Ihad a big idea, but I was broke and needed income. Luckily, an opportunity arose to help a client in California with strategies to mitigate tax liabilities. My percentage on this was $100,000, and it was enough to cover my family and business expenses for a long while (I’d always been an underspender). I had no idea exactly how long that would be. I was busy with non-income-producing activities—cleaning up the trouble made by my partner and working on a new venture.

My goal was to create a scientific trading system that would remove human emotion from buying and selling decisions and rely instead on a purely statistical approach built on preset rules. To pull it off, I needed to find a new partner with the formal training to build a model and rigorously test all of my ideas. A friend of mine introduced me to his brother-in-law, Peter Matthews, who was then in his late twenties, finishing a PhD in statistics at American University. Peter was doing consulting work for the federal government but was interested in trading futures. He came out to my office in Newark for a meeting, and I told him that I just couldn’t trust the human element anymore and was looking for someone to create an automated system that would make money. Then I had to convince him that he should join this venture even though I had no funds to pay him. I said, “If it works, you will share in the profits and be a partner.” He was extremely bright and at an age where he could take this kind of risk. He said yes.

Building an automated trading system was a major undertaking circa 1980. We knew of no one else doing this at the time. (In fact, I now know that Ed Seykota and others had started in the seventies.) There were no clear books or informative guides to follow. We also needed access to mainframe computers that could process huge volumes of data.

With these hurdles in place Peter began designing our trading trend following approach. He wrote algorithms to monitor moving price averages across many commodities, identify rising trends, computerize the odds that those trends would continue, filtering out trades that had too much risk, and trigger automated buying and selling actions when our particular conditions were met. In this era it was extremely tedious work (you can do it on your phone now). Peter was able to use the computers at American University at night, but even so it was slow going. His painstaking process also included checking his calculations by hand. There were moments when I did wonder if this could all work!

From the start, I wanted our system to be agnostic to whatever market we were trading. This was an unusual philosophy at the time, but ever since I’d moved from pork bellies to corn to coffee, I’d come to believe that human behaviors more or less are the same regardless of the particular market. Plus, by trading in so many types of markets we would get extreme diversification, which would help control risk. We also built in hedging rules, with system rules that went both long and short to protect against outsized losses.

After a year of painstaking design, Peter finished his work and brought in Michael Delman, an excellent computer programmer in his early twenties. (He began with us as a consultant but later became a junior partner.) Michael knew nothing of finance, but it didn’t matter; his job was to backtest Peter’s model to see if it would work on a larger scale. This involved buying and then inputting huge sets of historical trading data so that we could then run our model and see how it would have performed over past historical periods—not just one month or year, but across thousands of different markets and time periods. Now, obviously, just because you get something right in the past doesn’t mean you will get it right in the future—historical testing has its flaws. Just the same, these simulations were highly valuable because using real market conditions—even in the past—gave us far better information than hypothetical scenarios of us sitting around the office guessing. The result: We scientifically proved it. Our trading system worked.

Over time, we continued to evolve and refine it. For example, we also tested various holding periods as a measure of our system performance. It seemed to us that evaluating performance on a calendar-year basis was an arbitrary measure. So Peter and Michael quantified the odds of profitable performance for time periods of different lengths. In our simulations, we found that 90 percent of all 6-month holding periods, 97 percent of 12-month periods, and 100 percent of 18-month periods were profitable.

All of these critical behind-the-scenes steps led to the founding of our company Mint Investment Management Company, which began trading in April 1981.

LONDON

Mint was born out of crisis, yes, but it was also born out of a fortuitous trip to London in 1981 to find new brokers. Why London? It was expensive to operate in the United States. At that time, the tax rate was the highest in the world. Lawyers, investment bankers, and other middlemen took big commissions. And in 1981, a new law eliminated the tax structure I’d been using for many years. But also, other countries were more amenable to futures trading than the States. London was the new gateway to international financial markets right at the time when global trading was taking off. I went there to knock on doors.

At one appointment, I tried to set up a referral arrangement with a broker. I asked him if he would protect my commission if I sent clients to him. He wasted no time in saying no. It was a very short meeting. On my way out of his office, I stopped in the waiting room and picked up a magazine I’d been reading earlier and discretely ripped out an ad I’d seen for another commodities firm. I put it in my pocket. A little later, I called the number and spoke with David Anderson, who agreed to meet me.

It’s interesting to look back at this moment. If I had been the kind of person who was unaccustomed to failure, perhaps I would have brooded my way out of the office after that rejection. But being who I was, I immediately began thinking about my next move—hence, ripping out that ad. In many ways, this gesture was a small act of trend following. When one trend isn’t working, don’t hang on, just get out and look for the next opportunity. Or going back to my romance analogy: If you have a bad date, do you stop dating and become a monk?

The phone call to David Anderson changed my life. He was a leader in London’s futures trading world. He was also associated with ED&F Man, the elite global commodities merchant and trading firm. Anderson and Man had recently launched a joint venture: Anderson Man Limited. It was Man’s first step into the commodities futures market, and Anderson had helped open that door. He also opened the door for my partners and me.

We created an “advisor” relationship with Man and put our trading system to work in dozens of markets around the world. We carried out our business in the same US offices, using our hands-off statistical system that had been backtested and proven. When the system kicked out its recommendations, we sent the trades to Man, who executed them in London.

My partners and I had the right combination of complementary abilities. I was the idea person who also went out and did deals. Michael once said I had 20 ideas a week. Peter was the statistical mind who managed the trading program and performed analytics. And Michael executed all of the computer work and made sure the trains ran on time. In our first two years, we made more than 20 percent annually. People started to take notice. However, we still didn’t have the level of business that I wanted and needed. It was still hard to sell our style of funds in the first place. For our first few years at Mint, most people wouldn’t even talk to me. Plus, when I would explain that we traded coffee and gold the same way, they would get off the phone. Sometimes they would hang up. Today, systematic trading is more accepted, but back then it was unknown, untrusted, and unwanted by the masses. Again, being a dyslexic kid accustomed to failure, what did I care? I just picked myself up and went on to my next call and my next potential opportunity.

ED&F Man, however, had vast capital, reputation, and global connections. In 1983, I met with the chairman and told him I wanted Man to buy a stake in Mint. He was reluctant. Man was a very particular upper-class elite culture. The company had been founded in the eighteenth century as a sugar trader, and for some 200 years it did business with the British Navy. It was the world’s oldest commodity trading house, with agents all around the world who brokered deals from Europe to the Congo. Man’s clients were primarily giant manufacturers and governments. Our small company, Mint, on the other hand, was a commodity trading advisor (CTA). That meant we advised individual investors to buy, sell, and hedge in markets with techniques that some still saw as the Wild West—and from his perspective, perhaps a bit unseemly. He and his colleagues also had trouble believing that a computerized method could possibly be better than human judgment. Still, Man wanted to get in the futures markets, and so I made him an offer that was hard to refuse: a 50 percent stake in Mint in exchange for paying the salaries of my partners and me for five years, free access to their mainframe computers, and a $5 million line of credit to get us started.

It was a great deal for us because Man had the banking connections, money, and computers that I couldn’t afford. It was a good deal for him because Man got a chance to make a lot of money in a fast-growing field. Commodities futures were taking off, and not many players had a legitimate strategy to trade them and manage risk.

He said yes. Now we could take off.

• • •

You always want to know where you are when playing the game. In many ways, England was the best for me. As I began flying over there, I assumed the role of a cultural anthropologist. We all speak English, I said to myself. Now I’ve just got to figure out what they mean. I learned early on that sometimes when my British colleagues said one thing, they meant the exact opposite. (Being married to a Brit wasn’t much preparation. She was a very sincere person and wasn’t like my colleagues, because she wasn’t of their class.)

I learned on the ground and came to like the people at Man. They were polite and some of the smartest associates I ever worked with. In many ways, it was a place made for me. Anti-Semitism was widespread in England at the time, but far less present at Man, and once I proved myself, it faded away. I discovered that my colleagues in England really wanted to make money

Of course, as the Brooklyn guy, I was a bit more aggressive than they were used to. I remember one time being at a meeting with a big long table, and there were phones all about because it was a brokerage firm. I was meeting with the lawyer who represented one of the country’s major exchanges, perhaps it was the cocoa exchange. He was very British, and I was trying to convince him to change a rule. I made a strong case and then said, “It will benefit everyone.”

“Well, I’ll pen a letter to so and so . . .”

Now I had just flown in on the Concorde jet. I reached over and picked up the phone and held it out.

“Call him,” I said. An Englishman never would have done that. But a kid from Brooklyn could be direct like this. To be sure, there were also times when I held back to make my more reserved colleagues more comfortable. This is why I say you need to know where you are playing the game. You need to understand the rules and perspectives of the other players in their culture. If you adapt yourself to the place, you improve your odds. Though I liked the people, I never liked the politics. If you are this way also, then pay especially close attention to the rules of engagement in the place where you are working. Using those rules to your advantage is your responsibility.

Man had been a cash commodity firm, which is a business built heavily on credit, and so it had excellent relationships with bankers and hired many ex-bankers into its ranks. This opened doors for Mint—big time. Through Man, I could do business in the Middle East, Europe, Australia, and Japan—basically all over the world. Even so, convincing people about our trading still took some persuasion. For example, I got a meeting with a venerable old financial firm in Australia where no one had ever done a fund like ours. I explained how our system worked and asked them to hold bonds for us and guarantee them. Usually once you make the sale, the other firm gets a commission and it’s over; they are unemployed. But I told my counterpart that if they would work with us, they’d get money for guaranteeing, and instead of selling once for one commission, they’d be getting money all the time. This got his attention.

By 1988, we registered an average annual compounded return of over 30 percent since our 1981 founding. During that time our best year was 60 percent growth (1987, the year of a stock market crash), and our worst year was plus 13 percent. We were by then receiving a lot of attention in the business media, including a 1986 “best of” award from Businessweek. Jack Schwager then profiled me in his 1989 book, Market Wizards.

Soon, I was on a rhythm going on the Concorde, making the three-and-a-half-hour flight from New York to London regularly. I flew over on Sunday night and worked there and traveled through Europe during the week. Then on Friday afternoon I got back on the Concorde to fly home and see my wife and kids. I flew so much that one year they gave me a leather pilot’s jacket. By 1990, less than 10 years after we started, we were the biggest hedge fund in the world with a record-breaking $1 billion under management.

ASYMMETRICAL LEVERAGE AND THE GUARANTEED FUND: OUR WINNING FORMULA

One of the biggest engines behind our success was a risk management concept I called asymmetrical leverage (AL). AL is how I got rich and how you can too. Essentially it means that what you risk and what you can gain are of dramatically different weights. Or as I like to think of it, you bet pennies, but you can potentially win dollars. Asymmetrical leverage can be especially important for people or organizations in a weaker position (think David and Goliath).

Our big asymmetrical idea came out of a London cocktail party. Lord Stanley Fink (later to become CEO of the Man Group), David Anderson, and other directors of Man excelled at social networking and getting to know the right people (those with money to invest). I was out with them one night at an event Man sponsored and started chatting with a guy who, it turned out, was a high-net-worth investor.

“Your returns are impressive,” he told me. “But my current manager is getting close to that and your fees are higher. You are charging 2 percent of the management fee and 20 percent of the profits. They are taking no management fee—just 20 percent of profits. Why should I invest with you?”

I went home and thought about what he said. I could see his point. I wondered, “How can I do this? How can I lure more investors to Mint?” This was 1985, and by now, I had two kids and a house. Man was getting 50 percent of all profits, and I was also sharing with my other partners. I was motivated to do better.

I spoke with my partners about the idea of a “no lose” fund. What if we could take 60 percent of an investor’s money and put it in zero-coupon, five-year US Treasury bonds where it would not only be perfectly safe but would also double in about five years’ time? (Remember, this was the 1980s when interest rates were very high.)

Then we’d take the other 40 percent of the investor’s money and invest it in our trading program. Worst-case scenario, we lose everything in systems, but we could still return the entire principal within five years (and cover our management fees). In other words, we could say to an investor: Give us a million now and you are guaranteed that you will, at minimum, get a million back after five years. The only thing you’d lose was the time value of the money. What you could win, however, was a major capital gain because our trading system was delivering stellar results year after year. We called it the “Mint Guaranteed Ltd. Fund.” When we first announced the fund, it was highly publicized in places such as the New York Times, for example. Some coverage suggested it was too good to be true, including one reporter at a major British paper who ridiculed the new fund—on the same page, the paper ran a separate article about Ponzi schemes. His implication about our fund was clear. (The executives at Man considered suing the paper for libel but decided instead to invite the editor in for lunch and clear the air.) Nonetheless, the guaranteed fund took off, and we made $75 million in our first year.

I look for asymmetrical opportunities all the time and suggest you do the same for all aspects of your life. When I sold ED&F Man on our merger, I was offering them asymmetrical leverage—though I didn’t call it that at the time. A few years later, I wrote a white paper for my partners at the Man Group explaining the philosophical and financial phenomenon of what we’d done. No one has read this analysis outside of a few partners until you.

In the paper I summed up the principles underlying the asymmetrical leverage of Mint’s merger with the Man Group. Here is a brief excerpt:

AL [asymmetrical leverage] is unique in that it affords one the benefits of conventional leverage minus the proportional risk. . . .

The Man acquisition is an example of good AL for both sides. Man was worth over $100 million at the time and its risk was only $750,000, a small percentage of Man’s net worth. They had the opportunity to buy 50 percent of Mint at a less than 5 percent chance of losing their $750,000, which set their real risk at $40,000, with a large body of statistical evidence showing them that they could not lose.

From the Hite, Delman, and Matthews (HMD) side we received the best AL factors possible: time and money. We got five years and the use of several million dollars for our own account plus an absolute income floor.

The structural factors that supported the initial partnership were:

a.   Predetermined probabilities in trading risk; and

b.   The fact that futures margins paid T-bill rates and Man was able to borrow under prime, making financing cheap.

These are the same factors that make our guarantee deals work. They allowed us to risk $250,000 out of a cash flow of two million at the time we launched the first guaranteed fund, which will earn us over 50 million by the end of this year. This will give us a return of 40 times our original investment of $250,000, which was 12.5 percent of our then cash flow.

I wrote the paper to get my partners fired up about a proposal for a new strategy using asymmetrical leverage. I used a number of examples such as Mint’s arrangement with a Middle Eastern financial institution. We built a $15 million Islamic portfolio for their investors, earning 23 percent of the profit per month while risking none of Mint’s money.

In all I’ve learned then and since, three ingredients make up the secret sauce of asymmetrical leverage—ingredients that led the Mint Fund to become the largest commodity trading advisor in the world. Anyone can understand the ingredients and apply them to different business, investing, policy, and life situations.

The First Ingredient Is Time

Often in life (but not always) the faster you move, the better. But with time to identify the best opportunities, you can improve your odds. Now I have talked about this in a previous chapter, but let’s take a closer look at how powerful time is as an element of asymmetrical leverage. With the guaranteed fund, we made investors wait five years. Time is an especially powerful form of leverage in growing money. With time, we could take advantage of bond maturity and a good long stretch of trading opportunity. Though five years was a relatively long time, investors were willing to give it to us because of what we offered in exchange—a dream combination of no-risk profit.

The Second Is Knowledge

If you don’t know the odds, you can’t make an intelligent bet. If you’ve read the book this far, you’re conversant with the importance of knowing the odds for any decision. But there’s a role for knowing the game, as well. In Mint, I brought knowledge from a decade’s experience in trading. I also brought in bright partners who contributed essential knowledge of statistics and computers that other traders weren’t yet using. Without them, there would have been no Mint. By now I definitely had learned to trust.

One of the greatest (and most famous) examples of knowledge-powered asymmetrical leverage is found in the success story of the Oakland A’s under the management of Billy Beane—as told in Michael Lewis’s book Moneyball and the movie starring Brad Pitt. When Beane became general manager of the A’s in late 1997, it was one of the worst teams in baseball with one of the lowest payrolls. Up until then, most baseball scouts used subjective criteria for drafting their talent. They looked for players who possessed a combination of qualities, such as having “the face” (i.e., a handsome visage), a 99 mph “heater,” or a “can’t-miss swing.” Beane believed this was all bullcrap. He knew you could measure performance by numbers and revolutionized the game by pioneering a statistical approach to acquiring talent.

If you’ve read the book or seen the film, you know that one of the most important decisions Beane ever made was to hire an assistant general manager who had an economics degree from Harvard. Beane and Paul DePodesta introduced the analytical principles of sabermetrics to analyze player performance. Many players overlooked by other teams, and who could be signed for lower salaries, possessed skills that were not in vogue—getting on base, hitting for power whether or not the hitter struck out frequently. The A’s piled up incremental advantages of high on-base average and slugging for power to outperform many teams that paid top-tier free agents. Analytics showed that two players who make vastly different sums can generate equivalent production. That was Beane’s asymmetrical leverage.

By recruiting unconventional sources of knowledge, Beane says he was able to make “rational objective decisions in a business where everybody was making subjective decisions.” The Oakland A’s made the playoffs eight times between 1999 and 2014. Beane did this with a small payroll but outsized knowledge.

Today, every team in baseball, and even the National Basketball Association (NBA) too, has adopted an analytics approach. As a result, Beane’s asymmetrical leverage has waned because other teams began using similar strategies.

But his numbers revolution did not wane. Beane then exploited asymmetrical leverage in a different way and began questioning the game’s conventional use of a single pitcher to play seven or eight innings of a nine-inning game. Faced with a long history of devastating injuries to starting pitchers, a relatively thin national talent pool for starting pitcher prospects, and the huge amount of salary pitchers demand, teams were gradually embracing a new model of keeping individual pitch counts under 100 per game to protect the arms of starting pitchers. The best medical research pointed in this direction. Beane and a few other executives realized this was a long trend, a likely permanent shift in the game. Beane invested in the “back end” of his pitching staff with more and better relievers. Because the game’s history had long established a view of relief pitchers as having lesser status and value than starting pitchers and “aces,” their salaries were cheaper. Beane’s knowledge of analytics and more emotionally detached approach to the game gave him new asymmetrical leverage. He spent less on starters and invested more on top-quality relievers, who would control far more of the game than in the past. The A’s continue to be one of the best stories in baseball, thanks to a management approach that leveraged a unique type of knowledge and strategy that no one else was using.

The Third Ingredient Is Money (Not Your Own Money—Other People’s Money)

Money buys you time, buys you knowledge, and allows the long-terms odds to work in your favor. Money leverages the advantages of the first two ingredients. In the case of the guaranteed fund, we leveraged money that was not our own—money provided by the US Treasury in the form of interest paid on a five-year bond. As I mentioned earlier, using OPM (other people’s money) provides great leverage in building wealth. We built Mint using the start-up money provided by ED&F Man.

In 1994, Man became a public company. Man and Mint parted ways and the British era of my life ended—at least for a time. But after 20 years of managing other people’s money, I didn’t want to have to answer to political interests, and working in a public company would only bring more people to please.

I wanted to execute my own ideas without having to ask permission or sell my ideas before I could test them. After 20 years as an asset manager, I simply wanted to manage my own money, research my ideas, and advise a few friends and supporters. If you have had the same job for 20 years, even if it has been a great boon, you probably have yearned for a fresh new challenge and a few less meetings. When the Man Group went public, Stanley Fink, who was then a CEO, wanted me to help him run the businesses. But I preferred the research side, not the operational side, and said no. That decision probably cost me $100,000,000, give or take a zero or two.

One of the earliest recommendations of this book is to know who you are. I have realized that I am happiest when I am independent and free to come up with new creative ideas to make money. In 1994, it was time to shift the game back to stateside and focus on managing my own money in a family office. In the final score, my partners and employees and I all did extremely well.

In your own way, in your own time, I want you to leverage that kind of success in your own life. You might not make $100,000,000, but if you make enough good bets, the odds will be in your favor in the long run. I realize that for many of my readers, the prospect of having $100,000 of seed money to start seems unlikely. In the next chapter, I will share step-by-step advice on applying my methods—steps that any investor can take.