robert engle and asger lunde nyu and ucsd and university of aarhus may 2001

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1 Robert Engle and Asger Lunde NYU and UCSD and University of Aarhus May 2001

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Robert Engle and Asger Lunde NYU and UCSD and University of Aarhus May 2001. Trades and Quotes: A Bivariate Point Process. MICROSTRUCTURE ECONOMETRICS FOCUSES MAINLY ON TRANSACTION TIMES. WE ALSO SEE QUOTE REVISION TIMES. CENTRAL QUESTION: - PowerPoint PPT Presentation

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Page 1: Robert Engle and Asger Lunde NYU and UCSD and University of Aarhus May 2001

1

Robert Engle and Asger Lunde

NYU and UCSD and University of AarhusMay 2001

Page 2: Robert Engle and Asger Lunde NYU and UCSD and University of Aarhus May 2001

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MICROSTRUCTURE ECONOMETRICS FOCUSES MAINLY ON TRANSACTION TIMES. WE ALSO SEE QUOTE REVISION TIMES. CENTRAL QUESTION: HOW LONG DOES IT TAKE FOR INFORMATION TO BE INCORPORATED INTO PRICES? INSOFAR AS INFORMATION IS REVEALED BY TRANSACTIONS, A KEY INGREDIENT IS THE TIME IT TAKES FOR QUOTES TO BE REVISED IN RESPONSE TO A TRANSACTION.

Page 3: Robert Engle and Asger Lunde NYU and UCSD and University of Aarhus May 2001

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PREVIOUS RESEARCH 

Dufour and Engle “Time and the Price Impact of a Trade” Extending Hasbrouck’s model, they showed that the impulse response of prices to a signed trade depends upon the time between trades, the volume of the trade and the bid-ask spread at the time of the trade. The effects are measured in transaction time but if examined in calendar time they reveal that not only are the price impacts greater when the market is active, but they are faster too.

Page 4: Robert Engle and Asger Lunde NYU and UCSD and University of Aarhus May 2001

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Engle and Russell, “The Econometric Analysis of Discrete-Valued Irregularly-Spaced Financial Transactions DataUsing the Autoregressive Conditional Multinomial Model"  Showed that transaction price changes are more permanent when volume is higher, spreads are wider and transaction rates are higher.  The same effects are quicker in calendar time for high transaction rates.

Page 5: Robert Engle and Asger Lunde NYU and UCSD and University of Aarhus May 2001

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ECONOMIC MODELS OF QUOTE TIMING

1.   THERE AREN’T ANY – IN THEORY, QUOTES SHOULD BE REVISED IMMEDIATELY.

2. QUOTES WOULD NOT BE REVISED IF A TRADE CONTAINED VERY LITTLE INFORMATION – HENCE THE TIME WOULD BE LONG.

3. QUOTES WOULD NOT BE REVISED INSTANTLY BECAUSE IT TAKES TIME TO CALCULATE THE NEW PRICES.

 

4. QUOTES WOULD ONLY BE REVISED WHEN THE LIMIT ORDER BOOK CHANGES AND THEN WOULD REFLECT THE NEW PRICE AND DEPTH OF LIMIT ORDERS.

Page 6: Robert Engle and Asger Lunde NYU and UCSD and University of Aarhus May 2001

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Page 7: Robert Engle and Asger Lunde NYU and UCSD and University of Aarhus May 2001

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A BIVARIATE MODEL OF TT AND QQ DURATIONS IS NOT WELL SPECIFIED AS THEY ARE NOT IN A NATURAL ORDER.  MORE SPECIFICALLY, THEY DO NOT HAVE A COMMON INFORMATION SET.

Page 8: Robert Engle and Asger Lunde NYU and UCSD and University of Aarhus May 2001

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Page 9: Robert Engle and Asger Lunde NYU and UCSD and University of Aarhus May 2001

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CENSORING OF TQ DURATIONS FROM THE ECONOMIC MODEL IT IS CLEAR THAT THE DISTRIBUTION OF POSSIBLE QUOTE ARRIVAL TIMES WILL BE ALTERED BY AN INTERVENING TRADE.  HENCE SUCH DURATIONS SHOULD BE VIEWED AS CENSORED AND NOT OBSERVED.

,~),min(~

1 iiiii ttXYY

where ),'min(~

' iii ttt

Page 10: Robert Engle and Asger Lunde NYU and UCSD and University of Aarhus May 2001

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Page 11: Robert Engle and Asger Lunde NYU and UCSD and University of Aarhus May 2001

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Page 12: Robert Engle and Asger Lunde NYU and UCSD and University of Aarhus May 2001

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Page 13: Robert Engle and Asger Lunde NYU and UCSD and University of Aarhus May 2001

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Page 14: Robert Engle and Asger Lunde NYU and UCSD and University of Aarhus May 2001

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ESTIMATION Each likelihood can be maximized

separately Because there are parameters in common,

this will be inefficient but consistent Instead we use these estimates as starting

values for a joint maximization of the full likelihood

Page 15: Robert Engle and Asger Lunde NYU and UCSD and University of Aarhus May 2001

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DESCRIPTION OF THE DATA –TAQ-Trades and Quotes from NYSE August and September, 19978 randomly selected large cap stocks THERE ARE MORE QUOTE CHANGES THAN TRADES. MANY ARE JUST DEPTH CHANGES.

Page 16: Robert Engle and Asger Lunde NYU and UCSD and University of Aarhus May 2001

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DATA: TAQ – August 4,1997-September 30,199742 Trading Days (sixteenth ticks) 8 randomly selected stocks from the 50 most active. Between 25,000 and 50,000 tradesBetween 27,000 and 60,000 quotesBetween 10,000 and 30,000 midquote changes Between 20 and 40 sec between tradesBetween 1000 and 3000 shares in avg tradeBetween 10 and 22 seconds from Trade to Quote on averageBetween 30 and 130 seconds from Trade to Midquote changes Between 50% and 85% midquote changes are censored

Page 17: Robert Engle and Asger Lunde NYU and UCSD and University of Aarhus May 2001

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DATA TRANSFORMATIONS 1.        LEE AND READY: Transaction is a buy when transaction price exceeds midquote Transaction is a sell when price is below midquote Prices at the midquote, we take as undetermined 2.        LEE AND READY: Quotes are posted faster than transactions are recorded, hence add 5 seconds to quote times to get order correct

Page 18: Robert Engle and Asger Lunde NYU and UCSD and University of Aarhus May 2001

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TRADE EQUATION The expected trade duration equation:

x is the trade duration Lev.QQ is the Mean of the 10 most recent QQ durations Spr is the change in relative spread from the previous trade to this trade Lev.Spr is the level of the spread over the 10 most recent relative spreads Volume is the number of shares traded netVolume is the sum of buy volume minus sell volume over last 10 trades Back.Q is the time since the last quote was posted D are hourly dummy variables

11 1 1 2 1 3

1

4 1 5 1 6 1

ln( ) ln . .

.

ii i i i

i

ji i i j i

xlev QQ Spr lev Spr

Volume abs netVolume Back Q D

Page 19: Robert Engle and Asger Lunde NYU and UCSD and University of Aarhus May 2001

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MIDQUOTE EQUATION Expected time from a trade to next quote

y tilda is a trade-quote duration which may be censored d is a dummy variable for censored trade-quote durations

1 1 11 1 2 1 1 2 1

1 1 1

3 1 4 1 5 6 1

7 1 8 1

ln( ) ln ln

. .

.

i i i ii i i i

i i i i

i i i

ji i j i

y y x xd

lev QQ Spr lev Spr Volume

abs netVolume Back Q D

Page 20: Robert Engle and Asger Lunde NYU and UCSD and University of Aarhus May 2001

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TRADE EQUATION RESULTS Red indicates uniform high significance

across all 8 stocks Magenta is often significant with typical

sign across stocks

11

1

5 1 6 1

1 1 2 1 3

4 1

ln( )

.

. .ln ii

i

i

i ii

ji i j i

lev QQ Spr lev

abs netVo

x

Volume lume Back Q D

Spr

Page 21: Robert Engle and Asger Lunde NYU and UCSD and University of Aarhus May 2001

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INTERPRETATION:

1.       TRADE DURATIONS ARE LONGER WHEN LESS INFORMATION IS BEING REVEALED: THAT IS-

Past durations are long

Trades are small

Spreads are low

AND WHEN

Spreads have just increased

Quote changes are far apart

Page 22: Robert Engle and Asger Lunde NYU and UCSD and University of Aarhus May 2001

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MIDQUOTE RESULTS

11 1

1

3 1 4 1 5

11

12 1

1

6 1

7 1 8 1

2 11

ln( ) lnln

. .

.

ii i

i

j

i ii

i i

i i i

j i

ii

i

i i

y x

lev QQ Spr lev Spr Volume

abs netVolume Back Q

yd

x

D

Page 23: Robert Engle and Asger Lunde NYU and UCSD and University of Aarhus May 2001

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TRADE TO MIDQUOTE DURATIONS

ARE LONGER WHEN: Past TQ durations are long Current TT duration is long QQ durations are long It has been a long time since quotes were changed Spreads are low Spreads have fallen Volume is small Volume is unbalanced These are all indicators of low information flow

Page 24: Robert Engle and Asger Lunde NYU and UCSD and University of Aarhus May 2001

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QUOTE EQUATION INCLUDING PURE DEPTH QUOTES

Notice reduced significance and changed signs on spread variables and volume

1 11 2 2 1

4 1

11

7

1 11 1

3 1

1

8 1

1

1

5 6

ln( ) lnln

.

.

.

i i

i

i ii i

i i

i i

ji

i i

i i

ji i

y xd

lev QQ lev Spr VoSpr

abs netVolume D

y x

Bac

um

k Q

l e

Page 25: Robert Engle and Asger Lunde NYU and UCSD and University of Aarhus May 2001

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All Quote Durations are long when Past TQ durations are long Current TT duration is long QQ durations are long It has been a long time since quotes were changed Spreads are low XXX Spreads have fallen Volume is small XXX Volume is unbalanced These are all indicators of low information flow

Page 26: Robert Engle and Asger Lunde NYU and UCSD and University of Aarhus May 2001

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CONCLUSIONS PRICES ARE REVISED MORE RAPIDLY WHEN INFORMATION FLOWS INTO THE MARKET. VOLUME, SPREAD AND TIME BETWEEN TRADES ARE ALL INDICATORS OF INFORMATION FLOW.