. The (subsequent split-adjusted) price action in J-Comstock on December 8, 2005 and subsequent days is depicted in Figure 10.1.6The eventual cost of the error for the Mizuho Financial Group—parent of Mizuho Securities Company—was 40.5 billion yen, orabout $350 million at an exchange rate of 115.89 yen to the dollar.7
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Daily trading range of J-com split-adjusted stock price from its IPO on December 8, 2005 to January 31, 2006.
FIGURE 10.1
The accidental catalyst: J-Com December 2005.307
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However, the influence of the erroneous order did not end simplywith a volatile market for J-Com stock on December 8, 2005. Theidentity of the firm that made the erroneous trade was not knownimmediately. Many market participants assumed that it was a Japanesebrokerage firm or investment bank. Mizuho did not own up to it untilafter the market closed. Not surprisingly, traders sold shares in majorJapanese brokerage firms and investment banks. Nomura closed down3.7%. Daiwa closed down 3.3%. Nikko closed down 3.3%. Mizuhoclosed down 3.4%. Indeed, some observers blamed the 2% decline inthe Nikkei 225 stock index on December 8 to Mizuho’s erroneousJ-Com trade, although other reasons could explain the overall marketdecline.8 Figure 10.2 depicts that trading range for the Nikkei 225 inthe days immediately before and after December 8, 2005.Although the Tokyo Stock Exchange (TSE) initially denied anyresponsibility for the error, this episode is an illustration of how aflawed trading system allowed an error to occur. Managers of theTSE trading system failed to intervene in a timely fashion to cancelthe unusually large trade at an unusually low price. To be sure, TokyoStock Exchange rules limited the price that the stock could be sold at.This helped limit the ultimate loss to the Mizuho Financial Group.Following the admission of TSE responsibility for not allowing theerroneous order to be cancelled, three senior TSE officials resigned,including the president and the senior managing director. Six othermanaging directors and executive directors voluntarily agreed to a10% pay cut for three months as a result of this incident. The incidentprovided the impetus for the TSE to change its trading system to prevent similar problems in the future.9
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16800.0012/8/05date.open 15470.65date.high 15523.15date.low 15183.36date.close 15183.36
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Daily trading range of the Nikkei 225 stock index from December 6, 2005 to January 31, 2006.
FIGURE 10.2
The accidental catalyst: Nikkei 225 December 2005.309
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The principal trading lesson is that erroneous orders can impactnot only the security or commodity in question but may extend toother markets as well. An ancillary lesson that this episode teaches isthat an electronic trading system may not protect traders from erroneous orders. Not surprisingly, there were calls for the firms that hadprofited from the trade to return their trading profits. Another tradinglesson is that the ability to keep trading profits arising from erroneousorders of counterparties may be limited by political concerns.
Lost in TranslationThe opening example in this chapter illustrates how a mistake inorder size can impact both the market for an individual stock and theoverall market. An earlier chapter showed that the trading theses ofmarket participants may, at times, differ sharply from received economic theory, yet the market reacts according to the trading thesis—that is, traders are trading off of noise rather than fundamentaleconomic information. Put differently, the information is correct butthe interpretation of the information by traders is not correct.Sometimes, the supposedly important information that the market is reacting to is mistaken—that is, the market reaction is appropriate if the information is correct but the information is wrong. Thishappens with rumors. The trader is in a difficult position as therumored information may, in fact, be correct. In such cases, the mistaken information acts as a trading catalyst, at least until the factscome out and the markets have readjusted. Once again, existingtrader positions may exacerbate the market reaction to the mistake.To be sure, the market usually reacts sharply to the occurrence ofextreme events (i.e., perceived low probability events). The market isalso likely to react sharply to an erroneous report if the report confirms a commonly held belief and trading position. For instance,during much of 2004 and the first half of 2005, many traders anticipated a sudden revaluation of the Chinese yuan against the dollar.
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News reports at the time suggested that the Chinese currency couldbe as much as 40% undervalued. At the same time, political pressurefrom the U.S. and, to a lesser extent from other countries, added to achorus of voices encouraging the Chinese government to revalue itscurrency, the renminbi (RMB), upward against the dollar. Not surprisingly, traders paid close attention to any news that the Chinesegovernment might revalue its currency.Many traders attempted to bet on the anticipated revaluation.Those who were able to acquire Chinese assets or RMB-denominatedsecurities directly (despite official impediments) did so. Other traderstook positions in the non-deliverable forward (NDF) market thatwould benefit if the Chinese authorities revalued the yuan before theNDF contract matured.10 Those who could not bet on the revaluationof the RMB directly bet on it indirectly by taking positions that wouldlikely benefit after the news came out. A common trading thesis at thetime was that a revaluation of the Chinese yuan would cause the U.S.dollar to fall against certain Asian currencies such as the Japanese yenand South Korean won. The conditions were ideal for the market torespond to erroneous news that the Chinese government was about torevalue its currency.One instance occurred on Wednesday, May 11, 2005 whenBloomberg News ran a story that quoted the online English languageversion of a Peoples Daily story that suggested a revaluation of theChinese yuan was imminent. Other news outlets picked up the report(which was later modified by Bloomberg News). The market reactedin a predictable fashion. The U.S. dollar fell against the Japanese yen,Singaporean dollar, and South Korean won soon after the news reportcame out. The discounts in the yuan NDF market rose sharply toreflect the greater probability of a revaluation of the RMB. The market reaction was also short-lived as the report was denied by thePeople’s Bank of China—China’s central bank—later in the afternoonand exchange and NDF rates reversed course.11 Interestingly,although the impact of the report on spot exchange rates largely
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washed out after the erroneous report was denied, the impact persisted on the one-month NDF rate with the discount ending sharplydown from the high of the day, but two-thirds higher than the low forthe day before the erroneous news report came out.12The news report underlying the People’s Daily report was writtenin Chinese and poorly translated by People’s Daily staff into English.Basically, the market responded to a poorly translated report. Thereis an old Wall Street adage: “Buy on the rumor and sell on the news.”The essential idea is that the time to act is before all the facts areknown because after all the facts are known, the new information isfully priced into the market. This makes market participants very sensitive to rumors and raises a very important point—namely, a traderneeds to be ready to respond to both rumors and facts.A trader must limit her exposure to any one position and be readyto exit trades early enough such that she has enough capital to tradeagain. A rumor that precipitates an adverse price move relative to thetrader’s current position may cause the trader to exit her existing position. This is simply good money management and risk control. Theseactions are based on the behavior of market prices and are independent of whether the news report that precipitates the price changeturns out to be correct. Put differently, traders need to be able toadjust their positions to reflect the current realities of the marketindependent of whether the factors driving price changes are correct.In this case, the news report precipitated a significant change inexchange rates even though the report later turned out to be false.13These changes may have been significant enough to cause sometraders to exit their positions.
Dollars or Shares?At approximately 10:35 A.M. on Monday, November 15, 1999, themarket for Nasdaq 100 stock index shares traded on the American
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Stock Exchange (AMEX) was $139 7/8 bid and $140 1/8 offered for25,000 shares.14 The market for the S&P 500 stock index sharestraded nearby stood at $137 5/8 bid and $137 13/16 offered.15According to market participants, a broker representing Bear Stearnsentered the market with an order to sell 2.5 million shares of the Nasdaq 100 stock index and 2 million shares of the S&P 500 stock indexshares. The broker requested a single price to sell all 2.5 million Nasdaq 100 stock index shares and a trade was soon executed at $138 3/4.The broker was able to sell two million S&P 500 stock index shares atan average price of $137 1/2 at about the same time.The fact that Bear Stearns was able to quickly sell several hundred million dollars worth of index shares at one time is a testamentto the depth of the exchange traded fund (ETF) market. It is also anillustration of the impact that large trades can have on market prices.Notice that the Bear Stearns order was 100 times what the Nasdaq100 market makers were willing to buy (sell) at the existing bid(offer). The price impact of the large ETF trades was $1.125 for theNasdaq 100 stock index shares ($139 7/8 – $138 3/4) and only $.125for the more liquid S&P 500 stock index shares. The order alsocaused the effective bid/ask spread to widen.A common trading thesis is that large sell orders should depressmarket prices, whereas large buy orders should boost market prices.This reflects the belief that the demand curve for securities is downward sloping and the supply curve for securities is upward sloping. Italso reflects the suspicion that the party placing a large trade mayhave information that other market participants do not have. Theimpact of the Bear Stearns order was not limited to the AMEX ETFmarket. The AMEX traders who had bought Nasdaq 100 and S&P500 stock index shares immediately attempted to protect themselvesby selling stock index futures to hedge any unwanted portion of theirnewly acquired long position. Information about the large sell orderin the ETF market put additional downward pressure on stock indexfutures prices even before the order was filled.
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However, the original order was a mistake. According to anAMEX trader on the floor that day, a customer order to sell 2.5 million shares of the Nasdaq 100 stock index and 2 million shares of theS&P 500 stock index was misinterpreted. It was supposed to be anorder to sell $2.5 million of the Nasdaq 100 stock index and $2 millionof the S&P 500 stock index. This interpretation was validated by thesubsequent behavior of the Bear Stearns broker. About 14 minutesafter selling 2.5 million Nasdaq 100 index shares and 2 million S&P500 index shares, the Bear Stearns broker returned trying to buy2 million index shares of the Nasdaq 100 stock index and 2 millionshares of the S&P 500 stock index.The Nasdaq 100 index shares market stood at $139 1/2 bid and$139 7/8 offered for 25,000 shares immediately before Bear Stearnscame in to reverse most of its earlier trade at 10:49. Bear Stearns wasable to buy 2 million Nasdaq 100 stock index shares at $140 1/2. BearStearns was able to buy two million shares of the S&P 500 stock indexin two transactions at an average price of $137.84. Bear Stearnsabsorbed the multi-million dollar loss that resulted from executingthe erroneous initial customer order and subsequently reversing it.16As noted earlier, many Nasdaq 100 and S&P 500 index AMEXtraders hedge their risk exposure to large positions by taking an offsetting position in the corresponding futures market. Many of theAMEX traders who took the other side to the initial erroneous BearStearns order and shorted the related futures contracts lost money ontheir hedged positions because the futures market had alreadyadjusted downward to reflect the size of the erroneous Bear Stearnsorder. In retrospect, the $138 3/4 bid price that AMEX tradersquoted to buy the entire 2.5 million share lot was too high. This illustrates how information about order size (and the potential information it may contain) can quickly travel across related markets.This raises another issue: The attempt by many ETF market makers to keep both their bid/ask spread and the quantity that they are
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willing to buy or sell constant regardless of the volatility or lack of liquidity of the underlying security (or hedging vehicle) is an example ofmental anchoring, a cognitive error. The pursuit of such a strategymay have an adverse effect on market maker profitability in an environment where the price volatility of the underlying securityincreases and liquidity decreases. It may also exacerbate volatility infinancial markets as market makers attempt to cut their losses short.Finally, the preceding example illustrates how a trading catalystmay exert a powerful, yet short-lived, effect on market prices. Tradingdays are often comprised of many relatively small trading catalyststhat buffet the market. Market participants with longer time horizonsmay choose to ignore the intraday fluctuation in prices these tradingcatalysts induce. However, a short-term trader cannot ignore suchprice swings.
Trading Lessons and SummaryTrading catalysts routinely impact financial market prices and volatility. The preceding examples demonstrate how even errors can actas trading catalysts. These accidental trading catalysts can havewidespread—albeit transitory—effects on financial markets.This book begins with an example of how a surprise cut in the targeted Fed funds rate on January 3, 2001 sparked a massive 20% plusintraday move in Nasdaq stock index futures prices and ends with anexample of how an erroneous customer order on November 15, 1999pushed the price of the Nasdaq 100 index shares down and then upwhen the order was later reversed. The numerous examples inbetween demonstrate that trading catalysts can come from many different sources. These examples range from natural disasters to elections to market interventions to company-specific announcements tofactors internal to the markets, among many others.
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The market impact and duration of trading catalysts varies acrosscatalysts and over time. Some trading catalysts affect only a singlesecurity or commodity. Other trading catalysts precipitate pricechanges in many markets. Some trading catalysts influence marketprices and volatility for a considerable period of time, whereas theinfluence of most trading catalysts on prices and volatility is shortlived.17 The market reaction to similar trading catalysts may vary overtime. For instance, weekly announcements of changes in the moneysupply used to exert a big impact on Treasury bond prices. They nolonger do. The forecast errors from other key economic reports stillimpact the market most, but not all of the time and not always in thesame way. Finally, the market reaction to a trading catalyst may notalways increase with the absolute size of the forecast error.Trading catalysts are seen through the twin prisms of newsreports and price changes. There is a natural tendency for reportersto use action words like “plunge” or “soar” that accentuate thereported reaction of a market to a given catalyst. There is also a tendency among reporters to frequently simplify matters by ascribing all,or most, of the price change during a trading period to a single factorwhen it is possible that multiple factors played a role. In addition,reporters may inadvertently report stories that contain the spin of theindividuals that they interview. And, it is always possible that thereported “catalyst” for a price move is simply a convenient rationalization by market participants for what they were intending to doalready. Despite the potential for getting it wrong, contemporarynews media accounts of what prompted many price moves provide areasonably accurate view of the market’s movements as seen bytraders. This interpretation of why the market reacted to a given trading catalyst may not be shared by academics and policymakers oraccord with financial economic theory.The reaction of market prices to perceived trading catalysts isoften puzzling. Sometimes, the market’s reaction seems disproportionate to the news that the trading catalyst brings—either too large
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or too small. Often, the market seemingly overreacts. This seeminglyanomalous behavior might be explained, in many cases, by marketdynamics. That is, by the presence of internal trading catalysts asmarket participants put on or unwind positions and positive feedbacktrading accentuates the price move. However, internal trading catalysts do not explain all of the anomalous behavior associated with themarket reactions to trading catalysts.Although this book has largely focused on trading catalysts thatprecipitated large changes in financial market prices, it should beemphasized that many trading catalysts exert only a modest impact onprices. Indeed, the trading day is often comprised of the reactions to anumber of trading catalysts whose impact is far smaller and shorter-livedthan many of the examples of trading catalysts discussed in this book.
Market Conditions, Sentiment, and Trading ThesesThe speed, magnitude, and duration of the market’s reaction to atrading catalyst also depend upon market conditions and sentiment.An apparently bullish trading catalyst may be discounted or ignoredin a bearish market environment, and vice versa. Similarly, the pricemove that a trading catalyst precipitates may be exacerbated if positive feedback trading is triggered. The presence of positive feedbacktrading may cause the market’s response to similar trading catalysts todiffer over time.Which markets are expected to be most affected by a tradingcatalyst depend on the relationships that traders and other marketparticipants perceive. (For example, a widely held belief is thathigher crude oil prices cause lower stock prices overall.) These perceptions are encapsulated in the form of trading theses. At any pointin time, there is usually a dominant trading thesis that prevails in themarket. However, sometimes, there may be multiple trading thesesoperating simultaneously in the market. These theses often havea different time dimension and apply to a subsector of the market.
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For instance, the market reaction to a terrorist action might trigger aflight to safety (one trading thesis) that bids up bond and gold pricesand at the same time sparks a selloff in travel industry stocks and triggers a rally in defense and security stocks (another trading thesis).The flight to safety effect (i.e., higher bond and gold prices), forexample, may not last as long as the adverse impact on travel industrystocks.One lesson, from an examination of past market reactions to theforecast errors of economic reports, is that traders often have misconceived ideas of how economists think the economy works. Simply put,many trading theses are often what economists call partial equilibrium analyses. Some trading theses are combinations of conflictingeconomic theories. For example, a casual survey of traders wouldlikely reveal a variety of responses to the question of how an unexpected increase in the rate of growth of the money supply wouldaffect interest rates and would likely include some combination ofcompeting monetary theories.In a similar vein, many traders believe that economic theory hassomething to say about the relationship between certain economicreleases (e.g., durable goods) and interest rates when it does not. Inaddition, many widely held beliefs among traders, other market participants, and policymakers—such as the notion that budget deficitsaffect interest rates—lack empirical support.The fact that traders confuse the concept of stocks with flows(e.g., the price level versus the rate of inflation), use partial equilibrium analysis, or don’t understand the nuances of macroeconomic ormonetary theories is largely irrelevant to other traders. The principalobjective of trading is to make money. Traders must react to howother market participants and prices behave and not to how economictheory suggests the market should behave. For this reason, economictheory is often a poor indicator of how markets will react to a giventrading catalyst. This has been shown repeatedly in the foreignexchange market.
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Sometimes, the focus of market participants is not on the economic implications of the report directly but rather the potential policy implications of the report. For example, will the Federal Reservetighten or loosen monetary policy in response to the latest economicdata? That is, what do policymakers watch? The potential reaction ofeconomic policymakers to economic reports justifies, to some extent,the focus on the forecast errors of economic reports by traders.
Trading Is a GameOne recurrent theme of this book is that trading is a game. Althoughthe objective of the game remains constant—to make money—therules of the game seemingly change over time. As a game, it is imperative to know how other participants in the game are likely to behaveunder various conditions or react to various catalysts. Even morevaluable is knowledge of the positions that key traders have on. Forinstance, if most macro hedge funds are in the yen-carry trade, a sudden increase in the value of the yen against the dollar (when yeninterest rates are below dollar interest rates) may precipitate a moredramatic rise in the yen as hedge funds seek to cut their losses shortby buying yen and selling dollars. Simply put, the risk characteristicsof a trade changes over time and increases with its popularity amonglarge players.
News: Information versus NoiseFinancial markets react to news. And, news may consist of information (i.e., economic fundamentals) or noise (nonfundamentalinformation that affects prices). Markets react to both.18 As notedearlier, there is often a seeming disconnect between the apparentnews content of a trading catalyst and the market’s reaction to it. Pastrelationships between or among economic variables may not hold.Transitory periods of correlation may be followed by a seeming lackof relationship.
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Some news releases, and hence potential trading catalysts, arescheduled in advance, whereas others are not. Periodic macroeconomic reports are examples of scheduled news events. The schedulednature of economic reports means that there are often well-formedexpectations about the probable information content of key economicreports. The information content of economic reports lies in the forecast error. Other things being equal, the surprise potential of scheduled economic reports is probably lower than the surprise potential ofunscheduled news. Put differently, the power of trading catalystsfrom scheduled economic reports is lower than unscheduled news,everything else staying the same.As explained in Chapter 6, “Market Interventions,” what is “in themarket” (i.e., the implicit consensus forecast of traders) may differfrom the consensus forecast of economists usually reported in economic surveys. Moreover, the consensus forecast of economists maybe dated and not reflect the latest developments in the market. Ofcourse, traders care about more than the consensus forecast. Tradersare also interested in the dispersion of individual forecasts. However,as noted earlier, the size of the market response does not alwaysincrease with the absolute size of the forecast error even when it isadjusted for the dispersion of forecasts. In any case, an ability to forecast the information content of economic reports accurately is noguarantee of profitable trading off of the catalyst. It is also importantto be able to assess the likely response of the market to the presumptive trading catalyst. Simply put, the market does not always respondas expected to trading catalysts.Unscheduled news may be more difficult to trade off of thanscheduled news events because both the news and the timing of itsrelease are uncertain. Moreover, it is often difficult to assess what theconsensus forecast (and hence forecast error) is for such events. Evenwhen one is not able to obtain a consensus forecast of the unschedulednews event, there may be opportunities to trade on the event (if the fullreaction is delayed) or on an overreaction after the news comes out.19
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The Origin of Trading CatalystsSome trading catalysts, like earthquakes and natural disasters, may beimpossible to predict. Other trading catalysts may be difficult to predict. However, opportunities to trade may still exist. Even in caseswhere the trading catalyst is difficult to predict, the market reactionto the trading catalyst may be relatively easy to predict. Certain trading theses like the flight to safety thesis are common for some kinds oftrading catalysts, and other trading theses are common for othertypes of trading catalysts. Moreover, as the delayed response to theKobe earthquake of January 1995 or the Indian parliamentary elections of May 2005 indicate, there may be plenty of time to put ontrading positions after a catalyst has occurred. Recall that in bothinstances, the largest reaction occurred days after the trading catalystoccurred. Other trading catalysts, like the weather, may be easier topredict. Not surprisingly, some agricultural traders subscribe to private meteorological services to get a trading edge.The origin of a price change may influence how traders interpretits potential impact on other markets and on how a trader trades offof it. For instance, a shock originating in Asia or Europe may wellhave a less dramatic effect by the time it reaches the U.S. This meansthat a U.S.-based trader could play the likely overreaction of marketprices to the trading catalyst. Conversely, a shock originating in theU.S. may have a more dramatic impact on foreign markets, and foreign traders would take that into account. Similarly, the source of achange in commodity prices may influence the validity of a tradingthesis and explain apparently inconsistent reactions to it. Forinstance, a price increase in a commodity could result from anincrease in demand—a demand shock—or a decrease in supply—asupply shock. There is no reason to expect that the implications forother markets, like equities or fixed income, are the same for bothkinds of shocks.Although external trading catalysts often receive substantial pressattention, internal market catalysts may be far more important in
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determining the extent and magnitude of the market’s reaction to anexternal trading catalyst. Internal trading catalysts are especiallyimportant in bubbles, crashes, corners, and market crises. Althoughan external trading catalyst may precipitate a market move, internaltrading catalysts may exacerbate the price move. This means knowledge of market conditions that might exacerbate a price move (viapositive feedback trading) is very valuable to traders. Positive feedback trading may arise from technical analysis, stop-loss orders, margin calls, portfolio insurance, momentum investing, and dynamichedging.
Extreme EventsExtreme events occur more frequently than what would be expectedif changes in prices were normally distributed. This book has shownthat the trading catalysts that precipitate those extreme market eventsare many and varied.Because the market reacts to a host of different factors, it isimportant to know if a trader has an edge in certain trades. Forinstance, some individuals may have a comparative advantage in forecasting the outcome of certain potential trading catalysts such asgeopolitical events and government interventions in the marketplace.Such traders have an edge. The only caveat is that it is not enough tobe able to forecast outcomes better than the market consensus; thetrader also needs to know how the relevant markets are likely to reactto the trading catalyst. Similarly, the probability distribution fromwhich changes in financial market prices are drawn need not be constant over time. This means that traders who can recognize situationswhere the distribution is skewed while others do not have an advantage because their trading positions are less risky than it otherwisewould appear. In extreme cases, such as when central banks defend
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an indefensible exchange rate, one-sided bets may result. This situation arose in September 1992 when legendary trader George Soros“broke” the Bank of England.Independent of their origin, trading catalysts create both risk andopportunity for traders and other market participants. The large pricemoves that trading catalysts induce create the opportunity for substantial gains in a short period of time. The large price moves thattrading catalysts induce also create the risk for substantial losses in ashort period of time.Many traders contend that only a handful of trades during theyear account for the vast bulk of their trading profits. In theory, thelarge changes in market prices that many trading catalysts inducemake possible substantial gains or losses from a handful of trades. Inpractice, traders are unlikely to limit their trades to trading off oftrading catalysts because both the occurrence of the trading catalystand the market response to the trading catalyst may be difficult toassess in advance.Whether traders elect to bet directly on a trading catalyst, on thepresumed market reaction (or overreaction) to it, or not at all, thepotential impact on market prices and volatility means that all tradersmust pay attention to trading catalysts and the market reactions thatthey precipitate. A trader who eschews trading on the release of economic reports, for instance, should nevertheless, be cognizant of thescheduled release times of periodic economic reports because thevolatility that often follows the release of economic reports may affectthe timing of the trader’s entry or exit of positions. Similarly, uncertainty generated by geopolitical events, for example, may cause atrader to reduce his position size even though the trader is not placinga direct bet on the geopolitical event or the market reaction that follows its occurrence.
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