Book - Principles: Life and Work
Time is like a river that carries us forward into encounters with reality that require us to make decisions. We can’t stop our movement down this river and we can’t avoid those encounters. We can only approach them in the best possible way. - Ray Dalio, Principles
by Ray Dalio
Online version: https://www.principles.com/principles/7e32fcba-3c52-4f0d-8718-3cc342d88763/#table-of-contents
What are Principles and Mental Models?
Where can we find good Principles and Mental Models?
Be clear on your principles
Second-Order Thinking
Think for yourself
- What do you want?
- What is true?
- What are you going to do about it?
Part 1: Where I’m coming from
Chapter 1: My call to adventure 1949-1967
Staring at age 8, I had a newspaper route, shoveled snow off people’s driveways, caddied, bussed tables and washed dishes at a local restaurant, and stocked shelves at a nearby department store. I don’t remember my parents encouraging me to do these jobs so I can’t sy how I came by them. But I do know that having those jobs and having some money to handle independently in those early years taught me many valuable lessons I wouldn’t have learned in school or at play.
In my early years the psychology of the 1960s U.S. was aspirational and inspirational - to achieve great and noble goals. It was like nothing I have seen since. One of my earliest memories was of John F. Kennedy, an intelligent, charismatic man who painted vivid pic- tures of changing the world for the better-exploring outer space, achieving equal rights, and eliminating poverty. He and his ideas had a maior effect on my thinking.
In those days, Fortune magazine had a little tear-out coupon you could mail in to get free annual reports from Fortune 500 companies. I ordered them all. I can still remember watching the mailman unhappily lugging all those reports to our door, and I dug into every one of them. That was how I began building an investment library.
Investing seemed like simply a matter of buying anything and watching it go up. It would certainly go up, the common knowledge held, because managing the economy had developed into a science.
As a result, “dollar-cost averaging”-investing essentially the same dollar amount in the market every month, no matter how few or many shares it could buy-was the strategy most people followed. Of course, picking the best stocks was even better, so that’s what I and everyone else tried to do. There were thousands to choose from, all neatly listed pages of the newspaper.
I’ve always been an independent thinker inclined to take risks in search of rewards - not just in the markets, but in most everything. I also feared boredom and mediocrity much more than I feared failure. For me, great is better than terrible, and terrible is better than mediocre, because terrible at least gives life flavor. The high school yearbook quote my my friends chose for me was from Thoreau:
“If a man does not keep pace with his companions, perhaps it is because he hears a different drummer. Let him step to the music which he hears, however measured or far away.” - Thoreau
Chapter 2: Crossing the threshold: 1967-1979
I gradually learned that prices reflect people’s expectations, so they go up when actual results are better than expected and they go down when they are worse than expected. And most people tend to be biased by their recent experiences.
Around 1970 or 1971, I noticed gold was starting to tick up in world markets. Until then, like most people, I hadn’t paid much atten- tion to currency rates because the currency system had been stable throughout my lifetime. But as currency events increasingly appeared in the news, they caught my attention. I learned that other currencies were fixed against the dollar, that the dollar was fixed against gold, that Americans weren’t allowed to own gold (though I wasn’t sure why), and that other central banks could convert their dollars paper into gold, which was how they were assured that they wouldn’t be hurt if the U.S. printed too many dollars.
Then, on Sunday, August 15, 1971, President Nixon went on television to announce that the U.S. would renege on its promise to allow dollars to be turned in for gold, which led the dollar to plummet. Since government officials had promised not to devalue the dollar, I listened with amazement as he spoke. Instead of addressing the fundamental problems behind the pressure on the dollar, he continued to blame speculators, crafting his words to make it sound like he was moving to support the dollar while his actions were doing just the opposite. “Floating it,” as Nixon was doing, and then letting it sink like a stone, looked a lot like a lie to me. Over the decades since, I’ve repeatedly seen policymakers deliver such assurances immediately before currency devaluations, so I learned not to believe government policymakers when they assure you that they won’t let a currency devaluation happen. The more strongly they make those assurances, the more desperate the situation probably is, so the more likely it is that a devaluation will take place.
Instead of falling, the stock market jumped about 4 percent, a significant daily gain.
To try to understand what was happening, I spent the rest of that summer studying past currency devaluations. I learned that everything that was going on-the currency breaking its link to gold and devaluing, the stock market soaring in response-had happened before, and that logical cause-effect relationships made those developments inevitable. My failure to anticipate this, I realized, was due to my being surprised by something that hadn’t happened in my lifetime, though it had happened many times before. The message that reality was conveying to me was “You better make sense of what happened to other people in other times and other places because if you don’t you won’t know if these things can happen to you and, if they do, you won’t know how to deal with them.”
The lesson? When everybody thinks the same thing-such as what a sure bet the Nifty 50 is-it is almost certainly reflected in the price, and betting on it is probably going to be a mistake. I also learned that for every action (such as easy money and credit) there is a consequence (in this case, higher inflation) roughly proportionate to that action, which causes an approximately equal and opposite reaction (tightening of money and credit) and market reversals.
While I worked in the brokerage business, I also traded my own account. Though I had many more winning positions than losing ones, I can only recall the losing ones now. I remember one big one when I owned pork bellies. For several days the market for them was limit down - meaning that the price had fallen so low that trading had to be stopped. I later described the impact of this experience to Jack Schwager, the author of Hedge Fund Market Wizards:
In those days, we had the big commodity boards, which clicked whenever prices changed. So each morning, on the opening, I would see and hear the market click down 200 points, the daily limit, stay unchanged at that price, and know that I had lost that much more, with the amount of potential additional losses still undefined. It was a very tactile experience… [and] it taught me the importance of risk controls, because I never wanted to experience that pain again. It enhanced my fear of being wrong and taught me to make sure that no single bet, or even multiple bets, could cause me to lose more than an acceptable amount. In trading you have to be defensive and aggressive at the same time. If you are not aggressive, you are not going to make money, and if you are not defensive, you are not going to keep money. I believe that anyone who has made money in trading has had to experience horrendous pain at some point. Trading is like working with electricity; you can get an electric shock. With that pork belly trade and other trades, I felt the electric shock and the fear that comes with it.
Modeling Markets as machines
I was really getting my head into the livestock, meat, grain, and oilseed markets. I loved them because they were concrete and less subject than stocks to distorted perceptions of value. While stocks could stay too high or too low because “greater fools” kept buying or selling them, livestock ended up on the meat counter where it would be priced based on what consumers were willing to pay. I could visualize the processes that led to those sales and see the relationships underlying them. Since livestock eat grain (mostly corn) and soymeal, and since corn and soy- beans compete for acreage, those markets are closely related. I learned just about everything imaginable about them-what the planted acre- age and typical yields were in each of the major growing areas; how to convert rainfall levels in different weeks of the growing season into yield estimates; how to project harvest sizes, carrying costs, and live- stock inventories by weight group, location, and rates of weight gain; and how to project dressing yields, retailer margins, consumer preferences by cut of meat, and the amounts to be slaughtered in each season.
This wasn’t academic learning: People with practice in the business showed me how the agricultural processes worked, and I organized what they told me into models I used to map the interactions of those parts through time.
For example, by knowing how many cattle, chickens, and hogs were being fed, how much grain they ate, and how fast they gained weight, I could project both when and how much meat would come to market and when and how much corn and soymeal would be con- sumed. Likewise, by seeing how much acreage was planted with corn and soybeans in all the growing areas, doing regressions that showed how rainfall affected the yields in each of these areas, and applying weather forecasts and rainfall data, I could project the timing and quantity of corn and soybean production. To me it all looked like a beautiful machine with logical cause-effect relationships. By under- standing these relationships, I could come up with decision rules (or principles) I could model.
These early models were a far cry from the ones we use now; they were back-of-the-envelope sketches, analyzed and converted into com- puter programs with the technology I could afford at the time. At the very beginning, I did regressions on my handheld Hewlett-Packard HP-67 calculator, plotted charts by hand with colored pencils, and recorded every trade in composition notebooks. When the personal computer came along, I could input the numbers and watch them be converted into pictures of what would happen on spreadsheets. Know- ing how cattle, hogs, and chickens progressed through their stages of production, how they competed for meat-eater dollars, what meat- eaters would spend and why, and how the profit margins of meatpack- ers and retailers would influence their behaviors (for example, which cuts of meat they would push in advertisements), 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. The approach to price determination I was using was different from the one I had learned in my economics classes where supply and demand were both measured in terms of quantities sold. 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. I will explain this approach in Economic and Investment Principles.
This different approach was one of the key reasons I caught eco- nomic and market moves others missed. From that point on, when- ever 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 com- puter could “make decisions” for me all became standard practices.
Don’t get me wrong. My approach was far from perfect. I vividly remember one “can’t lose” bet that personally cost me about $100,000. That was most of my net worth at the time. More painful still, it hurt clients too. The most painful lesson that was repeatedly hammered home is that 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. This lesson changed my approach to decision making in ways that will reverberate throughout this bookâand to which I attribute much of my success. But I would make many other mistakes before I fully changed my behavior.
Building the business
In the late 1970s, I began sending my observations about the markets to clients via telex. The genesis of these Daily Observations (“Grains and Oilseeds,” “Livestock and Meats,” “Economy and Financial Markets”) was pretty simple: While our primary business was in managing risk exposures, our clients also called to pick my brain about the markets. Taking those calls became time-consuming, so I decided it would be more efficient to write down my thoughts every day so others could understand my logic and help improve it. It was a good discipline since it forced me to research and reflect every day. It also became a key channel of communication for our busi- ness. Today, almost forty years and ten thousand publications later, our Daily Observations are read, reflected on, and argued about by cli- ents and policymakers around the world. I’m still writing them, along with others at Bridgewater, and expect to continue to write them until people don’t care to read them or I die.