The Little Book of Market Wizards

by Jack D. Schwager

  The trick is to differentiate between what you want to happen and what you know will happen.

  A trader

  Emotional influences can compromise the objectivity of market analysis and trading decisions. For example, a trader who is long will be more inclined to dismiss market evidence that she would otherwise have interpreted as bearish in the absence of a position. It may just be too painful to accept a bearish forecast when she is long and hoping for higher prices. Or a trader might ignore signs that the market is moving higher because he has procrastinated in placing the position, and entering now would confirm the mistake of not having bought previously when prices were lower. As a final example, a trader who is on the record with a forecast for the market moving higher or lower will be reluctant to accept contradictory evidence. These types of internal constraints may cloud conscious analysis and trading decisions and prevent a trader from recognizing evidence that is uncomfortable to accept. The subconscious mind, however, is not inhibited by such constraints. As one trader I interviewed (who requested anonymity) said, “The trick is to differentiate between what you want to happen and what you know will happen.”

  What we call “intuition” may just be the objective synthesis of the available information based on past experience, unhindered by emotional distortions. Unfortunately, we cannot tap into our subconscious thoughts at will. However, when these market views come through as intuition, the trader should pay attention.

  Note

  1. Treasury bill prices move inversely to Treasury bill interest rates.

  Chapter Eighteen

  Dynamic versus Static Trading

  The Need to Adapt

  Although most (and maybe all) of the trading principles discussed in this book are timeless, trading strategies and methodologies need to adapt. When I asked Colm O’Shea if there were specific trading rules he followed, he replied, “I use risk guidelines, but I don’t believe in rules that way. Traders who are successful over the long run adapt. If they do use rules, and you meet them 10 years later, they will have broken those rules. Why? Because the world has changed. Rules are only applicable to a market at a specific time. Traders who fail may have great rules that work, but then stop working. They stick to the rules because the rules used to work, and they are quite annoyed that they are losing even though they are still doing what they used to do. They don’t realize that the world has moved on without them.”

  Traders who are successful over the long run adapt.

  Colm O’Shea

  Edward Thorp provided a perfect example of how successful traders adapt. Among the many firsts Thorp achieved in his long career, he was the first to implement statistical arbitrage as a strategy. Statistical arbitrage is a type of market-neutral strategy in which portfolios are constructed consisting of large numbers of long and short equity positions, balanced to minimize market directional moves and other risks. The strategy will go long underpriced equities and short overpriced equities, dynamically adjusting the holdings as prices change. Typically, but not necessarily always, a mean-reversion strategy will be used to determine which stocks are underpriced and which are overpriced.

  In 1979, Thorp launched a research effort he called the “indicators project.” He looked for indicators that might have some predictive value for individual equity prices. Thorp and his team examined a broad range of possible indicators, including earnings surprises, dividend payout rates, book-to-price ratios, and so on. As part of this project, one of the researchers looked at the stocks that had been up and down the most in the recent past. This factor turned out to be by far the most effective indicator tested in predicting near-term equity prices. Essentially, the stocks that were up the most tended to underperform in the subsequent period, while the stocks that were down the most tended to outperform. They called their strategy MUD for most up, most down.

  In the initial incarnation of the strategy, Thorp sought to control risk by balancing the long and short equity exposures. The strategy worked very well with reasonable risk control, but eventually the return/risk performance started to deteriorate. At this point, Thorp revised the strategy by constructing portfolios that were not only market neutral but also sector neutral. Then when even the sector-neutral model showed signs of losing its edge, Thorp switched to a strategy that neutralized the portfolio to various mathematically defined factors. By the time this third iteration was adopted, the original system version had significantly degraded. By continually adapting the strategy as needed, Thorp was able to maintain superior return/risk performance, whereas if he had stayed with the original system that had worked so well at one time, the profitability would have eventually evaporated.

  Scaling versus Single-Price Entry and Exit

  You don’t have to get into or out of a position all at once. Most traders tend to pick a single entry price and a single exit price. It is often better to scale into and out of positions. For example, consider a common dilemma faced by traders. Let’s say you have a strong conviction that a market will move higher, but prices have just witnessed a significant upswing. You are concerned that if you buy now and there is a correction, the initial loss may force you out of the market, even if you are right about the long-term direction. On the other hand, if the trade is really good, there is a substantial chance that waiting for a pullback will result in missing the entire move. There is a third alternative, however: You can buy a partial position at the market and then seek to enter the remainder of the position using a scale-down entry process. This scale-down buying approach will ensure that you have at least a partial position if the market keeps going, without assuming the implicit risk of buying the entire position after a substantial advance. By reducing the average entry price, it will also mitigate the chances of abandoning a good long-term trade because of an initial loss from entry.

  An analogous perspective would also apply to getting out of a position. For example, assume you are in a long position with a large gain and are concerned about surrendering those profits. If you get out of the entire position and the advance continues, you can miss out on a substantial portion of the total move. If, however, you hold on to the entire position and the market reverses, you can end up giving back a large portion of the gain. As an alternative, scaling out of the position will ensure that you still have a partial position if the move continues, while mitigating a surrender of profits if the market reverses. Bill Lipschutz, a former head of global foreign exchange (FX) trading at Salomon Brothers and the portfolio manager for Hathersage Capital Management, an FX money management firm, attributed his ability to stay with good long-term trades to his use of scaling-out orders: “It has enabled me to stay with long-term winners much longer than I’ve seen most traders stay with their positions.”

  Avoid the temptation of wanting to be completely right. By shunning all-or-nothing decisions and instead scaling in and scaling out of positions, you will never get the best outcome, but you will never get the worst one, either.

  Trading around Positions

  Most traders tend to view trades as a two-step process: a decision when (or where) to enter and a decision when (or where) to exit. It may be better to view trading as a dynamic process between entry and exit points rather than a static one.

  Perhaps no one I ever interviewed exemplified a dynamic trading process more than Jimmy Balodimas, a very successful proprietary trader for First New York Securities. He is the epitome of an unorthodox trader. I started my chapter on Balodimas in Hedge Fund Market Wizards with the sentence “Jimmy Balodimas breaks all the rules.” And he does. He will sell into sharp rallies and buy into plunging markets. He will add to losers and cut winners short. I don’t advise anyone to try to copy Balodimas’s trading method, which I think would be financial suicide for most people. But there is one element—and only one element—of his trading style that I think can be beneficial to many traders. This particular aspect of his trading, which we will get to soon, explains how Balodimas can often be net profitable, even when he
is on the wrong side of the market.

  I first interviewed Balodimas on February 22, 2011, a day when the stock market was down sharply. Prior to that day, the month had been particularly brutal for shorts, as the market reached new highs almost daily, never taking more than three days to do so. Balodimas had been heavily short throughout February. The steep sell-off on the 22nd surrendered a little less than half of the month’s gain, but it was enough for Balodimas to recover more than his entire loss for the month to date.

  One of the first questions I asked Balodimas was: “How can you still be ahead when you have been on the wrong side of the market?”

  I always take some money off the table when the market is in my favor. . . . That saves me a lot of money, because when the market rallies, I have a smaller position.

  Jimmy Balodimas

  He answered, speaking from his perspective as a short at the time of our interview, “I always take some money off the table when the market is in my favor. . . . That saves me a lot of money, because when the market rallies, I have a smaller position. That is a habit I have had since day one. I always take money off the table when it’s in my favor. Always, always, always.”

  The adjustment of position size counter to market fluctuations (e.g., reducing a short position on a break and rebuilding to a full position on a rally) is a key element in Balodimas’s success. He is so skillful in trading around his positions that he is sometimes, as in this instance, net profitable even when he is on wrong side of the market trend. Although few traders will be able to match Balodimas’s innate skill in trading around positions, many traders may find a dynamic rather than static approach to trades beneficial.

  How might a dynamic trading approach be used in practice? The basic idea is that the position size of a trade would be reduced on a profitable move and rebuilt on a subsequent correction. Any time a position was lightened and the market retraced to the reentry point, a profit would be generated that otherwise would not have been realized. It is even possible for a trade that fails to exhibit a favorable net price change, as measured from original entry to final exit, to be profitable as a result of trading against the position (i.e., reducing exposure on favorable price swings and increasing exposure on subsequent adverse price moves).

  Another important benefit of reducing exposure on a favorable price move is that it will lessen the chances of being knocked out of a good trade on a price correction, since if the position has already been reduced, a correction would have less impact and might even be deemed desirable to provide an opportunity to reenter the liquidated portion of the trade. For example, let’s say you buy a stock at 40 with a target objective of 50 and an expectation of interim resistance at 45. Given these assumptions, you might use a strategy of reducing exposure at 45 and reinstating the full position on a pullback. This type of approach will make you a stronger holder on a pullback. In contrast, if a static trading approach were used instead, a pullback could lead to concerns that the entire profits on the trade might be lost, thereby increasing the chances that the trade would be fully liquidated.

  The only time when a strategy of taking partial profits on favorable price moves and reinstating on corrections will be net detrimental is when the market keeps moving in the intended direction without pulling back to the reentry level. But in this instance, by definition, the retained portion of the position will be very profitable. So, on balance, this type of dynamic trading process can increase profits on price moves with corrections, as well as improve the chances of staying with good trades, at the expense of giving up a portion of profits on trades that move smoothly in the intended direction. Trading around positions will not necessarily be a good fit for all traders, but some traders should find the approach very beneficial.

  Chapter Nineteen

  Market Response

  A counter-to-anticipated response to market news may be more meaningful than the news item itself. Marty Schwartz credited his friend Bob Zoellner with teaching him how to analyze market action. Schwartz summarized the basic principle: “When the market gets good news and goes down, it means the market is very weak; when it gets bad news and goes up, it means the market is healthy.” Many of the traders I interviewed recalled trading experiences that echoed this theme.

  When the market gets good news and goes down, it means the market is very weak; when it gets bad news and goes up, it means the market is healthy.

  Marty Schwartz

  Gold and the First Iraq War

  Randy McKay described a trading approach that incorporated market response to fundamental news. Describing how he used fundamentals, McKay said, “I don’t think, ‘Supply is too large and the market is going down.’ Rather, I watch how the market responds to fundamental information.” McKay provided the classic example of the behavior of the gold market in response to the first Iraq war, the Gulf War, which began in January 1991. On the eve of the first U.S. air strike, gold was trading just below the psychologically important $400 level. During the night when U.S planes started the attack, gold rallied past the $400 level, moving to $410 in the Asian markets, but then retreated back to $390—lower than it was before the war-induced rally started. McKay viewed gold’s price decline in the face of what was expected to be bullish news as a very bearish sign. The next morning, gold opened sharply lower in the U.S. market and continued to decline in the ensuing months.

  McKay Gets Interested in Stocks

  McKay had long been influenced by the market’s response to news. Nine years earlier, in 1982, he became very bullish on the stock market. McKay was a futures trader and had never even traded stocks before. His conviction about the stock market was so strong, however, that it compelled him to open a stock account. I asked McKay what made him so convinced that the stock market was going higher when he had never even traded stocks. He answered, “Part of it was just seeing the market up almost every day without any particular supporting news. In fact, the news was actually quite negative: Inflation, interest rates, and unemployment were all still very high.” Here too, market tone—the ability of stock prices to advance steadily despite ostensibly bearish fundamentals—provided the crucial price clue.

  Dalio Is Surprised

  Ray Dalio recalled episodes early in his career when he was surprised by the market response to news. In 1971, after graduating from college, Dalio worked as a clerk on the New York Stock Exchange. On August 15, President Richard Nixon took the United States off the gold standard, causing an upheaval in the monetary system. Dalio thought this event was bearish news, but to his surprise, the market rallied.

  Eleven years later, with the United States mired in a recession and unemployment above 11 percent, Mexico defaulted on its debt. Dalio knew that the U.S. banks held large amounts of capital in Latin American debt. He naturally assumed that the default would be terrible for the stock market. Dalio’s expectations could not have been more wrong. The default by Mexico was near the exact bottom of the stock market and marked the beginning of an 18-year rally.

  Speaking of both these experiences where the market reaction was exactly inverse to his expectations, Dalio said, “In both the abandonment of the gold standard in 1971 and in the Mexico default in 1982, I learned that a crisis development that leads to central banks easing and coming to the rescue can swamp the impact of the crisis itself.” Indeed, we witnessed another dramatic example of this observation in the major bull market that followed on the heels of the 2008-to-2009 financial meltdown—a recovery that was heavily aided by aggressive central bank intervention.

  Investors are often baffled when markets respond counterintuitively to news events. This seemingly paradoxical behavior can be explained by the fact that markets often anticipate the news and discount the impending event. For example, a default in Latin American debt in 1982 was widely anticipated before Mexico actually defaulted. Ironically, the very occurrence of an anticipated event removes it as a market concern, thereby leading to a counter-to-anticipated price response. Another factor that
explains bullish market action in response to bearish news is that the bearish event—especially if it is significant—can trigger bullish repercussions. For example, developments that have very negative implications for the economy and market sentiment can prompt central bank measures that lead to a rally.

  A Most Bullish Report

  The market does not necessarily need to witness a strong counter-to-anticipated response to fundamental news to provide a market-tone-based signal; a weak response to what was expected to be a major bullish or bearish event can have the same implications.

  Always ask yourself, “How many people are left to act on this particular idea?” You have to consider whether the market has already discounted your idea.

  Michael Marcus

  Michael Marcus said, “Always ask yourself, ‘How many people are left to act on this particular idea?’ You have to consider whether the market has already discounted your idea.”

  “How can you possibly evaluate that?” I asked him.

  Marcus explained it was a matter of reading market tone. He provided what he considered the classic example, which involved a bull market in soybeans in the late 1970s. At the time, there was a severe shortage of soybeans, and each week, the government export report would drive prices higher. One day just after the latest weekly report was released, Marcus received a call from someone at his company. The caller said, “I have good news and I have bad news.”