ual relationship between the client and the fundmanager will not solve the problem, because you cannot improve theincentives in one area without reducing them in another. Improvements willtherefore depend on sponsors understanding transaction costs far better thanthey currently do.
Chapter 1: Recent Evidence on Market Quality
11
We are still a long way from getting a form of reporting on transactioncosts which sponsors can understand, and which would enable them tocompare effectively across managers. This represents a major challenge,which the industry – managers, clients, consultants and academics - needs toaddress.BENNETT: Thank you very much Anthony. We have a lot of ground tocover this morning, so I suggest we hold questions until the end. If you wanta copy of this report, is it available on the net?NEUBERGER: It is available on the Internet.5BENNETT: The report is well worth reading. I recommend it to you.Our next set of speakers will be a relay between Bob Schwartz, DenizOzenbas, and Bob Wood. They will talk about their study, Volatility in USand European Equity Markets: An Assessment of Market Quality.6ROBERT SCHWARTZ: My job this morning is to set the foundation.Deniz Ozenbas will talk about the empirical results on volatility, and BobWood will summarize the results of two surveys of people’s opinions aboutmarket quality. We will suggest that trading costs, which AnthonyNeuberger was talking about, and which we all know and care about, havean impact that we can see in the full array of trades that are made and pricesthat are set.Our primary window to trading costs and, hence, to market quality, is thevolatility of intra-day transaction prices. In a moment, Deniz will presentour evidence that intra-day volatility is accentuated. I believe that thisfinding would not surprise many practitioners. And other academicresearchers have also found this to be the case. Nevertheless, it is importantto capture the accentuation in the data.Before turning to the data, I would like to clarify the link between tradingcosts and accentuated short-period price volatility. I will do so with the aidof some charts. This will be a very simplified, stylized representation. First,let’s define some terms (see the legend in Exhibits 4).
5
See Richard A. Brealey and Anthony Neuberger, “The Treatment of InvestmentManagement Fees and Commission Payments: An Examination of the RecommendationsContained in the Myners Report,” available athttp://www.investmentfunds.org.uk/investmentuk/about_ima/reports/brealey.pdf.
6
Reprinted, with permission, from D. Ozenbas, R. Schwartz, and R. Wood, “Volatility inU.S. and European Equity Markets: An Assessment of Market Quality,” InternationalFinance, Blackwell Publishers, Volume 5 Number 3, Winter 2002, pp. 437-461.
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A Trading Desk’s View of Market Quality
Exhibit 4. Trading Costs and Price Volatility
C is the implicit transaction cost, per share, of buying or selling astock. The implicit cost is imbedded in the price of a transaction. Itincludes the bid-ask spread and market impact. It does not includecommissions.In our diagrammatic presentation, a donut represents a transactionprice that we observe when the transaction has been triggered by abuy order. A buy-triggered transaction price can reflect the bid-askspread (that is, an offer price that is higher then the bid), marketimpact, or whatever else might be pushing price up.A triangle represents a transaction price that we observe when thetransaction has been triggered by a sell order. A sell-triggeredtransaction price can reflect the bid-ask spread (that is, a bid pricethat is lower then the offer), market impact, or whatever else might bepushing price down.A straight, vertical line represents the magnitude of C. As we allknow, implicit transaction costs are very difficult to measure.Anthony, you certainly reflected that in your talk. And, as I say this, Iam watching Wayne Wagner of Plexus Group. I see him nodding hishead in a positive direction.
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P* represents a value that we cannot see but can, nevertheless,conceptualize. It is the unobserved, costless trading price that is onlytalked about by academicians. You might think of P* as a frictionlessmarket, consensus value (or equilibrium value).Let’s start with P*. There it is, in Exhibit 4. Exhibit 4 shows howP* may evolve over the course of a trading day. What causes P* tochange? The consensus value changes because the fundamental desireof investors to hold shares of the stock in their portfolios changes.Informational change (news) is the simplest factor to point to.Exhibit 5 replicates Exhibit 4 and adds the transaction prices.
Exhibit 5. Transaction Prices Added
In Exhibit 5, each transaction price is P* plus C for a buy-triggered trade,or P* minus C for a sell-triggered trade. The first trade of the day wastriggered by a buy order that arrived early in the morning. The firsttransaction price that we see is represented by the first donut. Next, anotherbuy order came in, triggered another trade, and we see a second donut. Thethird trade of the day was triggered by a sell order, and the first triangleidentifies the price of that trade.
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A Trading Desk’s View of Market Quality
Let’s keep the presentation simple. All of the vertical straight lines arethe same length. That is because this is an academic environment and weacademicians like to keep complex things simple.The trading day continues. There are more trades and transaction prices.More donuts and triangles. Let’s next consider the volatility implied by thisset of transaction prices. Volatility refers to how much these prices jumparound. The price changes we observe from jump-to-jump are returns.Alternatively stated, a return is any price change. So let’s see what thereturns look like. In Exhibit 6, I have added dotted lines to help identify thereturns.
Exhibit 6. Returns Added
The returns are the slopes of the dotted lines. Sometimes the dotted linesslope up, sometimes they slope down. Sometimes they are relatively flat.Exhibit 7 is the same as Exhibit 6 with the donuts, triangles, and verticallines removed.
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Exhibit 7. Donuts, Triangles, and Vertical Lines Removed
Exhibit 7 shows the dotted lines more clearly. I want to ask you all aquestion. Which is more volatile, P* or the transaction prices that weobserve? Can we have a vote on this? How many of you say P*? Thankyou. How many say the transaction prices that we observe? Come on, raiseyour hands, and don’t be shy. Thank you. More of you are saying that it isthe observed transaction prices that are more volatile. Yes, I agree. Theobserved transaction prices do jump around more. Why? Because ofimplicit transaction costs. It is in this context that I would next like to talkabout the accentuation of intra-day volatility.Why intra-day volatility? If I were to extend the price charts out over farlonger periods of time, the changes in P* would become very appreciablerelative to the magnitude of the implicit trading costs. This is because thecollective importance of informational change cumulates over time.Let’s look at it this way. How important would the straight, vertical linesbe if the value of P* changed a lot over time? Relatively speaking, theywould be a lot less important. As they become relatively less important, aninteresting thing happens – the volatility of observed transaction pricesconverges with the volatility of P*. Because these two volatilities convergefor longer period returns, we are able to infer P*’s intra-day volatility. It is
16
A Trading Desk’s View of Market Quality
this inference, in turn, that enables us to assess the intra-day volatilityaccentuation. Hence we can assess market quality and the magnitude of theimplicit trading costs. This, in essence, is what we have done. Deniz willexplain further in a few moments. First, I have another question.What do the following four things have in common: the bid-ask spread,market impact, momentum trading, and imperfect price discovery? All fourexist because of trading costs. Bid-ask spreads and market impact areobvious. They are costs, and they exist because of costs. What aboutmomentum trading?With momentum trading, when you see prices going up, you hop on thebandwagon and you buy. What does that really mean? To me it means thatyou do not have confidence in the sustainability of the current price, in themeaningfulness of the current price. You think that price is going to a newlevel. But, we might ask, why isn’t price already at the level that it seems tobe heading toward? Because of costs. Because trading is a friction process.Because price discovery is not simple. Because no one can see P*.Momentum trading is related to the imperfections of price discovery.I just asked, what do the four phenomena -- spreads, market impact,momentum trading, and imperfect price discovery -- have in common? Ipointed out that they all exist because of trading costs. There is a secondthing, and it is important. The four things all result in prices bouncingbetween two values, one high and the other low. Whenever you have pricebouncing between two values, it translates into accentuated volatility.Think again about the donuts and the triangles. Visualize price bouncingbetween the higher donuts and the lower triangles. With a bid-ask spread,you are bouncing between the higher offer and the lower bid. With marketimpact, you have the same thing. With market impact, price is effectivelybouncing back and forth across a larger spread. If it is momentum, pricewent down too low or it rose up too high. Either way, price is swinging toofar. And the last momentum trader always gets killed. You never want to bethe last momentum trader.Price discovery can be viewed in this context. Some of my frictionlessworld, random walk colleagues will not like me for this, but I will say itanyway. I am not anti-technical analysis. There is good theoretical supportfor technical analysis. One of the clearest patterns it looks for is support andresistance levels. Let’s further extend the notion of the bounce to includeprice swinging between a lower support level and a higher resistance level.All of these bounces give you accentuated volatility.The question is can the accentuation in short-period volatility that isattributable to these bounces be measured? Deniz will tell you what wefound.
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DENIZ OZENBAS:The volatility accentuation can indeed bemeasured.7 Our study took the following perspective. In academic circles,the length of time over which returns are measured is referred to as the“differencing interval.” In a perfectly frictionless, random walk world, alldifferencing intervals will give the same measure of volatility, if thevolatility measure is adjusted to reflect the length of the differencinginterval. That is, if we look at half-hour returns, hourly returns, dailyreturns, weekly returns, or whatever, the volatility for all of these adjustedfor the length of the differencing interval, should be the same. And theadjustment is simple. To normalize all measures to a one-day volatility, forinstance, divide a two-day measure by two, a one-week measure by five, etc.In other words, simply divide by the relative length of the differencinginterval.8On the other hand, in a world where prices do not follow a random walk,the scaled volatility may be observed to be higher when a short differencinginterval is used to measure returns. In other words, short-period returns mayexhibit accentuated volatility.We analyzed the short-period volatility accentuation for five markets –The New York Stock Exchange and Nasdaq in the U.S., and The LondonStock Exchange, Euronext Paris, and Deutsche Börse in Europe.Transaction prices for the year 2000 were used. We looked at the largeststocks in each market, and assessed each stock individually.Let us first look at half-hour volatilities. Average values for the stocks ineach of the five country samples are shown in Exhibit 8.
7
“Volatility in U.S. and European Equity Markets: An Assessment of Market Quality,” DenizOzenbas, Robert Schwartz and Robert Wood, International Finance, Volume 5 Number 3,Winter 2002, pp. 437-461.
8
The procedure of dividing by the relative length of the differencing interval holds whenlogarithmic returns are used to compute a variance. If the standard deviation oflogarithmic returns is being taken to measure volatility, then the square root of thedifferencing interval should be used.
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A Trading Desk’s View of Market Quality
Exhibit 8. Half-Hour Volatilities for Five Markets
Chapter 1: Recent Evidence on Market Quality
Exhibit 8. Half-Hour Volatilities for Five Markets
19
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A Trading Desk’s View of Market Quality
Exhibit 8. Half-Hour Volatilities for Five Markets
In the U.S. markets, the first period is from 9:30 to 10:00. We calculatedthe first half-hour return as the difference between the price of the openingtrade and the price of the last trade in that first period. For the second halfhour, the return is the difference between the price of the first trade after10:00 and the price of the last trade before 10:30. The half-hourly returnsare calculated that way, through the last half-hour period of the trading day(3:30 to 4:00 in the U.S.).Exhibit 8 shows a very significant volatility pattern for each of the fivemarkets. In each, volatility is very high at the beginning of the day. Itgradually declines through the middle of the day, and then picks up againtowards the end of the day.In a perfect world, the intra-day pattern of volatility should follow theaverage intra-day pattern of news releases. At times where there is generallya lot of news, volatility should be high. Do news releases, on average,follow a “U” shaped pattern through the day? No. Controllable newsreleases (for instance, corporate acquisitions or earnings announcements) arenot typically made in the first or last half-hour of trading. There must besomething else that is driving the intra-day volatility pattern.The “U” shaped pattern is pervasive across the markets. At the NYSE (asample of 72 Big Board stocks from the S&P 500), volatility is highest forthe 9:30 – 10:00 period. At Nasdaq (a sample of 80 Nasdaq 100 stocks),volatility is clearly highest in the opening half-hour period. The sameapplies in Europe. The opening volatility spike is highest for the LondonStock Exchange (a sample of 85 FTSE 100 stocks). It is also sizable forEuronext Paris (a sample of 39 CAC 40 stocks) and Deutsche Börse (a
Chapter 1: Recent Evidence on Market Quality
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sample of 28 DAX 30 stocks). Further, for each of these five markets, thesecond highest volatility reading is in the last half-hour before the close ofthe trading day.Now let’s contrast the short period and the longer period volatilitystatistics. For each of the five markets we have examined, we broke the2000-trading year into two periods. The findings for each market and periodare shown in Exhibit 26 (see page 167). Once again, because the volatilitymeasurements have been normalized, in a perfectly frictionless, randomwalk world, all of the numbers shown in Exhibit 26 would be centered on 1.9Exhibit 26 shows the normalized volatility numbers for the five marketsfor the first and the last half-hour intervals, for the closing call auction10(where applicable), for open-to-close price changes, and for the one-day,one-week, and two-week differencing intervals. For the five markets andtwo assessment periods, all values for the first half-hour volatility are greaterthan the benchmark value of 1. For the NYSE, Nasdaq, Euronext Paris, andDeutsche Börse, they are almost two times as volatile as what you wouldexpect in the first half hour. For the London Stock Exchange, prices in thefirst half-hour are almost three times as volatile. We investigated this issue.We looked at the pattern of volume during the day and it turns out that,relatively volume is the least in the London Stock Exchange. There isalmost no volume at the beginning of the day. London is a very institutionalmarket, and perhaps the institutions are holding out for a while before theyenter the market. Similarly for open to close volatility, it is accentuatedmost of the time, a bit. We also see from Exhibit 6 that the volatility valuesare generally greater than unity, particularly for the last half-hour pricechanges and the open-to-close price changes.In summary, the answer to Bob Schwartz’s question is, “yes, there isaccentuated short-term volatility in markets, and the accentuation exists for abroad array of market structures.” At this time, I will pass the microphone tomy other co-author. As Bob Schwartz did to me, I will pass it on with aquestion. “I have suggested that the accentuation of intra-day volatility is an
9
We normalized the volatility measures in presented in Exhibit 6 by dividing each volatilityby the differencing interval length and by the average half-hour volatility for the second tosecond-to-last half-hour trading periods. See Ozenbas, Schwartz and Wood, op. cit., forfurther discussion.
10
The returns for the closing call auction were defined as the difference between the price atthe close of the continuous market and the price established at the closing calls. For thethree European markets that have closing calls, the auctions were held roughly fiveminutes after the close of the continuous market.
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A Trading Desk’s View of Market Quality
inverse measure of market quality. Bob Wood, what do the U.S. andEuropean participants actually think about the quality of our markets?”ROBERT WOOD: What do they think, Deniz? I’ll tell you. I willpresent the results from two surveys of buyside and sellside traders. BobSchwartz and Dan Weaver conducted the first. It was published in 2001 inthe Journal of Portfolio Management.11 The second is a survey that Bob,Deniz and I conducted with European traders. I will start with some keyresults from the U.S. survey.The first question deals with liquidity.
Exhibit 9. U.S. Survey: “What is the general level of liquidity of the market in recentmonths compared with the level of liquidity in the market prior to 1997?”
As shown in Exhibit 9, the predominant sentiment on both the buysideand the sellside is that liquidity has deteriorated.11
Survey results reprinted with permission from R. Schwartz and D. Weaver, “What WeThink About the Quality of Our Equity Markets,” The Journal of Portfolio Management,Volume 27, Number 4, Summer 2001, pp. 63-70.
Chapter 1: Recent Evidence on Market Quality
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The second question deals with volatility.
Exhibit 10. U.S. Survey: “How do the levels of intra-day volatility experienced in recentmonths compare with the levels experienced prior to 1997?”
As shown in Exhibit 10, there was virtually unanimous agreement in theU.S. that volatility has increased in the U.S. markets. This is quiteinteresting to me because in my research, and in other research that I amaware of, we do not see that volatility has increased. This causes me towonder whether we academics are approaching the study of volatilityproperly. What do the practitioners see that we do not?Next are the issues of consolidation and fragmentation.
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A Trading Desk’s View of Market Quality
Exhibit 11. U.S. Survey: “Are markets more consolidated or morefragmented than they were prior to 1997?
Exhibit 11 shows that both the buyside and the sellside feel that marketsare more fragmented. Another dimension of fragmentation involves thebreaking up of orders for sequential execution over a series of trades.
Chapter 1: Recent Evidence on Market Quality
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Exhibit 12. U.S. Survey (BUY-SIDE): “Are you more frequently breaking upyour large orders for submission to the market into pieces compared to before1997?”
Exhibit 12 shows that buy-side participants are more frequently breakingtheir orders up for submission to the market over a succession of trades.Consistently, Exhibit 13 reveals that sellside participants are being shownless of total order size compared to before 1997.
Exhibit 13. U.S. Survey (SELL-SIDE): “How much of total size are investorsshowing you compared to before 1997?”
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A Trading Desk’s View of Market Quality
What is the impact of this? The markets are less transparent. Further, asa consequence, the answers displayed in Exhibit 14 indicate that the sellsideoverwhelmingly believes that market making is more difficult than it wasbefore 1997.
Exhibit 14. U.S. Survey (SELL-SIDE): “From your perspective, is marketmaking more or less difficult than it was before 1997?”
The Schwartz-Weaver survey also asked the U.S. participants to assessthe contributions of technology and regulation to market quality. Theresponses are shown in Exhibits 15 and 16.
Chapter 1: Recent Evidence on Market Quality
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Exhibit 15. “What is the broad contribution that technology has made to thequality/efficiency of the U.S. equity markets in recent years?
Exhibit 16. “What is the broad contribution of regulation by Congress and the SEC to thequality/efficiency of the U.S. equity markets in recent years?”
Participants on both sides of the market are in virtually unanimousagreement that technology’s contribution has been positive. Opinions aboutregulation’s contribution, on the other hand, are mixed. The buyside is fairly
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A Trading Desk’s View of Market Quality
evenly split, while sellside participants predominantly stated thatregulation’s impact has been harmful.Let’s move on to Europe. In telling you about the responses to ourEuropean survey, I will focus on four key questions that we asked:Is the current market structure meeting your needs?How would you rate the overall quality, efficiency of the Europeanequity market structure today?How would you rate the general level of liquidity of the market todaycompared with what you require and think could be achieved in an ideallystructured market?How relevant do you think stock exchanges will be to market structure infive years time?We asked these four questions about all stocks, and about three subcategories: blue chips, mid-caps, and small-caps.For each of the four classes – all stocks, blue chips, mid-caps, and smallcaps – we aggregated the answers to the four questions. We did so asfollows. The most positive response to each question was assigned a valueof 1, the second most positive a value of 2, through to the most negativeresponse that was assigned a value of 5. To get a composite, we thensummed, across the four questions, all of the “1” responses, all of the “2”responses, through all of the “5” responses. The results are shown inExhibits 17 – 20 for the four classes of stocks, respectively. These exhibitsalso give the breakdowns between the U.K. and Continental Europe, andbetween the buyside and the sellside.
Exhibit 17. European Survey, All Stocks
Chapter 1: Recent Evidence on Market Quality
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Exhibit 17, for all stocks, shows a fairly dispersed distribution that isskewed to the left (towards the more desirable ratings). Digging deeperreveals some interesting things.
Exhibit 18. European Survey, Blue Chips
The responses shown in Exhibit 18 for blue chip stocks arepredominantly positive. For the blue chips, the modal response is “high,”and the second most frequent response is “very high.”
Exhibit 19. European Survey, Mid Caps
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A Trading Desk’s View of Market Quality
Moving to the mid-caps, in Exhibit 19 we see that the distribution isshifted to the right (towards the less desirable ratings). Overall, for the midcaps, the distribution is fairly balanced.
Exhibit 20. European Survey, Small Caps
For the small-cap stocks in Exhibit 20, the distribution is shifted furtherto the right. This is not a good assessment. The small cap market is theincubator for the blue chips of the future. We conclude that, in Europe,concern exists about market quality, particularly for the small-cap stocks.BENNETT: Time is getting short, but we have time for a few questions.MICHAEL RICHTER12 [From the Floor]: I will address my question toBob, Bob and Deniz. In your discussion of intra-day volatility, you did notanalyze any causes, or hypothesize the reasons why you have observed thevolatility patterns that you have described to us. I will give you onehypothesis: volatility may be highly correlated with order flow. There is alot of order flow at the open, a lot of order flow at the end of the day, and itis slower in the middle of the day. If you could study that, that might giveyou one hypothesis as to the pattern.OZENBAS: Thank you for your observation. That was our expectationas well, and we did look at intra-day volume patterns. That is why we weresurprised to see that, at the London Stock Exchange, the volume was really12
Michael Richter is CEO of Lime Brokerage.
Chapter 1: Recent Evidence on Market Quality
31
small at the beginning of the day – almost non-existent, in fact – and thatvolatility was the highest at the beginning of the day.SCHWARTZ: I would add to that. I see the accentuation of volatility atthe opening as being related to the complexity of price discovery at the open.Another way to look at it is to ask, if you had good, crisp price discovery atthe opening trade, would you continue to see the heavy order flow for thefirst half-hour, and would you still see the price volatility spike at the openthat we have observed?There is another way to state this. We know that the market opens in atechnical sense with the first trade. But, if by opening the market for a stockwe mean achieving the price that best reflects the broad market’s desire tohold shares, I suggest that, in each of the five markets that we have studied,it takes the better part of half an hour to open the stocks.BENNETT: Let me add to the answer. I notice that my old colleaguefrom the New York Federal Reserve Bank, Mike Fleming, is here. Mike dida study of what happens at 8:30 when the bond market opens, and there is abig employment announcement.13Mike found that price did notimmediately go to a new equilibrium value. The bond market, of course, is adealer market, but the basic reaction to news is no doubt quite similar in theequity markets. It takes a little while for trading to pick up. What isinteresting, as I recall, and correct me if I am wrong Mike, is that there is nota lot of trading volume until the price gets at least in the neighborhood of thenew “right price” for the day. It takes the market a while to figure out whatthe right price is.SCHWARTZ: Mike’s paper was very helpful to me. In particular, Iwould like to underscore its demonstration that protracted surges in pricevolatility and trading volume attend major news announcements in the U.S.treasury market. This is consistent with our having found a volatility spikein the first half-hour of the trading day. Presumably the spike is part of theprotracted process of price adjusting to overnight news events.SHARON SALAMON14 [From the Floor]: I have one question for thegroup. Regarding your European survey, for the small-cap part of theEuropean market, the respondents feel that there are a lot of inefficiencies inthe way that the exchanges are structured. Do you feel that a consolidation13
Michael J. Fleming and Eli M. Remolina, “Price Formation and Liquidity in the U.S.Treasury Market: The Response to Public Information,” Journal of Finance 5, 1999, pp.1901-1915.
14
Sharon Salamon is currently Director of Institutional Equities for Product Management atThomson Financial. At the time of the conference, she was the Senior Sales andMarketing Executive at NeoNet Securities.
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A Trading Desk’s View of Market Quality
of the exchanges – with Euronext being a perfect example – is affecting theirresponses? Do you think that consolidation would hurt or help marketefficiency?SCHWARTZ: I could respond to that, but I have a better idea. LucaFilippa is here from the Borsa Italiana. Luca is a lot closer to what is goingon in Europe. Luca, would you care to answer?LUCA FILIPPA15 [From the Floor]: Sure, thanks, Bob. Sharon Salamonhas posed the one million dollar question in Europe. The efficiency of pricediscovery in European exchanges is quite good now. As you know, we hada large discussion in the year 2000 on a potential alliance between the eightmajor exchanges. That discussion, due in part to political and businessconstraints, ended in no alliance. But we did achieve an agreement on whatwe call the European market model. We agreed to have the same kind ofstructure in all of the European markets.The microstructure of the various European exchanges is basically thesame now, although some small differences still exist. The need forconsolidation is high, but there is a major difference. We always talk aboutfragmentation of markets, and in Europe, this is true. But the markets arefragmented in a different way than in the U.S. This is because we may havedifferent liquidity pools, but nevertheless have really liquid pools for theindividual stocks. Italian shares are really liquid – in Italy. German sharesare really liquid – in Germany. And so on.There are a few examples of fragmented liquidity for single stocks. Agood example is Nokia. 65% of the trading volume on the Helsinki StockExchange is accounted for by Nokia. Nokia accounts for some 20% of thevolume in Stockholm. Nokia also has large volumes in London and NewYork.The consolidation matter is basically a political one. The homogeneity ofthe structure now allows most users to access a virtual book. And there are alot of information service providers that connect the single intermediaries tothe different exchanges. Basically, the discussion in Europe has moved fromtrading integration to post trading costs. With regard to post trading issues,the role of domestic settlement institutions has remained large and the costof cross-border clearing and settlement is still huge.SCHWARTZ: Luca I have a quick extension of your response. Whetherit is Europe or the U.S. does not matter. When the dust settles on marketstructure, we will see that the small-cap market is not of the same quality asthe mid-cap or the blue chip markets. That will, obviously, always be the
15
Luca Fillipa is Head of Research & Market Analysis at the Borsa Italiana.
Chapter 1: Recent Evidence on Market Quality
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case because of the nature of the beast. On the other hand, I personally feelthat market structure can be improved across the board.BENNETT: We have time for one more question.RICHARD REPETTO16 [From the Floor]: I want to follow up on thediscussion about volatility at market openings and closings. The way that Iwould interpret it is that price discovery is difficult at the open because ofovernight news events, and that it is