Safe Haven. Mark Spitznagel

Sklansky wrote, “at war with luck.”

      Most people would say (or at least their actions imply) that they are the house in their investing. And 93% of people also say that they are above average drivers. They aren't, in either case.

      “At war with luck”—using our “skills to minimize luck as much as possible”—does indeed apply to risk mitigation. That is precisely how this war is fought in investing. In my case, it is no less than everything I do as an investor. So it is fitting that we begin to understand risk mitigation by deductively stripping it down to its bare bones, literally.

      This is one of the most valuable things I have learned from Nassim Taleb, his valid warnings against the ludic fallacy notwithstanding (where “the narrow world of games and dice” have so little in common with the untamed risk of the real world): that playing around with and meditating on simplified Monte Carlo simulations, or “alternative histories,” is the best way to figure things out.

      After all, according to Popper, science is “the art of systematic over‐simplification.”

      Beyond epistemological rigor, the biggest advantage I gain from building my safe haven hypothesis deductively and piecemeal using games of dice is transparency. You are going to see some things about safe haven investing that will seem to defy common sense. Couple that with the fact that there are frighteningly many ways that the investment industry regularly smokes people with complicated and unfalsifiable (and thus pseudoscientific) theories and cherry‐picked market data, and you can see my concern about a healthy skepticism. “Trust, but verify”: When something doesn't smell right, go back to the beginning, to our simple and transparent deductive dice illustrations. Roll your own and play along at home. There's no place to hide there.

As Feynman famously said:

       In general, we look for a new law by the following process. First, we guess it. Then, we compute the consequences of the guess to see what, if this is right, it would imply. And then we compare the computation results directly with observations to see if it works. If it disagrees with experiment, it's wrong. In that simple statement is the key to science. It doesn't make any difference how beautiful your guess is, it doesn't make any difference how smart you are who made the guess, or what his name is—if it disagrees with experiment, it's wrong. That's all there is to it.

      This will be my analytical framework for this book.

      In Part One, we start with “what comes first” (the a priori), with an intuitive construction and examination of those fundamental safe haven mechanisms, with the help of our deductive dice. “First, we guess it.” Then in Part Two, with “what comes after” (the a posteriori), we start to formulate testable safe haven hypotheses based on those mechanisms—hypotheses about how we might expect them to work. We will conduct clinical trials or experiments on different idealized safe havens (what I call cartoons)—to “compute the consequences of the guess.” Then, we can compare those results “directly with observations to see if it works,” by running those same experiments on the diverse range of real‐world safe havens themselves. Our aim is to try to falsify, in a meaningful and rigorous way, the hypothesis that safe havens as a group—and various safe havens in particular—can raise wealth by lowering risk. This is not a foregone conclusion; after all, it is considered a crackpot idea.

      Through this methodology, you will hopefully understand what works in risk mitigation, what does not, and why. And this understanding will protect you more than any individual safe haven ever could. It will guide you toward our goal as investors.

       If you think about it, cost‐effective risk mitigation—or raising compound growth rates and thus wealth through lower risk—is really our comprehensive goal as investors. It is the true essence of investment management. In and of itself, it is the specific meta‐purpose or meaning we pursue when we deploy capital—what we hunt for relentlessly, our buried treasure.

      Yes, there really is a buried treasure for investors, one that solves our monumental problem by showing that the great dilemma of risk—the ostensible tradeoff between higher returns and lower risk—is actually a false choice. But this treasure wasn't so much hidden away by pirates of lore as it was cloaked behind the flawed apparatus of modern finance, shrouded behind its veil of rigor. As a result, it appears as a myth, an idealized and elusive goal. But that's only because investors have been looking too narrowly and in the wrong places for it. We need a more holistic approach; we also need a treasure map to know where to dig.

      But just because that buried treasure exists doesn't mean we will ever find it. The greatest value—more than in the treasure itself—will be in what we gain from the hunt.