Adverse selection & liquidity supply in a fast electronic market

Bruno Biais, Fany Declerck, Sophie MoinasToulouse School of Economics

Very, very, very preliminary! Comments and leniency welcome!

Banque de France, November 2013

Specialists / dealers / designated market makers offer prices (liquidity supply), investors hit those prices (liquidity demand)

In the old days

Market structure changes

1) Transparent electronic limit order books: all investors can monitor, post & hit quotes

=> Facilitates entry for liquidity suppliers

=> “Endogenous” market makers (e.g., hedge funds) instead of only designated market makers

Technological changes

2) High speed computer connections: HFTFaster connections & faster information => lower risks in liquidity supply => HFT endogenous market makers

High FrequencyTrader

Market

How did these changes affect determinants of market quality?

1. LOB: Free entry, increased competition in liquidity supply+ 2. HFT: better monitoring capacities of liquidity suppliers

=> more liquid markets?

But

How is liquidity supplied and by whom?

Is there more or less adverse selection?

HFT adverse selection & liquidity supply

High frequency traders get info before others=> limit orders less exposed to adverse selection=> good at supplying liquidity, posting limit orders

High frequency traders get info before others=> hit slow quotes with market (marketable) orders=> increases adverse selection for slow limit orders=> deters placement of limit orders by slow

Brogaard, Hendershott Riordan 2013: market orders

HFT market order to buy followed by positive return (informed) and comes after negative return (supplies liquidity) unlike non HFT

HFT limit orders exposed to adverse selection, but less thannon HFT

Brogaard, Hendershott Riordan 2013: limit orders

Are high-frequency traders the only ones to follow such strategies?

Open/transparent electronic limit order books: many different categories of market participants can choose to supply liquidity, e.g., hedge funds

Do these traders need to rely on high speed connection to markets, or can they rely on other sources of comparative advantage?

Capital / ability to carry inventoryInformation (more fundamental than high frequency)

If so, how do their strategies compare to those of HFTs?

Data to answer these questions

Data from Euronext and AMF : 117 stocks traded in EuronextParis, in Eurolist 100 + Next 150, from Jan to Sept, 2010

Dropped: 9 with stocks splits, SEO, … & 5 with very few trades

Orders and trades

Best quotes time-stamped at the micro-secondNeed to replay the entire limit order book

Tick-by-tick data including anonymised member IDKnow if agency trading vs prop tradingKnow if order came from member with high speed connection

Agency trading vs prop trading

Pure play prop-trader/market maker20 “principal” traders

Pure broker only placing client orders37 brokers

Placing both prop & client orders82 “dual” traders

Data to answer these questions

Data from Euronext and AMF : 131 stocks traded in EuronextParis, in Eurolist 100 + Next 150, from Jan to Sept, 2010

Dropped: 9 with stocks splits, SEO, … & 5 with very few trades

Orders and trades

Best quotes time-stamped at the micro-secondNeed to replay the entire limit order book

Tick-by-tick data including anonymised member IDKnow if agency trading vs prop tradingKnow if order came from member with high speed connection

MemberchoosesThrouput

Memberchoosescolocation

Ex: 50

Ex: 200

High speed connection: direct measure

Throughput = max number of messages / sec

Speed Capacity = Σ throuputs

Speed

0%

2%

4%

6%

8%

10%

12%

14%

16%

18%

[0 - 25] ]25 - 50] ]50 - 75] ]75 -100]

]100 -150]

]150 -200]

]200 -300]

]300 -400]

]400 -800]

]800 -1300]

]1300 -1600]

]1600 -2400]

]2400 -4600]

% of members

Max # messages per second

Define as “fast” the 16 members with capacity > 1300 mssg/sec

Fast Slow(>1300 mssg/sec) (< 1300 mssg/sec)

Principal 5 15(100% trades as principal)

Dual trader 11 71

Broker(0% trades as principal) 0 37

5 types of players

Sample of stocksSample : 117 stocks

Sub-sample: 20 stocks (more than 4To = 700 CDs)

large cap & financial: 1 stock (3 stocks)large cap & non-financial: 6 stocks (14 stocks)mid cap & financial: 1 stock (1 stock)mid cap & non-financial: 8 stocks (8 stocks)small cap & non-financial: 4 stocks (4 stocks)

Other stocks = hold-out sample

Sample period (Jan 1, Sept 30, 2010)

0

5

10

15

20

25

30

35

40

45

50

04/01/2010 04/02/2010 04/03/2010 04/04/2010 04/05/2010 04/06/2010 04/07/2010 04/08/2010 04/09/2010

VIX

CrisisModeratevolat

April 23: Grece asks for bailout

May 7: June 14: bailout downgrade

Low volat

Descriptive statistics

Descriptive statistics# of

messages - Daily mean

# mess/second - Mean

# mess/most active sec -

Mean

Daily mean fill

rate

Daily mean cancellation

rate

Daily volume

Trade size

Fast proptrader 193 787 9 528 8% 64% 3 610 469 9 116Fast dual trader 115 356 6 228 16% 52% 4 016 132 14 107

Slow proptrader 8 881 2 88 39% 36% 1 012 390 9 772Slow dual trader 4 304 2 34 52% 27% 553 828 12 936

Slow broker 263 1 17 65% 19% 339 289 18 998

Fast traders seem different from slow traders and brokersExcept for trade size: prop are different from dual and broker

-

100 000

200 000

300 000

400 000

500 000

600 000

700 000

800 000

900 000

23/02/2010 23/03/2010 23/04/2010 23/05/2010 23/06/2010 23/07/2010 23/08/2010

16 fast members > ½ messagesIncreased volat => more messages (slow & fast)

Number of messages

0

1

2

3

4

5

6

7

8

9

3/02/2010 23/03/2010 23/04/2010 23/05/2010 23/06/2010 23/07/2010 23/08/2010

Principals & fast have smaller trade to message ratio// Hendershott & al 2011: trade to mssg ratio proxies for algo

Trades to message ratio

Market order

Information content of market order

Signed % change in midquote regressed on aggressor type

sign of market order x [(Mt+k – Mt-) / Mt

-] =

β1,k Indicator that market order stemmed from fast prop

+ β2,k Slow prop + β3,k Fast dual

+ β4,k Slow dual + β5,k Slow broker

+ Fixed Effect stock + Fixed Effect day + error

After market buy, price risesEspecially for prop (fast or slow) traders: 8 bp after 5 minutesProp trade on reversals: supply liquiditySlow non-prop ride short-term momentum

Info content of market orders

-0,0015

-0,0010

-0,0005

0,0000

0,0005

0,0010

0,0015

-1 h

-30

mn

-15

mn

-10

mn

-5 m

n-3

mn

-2.5

mn

-2 m

n-1

.5 m

n-1

mn

-45

s-3

0 s

-15

s-1

s-0

.5 s

-0.1

s 00.

1 s

0.5

s1

s15

s30

s45

s1

mn

1.5

mn

2 m

n2.

5 m

n3

mn

5 m

n10

mn

15 m

n30

mn

1 h

MO = Fast Prop trader

MO = Slow Prop trader

MO = Fast Dual trader

MO = Slow Dual trader

MO = Slow Broker

Info content of market orders in midst of crisis

Larger information content of market (marketable) orders=> More adverse selection for limit orders hit

Momentum stronger, not reversal

-0,0015

-0,0010

-0,0005

0,0000

0,0005

0,0010

0,0015

-1 h

-15

mn

-5 m

n

-2.5

mn

-1.5

mn

-45

s

-15

s

-0.5

s 0

0.5

s

15 s

45 s

1.5

mn

2.5

mn

5 m

n

15 m

n

1 h

MO = Fast Prop trader

MO = Slow Prop trader

MO = Fast Dual trader

MO = Slow Dual trader

MO = Slow Broker

Signed (midquote after trade – price)/midquote before

Profitability of market orders

Prop market orders profitable: 5 bp after 5 minutesMomentum riding market orders of slow brokers not profitable

(spread > info advantage)

-0,0015

-0,0010

-0,0005

0,0000

0,0005

0,0010

0,0015

-1 h

-15

mn

-5 m

n

-2.5

mn

-1.5

mn

-45

s

-15

s

-0.5

s 0

0.5

s

15 s

45 s

1.5

mn

2.5

mn

5 m

n

15 m

n

1 h

MO = Fast Prop trader

MO = Slow Prop trader

MO = Fast Dual trader

MO = Slow Dual trader

MO = Slow Broker

Limit order

Adverse selection for limit orders

Signed % change in midquote regressed on type of memberwho placed limit order

sign x [(Mt+k – Mt-) / Mt

-] =

β1,k Indicator that limit order had been placed by fast prop

+ β2,k Slow prop + β3,k Fast dual + β4,k Slow dual

+ β5,k Slow broker + Fixed effect stock + Fixed effect day + error

Fast limit orders exposed to less adverse selection than slowSlow broker ask hit after decline in price, continued after tradeNo pattern before fast limit hit

Adverse selection for limit orders

-0,0015

-0,0010

-0,0005

0,0000

0,0005

0,0010

0,0015

-1 h

-30

mn

-15

mn

-10

mn

-5 m

n-3

mn

-2.5

mn

-2 m

n-1

.5 m

n-1

mn

-45

s-3

0 s

-15

s-1

s-0

.5 s

-0.1

s 00.

1 s

0.5

s1

s15

s30

s45

s1

mn

1.5

mn

2 m

n2.

5 m

n3

mn

5 m

n10

mn

15 m

n30

mn

1 h

LO = Fast Prop trader

LO = Slow Prop trader

LO = Fast Dual trader

LO = Slow Dual traders

LO = Slow Broker

Signed (midquote after trade – price)/midquote beforeProfitability of limit orders

Losses of limit orders < adverse selection cost: earn spreadSlow brokers & slow prop traders limit orders incur largest lossFast limit order executions profitable if unwound < 1 minuteFast market more profitable than limit // Hendershott et al. 2012

-0,0015

-0,0010

-0,0005

0,0000

0,0005

0,0010

0,0015

-1 h

-15

mn

-5 m

n

-2.5

mn

-1.5

mn

-45

s

-15

s

-0.5

s 0

0.5

s

15 s

45 s

1.5

mn

2.5

mn

5 m

n

15 m

n

1 h

LO = Fast Prop trader

LO = Slow Prop trader

LO = Fast Dual trader

LO = Slow Dual trader

LO = Slow Broker

Number of executed orders per trader

Fast prop traders use both market & limit orders (because relatively immune to adverse selection)Slow prop traders trade rarely with passive limit orders (because exposed to adverse selection)

0

50

100

150

200

250

300

350

400

450

500

Fast prop Slow prop

market (or marketable limit)

(not immediately marketable) limit

Signed % change in midquote after limit order hit

Adverse selection cost largerGreater disadvantage of slow prop and brokers

Adverse selection in midst of crisis

-0,0015

-0,0010

-0,0005

0,0000

0,0005

0,0010

0,0015

-1 h

-15

mn

-5 m

n

-2.5

mn

-1.5

mn

-45

s

-15

s

-0.5

s 0

0.5

s

15 s

45 s

1.5

mn

2.5

mn

5 m

n

15 m

n

1 h

LO = Fast Prop trader

LO = Slow Prop trader

LO = Fast Dual trader

LO = Slow Dual trader

LO = Slow Broker

Number of executed orders per tradermidst of crisis

Fast prop traders use more market orders & less limit ordersNo significant change for slow prop traders

0

50

100

150

200

250

300

350

400

450

500

Fast prop Slow prop

market (or marketable limit)

(not immediately marketable) limit

Conclusion: Prop tradingProp traders’ market orders more informed than non-prop orders

impose more adverse selection costs on others

Slow prop and fast prop market orders equally informed

Info content = 8 bp after 5 minutes

Profitable (= info content – half spread): 5 bp after 5 minutes

Prop traders (fast and slow) execute market orders on reversals:Buy after price declineSupply liquidity with market orders

Conclusion: Fast trading

Fast limit orders less exposed to adverse selection than slow

For prop traders, speed matters more for limit orders than formarket orders

Fast traders, less exposed to adverse selection, execute larger% of trades via passive (limit) orders than slow traders

Slow prop, more exposed to adverse selection, mainly trade withmarket orders (marketable limit)

Non prop slow traders ride momentum (buy after price rise):some information content, but not profitable