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This chapter is from the book

The Nature of Trading Catalysts

Volatile financial markets create both risk and opportunity—that is, the risk of substantial losses and the opportunity for substantial gains. However, not all volatility is created equally. Sudden jumps or breaks in prices can impart a roller-coaster-ride quality to trading or investing in financial markets. This book examines the catalysts that spark large changes in prices suddenly or over time. These include the following, among other factors: ill-advised comments by policymakers, news of natural disasters, elections, certain economic reports, company-specific announcements, and factors internal to the market itself.

The direction, magnitude, speed, duration, intensity, and breadth of influence of trading catalysts on market prices are important to understand. It is also important to understand how trading catalysts differ in their influence on market prices and how the same trading catalyst may differ in its influence on market prices over time. Part of the difference in the influence of trading catalysts on market prices at any point in time, as well as over time, is a function of market conditions and sentiment, both of which are discussed in detail in Chapter 2, "Market Conditions and Sentiment."

The identification of which market or markets are most likely to be impacted by a trading catalyst seems easy but may sometimes be difficult as the preceding Fed rate cut example shows. Again, from a trading perspective, a trader wants to take positions that will achieve maximum benefit from the occurrence of the trading catalyst at minimum risk. Imagine a trader who anticipated the surprise Fed rate cut announcement shortly before it occurred or had advance knowledge of it. Which market or markets would the trader have placed his bet or bets on? It is not apparent that most traders would have selected the Nasdaq as the market most likely to have the largest reaction to the Fed rate cut announcement. Yet, in retrospect, it is clear that a long position in the Nasdaq 100 stock index or Nasdaq 100 stock index futures was the place to be immediately following the Fed rate cut announcement on January 3, 2001.

A trader needs to know the direction of the likely response to a trading catalyst to determine whether he should go long or short. Determining the likely direction of market prices in response to a trading catalyst seems easy. However, the implicit simple assumption that markets always behave a certain way in response to arguably the same trading catalyst is also not true. Sometimes, there is a shift in how a given trading catalyst is interpreted. Sometimes, the information content of the trading catalyst is simply ignored. For example, the Merchandise Trade Balance is a monthly report issued by the U.S. Department of Commerce. Yet, as discussed in Chapter 7, "Periodic Economic Reports," the conventional interpretation of the information content in the report changed 180 degrees between 1986 and 1987. Other times, the market seemingly ignores a trading catalyst. During most of the 1990s, the merchandise trade balance report—which was so important during the late 1980s—was largely ignored by bond market participants.

Financial and economic theory provides only limited guidance in how market prices should react to various trading catalysts. More important than financial or economic theory are traders' perceptions of both economic theory and how other market participants will react to the catalyst.

The speed of response in market prices ranges from immediate to extensive delays. The speed of a market's response to a given trading catalyst is usually fairly fast. However, as will be shown later in this book, sometimes there is a perceptible delay in the market's response. In any event, the relevant question for a trader is whether there is sufficient time after the trading catalyst occurs for the trader to position herself and profit from it. Other things equal, the speed of the market's response tends to increase the greater the liquidity and transparency of the market.

Consider once again the Fed's January 3, 2001 rate cut discussed previously. Most traders, of course, did not anticipate the surprise Fed action and may not have been positioned to take maximum advantage of it. Yet, a trader who was flat (i.e., had no position on) in Nasdaq futures before the Fed rate cut announcement still had time to put on a long position and profit from the attendant rise in prices sometime after the announcement came out. To be sure, prices moved quickly, but there was sufficient time to place a trade if one was willing to tolerate the risk associated with it.

A closely related issue is the duration of the response—that is, how long the trading catalyst continues to impact financial market prices. The length of the impact of a trading catalyst ranges from transitory to permanent. The impact of many trading catalysts is fairly short-lived. Indeed, sometimes the impact of a trading catalyst is entirely erased in the course of a single trading session, even in the absence of the arrival of any other trading catalysts. Consider, for instance, the following example reported in the January 11, 2005 issue of The Wall Street Journal.

  • Energy prices have turned volatile again, driven up by the impact of production outages and unfavorable weather that have prompted traders to snap up oil and gas contracts...

    Crude oil surged to a five-week high of $47.30 a barrel during trading yesterday before retreating to end moderately lower, as a broad rally in oil-related futures markets stalled. Analysts said the various production problems, combined with forecasts of cold U.S. temperatures, spurred the nearly $2 rally, but the supply snags were overshadowed by a sense that the market had gotten ahead of itself. February crude oil fell 10 cents on the day to settle at $45.33 a barrel on the New York Mercantile Exchange...14

The preceding example illustrates how two different trading catalysts—production outages and the weather—combined to impact crude oil prices on the upside. Although a single "fuzzy" factor—the "sense that the market had gotten ahead of itself"—caused a price break. In this case, the effects of two trading catalysts on market prices were short-lived because the market reversed course due to other concerns. Notice that the entire gain and some 10 cents more were supposedly wiped out by fears "that the market had gotten ahead of itself."

Another dimension by which to measure the influence of a trading catalyst is the intensity of trading in the reaction to market prices that they induce. The intensity of trading varies from infrequent trading at one extreme to a trading frenzy at the other extreme. The intensity of trading refers to the frequency as well as size of individual trades.

A trading frenzy might arise from either panic buying or panic selling—euphoria or despair. At first glance, one might suppose that trading catalysts that precipitate either panic buying or panic selling must be very significant because of the large price changes they induce. However, there is no necessary relationship between the significance of the trading catalyst and the panic buying or panic selling that ensues. Simply stated, panic selling or panic buying need not be precipitated by a momentous event. The trigger for episodes of panic buying or selling may be seemingly innocuous enough. It is also important to point out that trading frenzies need not start out as such—that is, trading may accelerate sometime after the trading event occurs, as it did in the Fed rate cut example discussed previously.

Consider another example. News of the assassination of President John F. Kennedy on Friday, November 22, 1963 sparked a sell-off in stocks and a sharp decline in stock prices that threatened to turn into a selling panic. The initial sell-off prompted the New York Stock Exchange (NYSE) to stop trading and close early. When the market reopened on Tuesday, November 26, stocks not only quickly recovered but rallied sharply higher. Indeed, in his book, 101 Years on Wall Street: An Investor's Almanac, John Dennis Brown characterizes the trading activity on Tuesday, November 26, 1963 as a "buying panic" that resulted in a 4.5% gain in the value of the Dow Jones Industrial Average.

This episode is interesting from another perspective: namely, how a news-oriented trading catalyst, the assassination of President Kennedy, which was only partially responded to because the market was closed early, can be quickly followed by a larger, and arguably, reflexive trading catalyst. Although it is impossible to know how far the Dow Jones Industrial Average would have fallen if the NYSE had not halted trading early, the sharp rally on Tuesday, November 26, 1963 illustrates the powerful impact that purely reflexive trading catalysts can exert on market prices.

At the other extreme is a slow market with infrequent trading following the occurrence of a trading catalyst. These catalysts are relatively rare but may occur when prices jump to reflect the impact of the trading catalyst without inducing additional trading activity. A variant of this is sometimes observed in satellite or related markets where there is a considerably more muted reaction than occurs in the primary market, even after adjusting for any differences in risk.

Another dimension of the impact of trading catalysts is the breadth of the market's reaction—that is, whether the response to a trading catalyst is localized (i.e., limited to one market or one sector) or generalized (i.e., affects multiple markets). In other words, a trading catalyst in one market can act as a trading catalyst for prices in another market. A frequent example in this regard is the impact that changes in oil prices have on equity prices and the impact that price changes in the equity market have on other markets. The reaction of other markets may be quick or slow.

Consider the following example reported in the Thursday, October 28, 2004 issue of the Financial Times.

  • World oil prices dropped sharply yesterday after the US reported a bigger than expected rise in crude stocks...sending equity prices scurrying higher.

    The dollar climbed broadly...as the fall in oil prices alleviated the threat to the US economy posed by further rises in energy prices.

    Nymex crude oil futures fell swiftly as news of a bigger-than-expected rise in stocks of crude oil and gasoline outweighed a fall in heating oil stocks...

    Nymex December crude fell almost 5 per cent to $52.46 per barrel...

    ...The Dow Jones Industrial Average gained 1.2 per cent to 10,002.30...The Nasdaq Composite put on 2.1 per cent.

    Yet while oil was the clear catalyst for yesterday's gains, next week's presidential election, the result of which is too close to call, is casting an uncomfortable pall over financial markets...15

There are several lessons to be gleaned here. First, it is important to understand that every trading day new catalysts can impact the marketplace. Consequently, some trading catalysts may have short lives. Second, other trading catalysts—like the impending presidential election in the U.S.—could exert an influence on day-to-day trading and otherwise color the market environment for some time. The underlying concern—in this instance, the uncertain outcome of the impending U.S. presidential election—could dampen the overall sensitivity of equity prices to oil price changes. Third, notice that the market seemingly chose to ignore certain information, namely the drop in heating oil stocks.

Trading catalysts can be defined in a number of different ways. The approach taken in this book is to divide trading catalysts into two principal categories: those external to the market and those internal to the market. External trading catalysts can be further subdivided as follows: the comments of policymakers and politicians; domestic and geopolitical risk; weather and natural disasters; scheduled economic reports; unscheduled economic news; earnings announcements, court or regulatory decisions, and other company-specific news; rumors; and noise—non-fundamental factors that affect prices among others. Internal catalysts can be subdivided into the following: reflexive catalysts; cases where trading feeds on itself and exacerbates the price move (i.e., positive feedback trading) because of stop loss orders being hit, margin calls being made, or perceived technical barriers violated; and cases where price changes in one market spill over and affect price actions in other markets.16 The latter category includes cases where the price action in foreign markets affects the subsequent price action in domestic markets as well as cases where the price action in one commodity, say crude oil, affects the price action in the stock market. Other ways of categorizing trading catalysts also exist.

One might classify reflex rallies as being precipitated by internally generated trading catalysts. However, the spark that causes the rally is more frequently a change in market perception rather than a specific event marking the end of the panic and a reversal of opinion. This is illustrated in the historic behavior of U.S. stock prices as measured by changes in the Dow Jones Industrial Average. Significant price reversals oftentimes seemingly come out of nowhere. John Dennis Brown, who examines the behavior of the Dow Jones Industrial Average from 1890 (the first full year that statistics were available) through 1990 in his book, 101 Years on Wall Street, includes a list of important one-day buying panics.17 These days are associated with substantial positive percentage changes in the Dow Jones Industrial Average ranging from a low of 4% to a high of 15.3%. Brown categorizes the rallies as "news-oriented," "war-influenced rallies," and "reflex from panic conditions." Of the 29 examples listed, 12 are classified as reflex rallies from panic conditions.18

Two examples of reflex rallies are the 12.3% rally on October 30, 1929 following the market crash of October 28 and 29, 1929 and the 10.1% rally in the Dow on October 21, 1987 following the market crash of October 19, 1987. As noted earlier, one problem with using event time to predict future market sensitivity to trading catalysts is the small sample sizes that one has to deal with. The idea that prices should recover some of their losses from a major sell-off or market crash seems reasonable but, once again, the sample size is too small to draw valid statistical inferences from. Nevertheless, when the next market crash occurs, many traders may be looking for a major short-term rally following the crash based on what has happened in response to previous market crashes.

Probably most individuals would argue that news-oriented rallies or sell-offs would exert more impact on market prices than reflex rallies or breaks would. However, that need not be the case. Another interesting aspect of John Dennis Brown's list of important one-day buying panics is that many of the news-oriented rallies had a smaller impact on market prices than the reflex rallies did. This highlights the danger of relying on the arrival of new information to explain large moves in market price.

The preceding division of trading catalysts into external and internal factors is sometimes problematic. Consider, for example, a situation in which crude oil prices surge due to production disruptions also results in equity prices falling because of the fear that higher oil prices may have on the overall economy. Under the preceding definition, the trading catalyst for the oil price move would be classified as an external factor but the trading catalyst for the equity price move would be internal—namely the rise in crude oil prices. The relevant issue is whether the price changes in one market are driving the price changes in another market or whether fear has simply spread to other markets.

Another way of categorizing trading catalysts is to decompose them into informational and noninformational factors. A proponent of the efficient capital markets hypothesis would argue that only the first category should impact market prices. However, both types of trading catalysts exist. And, noninformational factors sometimes have a larger impact on market prices than fundamental news.

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