why etfs plunged during the flash crash

8/7/2019 Why ETFs Plunged During The Flash Crash

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Abstract

Exchange traded funds as a class were more affected by the flash crash of May 6 than any othercategory of securities. We connect the debates over the linkages between exchange traded funds

and the broader market, and a potentially severe mismatch in liquidity, by asking the question: how

did liquidity provision affect price discovery in the market for exchange traded funds? We provide

evidence that price discovery failed dramatically for this class of securities during the crash, and that

the proximate cause was an extreme deterioration in liquidity, both in absolute terms and relative

to individual securities in the baskets tracked by the funds. Our results are consistent with market

participants behavior in terms of liquidity provision, but not with conjectures concerning a failure in

market structure or in the exchange traded fund product.

Liquidity and Price Discovery inExchange-Traded FundsOne of Several Possible Lessons from the Flash Crash

May 2010

2010 Investment Technology Group, Inc. All rights reserved. 052710-32837

These materials are for informational purposes only, and are not intended to be used for trading or investment purposes. The information contained herein has been taken from trade and sta-tistical services and other sources we deem reliable but we do not represent that such information is accurate or complete and it should not be relied upon as such. No guarantee or warranty ismade as to the reasonableness of the assumptions or the accuracy of the models or market data used by ITG. These materials do not provide any form of advice (investment, tax or legal). ITGInc. is not a registered investment adviser and does not provide investment advice or recommendations to buy or sell securities, to hire any investment adviser or to pursue any investment ortrading strategy. The positions taken in this document reflect the judgment of the individual authors and are not necessarily those of ITG.

Milan Borkovec

Managing Director

Investment Technology Group, Inc.

Ian Domowitz

Managing Director


Vitaly Serbin

Director


Henry Yegerman

Managing Director


212.444.6300

[email protected]

www.itg.com


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Liquidity and Price Discovery in Exchange-Traded Funds

2Investment Technology Group, Inc. (ITG)

I. Introduction

On May 6, 2010, the U.S. financial markets exhibited an unusual drop in prices, lasting only a few

minutes before recovering. This event has become known as the flash crash, given its apparent

suddenness and short duration. Despite a comprehensive, 151 page report by the Securities and

Exchange Commission (SEC) and the efforts of a broad spectrum of market participants, little is

known about the crash, in terms of causal factors and lessons learned.1

One fact emerged early in the analysis of events. Of all equity transactions cancelled by exchanges

due to a price drop in excess of 60 percent from 2:40 PM ET prices, exchange-traded funds (ETFs)

account for roughly 70 percent of the total. This leads the SEC to conclude that ETFs, as a class,

were affected more than any other category of securities. As a result, SEC staff advises that they

are considering linkages between ETF price declines and the fall in the broader equity market as asingular research item.2 Separately, the staff conjectures that the market experienced a severe mis-

match in liquidity, as evinced by sharply lower trading prices, although direct evidence on this point

is currently lacking.

We connect these topics by investigating a broad question in the context of the events of May 6:

how did liquidity provision affect price discovery in the market for ETFs? Price discoveryis generally

conceded to be a central function of financial markets, although the term is generally only loosely

defined, or characterized narrowly in the context of a specific mathematical model of markets.

By any definition, however, price discovery is the revelation of value through the trading process.3

Attempts to quantify price discovery generate large amounts of technical detail, largely because

no one really knows what fundamental value is in practice. Attempts to link price discovery and

liquidity then often suffer from lack of data on liquidity, with the effect of resorting to volume

data which may not be representative or to indirect measures, such as the bid-ask spread.

A fundamental tenet of ETFs as an asset class is the adherence of the price of the ETF to the price of

the underlying basket of stocks. Although this relationship is rarely perfect for a variety of reasons,

natural market activity lines up pricing and most deviations are merely noise from the perspective of

longer term investors. For our purpose, price discovery is the process by which the ETF value mimics

the value of the underlying portfolio. A measure of price discovery is the extent to which trading the

ETF correctly values the portfolio.

By this definition, price discovery failed during the events of May 6. Unlike many other studies, we

do not require elaborate statistical techniques or models to reach this conclusion. The deviations

reported in this study are massive enough to be obvious to the naked eye. Our interest is in the

characteristics of liquidity provision that accompanied such failure.

1 Preliminary Findings Regarding the Market Events of May 6, 2010, Report of the Staffs of the CFTC and SEC to the Joint Advisory Committee on Emerging Regulatory Issues, May 18, 2010; henceforth referred to as the SEC Report.

2 SEC Report, pages 5 and 6.

3 This notion is closest to literature from the mid 1980s that equated transaction prices with the equilibrium value of the security. Al-ternative definitions include: the dynamic process by which market prices incorporate new information, innovations in the efficientprice, and a notion of fair pricing, in which a price should accurately reflect the demand propensities of all traders, which in principleshould not be obscured by transitory market thinness or by the design of trading market structure. The academic literature is volumi-nous; 81 papers related to the topic are cited by one paper in our experience, over seven years ago. We make no attempt to survey allthe nuances therein.


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Our conclusions are based on a sample of 116 ETFs and a subsample of 24 such securities for whichwe can construct the underlying portfolio of stocks and its returns for each ETF. We do not rely on

Intraday Indicative Values published by market data vendors, preferring to calculate an exact price

from the basket at relatively high frequencies, especially given the extreme price volatility over the

period. Some of our computed statistics rely on publicly available Level 1 data, archived before data

vendors purged May 6 data of broken trades. The remainder, and in many ways the most interest-

ing, of the results are derived from consolidated limit order book data, based on Level 2 data feeds

from BATS, Arca, NYSE, and Nasdaq. Data are subject to no filtering process, given the unusual

events of May 6, in particular. The order book data provide information on depth for 10 price levels,

on both sides of the market.

We begin in Section 2 with an overview of trading activity across the entire ETF sample. The results

are reminiscent of those in the SEC Report for the broader market, as might be expected, although

the magnitude of some of the changes in the ETF space may be surprising. Share volumes and

trading activity rise sharply starting at 2:40, beginning from already elevated levels relative to the

previous three days. An explosion in volatility followed within several minutes, with multiple spikes

representing increases of several orders of magnitude. We also examine cancel-and-correct activity,

as well as high-frequency pinging of the consolidated order book, and correlate observed behavior

with volume and volatility events.

Liquidity provision is the topic of Section 3. Average bid-ask spreads for our ETF sample are on

the order of three to five basis points in normal periods, but rose into the hundreds of basis points

over the course of the event. Spreads are simply an indicator of liquidity, however, and the extreme

volatility of prices makes this measure more unreliable than usual. We therefore examine displayed

liquidity of the consolidated limit order book, including depth at the best bid and offer, and depth

across the first ten price levels on both sides of the market. By either measure, and on both sidesof the market, liquidity declined abruptly to levels close to zero for an extended period. Depth at

the best bid and offer begins its decline long before spreads provide a reliable indication of a

decrease in liquidity provision. The evidence with respect to spreads leads observers to believe in

an exit by participants performing a market-making function, but the data suggest a much broader

exodus from the markets in terms of liquidity provision.

Our main hypothesis is addressed in Section 4, namely that the price discovery process broke down

for ETFs during the flash crash, and that the massive withdrawal of liquidity is a driver of that failure.

Underlying portfolios for a subsample of ETFs are constructed, and returns of those baskets are

contrasted with the returns of the ETF sample. Liquidity is modeled as the depth of the consolidated

limit order book through ten price levels, as well as depth at the top of the book. The sharp drop

in liquidity and its correlation with the failure of the price discovery process is unambiguous. That

failure is clear, even from a simple visual examination of the data.

We conclude the paper with a short discussion of the role of these results in the debate centered

on the flash crash. Our explanation of the behavior of ETFs as a class does not fit neatly into current

thinking, being largely behavioral in nature and not directly related to either market structure or the

structure of an ETF product. Market participants supply liquidity, as opposed to execution venues.

It is also difficult to explain how the nature of the product itself might have contributed to the

decline in liquidity, the lack of price discovery, and the consequent fall in pricing relative to the

underlying market.


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II. Trading Behavior Across ETFs

The SEC Report paints a broad picture of the flash crash, and we refer the reader to that document

for its detail across markets and asset classes. The description of events in this section is isolated to

116 relatively liquid ETFs.4 Based on our own analysis of these 116 securities, we can safely say that

all metrics presented in this section have typical intraday patterns, with the exception of May 6,

as measured over the course of the three days leading up to the event. Our data are based on 15

second intervals, and the charts below are limited to the 2:40 to 3:00 time-frame on May 6. This

interval coincides with the SEC finding that, despite a generally depressed day for equity values,

prices began their steep decline at 2:40, leading to a fall in major indexes in excess of 5 percent in

the next five minutes. We deal with pricing in Section 4, and concentrate on the backdrop of the

price decline and rise here. This short period began with an explosion of ETF volume and number of

trades, illustrated in Figure 1.

4 This represents approximately 15 percent of the total number of ETFs identified in the SEC report, but we deal only with equity ETFs.

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At the peak, about 2:45 in the afternoon, volume is up 89 percent compared to that observed at

2:40. The 2:40 volume itself represents an increase of 800 percent relative to the average for thattime over the preceding three days, although minute by minute comparisons of May 6 to those

days all show volume increases of reasonably large magnitude. Volume then declined sharply, and

is down 70 percent compared to the 2:40 baseline. The number of trades shows a similar pattern.

The peak in this case is at 2:45:30, an increase relative to the baseline of 137 percent, representing

a small decline in the number of shares per trade over the interval.

The correlation between volume and volatility is well documented, and the flash crash is no excep-

tion, although the timing is a bit different, as illustrated in Figure 2. Volatility is calculated based on

midquote pricing over the 15 second interval.

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The explosion in volatility lags that of volumes and trades by several minutes.5 Levels do not rise

significantly relative to the average over the preceding three days until roughly 2:45. The increasewas abrupt. At 2:44:30, volatility was up about 28 percent relative to the baseline and at 2:45, the

increase is 231 percent. Two spikes are obvious. At 2:47:45, volatility is up by several orders of mag

nitude compared to that at 2:40. After a short recession, the movement at 2:49:30 is even larger.

This spurt in volume and volatility is signaled by a sharp increase in the number of buy and sell limit

order cancellations, illustrated in Figure 3.

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Figure 2. ETF Volatility


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The behavior of cancel-and-correct activity on the buy and sell side of the market is similar. At 2:40,activity on the buy side is already up by 456 percent, and on the sell side, by 391 percent relative

to the three-day average preceding May 6, at the same time during the day. The peak occurred at

about 2:45:30 in both cases, as well, before declining to normal levels at 2:47. These particular

statistics may be of interest in the context of liquidity provision, based on anecdotal evidence that

some trading shops were monitoring message traffic and withdrew from the market based on the

type of spikes observed.

Although not pictured here, it is possible to construct the analogue of order imbalances for cancel

and order modification activity. Until 2:43:30, such imbalances between buy and sell activity hovered

around zero, and then turned negative as selling activity increased. Negative spikes were observed

until just after 2:49, by which time cancellation activity had returned to normal, for the most part.

This is followed by roughly three minutes of positive imbalances, before settling down.

Trade imbalances for the ETF sample follow a somewhat different pattern, illustrated in Figure 4.

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Depth at the quotes begins its decline long before the spreads provide a reliable indication of adecrease in liquidity. At 2:40, average bid size is 46 percent lower than the average during the

earlier part of the week, and depth at the offer is 50 percent down relative to the same average.

A further decline is observed at approximately the same time as volatility begins its rise. From 2:46

through 3:00, depth on both sides is 60 to 80 percent lower than the 2:40 baseline.

A comparison of Figure 7 with the volume activity in Figure 1 illustrates that volume is not indica-

tive of liquidity supply, merely of transactions at potentially widely disparate prices. Volume is rising

steadily as liquidity declines, and does not begin to fall until liquidity provision stabilizes at 2:47. The

number of ETF trades in the market also levels off from a previous peak at roughly the same time.

We will see in Section 4 that the big deviation in ETF prices relative to the underlying basket does not

begin much before 2:45. Nevertheless, trading activity works its way through the aggregate order

book, resulting in a precipitous drop in liquidity across the first ten price levels as liquidity fails to be

replenished by market participants. This is evident from Figure 8, which contains bid and ask depth,

aggregated across the top ten price levels and charted over the period.

Figure 8. ETF Depth for Ten Levels of Prices

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The decline in consolidated liquidity is massive. The peak during the period is roughly 14 times the

liquidity at the trough, and the bottom persists within a small range for the remainder of the crash.It is not much of a stretch to say that liquidity fell to zero in relative terms, and on an ETF by ETF

basis, that statement is literal in some cases.

We hasten to add that a sample of visible liquidity is the basis of these conclusions. We have no

information on resting orders in dark pools, for example. The structure of order book markets

does encompass reserve orders, however, a form of hidden liquidity. While we cannot observe this

depth explicitly, a floor to such reserve liquidity can be estimated by examining executions against

orders which do not visibly rest on the order books during the period. This is illustrated in Figure 9.

Figure 8. ETF Depth for Ten Levels of Prices

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Figure 9. ETF Hidden Liquidity

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These charts show more volatility than displayed depth, being dependent on transaction informa-tion. Although what we label hidden order liquidity appears much higher during the period than

the remainder of the weeks activity, the burst in transactions shown in Figure 1 may account for this

behavior. The peaks between 2:45 and 2:46, for example, coincide with spikes in the number of

transactions in the sample. By 2:45:30, visible liquidity is evaporating, transaction volume is peaking

and hidden order driven trades are at their height.

Although not explicitly shown here, hidden order imbalances (buy versus sell) exhibit roughly the

same behavior as observed in Figure 4 for aggregate trade imbalances. The difference is scale.

While aggregate trade imbalance saw a trough at 2:42:30, the negative share count at that time is

over 20,000 for the 15 second interval. In the case of hidden orders, the same imbalance is almost

exactly half that number.

IV. Price Discovery and Liquidity

The SEC Report notes that the pricing of ETFs as a class was affected more than any other category

of securities. Nearly 70 percent of the securities in which trades were broken on May 6 were ETFs,

and breaks were determined by returns falling below a 60 percent threshold. Roughly 160 ETFs

experienced lows during the day, relative to the close on May 5. In this section, we concentrate on

a sample of 24 ETFs, for which we can construct the underlying portfolio.7 Of these, 18 experienced

a decline of over 60 percent, and the remainder did not have any trades broken.

Our hypothesis is that the price discovery process for ETFs broke down during the flash crash, and

that the withdrawal of liquidity discussed in the last section is a driver of that failure. Price discoveryis the revelation of value through the trading process. In the case of ETFs, price discovery is mea-

sured by the extent to which trading in the ETF correctly values the underlying portfolio.

The breakdown of price discovery during the period can be illustrated through a simple correlation

analysis. Prior to the event, all contemporaneous correlations between ETF and underlying returns

are close to one, as they should be. For all 24 ETFs, the contemporaneous correlations between the

ETF returns and the underlying fell to below 0.4 during the flash crash; in many cases, the correlation

fell through zero and turned negative for the period. We also looked at the correlations between

ETF and underlying in terms of lead-lag relationships, e.g., the correlation between the ETF at 2:45

and the underlying at 2:44:45 or vice versa. All correlations fall sharply and slowly recover beginning

at 3:00.

Regardless of whether the underlying exhibited pricing that represents fundamental value, price

discovery for the ETFs clearly failed. The ETF simply decoupled from its underlying portfolio. The

question is the extent to which liquidity provision, or lack thereof, may have contributed to the

decoupling. We begin by example, starting with liquidity at the best bid and offer for IVW (S&P

500 Growth Index) and for SPY (S&P 500), based on depth at the top ten price points in the market.

Figure 10 shows the situation for IVW, for which trades were broken.

7 These ETFs are listed in the Appendix. We do not use published intraday indicative values, and construct pricing and liquidity infor-mation directly from the components of the baskets underlying the ETFs.


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Figure 10. Cumulative Returns and Liquidity at the Best Bid and Offer for IVW

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IVW Vs. Portfolio: Ask Depth Level 1

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IVW Vs. Portfolio: Bid Depth Level 1

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These charts, and those that follow, have the following format. Cumulative return over the periodis in percent, on the right-hand axis. Liquidity is indexed on the left axis, to make the results more

obvious and to scale the data so that liquidity may be shown on the same graph. The initial index

value is 1.0 for all liquidity series, representing the level of liquidity at 2:35. Absolute levels of liquid-

ity, in share terms, are not comparable here, but their changes over time are represented by changes

in the index values.

The bid and the ask depth, at the best bid and offer, tell similar stories, but with different timing.

The disconnect in pricing begins with an increase in ETF liquidity, but a decrease in the depth of the

underlying. ETF liquidity turns sharply negative on the bid just prior to 2:47, and on the offer about

a minute later. Between 2:49 and 2:51, the ETF and its portfolio are completely decoupled. While

the underlying portfolio is recovering value from its earlier dip, the ETF return is plunging by over 60

percent. At 2:49, liquidity at the top of the book drops to zero, and that of the underlying reaches

its low on the offer side. This situation persists for two minutes, during which the ETF return is

virtually pegged to its current low, before recovering somewhat and then falling again sharply. With

relatively few exceptions, liquidity in the ETF remains below the initial index value of one, and is near

zero on the offer side for much of the period starting at 2:48. Except for the fact that liquidity in the

underlying does not touch zero, much the same can be said for the portfolio of stocks itself.

The situation is even more starkly illustrated by depth of book over the first ten price levels of the

securities, given in Figure 11.

Figure 11. Cumulative Returns and Liquidity at Ten Price Points for IVW

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IVW Vs. Portfolio: Ask Depth Level 1-10

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In contrast to the results for the top of the order book, there is no ambiguity here with respect to a

sharp fall in liquidity and its correlation with the failure in the price discovery process of the ETF. Both

downward spikes in ETF return more or less coincide with a fall of ETF liquidity to zero. The under-

lying portfolio is actually recovering during those periods. The decoupling of prices, between the

underlying and the ETF, follows a continuous erosion of liquidity provision in both the portfolio and

the ETF security.

Although the price drop in the SPY ETF is a small fraction of that observed for its growth counter-

part, IVW, the same behavior is observed, illustrated in Figure 12.

Figure 11. Cumulative Returns and Liquidity at Ten Price Points for IVW

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IVW Vs. Portfolio: Bid Depth Level 1-10

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Figure 12. Cumulative Returns and Liquidity at Ten Price Points for SPY

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1.4

1.6

1 4: 35 1 4: 37 1 4: 39 1 4: 41 1 4: 43 1 4: 45 1 4: 47 1 4: 49 1 4: 51 1 4: 53 14 :5 5 1 4: 57 1 4: 59 1 5: 01 1 5: 03 1 5: 05

Liquiduty-Ask_

Depth_

Level1

IndexChange

-10

-9

-8

-7

-6

-5

-4

-3

-2

-1

0

Cum

ulativeReturnPct.

Ind SP Y As k_1 0 Ind P ortfolio As k_1 0 S PY Cum Re t Por tfolio Cum Re t

SPY Vs. Portfolio: Bid Depth Level 1- 10

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1 4: 35 1 4: 37 1 4: 39 1 4: 41 1 4: 43 1 4: 45 1 4: 47 1 4: 49 1 4: 51 1 4: 53 14 :5 5 1 4: 57 1 4: 59 1 5:0 1 1 5: 03 1 5: 05

Liquiduty-Ask

_Depth_

Level1IndexChange

-10

-9

-8

-7

-6

-5

-4

-3

-2

-1

0

CumulativeReturn

Pct.

Ind SPY Bid_ 10 Ind Portfolio Bid_ 10 SPY Cum Re t Por tfolio Cum Ret


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Relative to IVW, the SPY ETF exhibits less volatility, and a smaller deviation from its underlyingportfolio. Nevertheless, the failure of price discovery follows a similar decline in liquidity, both

for the ETF and the underlying. Deviations in pricing persist until after 3:00, consistent with the

continuing lack of depth, particularly on the offer side of the ETF market.

These examples suggest that the breakdown in price discovery occurred even for the most liquid

of ETFs. Securities subject to trade cancellations show somewhat different behavior in this respect,

compared to ETFs that did not experience a broken trade. We separate these two groups in the

figures below, which illustrate behavior in the aggregate across the sample. Figure 13 contains

information on ETFs which we labelAffected, for which trades were broken. Figure 14 concerns

UnaffectedETFs, for which there were no trade breaks.

Figure 13. Cumulative Returns and Liquidity at Ten Price Points for

Affected ETFs

!

Affected ETF's and Aggregated Portfolio

Bid Depth Level 1-10

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

2

1 4: 35 1 4: 37 1 4: 39 1 4: 41 1 4: 43 1 4: 45 1 4:4 7 1 4: 49 1 4:5 1 1 4: 53 14 :5 5 1 4: 57 1 4: 59 1 5: 01 1 5: 03 1 5: 05

Liquidity-Bid_

Depth_

Level1-1

0Index

Change

-70

-60

-50

-40

-30

-20

-10

0

CumulativeReturnPct.

Indx-AffectedETF's-Bid Depth10 Indx-Affected Portfolio-BidDepth10

AffectedETF's-CumRet Affected P ortfolio-CumRet


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Figure 14. Cumulative Returns and Liquidity at Ten Price Points for

Unaffected ETFs

!

!

Unaffected ETF's and Aggregated Portfolio

Bid Depth Level 1-10

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1 4: 35 1 4: 37 1 4: 39 1 4: 41 1 4: 43 1 4: 45 1 4: 47 1 4: 49 1 4: 51 1 4: 53 14 :5 5 1 4: 57 1 4: 59 1 5: 01 1 5: 03 1 5: 05

Liquidity-Bid_

Depth_

Level1-10

Index

Change

-12

-10

-8

-6

-4

-2

0

CumulativeReturnPct.

Indx-UnaffectedETF's-Bid Depth10 Indx-UnAffected Portfolio-BidDepth10

UnaffectedETF's-CumRet UnAffected P or tfolio-CumRet

Unaffected ETF's and Aggregated Portfolio

Ask Depth Level 1-10

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1 4: 35 1 4: 37 1 4: 39 1 4: 41 1 4: 43 1 4: 45 1 4: 47 1 4: 49 1 4: 51 1 4: 53 14 :5 5 1 4: 57 1 4: 59 1 5: 01 1 5: 03 1 5: 05

Liquidity-Bid_

Dep

th_

Level1-10Index

Change

-12

-10

-8

-6

-4

-2

0

Cumulative

ReturnPct.

Indx-GoodETF-Ask Depth10 Indx-UnAffected Portfolio-AskDepth10 Good ETF-CumRet UnAffected Portfolio-CumRet


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The group of unaffected ETFs look very much like the SPY, in terms of return and liquidity behavior,averaged across this sample. Liquidity supply begins to collapse early on for the underlying portfolio

of stocks, and the slide in ETF depth begins at roughly 2:43. These declines appear to be even more

sudden than for the affected ETF sample, and on the offer side of the consolidated book, depth goes

almost to zero for an extended period. Price discovery is not restored until after 3:00, which is off

these particular charts.

The price slide for unaffected ETFs is less than that for those affected, by definition. Failure of price

discovery in the former includes periods during which the returns on the ETFs exceeded those of the

baskets, while for the latter, the extreme price move kept ETF pricing below that of the basket in

terms of cumulative returns. We have no explanation at this time as to why one group saw declines

in excess of 60 percent when the other did not. We suspect, however, that a detailed look at the

various price levels in the order book would reveal salient differences. For example, fully half of the

affected ETFs in the sample encountered quotes of ten cents or less within the top ten prices on the

order book, and a third of the affected securities hit a penny within those ten price points. This is

relevant for the regulatory discussion with respect to a ban on stub quotes, especially since none of

the unaffected securities hit such prices in the book. Regardless, the main conclusion from the data

holds for both groups: the flash crash for ETFs embodies a failure of price discovery, which in turn

may be characterized as a severe liquidity crisis.

V. Conclusion

Two broad explanations have been proposed for the behavior of ETFs as a class of securities during

the flash crash of May 6. The first is an unspecified problem with ETFs as a product; the second isthat there are flaws in the U.S. trading market structure. Opinions may legitimately vary, and much

awaits the larger cross-market study of extremely granular data proposed by the SEC in its Report.

The data in this paper suggests another way of thinking, which does not fit neatly into either

category. Price discovery failed for ETFs during the crash, and the proximate cause was an extreme

deterioration in liquidity, both in absolute terms and relative to individual securities in the baskets

tracked by the ETFs. The reason that this explanation does not fit nicely into current thinking is

rather simple: investors, and market participants generally, supply liquidity; exchanges, alternative

trading systems, and other elements of market structure do not. ETFs as a class of product have

attracted much liquidity interest in other periods. It is unrealistic to believe that the integrity of the

product offering was somehow reassessed by the investing public in a matter of minutes, leading to

a severe decrease in investor interest exhibited by lack of depth.

The fact that our own explanation is almost behavioral in nature does not mean that the conclu-

sions reached here are irrelevant to other parts of the debate. For example, much has been made

of the use of market orders during the crash, including stop loss orders. We have little to say with

respect to the basic objections to market orders; they have been part of the landscape long before


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current market structure. The origins of the market order debate are clear from these data, howeverMarket orders tore through price levels in a market, within which depth had fallen already by over

90 percent at the height of the dislocation. Liquidity deterioration in the individual stocks was less

pronounced, and market orders found depth levels that limited price drops, in relative terms.

There are many avenues for further study, and the SEC Report itself raises a plethora of questions.

Some of those questions may never get answered, at least to the extent that the answers explain

the origins and fundamental causes of the crash. Price discovery is a central function of securities

markets, however, and we would encourage additional work in this direction, in particular.

The information contained herein has been prepared for informational purpose only and should not be considered as a solicitation tobuy or offer to sell any security. The information has been compiled from sources believed to be reliable, but cannot be guaranteed.Supporting documentation, including details of any assumptions used in the completion of this information, is available upon request.ITG Canada Corp (Member CIPF) is registered as an Investment Dealer in the provinces of Ontario, British Columbia, Alberta, Saskatch-ewan, Manitoba, Quebec, New Brunswick and Nova Scotia. Consultative and related services by ITG do not constitute legal advice.

2010 Investment Technology Group, Inc. All rights reserved. 052710-32837


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Appendix

The 24 ETFs for which underlying portfolios are constructed and tracked through May 6 are listed

below. Asterisks denote ETFs for which trades were broken during the flash crash.

IJH ISHARES TRUST S&P MIDCAP 400 INDEX FUND*

IJJ ISHARES TR S&P MIDCAP 400 VALUE INDEX FUND*

IJK ISHARES TR S&P MIDCAP 400 GROWTH INDEX FUND*

IJR ISHARES TRUST S&P SMALLCAP 600 INDEX FUND*

IJS ISHARES TR S&P SMALLCAP 600 VALUE INDEX FUND*

IJT ISHARES TR S&P SMALLCAP 600 GROWTH INDEX*

IVE ISHARES TR S&P 500 VALUE INDEX FUND*

IVV ISHARES TRUST S&P 500

IVW ISHARES TR S&P 500 GROWTH INDEX FUND*

IWB ISHARES TRUST RUSSELL 1000 INDEX FUND*

IWD ISHARES TR RUSSELL 1000 VALUE*

IWF ISHARES TR RUSSELL 1000 GROWTH*

IWM ISHARES TRUST RUSSELL 2000 INDEX FUND

IWN ISHARES TR RUSSELL 2000 VALUE*

IWO ISHARES TR RUSSELL 2000 GROWTH

IWP ISHARES TR RUSSELL MCP GROWTH*

IWR ISHARES TR RUSSELL MIDCAP*

IWS ISHARES TR RUSSELL MCP VALUE*

IWV ISHARES TRUST RUSSELL 3000 INDEX FUND*

IWW ISHARES TR RUSSELL 3000 VALUE*

IWZ ISHARES TR RUSSELL 3000 GROWTH*

MDY SPDR S&P MIDCAP 400 ETF TRUST

OEF ISHARES TRUST S&P 100 INDEX FUND

SPY SPDR S&P 500 ETF TRUST

why etfs plunged during the flash crash

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