What I Learned Losing a Million Dollars

by Jim Paul

  Conventional gambling serves no purposes other than those common to other forms of play. The gambler isn’t playing a game; he is just playing. To a gambler, all normal criteria of odds (respective return, probability of winning, etc.) are irrelevant. At the poker table you always see some guy who stays in every hand, going for the inside straight even though the odds are he’s not going to hit it. In a best case situation, the odds are 12:1 against him and deteriorate from there if one of the cards he needs has already been played or is in another player’s hand. When I was in Las Vegas with Larry and Conrad, I saw gamblers at the roulette table just throwing money away. But they didn’t care; they were interested in entertainment and excitement, not money.

  It is important to understand that not all participants in gambling games are gamblers. The aim of the “professional gambler,” as he is called, is to make money. He can be recognized by deliberate and extremely disciplined wagering. His wagering is systematic and usually limited to infrequent but highly favorable opportunities. The behavior of the professional gambler is highly controlled and usually the result of a studied approach to his chosen game. He concentrates on games where the element of skill is sufficient to produce the possibility of a player advantage such as blackjack and pari-mutuel betting. The professional gambler is similar to the stock arbitrageur in that they both take calculated risks. They are dealing with an uncertain outcome and seek to profit from their ability to anticipate the future or to see the future — in other words, to speculate. Professional gamblers are actually speculators because of the characteristics they exhibit when risking money. They are not seeking entertainment at the tables like gamblers do, and they are not trying to be right. They are trying to make money.

  Consider Edward 0. Thorp, the author of Beat The Dealer and a mathematics professor who devised a winning card counting system on a high-speed computer. He won so much money in Las Vegas playing blackjack that the Vegas Resort Hotel Association changed the rules of the game. Thorp wasn’t gambling, even though he was playing cards. He was a professional speculator. Or consider a story reported in Business Week about an entrepreneur who started a small service company, took it public, made $20 million and then turned around and lost it in another business venture. He said “the relationship between gambling and entrepreneurship was an uneasy one” and confessed to behaving like a gambler in a business enterprise.27 This guy wasn’t speculating on a business venture — he was gambling and fell prey to “gambler’s ruin.” That is, he wagered it all on that one venture just as I had wagered disproportionately on the bean oil trade. If a person approaches a business risk or a risk in the financial markets for excitement, then he is gambling — regardless of how much control he supposedly has over the outcome.

  If you can find speculators in casinos, then you can also find gamblers and bettors in the stock and commodity markets either as customers, brokers or analysts. Whether they are betting or gambling is a function of how they go about participating in the markets. Are they exhibiting the characteristics of a bettor or gambler? If so, then they are betting or gambling — regardless of what they think they are doing or say they are doing.

  A Dangerous Combination

  As the epigraph to this chapter indicates, most people don’t know whether they are engaging in inherent or created risk activities. Couple this with people’s failure to distinguish between the two types of loss-producing events, continuous and discrete, introduced at the end of the last chapter and you have a disaster waiting to happen. Recall that in discrete events, such as gambling and betting games, there is a defined end to the risk activity. But inherent risk activities are continuous processes with no predetermined end. For instance, running a business keeps you continuously exposed to the risks coincident with the commitment of resources to future expectations. A single sales transaction may be a defined event with a beginning and an end, but the business operation itself is a continuous process. Likewise, a market position is a continuous process, which introduces the possibility of internal losses because of the uncertainty of when the process will end. On the other hand, created risk activities are associated with discrete events, such as sports games, political contests or the rolls of the dice; the game ends, the contest finishes and the dice stop rolling.

  Betting and gambling are suitable for discrete events but not for continuous processes. If you introduce the behavioral characteristics of betting or gambling into a continuous process, you are leaving yourself open to enormous losses. In betting and gambling games, you wager and wait to see if you are right or to experience some excitement, respectively. Any resulting monetary losses are real, but they are also passive because the discrete event ends all by itself. On the other hand, a position in the market is a continuous process that doesn’t end until you make it end. If you “wager and wait” in the market, you can lose a lot of money. In betting and gambling games if you stop acting and do nothing, the losses will stop. But when investing, trading or speculating if you’re losing and stop acting, the losses don’t stop; they can continue to grow almost indefinitely.

  Psychological Fallacies

  We’ve already seen that everyday life involves risk. Likewise, estimating and managing those risks is a necessary part of everyday life. Probability is the mathematics of estimating risk and you know how I feel about math. I’m not going into a long dissertation on the subject. I am, however, going to point out some of the more common misunderstandings about probability and how we psychologically distort situations to make the odds seem more in our favor. In this section, I want to point out a few examples of the fallacies in popularly held beliefs about probability and how market participants apply the same fallacies to their market strategies and positions. Succumbing to the fallacies is harmful enough when applied to discrete events, but it is catastrophic when applied to continuous processes. Below are a few examples of the psychological fallacies most people have when it comes to risk and probability.28

  1. The first psychological fallacy is the tendency to overvalue wagers involving a low probability of a high gain and to undervalue wagers involving a relatively high probability of low gain. The best examples are the favorites and the long shots at racetracks.

  2. The second is a tendency to interpret the probability of successive independent events as additive rather than multiplicative. In other words, people view the chance of throwing a given number on a die to be twice as large with two throws as it is with a single throw — like throwing sixes four times in a row in craps and thinking that must mean their chances of throwing a seven next have improved.

  3. The third is the belief that after a run of successes, a failure is mathematically inevitable, and vice versa. This is known as the Monte Carlo fallacy. A person can throw double sixes in craps ten times in a row and not violate any laws of probability, because each of the throws is independent of all others.

  4. Fourth is the perception that the psychological probability of the occurrence of an event exceeds the mathematical probability if the event is favorable and vice-versa. For example, the probability of success of drawing the winning ticket in the lottery and the probability of being killed by lightning may both be one in 10,000; yet from a personal viewpoint, buying the winning lottery ticket is considered much more probable than getting hit by lightning.

  5. Fifth is people’s tendency to overestimate the frequency of the occurrence of infrequent events and to underestimate that of comparatively frequent ones, after observing a series of randomly generated events of different kinds with an interest in the frequency with which each kind of event occurs. Thus, they remember the “streaks” in a long series of wins and losses and tend to minimize the number of short-term runs.

  6. Sixth is people’s tendency to confuse the occurrence of “unusual” events with the occurrence of low-probability events. For example, the remarkable feature of a bridge hand of thirteen spades is its apparent regularity, not its rarity (all hands are equally probable). As another example,
if one holds a number close to the winning number in a lottery, he tends to feel that a terrible bad stroke of misfortune has caused him just to miss the prize.

  Some Examples

  Independent Events

  A dealing shoe in baccarat doesn’t know anything about what cards have already been dealt. Cards coming out of a deck are statistically independent events. In fact, one might argue that according to the law of large numbers, each side has a fifty/fifty probability of winning and one should bet against the run in baccarat. Nevertheless, people bet in baccarat on the premise that the random events of drawing cards from a dealing shoe are somehow related to each other and will tend to create a string of runs.

  Risk, Exposure, and Probability

  The definition of risk is to expose to the chance or possibility of loss. Most people erroneously try to assign a numerical value to that chance, which simply confuses risk with probability. In the markets we are talking about unique, non-repeatable events so we can’t assign a frequency probability to their occurrence. In statistical terminology, such events are categorized under case probability, not class probability. This means the probability of market events is not open to any kind of numerical evaluation. All you can actually determine is the amount of your exposure as opposed to the probability that the market will, or will not, go to a certain price. Therefore, all you can do is manage your exposure and losses, not predict profits.

  Money Odds vs. Probability Odds

  Perhaps the most common fallacy to which market participants are susceptible is: Money Odds vs. Probability Odds. Many market participants express the probability of success in terms of a risk/reward ratio. For example, if I bought my famous takeover stock (which you will hear about in the next chapter) at $26 and placed a sell stop below the market at $23 with an upside objective of $36, my risk/reward ratio would be 3:10. Risk $3 to make $10. It is clear that I don’t understand probability. Couching my rationalizations in arithmetic terms does not automatically lend credibility to my position. The 3:10 ratio has nothing to do with the probability that the stock can or will get to $36. All the ratio does is compare the dollar amount of what I think I might lose to the dollar amount of what I think I might make. But it doesn’t say anything about the probability of either event occurring.

  Some Dollars Are Bigger Than Others

  Why did the dollars seem so big at the blackjack table? Because I was accustomed to dealing with price ticks in the market, not tokens with $25 or $100 printed on them. Ordinarily, the use of chips is a psychological gimmick to minimize the importance of money, and it works on most people. But I was used to handling hundreds of thousands of dollars of market transactions on the simple shout of my voice, which made it seem like money wasn’t actually involved. When I had to physically take two $25 chips and throw them on the blackjack table, it felt like real money.

  Being down $2,000 in ticks in the market doesn’t feel the same as being down $2,000 at that baccarat table. It hurt a lot in baccarat. Also, the $7,000 in baccarat winnings felt like a lot more money than $7,000 in the market. Why? In the pit I was supposed to be working to try to make that kind of money, but in baccarat it was like free money. That means spending the $7,000 won in the casino was a lot easier than spending money made in the markets. The night after we’d won all the money, Conrad, Broderick and I met a broker-friend of Conrad’s who was trying to get some of Conrad’s business. We wanted to go to the best restaurant in town. The broker swore we wouldn’t be able to get a table on such short notice and without a reservation. Well, we went to the restaurant anyway and I slipped the maitre d’ hundred dollar bills until he got us a table. It cost $600 but it was worth it to upstage the other broker. The money wasn’t important because we hadn’t worked for it. Those $100 bills were not nearly as big as the ones I had to work for in the pit.

  Profit Motive or Prophet Motive?

  There are two kinds of reward in the world: recognition and money. Are you in the market for recognition, congratulating yourself for calling every market move ahead of time and explaining the move after the fact, or are you in the market to make money? Are you more interested in the psychological reward of gold stars than the financial reward of gold coins? Are you trying to be right or to make money? Are you motivated by the prophet motive or the profit motive? To answer, you have to figure out which type of participant you are: bettor, gambler, investor, trader or speculator. You do this by examining the characteristics and behaviors you are exhibiting, not the activity, i.e., opining on the outcome of a political race, playing at a blackjack table, buying stocks, trading in the pit or buying I selling commodity futures from your Blue Bird Wanderlodge. The characteristics displayed determine the activity.

  Embarking upon games or entering the markets can be either an end or a means.29 It is an end for people who yearn for the stimulation and excitement which the vicissitudes of a game or the market provide them (e.g., gamblers), or those whose vanity is flattered by the display of their superiority in playing a game which requires cunning and skill (e.g., bettors). It is a means for professionals who want to make money (e.g., speculators, investors and traders).

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  One morning Joe Siegel and I were on the trading floor when one of my accounts called in from vacation.

  “What’s lumber doing today?”

  “It’s limit up.”

  “Why?”

  “The cash market is a lot stronger because storms in the Northwest are making it hard to get the lumber out from the mills.”

  “Where’s cash?”

  I told him prices for two-by-fours of White Fir, Western SPF and Green Douglas Fir, and continued reading the news wire. The “green” in Green Douglas Fir refers to the fact that it has been newly cut (it has not been dried). Just like someone who is new at something is referred to as green. Siegel looked over at me and said, “I never have understood why they get such a premium price for lumber that they paint green.”

  I couldn’t believe it. Here was Joe Siegel easily trading more lumber futures than anyone else on the floor, and he didn’t even know the difference between green and kiln dried lumber in the cash market. I wasn’t sure if he was kidding me or not. But looking back, I can only now see how it was possible for him to be such a successful trader without knowing that green lumber isn’t actually painted green. He was a trader, and he relied on short-term information like order flow and price action to make his decisions because his time frame was short-term. He didn’t let longer-term information more suited for investor types interfere with his trading. He knew the difference between traders and investors.

  8

  The Psychological Crowd

  “Man is extremely uncomfortable with uncertainty. To deal with his discomfort, man tends to create a false sense of security by substituting certainty for uncertainty. It becomes the herd instinct.”

  Bennett W. Goodspeed, The Tao Jones Averages

  One day in the summer of 1980, my partner Larry Broderick called me and said, “Hey Jim, my stockbroker just called me with a tip, and we gotta buy this stock.” Some company I can’t even remember the name of (I told you I made investments that I couldn’t remember) was a rumored takeover candidate. The broker said the “talk” was: if the takeover happens, it would probably be within sixty days and probably at $60 a share. At the time, the stock was at trading $25.

  So we checked to see if there were options on the stock. The 35 strike calls were trading way out of the money and with very little time premium. They were trading for 1/16 or ⅛. You could buy thousands of these things for very little money. Well, we liked buying thousands of anything, so we bought thousands of these call options. And I did exactly the same thing I would do later in the bean oil; almost everybody I knew had to have a couple of hundred of these options. Among all of our clients and acquaintances, we had tens of thousands of the 35 strike calls. I’d call my futures customers and say, “Look, I can’
t sell you this stuff but trust me, go call your stockbroker and buy some.” Now, who’s not going to believe me when I tell them to buy something I can’t even sell them, or make any money on? They believe! So, they bought the options. They all bought them. Everybody we knew bought them. Then the stock started to move, $25 . . . $26 . . . $27 . . . $28 . . . $29 . . . , and volume started picking up too. Pretty soon the options started moving even though they were still trading for less than $1. When an option goes from 1/16 to ¾, if you own 2,000 or 3,000 of them, you’re talking some serious money. I had control of 300,000 shares at $35. At the $60 takeover price that’s a $7,500,000 profit.

  Naturally, once something starts to work it’s real easy to get people to believe you. “Okay, I told you to buy these options two weeks ago when they were at 1/16 . Now they are at ¾ . Do you want to get in or do you want to stay stupid?” If I knew you, you had to have at least of couple of hundred of these things just for health insurance. What do I mean by health insurance? If I tell you that something which costs 1/16 today might be worth $25 inside of one month, you have to buy some of it. It’s health insurance because once I tell you a story like that and you don’t buy some and it happens, you’re going to kill yourself. That’s health insurance.

  In three weeks the stock was up to $37 or $38 and our options were in the money. We had paid 1/16 for them and now they were worth $3 or $4. Then one Friday afternoon after the futures markets had closed, we were all up in my office and I was holding court. The phone rang. It was my partner, Larry. “Holy shit! They just stopped trading in our stock, Jim! News to follow!”