The Market’s Response to Unanticipated Events

7/28/2019 The Markets Response to Unanticipated Events

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The Markets Response to Unanticipated Events

Raymond M. Brooks*

Oregon State UniversityDepartment of Accounting, Finance, and Information Management

200 Bexell HallCorvallis, Oregon 97331

[email protected]

Ajay PatelWake Forest University

Babcock Graduate School of ManagementWinston-Salem, North Carolina 27109

[email protected]

and

Tie SuDepartment of Finance

University of MiamiP.O. Box 248094

Coral Gables, Florida 33124-6552(305) 284-1885

[email protected]

Original Draft: February 1998Current Draft: December 1999

*We would like to thank Laura Starks for helpful suggestions, Ron Howren for computer support, and

Eric Schuster and Bob Hebert for gathering the sample. Ajay Patel thanks the Babcock ResearchFellowship Program for partial support of this project. The usual disclaimer applies.


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Abstract

We examine the reaction of prices, volume, spreads, and trading location when firms

experience unanticipated events. These events are totally unanticipated by the market in terms of both

timing and content. Due to the distinct nature of these news announcements, trading patterns are

somewhat different from those documented for scheduled or partially anticipated announcements. We

find that the response time is clearly longer than that reported in prior event studies of anticipated

events. Moreover, selling pressure, wider spreads and higher volume remain significant for over an

hour. In addition, we find an immediate price reaction at the opening call market. However, for events

that occur while the market is open, price reaction, the increase in volume and selling pressure, and

wider spreads take eight to fourteen minutes to catch up to those for the overnight events. Therefore,

while trading may not be necessary to process new public information it may take time to settle

differences of opinion.


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One of the major premises of finance is that markets are efficient. In general, any publicly

available information, including macroeconomic information, which might be used to predict

stock prices, should quickly be impounded in prices. It is only new information, more specifically,

new and unpredictable information, which moves prices. While this argument is well accepted in

finance, many studies that examine the market reaction to new information examine

announcements that have a predictable component, for example, the timing and/or anticipated

amount of earnings. Researchers typically select a proxy for the anticipated portion of the news

announcement and then test the markets reaction to the unanticipated portion of the

announcement. The process of separating the anticipated and unanticipated portions of news

announcements is critical to conclusions that can be drawn about price changes, speed of

adjustment, and trading activities. We avoid this separation problem by looking at what we deem

fully unanticipated events.

We collect a set of unanticipated events and then examine the equity markets reaction to

these events. Some of these events take place when the market is open, while others take place

while the market is closed. For events that occur while the market is open, there is an immediate

opportunity to trade on the information. For the other events, there is a period of no trading

before the information can be impounded in prices. However, one of the unique features about the

equity market is the structure of the opening of the markets at the New York and American stock

exchanges. Both markets begin trading with a call auction, and then switch to a continuous

trading process. Thus an interesting question arises: How does the opening call market handle

unanticipated information differently from the continuous trading market? We partition our

sample into events that take place while the market is closed, and while the market is open. We


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find different speeds of adjustment and trading processes for these partitioned events. This

partition also lets us examine whether trading is necessary for the resolution of uncertainty with

new public information.

Our general findings are that unanticipated events have an immediate impact on prices.

What is different from previous studies (Dann, Mayers and Raab (1977), Patell and Wolfson

(1984), Jennings and Starks (1985), and Ederington and Lee (1993, 1995)) is the speed of the

adjustment. Prior studies have documented that the price reaction takes place within one to fifteen

minutes. In our study, the initial price reaction takes over twenty minutes; however, prices tend to

reverse over the following two hours. Since the events we examine are negative news events to

the firm, the reversal pattern is consistent with earlier findings that the market overreacts to bad

news (DeBondt and Thaler (1985, 1987) and Brown, Harlow and Tinic (1988)). In addition, we

find evidence of an increase in selling pressure, trading volume, and in quoted dollar spreads

following these announcements. In fact, selling pressure and volume remain significantly higher

for over two hours. Dollar spreads are significantly wider for over an hour.

We also document that for those events that occur while the market is open, the increase

in volume, selling pressure and dollar spread takes about eight to ten minutes to "catch-up" to

those events that occur while the market is closed. Prices for events that occur during the day,

however, take at least fourteen minutes to reach the levels for events that occur while the market

is closed. Once changes in volume, selling pressure and prices for daytime events catch up to

those for overnight events, subsequent changes in price, volume, and trading pressure are similar

for at least the next three hours. Only spreads behave differently; the size of the spread remains

much wider for those events that take place while the market is open. This pattern continues to

exist for at least the next three hours. This extended pattern of wider spreads for daytime events


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suggests an inventory control problem for the specialist. Finally, we find a three-minute delay in

reaction to the daytime events. This short delay may be necessary to analyze the impact of new

information or clean out stale quotes from the limit order book. Overnight events do not have this

delay once trading opens, suggesting that trading may not be necessary to resolve uncertainty

about new public information.

The remainder of this paper is organized as follows: The next section presents a short

literature review. Section II describes the data, sample, and variables examined in the study.

Section III outlines the procedures. Section IV discusses the results. The last section presents a

short summary and conclusion.

I. Literature Review

Inquiry of financial market efficiency and the speed with which markets adjust to new

information date back to Famas (1965) introduction of an efficient market, and to the event study

methodology by Fama, Fisher, Jensen and Roll (1969) (henceforth FFJR). Empirical research

since FFJR has amply documented that the stock market reacts only to unanticipated information.

However, as the surveys of Fama (1970, 1991) and LeRoy (1989) indicate, the stock market

overreacts to new information [DeBondt and Thaler (1985, 1987) and Brown, Harlow and Tinic

(1988)], underreacts to earnings announcements [Bernard and Thomas (1990)], and is too volatile

given economic fundamentals [Shiller (1981)]. Therefore, while academics generally agree that

markets are fairly efficient, the debate on market efficiency is kept alive by the discovery of

market anomalies.

Research into how quickly markets adjust to new information using intraday data dates

back to at least Dann, Mayers and Raab (1977) who examine the markets reaction to


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announcements of block trades. They find that a trader would have to react within five minutes of

the announcement to earn a positive return, and that transaction prices adjust completely fifteen

minutes after block trades.

Several studies have examined the stock markets response to dividend and earnings

announcements. Patell and Wolfson (1984) and Jennings and Starks (1985) find that the ability to

earn excess returns lasts no longer than ten to fifteen minutes. However, volatility remains high

for several hours following the announcement. Greene and Watts (1996) examine the markets

response to earnings announcements made during trading and nontrading hours on the NYSE and

NASDAQ. Their results indicate that information is impounded in prices differently on the two

exchanges. Specifically, for earnings announcements during nontrading hours, the first post-

announcement trade (i.e., the opening trade) on the NYSE impounds most of the price response.

In contrast, the price response is spread evenly over several of the initial post-announcement

trades following announcements during trading hours. Greene and Watts attribute the speed of

adjustment at the opening trade on NYSE following announcements during nontrading hours to

the opening procedure used by specialists to determine the opening price.1

On the NASDAQ,

however, the first post-announcement trade impounds most of the price response regardless of

whether the announcement occurs during trading or nontrading hours. Moreover, the price

adjustment at the first post-announcement trade is greater on the NASDAQ than on the NYSE for

both sets of events.

Cao, Ghysels and Hatheway (2000) examine NASDAQ market makers activities during

the pre-opening period. They find that price discovery on the NASDAQ during the pre-opening

1In footnote 7, Greene and Watts (1996) explain how specialists announce trial clearing prices before settling on

an opening price. Based on Greene and Watts findings, the use of these indications allows for price discovery in

a manner similar to the pre-opening process on NASDAQ.


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period is conducted via price signaling as opposed to the auction process used at the opening on

the NYSE, or the continuous market used during the trading day. Moreover, they also shed light

on the faster speed of adjustment to overnight news announcements on the NASDAQ, when

compared to the NYSE. Their results indicate that the pre-opening period facilitates greater price

discovery than the call auction process on the NYSE resulting in faster price adjustment for

NASDAQ stocks at the open.

Ederington and Lee (1993, 1995) examine the impact of scheduled macroeconomic news

releases on the interest rate and foreign exchange markets. They find that, in contrast to the stock

market, prices react within ten seconds and that the major price adjustment occurs within one

minute of the scheduled news releases. Their findings suggest that the interest rate and foreign

exchange markets react much faster to public announcements than the stock market. More

recently, Fleming and Remolona (1999) look at the impact of scheduled macroeconomic news

releases on the U.S. Treasury Market. They find that the arrival of public information results in a

two-stage adjustment process. In the brief first stage, prices react immediately, trading volume

drops, and bid-ask spreads widen. In the longer second stage, volume surges, volatility persists,

while spreads remain wide. Their first-stage results are consistent with the markets response to

the arrival of public information, while the second-stage findings indicate disagreement among

investors as to the information content of the public announcement. Liquidity and volatility return

to their normal levels once the market reaches a consensus.

Even though researchers have generally been interested in the speed and magnitude of

price adjustment to public announcements, some event studies have used abnormal returns to

signify the arrival of new information. These studies begin with a change in abnormal returns and

then investigate the markets efficiency by examining reversing trends in the market, the


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overreaction hypothesis. Bremer and Sweeny (1991) find that following large price decreases,

prices rebound in subsequent periods, but following large price increases, prices remain at the new

level. The implied conclusion in this study is that the market does not efficiently handle bad news.

While previous studies of stock, interest rate and foreign exchange markets indicate that

information is incorporated in prices fairly rapidly; each of the studies examines an event that is

partially anticipated by the market. For example, the market largely anticipates the timing of

earnings and dividend announcements. Moreover, the market also partially anticipates the amount

of the earnings or dividend announcement. Similarly, both Ederington and Lee (1995), and

Fleming and Remolona (1999) examine the markets reaction to scheduled announcements of

macroeconomic news. The macroeconomic news announcements that they examine are also

partially anticipated by the market. Since the events are partially anticipated, spreads, volume and

volatility may, and probably do, change during the pre-announcement period in anticipation of the

event. In fact, Fleming and Remolona document a widening of the spread prior to the release of

the macroeconomic news.2

Moreover, the markets adjustment to the news release should be

fairly rapid for these partially anticipated events as traders plan strategies for different potential

scenarios. Then, as one of the scenarios is revealed at the announcement, traders can quickly

implement the trading strategy that corresponds to the revealed scenario. Therefore markets can,

and apparently do, react quickly to the information released at these anticipated events.

In contrast to previous studies that examine partially anticipated events, this study focuses

on the markets adjustment to fully unanticipated firm-specific events. By focusing on

unanticipated events, this paper provides new and unique evidence on how financial markets

process information, and on the trading activity following the arrival of unanticipated public

2

Krinsky and Lee (1996) document a widening of the spread prior to earnings announcements.


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information. Moreover, by comparing the adjustment process for unanticipated announcements

that occur when the market is open to those announcements that occur while the market is closed,

we provide valuable information about the speed of adjustment and necessity of trading for the

resolution of uncertainty.

II. Data, Sample, and Variables

Our study utilizes the intraday transaction data on the 1989 through 1992 NYSE and AMEX

Trades and Quotes Transaction File prepared by the Institute for the Study of Security Markets

(ISSM). Intraday data from the ISSM tape include time stamped transactions, bid quotes, and ask

quotes. In addition, the database contains the price and size of each transaction, the support for a

quote, opening prices, and closing prices. We use intraday data to calculate returns, classify trades (buy

or sell), determine trade size, and measure bid-ask spreads.

A sample of event firms is constructed by searching Lexis/Nexis using various key words

that highlight unanticipated events. Once a news announcement is identified as a potential

unanticipated event, the exact time of the event is determined from the Dow Jones Newswire.

All firms that have unanticipated events, and have intraday trading data on the ISSM tapes,

qualify for the event sample. We examine twenty-two fully unanticipated events ranging from the

Exxon Valdez running aground on Blight Reef in Prince William Sound, to an explosion at a

Texaco refinery in Los Angeles that injured more than sixteen employees. The events are negative

news in that they are unpredictable accidents that occur to a specific firm. Table I contains the list

of events examined in this study.

Insert Table IAbout Here


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We also look at the stock markets reaction for competing firms to see if the unanticipated

event has a contagion effect for competitors. A competing firm is from the same industry and is of

similar size to its corresponding event firm. Finally, to control for the impact that macroeconomic

news announcements may have on the trading process for our sample firms and their competitors,

we also examine firms that are of similar size, but outside the industry of our sample firms. The

competing firms are used to examine any contagion effects, while the control firms are used to

benchmark trading variables not subject to the firm-specific event. In addition, each firm selected

must have intraday trading data on the ISSM tapes. Therefore we have an additional twenty-two

competing firms, and an additional twenty-two control firms for the study.

In this study we use five variables to examine the trading process following announcements of

unanticipated events. The first variable is stock price, which includes transaction prices, quoted bid-ask

prices, and bid-ask spread midpoints. The second variable is spread in quoted prices, both in relative

and nominal terms. The third variable is trading volume measured in total trading dollars and number of

shares traded. The fourth variable is stock return volatility, which is computed using percent change in

bid-ask spread midpoints. We measure volatility over each ten-minute window around event

announcements. Finally, we use Keims (1989) trading location measure, which is defined as the

transaction price minus the bid price divided by the current bid-ask spread. Trades at the bid receive a

value of zero, while trades at the ask receive a value of one. On average, the expected value of the

trading location variable is 0.5, indicating that half the trades are above, while half are below the bid-

ask spread midpoint. Selling pressure is indicated when the average trading location is below 0.5, while

buying pressure is indicated when the average trading location is above 0.5.


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III. Procedures

The event day and time for an unanticipated event is selected based on the time stamp

from the Dow Jones Newswire. We then calculate the pre-event averages for the trading price,

volume, nominal spread, relative spread, and trading location, where the pre-event period is ten

days long, beginning eleven days before the event and ending the day prior to the event. The pre-

event averages are computed on an hourly basis over the ten-day pre-event period. Table II

presents the average values for these measurement variables during the pre-event period for the

event firms, the set of competing firms and the set of control firms.

For the pre-event period, the average value of each of the variables examined is similar

across the three sets of firms. Moreover, the trading location is near 0.5 for all three samples

indicating no buying or selling pressure during the pre-event period. Since prices, volume, and

spreads are similar for the three sets of firms, the data suggest that the market does not anticipate

the event. If the event were partially anticipated by the market, spreads for the event firm would

have widened during the pre-event period relative to the competing and control firms.

Next, we calculate the same variables over a full trading day following the event. We

examine the variables using 15-minute, 30-minute, 60-minute, 90-minute and 120-minute

windows. We also examine minute-by-minute changes in the four variables. Finally we separate

the events into those that occur while the market is open, and those that occur while the market is

closed.

Insert Table IIAbout Here


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IV. Results

In contrast to the findings of studies of partially anticipated events, we find that the market

does not react "quickly" to announcements of unanticipated events. Table III provides changes at

specific time intervals of 15, 30, 60, 90 and 120 minutes, with significance testing for each time

interval.3

The control firms do not experience a significant change in any of the variables. For the

event firms, however, trading prices fall by an average of about eighty cents per share during the

first fifteen minutes following the announcement. Prices continue to move downward for another

seven minutes, and then start to rebound.4

After thirty minutes of trading, prices are lower than

the pre-event price by nearly seventy cents. By the end of the first hour, prices are still down by

about twenty-nine cents per share for event firms. After another hour of trading, prices are

essentially back to their pre-event level (eight cents below their pre-event average). Prices

continue a slight upward trend for the day, finishing about twelve cents per share higher for the

entire trading day.

For competing firms, prices fall by about fifteen cents a share during the first fifteen

minutes. Then, prices reverse, a positive spillover effect, and drift upward for the next 105

minutes, reaching as high as sixty cents above the pre-event average. The price increase does

partially reverse, before settling at about forty-eight cents above the pre-event level at the two-

hour mark. Prices remain higher for the entire day and continue to drift upward finishing the first

3The 15-minute results are tested against the pre-event averages computed over the 10-day period using 15-

minute intervals. Similarly, the 30-, 60-, 90- and 120-minute results are tested against the pre-event averages

computed using the appropriate time interval.4These results are based on the minute-by-minute examination of the data over the entire trading day. These

Insert Table IIIAbout Here


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trading day sixty cents per share higher, on average. The price changes are not statistically

different from the pre-event level after one-hour of trading, but appear to be economically

significant over the first day of trading. The first 30 minutes of trading clearly show both an

immediate (negative) reaction to the event and a (positive) spillover effect to competing firms.

During the next 90 minutes, event firms experience a price reversal, while prices for competing

firms continue to experience an upward drift. Our results are consistent with the overreaction

results in Bremer and Sweeny (1991), andBrown, Harlow and Tinic (1988), but price recovery in

our study takes longer.

Volume, while significantly higher during the first hour of trading for both event firms and

competing firms, begins to return to the pre-event level for both event firms and competing firms

during the second hour of trading. The control firms do not experience a significant change in volume

over the two-hour window, or for the entire trading day.

The dollar bid-ask spread increases significantly for event firms over the first hour of trading,

and then starts to reverse. However, the spread remains wider throughout the first two hours of

trading. The competing firms experience a small increase in dollar spreads, but the changes are

insignificant. The control firms, again, experience essentially no changes in dollar spreads.

Event firms experience a significant increase in selling pressure as the trading location

measure decreases from 0.48 to 0.32 during the first thirty minutes of trading.5

Concurrently,

competing firms experience a slight rise in buying pressure as the trading location measure

increases from 0.51 to 0.54. The control firms, however, show no significant change in trading

location during the first hour, or through out the first trading day.

results have not been presented in the paper to conserve space, but are available from the authors upon request.5The estimate of 0.32 can be computed through data in Tables 2 and 3. Table II indicates that the pre-event

average trading location for event firms is 0.48, while Table III indicates that the change in trading location for

these firms during the first thirty minutes of trading is 0.16. This suggests that the trading location at the end of


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The second hour of trading provides additional evidence on trading pressure and the

momentum of trading. For event firms, selling pressure decreases, as the trading location measure

is 0.40, moving back towards the pre-event average of 0.48. It returns to normal by the end of the

third hour (0.49).6

For competing firms, buying pressure stays high for the first three hours, but

returns to normal by the fourth trading hour. Finally, as one would expect, the control firms

exhibit no distinctive pattern of buying or selling pressure throughout the trading day.

The small sample size makes it possible to look at each event firm's price reaction over the

first two hours. Table IV presents the percentage price reactions for each of the twenty-two event

firms at fifteen-minute intervals.

The firm with the largest initial price reaction is ARCO, with a negative price reaction of

2.50 percent in the first fifteen minutes.7

The firm with the smallest negative price reaction is

McClatchy Newspapers, with a 0.79 percent reaction in the first fifteen minutes. All twenty-two

firms have a negative price reaction over the first fifteen minutes, and the first thirty minutes of

trading. It is not until an hour of trading is completed do firms reverse the early trading trends. At

the sixty-minute mark, the percentage price change for fifteen of the twenty-two firms is still

negative. Interestingly, it is not the firms with the smallest initial reactions that are the first to

reverse.

the first thirty minutes of trading is 0.32 (0.48 0.16).6 These results are based on an examination of the trading process during the six hours following the

announcement of the unanticipated event. While these results have not been provided in this paper, they are

available from the authors upon request.7While the results presented earlier reflect the dollar change in prices (Table III), the results in Table IV reflect

the percentage change in price following the event.

Insert Table IVAbout Here


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After two hours of trading, thirteen firms still have a negative price reaction, and nine

firms have had a complete reversal and are trading with a positive price change. However, of the

thirteen with negative price reactions after two hours, six had a complete reversal prior to the

two-hour price change measurement. Therefore, only seven firms had negative prices across the

entire time window.

The size of the initial negative price reaction does not predict which firms will have

negative prices across the two-hour window. Therefore, the immediate price reaction is not an

indicator of how long it will take for the price to reverse, or even if the price will reverse. In fact,

ARCO with the largest initial negative price reaction reverses after ninety minutes of trading,

while McClatchy Newspapers with the smallest initial reaction does not reverse over the two-hour

window.

Next, we partitioned the events into two groups; initial announcements of an event that

crossed the newswire while the markets were open (NYSE and AMEX), and those that crossed

the newswire while the markets were closed. Figures 1 through 4 show minute-by-minute changes

in price, spreads, trading location, and volume for the event sample beginning five minutes prior

to and ending twenty minutes following the unanticipated announcement. While the small sample

severely restricts many statistical tests, graphical representation of the results appears interesting

nonetheless.

Price changes are immediate for the overnight events (events while the market is closed),

and suggest that it does not take trading to impact prices. This finding is consistent with the price

adjustment in Greene and Watts (1996) following earnings announcements during nontrading

Insert Figures 1 - 4About Here


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hours. However, the daytime events (events while the market is open) experience a short three-

minute delay before prices move. Prices, following daytime events, take nearly fifteen minutes to

have the same price impact as the overnight events. It is important to note that minute 1 is

different for the two partitioned samples. The overnight event minute 1 is the last minute of

trading for the prior day, while the daytime event minute 1 is one minute before the

announcement during the trading day.

One explanation for the short three-minute price reaction delay is trading against stale

quotes. A large majority of the trades in the first three minutes following the event are small

volume trades transacted at the bid quote. Applying Occam's razor, the simplest explanation

would be that market-sell orders are being matched to limit orders that remain on the limit-order

book immediately following the event. Therefore, the initial three-minute delay has minimal price

movement as the first trades are simply removing stale bid quotes. Once the stale quotes are

removed, transactions start to move prices.

Volume immediately jumps up for the overnight events. But again, it takes time to build

up for the daytime events. After about eight to ten minutes of trading, the daytime events show

similar trading volume as the overnight events. Selling pressure, as measured by the trading

location variable, behaves almost identically to the volume variable. After about eight to ten

minutes, the location variable is similar for both daytime and overnight samples.

The fourth measure is the bid-ask spread. For the overnight events, the bid-ask spread

jumps in the first minute and remains at this same level over the next twenty minutes of trading.

The daytime events, again, take about eight to ten minutes to reach this same level, but continue

to widen over the next five to six minutes. The spreads remain wider for the next two hours.


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Why do spreads remain wider for daytime events? One of the features of the equity

markets is the difference between the opening trade and continuous trading throughout the day.

At the opening trade, the specialist examines the overnight order flow, the current limit order

book, and opens the stock at a price that incorporates the order information. The specialist may,

or may not, take an inventory position to increase the number of orders crossed at the opening,

based on the order flow. Thus, when an event takes place while the market is closed, the specialist

can utilize the order flow to pick the opening price and, simultaneously, his inventory position.

When a daytime event takes place in the continuous market, the specialist is acting in a

different trading environment. In both cases, the specialist is charged with maintaining an orderly

market, but now may need to take the opposite side of a market order to complete this charge.

Thus, as selling pressure and volume increases, the specialist is probably participating in more and

more trades to maintain an orderly market. This is consistent with Madhavan and Sofianos (1998)

who find that the specialist participates more actively when bid-ask spreads are wide, and

previous price movements are volatile. Knowing that his posted bid price will probably be the

highest bid, the specialist increases the spread (lowers his bid) to minimize his long and growing

inventory position. In addition, it will take the specialist longer to unwind this long inventory

position throughout the trading day, so he needs to maintain a wider bid-ask spread. Hence, the

spread is wider, and stays wider longer for daytime events. A wider spread is a reflection of the

inventory cost component of the bid-ask spread.8

Ten-minute volatility changes for the partitioned event firms are presented in Figure 5.

Volatility increases in the first ten minutes by a magnitude of 50 percent. The daytime event

8The NYSE does allow the specialist to request a trading halt for a firm with a large order imbalance, or for a

firm with an important announcement. However, we did not detect any trading halts for our sample of events.


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volatility increase has a slight lag in adjustment over the first twenty minutes, but is nearly the

same for the next three hours. This increased volatility pattern is another indication of the price

uncertainty faced by the specialist. High volatility following the events indicates that there is

uncertainty about the impact of the events on the firms, or inventory control problems for the

specialist, or both. One potential reaction by the specialist is to widen the bid-ask spread during

this period of greater uncertainty. The slight lag for daytime events (over the first twenty minutes)

is consistent with the wider spreads for daytime events. A specialist has time to evaluate an event

that took place overnight prior to opening the market. With the overnight order flow, there is less

uncertainty about the impact of the event on prices and spreads when trading begins.

Finally, overnight events do not have this delay in price, volume, selling pressure, or spreads,

once trading opens suggesting that trading may not be necessary to resolve uncertainty about new

public information. Cao, Ghysels, and Hatheway (2000) also document price discovery without

trading. They show how quote behavior in the pre-opening of the top 50 NASDAQ stocks influences

price changes between the close and opening prices. For announcements of unanticipated events while

the market is closed, price discovery on NYSE takes place via overnight order flow before the market

opens, and the specialist announcing trial clearing prices (indications) prior to settling on an opening

price, instead of any formal pre-opening price quotations.

V. Summary and Conclusion

We examine twenty-two fully unanticipated news events and measure the equity markets

reaction to these events using prices, volume, trading location, spreads, and volatility. We find

Insert Figure 5About Here


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three interesting results. First, the reaction to unanticipated information is not impounded into

prices as quickly as suggested by previous research on scheduled events. However, the market's

response to unanticipated events that take place while the market is closed suggests that trading is

not necessary for prices to react. When the market has time to digest the information prior to the

opening of the trading day, the reaction is immediate in price, volume, selling pressure, and bid-

ask spreads. When the news comes to the market while the market is open, the market reacts

slower than previous research would indicate on price, volume, selling pressure, and bid-ask

spreads.

Second, consistent with partially anticipated events, the market overreacts to bad news,

but not good news. The initial price reaction drifts downward for at least fifteen to twenty

minutes but, on average, completely reverses over the next hour and a half for event firms. The

competing firms apparently receive a positive spillover from the bad news, but this price increase

is not reversed in later trading.

Finally, daytime events induce wider bid-ask spreads, and longer duration of wider spreads

when compared to overnight events. We suspect that this is due to the inventory cost faced by the

specialist for managing an orderly market across daytime events.

Another interesting finding is an apparent trading pattern that locks in a loss. We find that

selling continues well past the initial negative price reaction, and throughout the price reversal

phase. The persistent selling pressure should continue to lower prices. We also find that volume

remains significantly higher during the price reversal stage after the first twenty-minute negative

reaction. This result provides an interesting conclusion for efficient markets. It seems many

traders are closing and locking the proverbial barn door after the horses are gone and before the

horses choose to wander back into the barn, thus selling to lock in a loss.


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References

Bernard, V. J. and J. Thomas, 1990, Evidence That Stock Prices Do Not Fully Reflect theImplications of Current Earnings for Future Earnings,Journal of Accounting and Economics13, 305-340.

Bremer, M., and R. Sweeny, 1991, "The Reversal of Large Stock-Price Decreases," Journal ofFinance 46, 747-754.

Brown, K., W. Harlow and S. Tinic, 1988, "Risk Aversion, Uncertain Information and MarketEfficiency,"Journal of Financial Economics 14, 6-13.

Cao, C., E. Ghysels, and F. Hatheway, 2000, "Price Discovery without Trading: Evidence from theNasdaq Pre-opening," ForthcomingJournal of Finance.

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Table I

Unanticipated Firm Events, Time of Event, Competing Firm and Control Firm

The sample of event firms is constructed by searching Lexis/Nexis for unanticipated events using

various key words, while the exact time of the event is obtained from the Dow Jones Newswire. Thetime of the event is based on Eastern Standard Time. A competing firm is from the same industry and isof similar size to its corresponding event firm. The control firm is of similar size, but outside theindustry of the event firm.

Event Firm1 Date Time Competitor Control

Exxon 3/24/89 5:20 a.m. Chevron IBM

Chevron 4/10/89 5:57 p.m. Amoco AT&T

McClatchy Newspapers 4/16/89 7:33 a.m. Lee Enterprises Harvard Industries

UAL 7/19/89 5:26 p.m. Delta Weyerhaeuser

Quantum Chemical 9/12/89 10:06 a.m. Rohm Haas Quaker Oats

USAir 9/21/89 7:32 a.m. Delta Owens IllinoisPhillips Petroleum 10/23/89 2:38 p.m. Unocal Deere & Co.

ARCO 7/5/90 7:31 a.m. Hanson PLC Harris Corp.

Gillette 1/25/91 3:17 p.m. Warner Lambert Dial Corp.

UAL 3/4/91 9:00 a.m. Delta Sun Co.

USAir 2/2/91 10:20 a.m. Delta Capital Cities ABC

Dominion Resources 8/27/91 3:50 p.m. Virginia Electric ALCOA

Conoco 9/4/91 9:03 a.m. Mobil Travelers Insurance

People's Natural Gas 1/17/92 6:11 p.m. Questar Payless Cashways

Amoco2 4/5/92 8:56 a.m. Chevron BellSouth

Enron2 4/5/92 8:56 a.m. Vastar Reebok

Union Carbide2 4/5/92 8:56 a.m. Dow Chemical American StoresBurlington Northern 6/30/92 11:34 a.m. Consolidated Rail Pitney Bowes

Texaco 10/8/92 8:44 a.m. Amoco NYNEX

Panhandle Eastern Pipeline 10/9/92 12:22 p.m. El Paso Nat. Gas National Western Life Ins.

TimeWarner 12/20/92 7:05 a.m. Disney Golden West Financial

McDonnell Douglas 12/21/92 7:30 a.m. Boeing USF&G

1Two firms, U.S. Air and United Airlines, have more than one event.

2One event impacted three firms. A fire and explosion on April 5, 1992 impacted refineries for

Amoco, Enron and Union Carbide that had common boundaries for their facilities.


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Table II

Pre-event Averages for Event, Competitor, and Control Firms

The sample of event firms is constructed by searching Lexis/Nexis for unanticipated events. A

competing firm is from the same industry and is of similar size to its corresponding event firm. Thecontrol firm is of similar size, but outside the industry of the event firm.Price is defined as the averagetransactions price on an hourly basis; Volume is measured as the average number of shares traded on anhourly basis;Location, based on Keim (1989), is defined as the transaction price minus the bid pricestandardized by the current bid-ask spread, and is also computed on an hourly basis; the Dollar Spreadis the average nominal spread calculated using all quotes available on an hourly basis; Relative Spreadis the average of the nominal spread standardized by the most recent transaction price. The pre-eventperiod is defined as the ten days beginning eleven days before and ending one day prior to theunanticipated event. The pre-event averages are the average hourly estimates for the variables understudy over the pre-event period.

Pre-Event Average(Standard Deviation)

Variable Event Firms Competitor Firms Control Firms

Price$45.66

($33.15)$47.86

($20.17)$46.00

($26.12)

Volume30,322

(25,758)46,392

(55,917)49,968

(54,970)

Location0.48

(0.20)0.51

(0.17)0.50

(0.16)

Dollar Spread$0.29

($0.13)$0.31

($0.14)$0.30

($0.13)

Relative Spread0.85

(0.64)0.80

(0.58)0.86

(0.49)


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Table III

Changes in Price, Volume, Location and Spreads over the First Two Hours of Trading

Following the Announcement of an Unanticipated Event

Price is defined as the average transactions price; Volume is measured as the average number of sharedtraded; Location, based on Keim (1989), is defined as the transaction price minus the bid pricestandardized by the current bid-ask spread; the $ Spreadis the average nominal spread calculated usingall quotes available; % Spread is the average nominal spread standardized by the most recenttransaction price. Average values for these variables are computed over 15-, 30-, 60, 90- and 120-minute intervals following the announcement of the unanticipated event. These average values arecompared to that over a similar time interval during the pre-event period defined as the ten daysbeginning eleven days before and ending one day prior to the unanticipated event. The change in priceover the first 15 minutes following the event is defined as the average value over the first 15 minutesfollowing the event minus the average price during the pre-event period over each 15-minute interval.Changes for the 30-, 60-, 90- and 120-minute intervals are computed similarly using the appropriate

time interval.

Average Changes in VariablesVariableSample 15 Min. 30 Min. 60 Min. 90 Min. 120 Min.

PriceEvent -0.82** -0.69* -0.29 -0.18 -0.08

Competitor -0.15 0.30 0.28 0.48 0.05

Control 0.05 0.04 -0.12 -0.19 0.15

VolumeEvent 1700*** 1703*** 1317*** 624** 355*Competitor 1936*** 2037*** 1915*** 1039** 427*

Control 700* 559 740* -455 8

LocationEvent -0.14** -0.16** -0.07* -0.09* -0.12*

Competitor 0.03 0.03 0.03 0.05 0.05

Control 0.03 0.03 0.01 -0.02 0.01

$ SpreadEvent 0.14** 0.08** 0.09** 0.02 0.06

Competitor 0.06 0.03 0.03 0.07* -0.01Control 0.03 0.04 -0.02 -0.04 0.01

% SpreadEvent 0.07 0.11 0.08 0.05 0.20

Competitor -0.02 -0.02 -0.04 0.00 -0.09

Control 0.05 0.04 -0.09 -0.03 0.00

*, **, *** indicate significance at the 0.10, 0.05, and 0.01 levels, respectively.


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Table IV

Percent Price Change by Firm at Fifteen Minutes, Thirty Minutes, Sixty Minutes, Ninety

Minutes, and One Hundred and Twenty Minutes

The sample of event firms is constructed by searching Lexis/Nexis for unanticipated events, whilethe exact time of the event is obtained from the Dow Jones Newswire.Open indicates that theunanticipated announcement occurred while the market was open, while Closedindicates that theannouncement occurred while the market was closed for trading. The percentage price changesare computed relative to the last trade prior to the news announcement. The firms are listed indescending order based on the magnitude of the percentage price change over the first 15 minutesof trading following the unanticipated announcement.

Firm Open/Closed 15 Minutes 30 Minutes 60 Minutes 90 Minutes 120 Minutes

ARCO Closed -2.50 -0.70 -0.71 0.06 -0.63Burlington Open -2.43 -0.62 0.40 0.36 -1.04

McDonnell Closed -2.40 -2.37 -1.45 -0.17 -1.04Amoco Closed -2.27 -2.01 -0.10 -1.19 0.01U.S. Air Closed -2.11 -1.05 -0.98 0.06 0.78People's Closed -2.04 -2.22 -0.11 -1.18 0.40Panhandle Closed -1.99 -0.76 -1.59 0.31 0.13Quantum Open -1.86 -1.40 0.06 -0.28 0.54Exxon Closed -1.86 -2.10 -1.29 -1.06 -0.95Enron Closed -1.78 -1.67 -1.44 0.52 -0.16Chevron Closed -1.65 -1.06 -0.40 -0.93 -0.68UAL Closed -1.60 -0.88 -1.07 -1.13 -0.04U.S. Air Open -1.48 -1.54 -1.12 -0.15 0.09

Gillette Open -1.36 -1.11 -0.05 -0.55 -0.12Dominion Open -1.35 -1.35 0.37 -1.09 -0.10UAL Open -1.31 -0.84 0.30 0.61 -0.92Texaco Closed -1.18 -1.44 -0.96 -0.02 0.62Phillips Open -1.14 -0.68 0.28 0.67 0.21TimeWarner Closed -1.14 -2.12 -1.38 -0.91 -0.24Conoco Open -0.82 -2.08 0.26 -0.31 -0.19McClatchy Closed -0.79 -0.50 -0.97 -0.78 -0.52

Average -1.67 -1.38 -0.60 -0.37 -0.16


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Figure 1

Price Change by Minute for Event Firms.

Following the event, the price is defined as the bid-ask spread midpoint. An average price is computed for each

minute beginning 5 minutes before the event, ending 20 minutes following the event. The change in price is the

average price during each minute surrounding the event less the average price during the pre-event period. The

average price during the pre-event period is also computed on a minute-by-minute basis. Overnight events occur

while the market is closed, while daytime events occur while the market is open.

-1

-0.5

0

0.5

-5 0 5 10 15 20

Event Time in Minutes

PriceChanges($)

Overnight Events Daytime Events

Figure 2

Volume Changes by Minute for Event Firms

Average volume is computed for each minute beginning 5 minutes before the event, ending 20 minutes following

the event. The change in volume is average volume during each minute surrounding the event less average volume

during the pre-event period. The average volume during the pre-event period is computed on a minute-by-minute

basis. Overnight events occur while the market is closed, while daytime events occur while the market is open.

-1000-500

0500

1000150020002500

-5 0 5 10 15 20


Volu

meChanges



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Figure 3

Trading Location Changes by Minute for Event Firms

Keims (1989) trading location measure is defined as the transaction price minus the bid price divided by the

current spread. Following the event, the bid-ask spread midpoint is used instead of the transaction price. The

average trading location measure is computed for each minute beginning 5 minutes before the event, ending 20

minutes following the event. Change in location is the average location during each minute surrounding the event

less the average location during the pre-event period. The average location during the pre-event period is computed

on a minute-by-minute basis. Overnight events occur while the market is closed, while daytime events occur while

the market is open.

-0.2-0.15-0.1

-0.050

0.050.1

-5 0 5 10 15 20


LocationChanges


Figure 4

Spread Changes by Minute for Event Firms

The average bid-ask spread is computed for each minute beginning 5 minutes before the event, ending 20 minutes

following the event. The change in spread is the average spread during each minute surrounding the event less the

average spread during the pre-event period. The average spread during the pre-event period is also computed on a

minute-by-minute basis. Overnight events occur while the market is closed, while daytime events occur while the

market is open.

-0.1

0

0.1

0.2

0.3

-5 0 5 10 15 20


SpreadCha

nges($)



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Figure 5

Trading Volatility by Ten-Minute Intervals for Event Firms

The sample of event firms is constructed by searching Lexis/Nexis for unanticipated events, while

the exact time of the event is obtained from the Dow Jones Newswire. Volatility is defined as thestandard deviation of returns during each ten-minute window. Returns are computed during eachten-minute window using the bid-ask spread midpoint.

0.2

0.3

0.4

0.5

0.6

-6 0 6 12 18

10-Minute Time Intervals

Night Day

Documents

The Market’s Response to Unanticipated Events