Class 7 Class 8 Class 9

NSC

Sets - Iob

Sets - Oob

0.2537% 0.2469% 0.2476% 0.254%0.2673% 0.2793% 0.2564%

0.2348%

0.9591%

0.4103% 0.4038% 0.4038% 0.4147%

0.6069% 0.6686%

0.7046%0.7571%

0.2129%

0.457% 0.5025% 0.5025%

0.5736%

0.4199% 0.4386%

0.4704% 0.4622%

0.3435%

Components of the bid-ask spread on NSC and SETS (1)

Market Parameter

Adverse selection and inventory holding cost component

Mean Std. Err. Median T S

SETS (all trades) SETS 17.59% 0.1075 16.01%

SETS (order book

trades only) SETS_iob44.53% 0.0151 44.59%

NSC NSC 38.16% 0.0097 36.55%

SETS vs NSC SETS - NSC -20.57%*** 0.0139 -20.51%*** -14.76-3.37

(52<0)

SETS(ob) vs NSC SETS_iob- NSC 6.36%*** 0.0163 6.34%* 3.91.82

(37>0)

Huang & Stoll’s 2-way decomposition (GMM estimation)

= ASC + IHC in % of the spread

1- = order processing costs in % of the spread

Components of the bid-ask spread on SETS and NSC (2)

MarketNb of

stocks

Mean Mean Mean

SETS(all trades)

18 0.4134 5.82% 11.52%

SETS(order book trades only)

44 0.4214 28.6% 25.57%

NSC 25 0.5148 9.24% 17.43%

Huang & Stoll’s 3-way decomposition (GMM estimation)

= adverse selection component = inventory holding cost component

Same conclusions with non-parametric tests on a 7-pair matched sample

Economic and institutional factors explaining the difference in spreads: Panel regressions

Float cap. is not significant

# trades, P: ns

Inter-cept

volatility volume Imbalance Tick size FR R²

Quoted spread *** *** ** *** *** 60.31%

Quoted spread *** *** ** *** *** 63.47%

Effective spread *** *** *** *** *** 66.19%

Effective spread *** *** ** *** *** 68.09%

Concluding remarks

VolatilityShort-term volatility of SETS stocks significantly exceeds the one of NSC stocks (Rejection of H1).

Spreads and trade size

The hybrid order-driven market is globally more expensive (H2, rejection of H3b) but trades are larger in this market (H3a).

Spread components

The order processing cost component = a much bigger part of the spread on the hybrid market than on the centralised order book (H4).

Weight of the inventory holding component is not lower on NSC than on SETS (rejection of H5)Higher on SETS when considering order book trades only.

ASC on SETS < ASC on NSC (week evidence, H6)but ASC is maximum on SETS when considering order book trades only (H7).

Factorstick size & share of volume executed by dealers in the SETS market