Modern Investing

by David Schneider

  In this chapter, we'll see how most speculators use the same strategies and thinking in their investing as gamblers, and how real investors play a different game altogether.

  The Money Game and Wall Street

  Before we go deeper, let’s define what I mean by “The Money Game” and “Wall Street,” two terms that have captivated generations of players and seekers of fortune.

  The money game is the entire process of investing within the current system. I don't call it simply “investing,” because, as we'll see, it's more akin to the structural model of casinos where huge institutions facilitate people’s entry into the process in order to profit off them. Hence, success and failure become a competition between the investor and institutions—the money game.

  According to the late George J. W. Goodman, author of The Money Game (1976); it “is about image and reality and identity and anxiety and money…The money which can preoccupy so much of our consciousness is an abstraction and a symbol. The game we create with it is an irrational one, and we play it better when we realize that, even as we try to bring rationality to it.”11

  The most powerful and captivating games for money can be found on Wall Street. Whether we talk about stocks, mutual funds or exotic financial products, we truly have games on our hands with no equal. These games promise us an endless stream of entertainment and, more importantly, a possibility of riches that has only existed in our wildest imaginations.

  Wall Street, however, has made this a reality for a few. Today, it’s much more than just a single street in New York. It is, in fact, the collective name “for the financial and investment community, which includes all exchanges and large banks, brokerages, securities and underwriting firms, and big businesses.”12 Foremost, it symbolizes the brokerage, investment banking, and money management firms that sponsor, control, and dominate the money game.

  The Gambler

  Theoretically, investing and gambling are very different ideas. That does not mean that they don’t share some common traits, and it is precisely the failure of people to understand how investing should be different than gambling that creates so many problems. To explain the crucial difference between the two, we first need to understand precisely what gambling is.

  Gambling, according to the standard definition, “is the wagering of money or something of value (often referred to as "the stakes") on an event with an uncertain outcome with the primary intent of winning additional money and/or material goods.”13 Peter L. Bernstein, the author of Against the Gods, has called it “the very essence of risk taking.”14

  According to this definition, any decision involving making money that involves pure uncertainty are gambles because they incur the possibility of financial loss. On the other hand, gambling also promises untold riches. It is precisely this fascination for creating riches out of nothingness that has captivated and ruined generations of gamblers.

  William Poundstone, in his book Fortune’s Formula, had a great example: “In 2004, a London man named Ashley Revell sold all his possessions, including his clothes, and staked his entire net worth of $135,300 on a roulette wheel at the Plaza Hotel in Las Vegas. Revell wore a rented tuxedo and bet on red. He won. He decided against going for double or nothing.” It was a good decision. In American Roulette, the chance of him winning again on either color is 46.37%. You might ask yourself why only 46.37, and not fifty. Well, you might have noticed the green zeros on the wheel. This is called a house edge: the advantage the casino holds over the player. In American roulette, the house edge is about 5.60%.

  According to Poundstone, “Revell was playing an unfavorable game. His actions would hardly have been less reckless had he had an edge. The bet-it-all policy works only until you lose.” And that’s the thing with gambling—it’s all great until it isn’t, and when it isn’t, it is often catastrophically bad.

  You see, all gamblers share one aspect of taking chances, known as the gambler’s ruin. The original meaning is that “a gambler who raises his bet to a fixed fraction of bankroll when he wins, but does not reduce it when he loses, will eventually go broke, even if he has a positive expected value on each bet.”15 Or, as Poundstone observed, “You can be the world’s greatest poker player, backgammon player, or handicapper, but if you can’t manage your bankroll, you’ll end up broke. The sad fact is, almost everyone who gambles goes broke in the long run.” In the first example above, we can intuitively understand this conundrum. If Ashley had continued to gamble in the same fashion, he would have eventually lost it all. Surprisingly or unsurprisingly, this doesn't deter many from trying to find riches in gambling. In taking chances on uncertain outcomes whatever the mathematical probability of win or loss are, you are bound to lose a few bets. Those who have very bad money management, i.e. bet more than they can afford to lose, will go broke. It is a mathematical certainty. As a dedicated investor, this might not directly apply to you, but it has indirect consequences for all of us when a few gamblers experience such a scenario. Keep that in mind for the rest of the book, as it will be mentioned later on.

  The Speculator

  According to Peter Bernstein, “Games of chance must be distinguished from games in which skill makes a difference.”16 Playing the lottery doesn’t require any skills whatsoever. However, games such as poker or betting on horses can be influenced by the individual player’s skill in determining possible outcomes. These are the games that depend on skill as well as luck. If you ever sat with a professional poker player to play a few rounds of poker, you would instantly understand the difference. Both of you might depend on luck to get good hands, but the professional poker would still beat you comfortably, due to his superior skills in anticipating and calculating the odds much faster and more accurately. A more mundane reason could be that your tells are just like an open book for anyone to exploit.

  The professional gambler’s close relative is the speculator. According to Benjamin Graham, a speculator’s main aim is to make money quickly; “money in a hurry,” as he puts it. Capital protection and the underlying yields, such as dividends or rental income, play only a limited role in decision-making. Speculators and professional gamblers alike make many decisions every day that directly influence their bankroll. A speculator’s only way to win is to have an edge, by either being more accurate and quicker at calculating odds of each new game and allocating their money accordingly without going broke, or knowing something that the other players don’t. If either applies, then they have an edge and the skills required to be professionals.

  Graham himself was an avid speculator in his early days. He lost it all in one giant leveraged bet after the crash of 1929, and because he had borrowed a substantial amount of money, he was forced out of the markets for a longer period than he had wished.

  Graham had an interesting take on speculators. He argued that those who are obsessed with minute price changes are only interested in changes they believe they can anticipate accurately with the help of their betting system. For example, if a central bank announces a new interest-rate policy on a set date, speculators anticipate price movement in currency markets and interest rate products sensitive to any such changes. They, then, place their bets before or immediately after such an event. Listed companies report their quarterly earnings and speculators aim to anticipate favorable price movements. The difference between the two actions could be a matter of a few seconds.

  Hence, speculating involves a great deal of anticipating how many of the other players react to market news. On top of that, speculators almost always work with borrowed money to magnify their profits. These days, they trade in and out so many times that each small price change is meaningless unless it is magnified with borrowed money.

  Today, the financial markets are dominated by speculators: professional and amateur. Ever-increasing trading volumes, daily volatility, and continuous increase in financial leverage has made it obvious that there are fortunes to be made, and they think they know how.

  Speculating vs. Gambling />
  Let's take a look at the similarities and structural differences between gambling and speculating. How do they relate to each other and how can we distinguish between them?

  If you compared betting on horse races or stock price movements, you could find many similarities. Betting on horses is as exciting, random, and unpredictable as betting on price movements. Like a giant board depicting the odds of various horses, the stock tickers also display information about falling and rising trends. But the information on both boards is useless, as they only depict the immediate past. At the tracks, you need to place your bets through bookies or at the race tracks. If you bet on price movements, you need to go through your online broker or private banker. In both cases, there are no 100% sure things, unless you rig the games, and even that has its risks. Like at the tracks, you are easily affected by how the majority of other bettors place their bets. In each case, seeing yourself alone on the other side of a bet or trade makes even the most experienced punter nervous.

  There are, of course, many differences between a racetrack and a stock exchange. A horse must win, or at least place in a particular way, so there are only limited outcomes. For financial products and securities, such as stocks or funds, there is a whole sequence of possible outcomes. They can rise, fall, or have special events, such as dividend payments or mergers and hostile takeovers. Beyond that, each race has a predetermined ending, just like each bet at the roulette table or hand in a poker game. There is a reason, why all-in games in no-limit poker are so fascinating. This is in stark contrast to purchasing general financial products. A speculation could go on indefinitely. As long as the stock, real estate or fund exists, a player could decide to stay in the game, even if a short-term price speculation didn’t pay off as expected.

  But there is a more subtle difference between ordinary gamblers and speculators, and it lies in their attitudes on how they approach each bet. In a game where the outcome is determined by both chance and skill, the more skillful player wins in the long-term. Hence, one could argue that professional gamblers and speculators are just more skillful gamblers. As a matter of fact, no self-respecting speculator considers him or herself as an ordinary gambler; they tend to assume, on some level, that they are superior. Speculators feel that they are more capable of making rational, calculated bets. Their confidence is a result of the tools and technology they use. These days, they use powerful hardware, elaborate databases and complex software that can spit out hundreds of possible gambling scenarios in a millisecond.

  Speculators and Risk

  Speculators might be more skillful gamblers, but they still had to deal with an uncertain future when it came to anticipating price movements. They needed to calculate the odds of each bet with mathematical precision so that they could make more rational, and hence superior decisions than a common gambler. They needed to understand risk in a different way than traditional investors have been doing for centuries—more sophisticated and with more mathematical precision.

  Academia was up to the task, and they based their theories on a relatively young mathematical concept derived from gambling—probability theory and the laws of probability. Three Frenchmen, (Chevalier de Méré, Blaise Pascal and Pierre de Fermat), are responsible for revolutionizing gambling and laying the groundwork for modern risk management. Chevalier de Méré, a notorious gambler, made history by challenging Blaise Pascal, a gifted mathematician, to explain his unexpected losses from gambling. In trying to solve this riddle Pascal turned to Pierre de Fermat, an equally gifted mathematician. In lengthy correspondences, they wrote each other about games of chance. Together they laid out the mathematical foundations for the theory of probability in 1654.

  Over the following centuries, many more famous mathematicians contributed to the subject of probability. Jacob Bernoulli and Abraham de Moivre solidified the theory of probability within the academic field of mathematics, by showing how to calculate a wide range of complex probabilities. In 1713, Bernoulli proved a version of the fundamental law of large numbers, which states that "in a large number of trials, the average of the outcomes is likely to be very close to the expected value." For example, in 1,000 throws of a fair coin, it is likely that there are close to 500 heads. The larger the number of throws, the closer to half-and-half the proportion is likely to be.17 Not much later, Thomas Bayes, a former English minister, offered the Bayes’ theorem, which is another interpretation of the concept of probability. It demonstrates how to make better-informed decisions by mathematically blending new information with old information.

  But, there was a challenge to convert the theories derived from gambling based on the simple acts of tossing a die or spinning the roulette wheel to the complex behavior of financial markets and its erratic price movement with a much wider range of outcomes. It needed to be based on numbers and lots of historical data to get any conclusive results about future price movements.

  In 1917, Ladislaus Bortkiewicz achieved a breakthrough and added a missing piece to make modern risk management possible. Based on Bernoulli’s work, he developed the field of stochastic: “A stochastic event or system is one that is unpredictable because of a random variable.”18 This is where the world of modern finance and academia got together. It finally provided a model for the study of random fluctuations in stock markets, leading to the use of sophisticated probability models in mathematical finance with normal distributions and standard deviations. It shaped the field of risk management as we know it, and it is used by insurance institutions and financial organizations around the world ever since.

  For Wall Street, the concept of quantifying risk for financial markets was born. Central to much of this is the idea of the “standard deviation.” Standard deviation means the recorded volatility of a price instrument. A high standard deviation simply means this investment is very risky– it changes the price a lot. A stock that fluctuates 3% up and down on a daily basis is characterized as having a higher standard deviation than a stock that fluctuates 1% per day. In reverse, it also means that if you construct a portfolio where different holdings trade in exactly opposite directions based on historical data, the mathematical risk is assumed to be zero, as each financial instrument cancels its prices volatility. For example, if the price of investment A goes up, the price of investment B simultaneously goes down and for the same amount. This is what historical data has shown in the past. But here is the true magic—the theoretical volatility would be zero as the total investment of both would always be flat. Investors feel psychologically assured that everything is fine, all the while they collect income, such as dividends or interest payments. Now let’s add some financial leverages, to the tune of 10:1 ratio and investors can make some serious money without worrying too much about risk. The portfolio risk is still zero, and they have just multiplied their income by ten. With a few simple tricks, we have created the finest financial alchemy.

  This last part is crucial because it revolutionized professional investment management and finance. Speculators were able to create all sorts of new formulas, calculate all sorts of sophisticated investment portfolios, and all based on standard deviation and assumed a small risk. They finally made speculating “scientific,” socially acceptable and imbued with a touch of real sophistication. Luckily, all the data necessary for these complex calculations was there and readily available. At the same time, the processing power to work with this data continuously increased from the early 1950s to cope with the new amount of data.

  The numbers were magical, and it created a world where you could invest with an engineering precision, in a portfolio that had an overall calculated risk of zero. And you didn’t have to be a financial genius to understand that. It is a sort of sleight-of-hand to convince people that there is no risk in handing over their money. Certainly, it is a grossly simplified explanation of how modern finance works today, but it explains the thought process of risk management departments around the world.

  Here is where it went wrong. Right from the start, academic
s, scientists and financial punters lost all sense for the underlying assets upon which they based their theoretical construct. An overemphasis on market prices, as convenient data points for quantifying risk, have become the main focus ever since. The underlying asset of a stock price might as well be a turd wrapped in the finest silk and promoted on stock exchanges as having future growth potential—it would not matter, as long as speculators have their price data to base their risk calculations on.

  The Investor

  So far, we can say that each and every decision that involves placing money on an uncertain future to gain financial rewards is very much a gamble. That counts for investors as well. When formulating views on the future and placing money on these views, there is always a possibility of being wrong. It is how all parties approach these risks and aim to improve the odds that differentiate them, whether they are gamblers, speculators, or investors.

  However, like in any game that is determined not only by the factor of chance but also the skills of their players, all parties aimed to improve their odds of winning by improving and honing their technical skills. All found their own elaborate ways to do so.

  Gamblers swear by their betting system or superstition, while speculators calculate complex theories and models using tools like chart analysis and historical data analysis. Investors also rely on a vast amount of historical financial data, such as financial statements or industry reports. All this effort has one purpose: improving their odds of experiencing a positive outcome. Unsurprisingly, everyone has great faith and trust in their respective systems. However, there is an obvious difference.

  Where gamblers or speculators care only about the immediate bet and its dualistic outcome of winning or losing, investors are concerned about the underlying asset. Rather than anticipating absolute price changes in a binary manner, investors make use of the fact that betting on financial assets offer a wider range of possible outcomes. Prices could go sidewards, but the asset itself throws off monthly rental income, semi-annual dividends or interests. Prices could initially fall for an extended period, but a long-term oriented investor wouldn’t mind waiting even years for an opportune moment to sell at better prices or never sell at all. In the meantime, they collect income. The classic example is real estate. An increase in real estate market prices is secondary for a long-term real estate investor. They are more concerned about monthly rental income and the stability thereof. In many cases, real estate investors actually prefer lower and falling prices, as to give them the chance to purchase more properties for their growing portfolios. They are only interested in rising real estate prices when they intend to sell; like any financially incentivized gambler would be.