Principles: Life and Work

by Ray Dalio

I could see how the machine produced cattle, hog, and chicken prices that I could bet on.

As basic as those early models were, I loved building and refining them—and they were good enough to make me money.

I found it much more practical to measure demand as the amount spent (instead of as the quantity bought) and to look at who the buyers and sellers were and why they bought and sold.

Same pattern re: why it's better to measure customer acquisition and retention in revenue instead of number of accounts acquired or retained.

From that point on, whenever I looked at any market—commodities, stocks, bonds, currencies, whatever—I could see and understand imbalances that others who defined supply and demand in the traditional way (as units that equaled each other) missed.

Visualizing complex systems as machines, figuring out the cause-effect relationships within them, writing down the principles for dealing with them, and feeding them into a computer so the computer could “make decisions” for me all became standard practices.

you can never be sure of anything: There are always risks out there that can hurt you badly, even in the seemingly safest bets, so it’s always best to assume you’re missing something.

meaningful relationships are those I have with people I care deeply about and who care deeply about me.

It’s smarter to start with what you really want, which are your real goals, and then work back to what you need to attain them.

I showed Lane how to use a mix of corn and soymeal futures to lock in costs so they could quote a fixed price to McDonald’s.

Combining my clients’ deep understanding of the way the “machines” of their own businesses operated with my knowledge of the way markets functioned worked to our mutual advantage, while making the markets more efficient overall.

debt, inflation, and growth moved up and down together in steadily larger waves, with each bigger than the one before, especially after the dollar’s link to gold was broken in 1971.

😏

In other words, inflation fell while growth accelerated. The stock market began a big bull run, and over the next eighteen years the U.S. economy enjoyed the greatest noninflationary growth period in its history.

As money poured out of these borrower countries and into the U.S., it changed everything. It drove the dollar up, which produced deflationary pressures in the U.S., which allowed the Fed to ease interest rates without raising inflation.

if you can do all that and in addition you have the cool nerves of a gambler, the sixth sense of a clairvoyant and the courage of a lion, you have a ghost of a chance.”

Second, I again saw the value of studying history. What had happened, after all, was “another one of those.”

finding other independent thinkers who are on the same mission as me and who see things differently from me. By engaging them in thoughtful disagreement, I’d be able to understand their reasoning and have them stress-test mine. That way, we can all raise our probability of being right.

I just want to be right—I don’t care if the right answer comes from me. So I learned to be radically open-minded to allow others to point out what I might be missing.

1. Seek out the smartest people who disagreed with me so I could try to understand their reasoning. 2. Know when not to have an opinion. 3. Develop, test, and systemize timeless and universal principles. 4. Balance risks in ways that keep the big upside while reducing the downside.

Doing these things significantly improved my returns relative to my risks, and the same principles apply in other aspects of life.

but a meritocracy that encourages thoughtful disagreements and explores and weighs people’s opinions in proportion to their merits.

I came to see that people’s greatest weaknesses are the flip sides of their greatest strengths.

What happens after we crash is most important. Successful people change in ways that allow them to continue to take advantage of their strengths while compensating for their weaknesses and unsuccessful people don’t.

beneficial change begins when you can acknowledge and even embrace your weaknesses.

“It was awful-tasting medicine, but I guess the patient needed it. Sometimes life hits you in the head with a brick. Don’t lose faith. I’m convinced that the only thing that kept me going was that I loved what I did.”

The most important thing you can do is to gather the lessons these failures provide and gain humility and radical open-mindedness in order to increase your chances of success. Then you press on.

I could either take on a lot of risk in pursuit of high returns (and occasionally find myself ruined) or I could lower my risk and settle for lower returns. But I needed to have both low risk and high returns, and by setting out on a mission to discover how I could, I learned to go slowly when faced with the choice between two things that you need that are seemingly at odds. That way you can figure out how to have as much of both as possible.

There is almost always a good path that you just haven’t discovered yet, so look for it until you find it rather than settle for the choice that is then apparent to you.

Coming out of my crash, I was so broke I couldn’t muster enough money to pay for an airplane ticket to Texas to visit a prospective client, even though the fees I’d earn were many times the cost of the fare—so I didn’t make that trip.

I was just getting the things I needed to play my game.

Computers were among the most valuable things I acquired, because of how they helped me think. Without them, Bridgewater would not have been nearly as successful as it turned out to be.

if there was a computer that could hold all of the world’s facts and if it was perfectly programmed to mathematically express all of the relationships between all of the world’s parts, the future could be perfectly foretold.”

what was most important wasn’t knowing the future—it was knowing how to react appropriately to the information available at each point in time.

Then, when I closed out a trade, I could reflect on how well these criteria had worked. It occurred to me that if I wrote those criteria into formulas (now more fashionably called algorithms) and then ran historical data through them, I could test how well my rules would have worked in the past.

I would start out with my intuitions as I always did, but I would express them logically, as decision-making criteria, and capture them in a systematic way, creating a mental map of what I would do in each particular situation. Then I would run historical data through the systems to see how my decision would have performed in the past and, depending upon the results, modify the decision rules appropriately.

Our system was like an EKG on the economy’s vital signs; as they changed, we changed our positions. However, rather than blindly following the computer’s recommendations, I would have the computer work in parallel with my own analysis and then compare the two.

This was great, because it was like having a chess grandmaster helping me plot my moves, except this player operated according to a set of criteria that I understood and believed were logical, so there was no reason for us to ever fundamentally disagree.

we always had the freedom to override the system, which we did less than 2 percent of the time—mostly to take money off the table during extraordinary events that weren’t programmed, like the World Trade Center going down on 9/11.

That’s why our brains working with the computer made such a great partnership.

Truth be known, forecasts aren’t worth very much, and most people who make them don’t make money in the markets. . . . This is because nothing is certain and when one overlays the probabilities of all of the various things that affect the future in order to make a forecast, one gets a wide array of possibilities with varying probabilities, not one highly probable outcome. . . . We believe that market movements reflect economic movements. Economic movements are reflected in economic statistics. By studying the relationships between economic statistics and market movements, we’ve developed precise rules for identifying important shifts in the economic/market environment and in turn our positions. In other words, rather than forecasting changes in the economic environment and shifting positions in anticipation of them, we pick up these changes as they’re occurring and move our money around to keep in those markets which perform best in that environment.

Now, as real-time data is released, our computers parse information from over 100 million datasets and give detailed instructions to other computers in ways that make logical sense to me. If I didn’t have these systems, I’d probably be broke or dead from the stress of trying so hard.

I believe one of the most valuable things you can do to improve your decision making is to think through your principles for making decisions, write them out in both words and computer algorithms, back-test them if possible, and use them on a real-time basis to run in parallel with your brain’s decision making.

For example, we would build a plan to help a multinational company deal with the currency exposure it faced from operating in different countries.

My approach was to immerse myself in a business until I got to a point where I felt that the strategies I was handing off were the ones I would use were I running the company myself. I would break each company down into distinct logical components and then come up with a plan for managing each part, using a variety of financial tools, especially derivative instruments. The most important components to separate were the profits coming from the core business and those that were speculative profits and losses coming from price changes.

“alpha overlay,” in which passive (“beta”) and active (“alpha”) exposures are separated. The return of a market (such as the stock market) itself is called its beta. Alpha is the return that comes from betting against others. For example, some people outperform the stock market and others underperform it; they are said to have positive or negative alpha. With alpha overlay, we were offering a way of making bets independent of underlying market performance.

only take bets you are highly confident in and to diversify them well.

I worked with Paul Tudor Jones, a good friend and a great trader, to design a U.S. dollar futures contract (a tradable index tracking the price of the U.S. dollar against a basket of foreign currencies) that traded (and still trades) on the New York Cotton Exchange.

All I wanted was to trade the markets and build relationships, doing for our clients exactly what I would do if I were in their shoes. But I also loved building brand-new things, especially if they were great and revolutionary.

We went on to become the top-performing U.S. bond manager in the world.

By then, I was convinced that China was poised to become the greatest economy in the world in the twenty-first century, but hardly anyone was investing in China yet; good deals could still be struck.

Essentially, I was setting up the first U.S.-based private equity firm in China.