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December 15, 2015

The CIA’s Guide to Investing

When the intelligence community gets a problem, invariably it’s what’s called “underdetermined.”
That’s just a fancy way of saying “you don’t have enough information.”
In my counterterrorism work for the CIA, we were constantly confronted with problems that could not be solved with the information available. That’s the nature of intelligence work – you never have enough information.
After all, if you had all the information, you wouldn’t need an intelligence service; a smart college kid could do the job. The reason you have an intelligence community is because it’s a very hard problem and you don’t have enough information. That’s why you have intelligence analysts filling in the blanks and trying to make sense of the puzzle, even when a number of the pieces are missing.
The CIA is divided into two main branches – the clandestine service and the analytical branch. The clandestine service is the “collectors.” They recruit spies and gather information from hard-to-get places. The analytical branch takes the information provided by the collectors and tries to connect the dots and draw actionable conclusions to deliver to policymakers up to and including the president.
The same is true in financial analysis. You may have a lot of information, but you always need more. Some of the most important information is buried inside company management or the Federal Reserve boardroom and not easy to get to.
So what do you do when you don’t have enough information?
You can throw up your hands. That’s not a good approach…
You can guess – also not a good approach…
Or you can start to fill in the blanks and connect the dots.
To do that you need an analytical method – and I recommend using the same one we use at the CIA. We’re not sure how events are going to turn out, but we can come up with three or four different scenarios.
In all probability, for example, the market will see one of several outcomes.
One of them may be deflation. Another may be inflation. There could be a market crash. And maybe there’s a positive outcome, too, on the off chance that tough policy choices are made and crisis is averted.
Then, you take those outcomes and model them to determine the possibilities.
A lot of analysts don’t get that far. They put a stake in the ground and say, “This this is what’s going to happen.”
I don’t do that and I don’t recommend you do either. I remain open to the possibility that three or four things can happen.
But even if some analysts get that far, they start tagging probabilities on the potential outcomes. They might say, for example, “There’s a 30% chance of deflation”… “there’s 40% chance of inflation,” et cetera.
I don’t do that either and I recommend you follow suit.
Here’s the way I think about probabilities: There’s a 100% chance of one outcome happening and there’s a 0% chance of all the other outcomes occurring. It’s just that you don’t know in advance which one it’s going to be.
So what do you do?
Well, in intelligence work, we come up with what we call indications and warnings, or “I&W.” These are like signposts, or milestones on the path to one of those outcomes.
Say I’ve identified four possible outcomes, or four paths. If I start down a path but don’t know which one I’m on exactly… and I don’t know what the outcome will be… my best bet is to seek out the indications, warnings, and signposts that will help me determine where I’m headed.
When I make out the signposts, then I can begin to know which way I’m going.
There’s a full mathematical formula behind this, but here’s a simple analogy I use to explain it to people…
I’ve lived in the New York area. It just so happens that if you drive to Boston, all the roadside restaurants are McDonald’s. If you drive the other way, to Philadelphia, all the roadside restaurants are Burger Kings.
So, if you blindfold me, put me in a car and don’t tell me which way we’re going I’ll have no way of knowing where I’ll end up.
But say we took the same trip and you blindfold me… but this time you told me “We’re stopping at Burger King”; I know I’m not going to Boston. I wouldn’t have to see where I was going to know where I’ll end up.
The Burger Kings and the McDonald’s in this example are the signposts. They’re the indications and warnings.
The art of this technique is to first map out the possible events so you can get the possible outcomes correct. Then, instead of just assigning arbitrary numbers to them, you watch for the indications and warnings to tell you which one you’re headed for at any given time.
You have to watch the data, the geopolitical developments and the strategic developments. When you see a particular signpost, you know where you’re going. Then you can take action in advance.
That’s why I take what I’ve learned working for the national security and intelligence community. You can apply that learning to Wall Street and financial markets along with me. When you click here, you’ll see the brand-new service in which we’re applying these intelligence techniques to understanding capital markets.
One of the most powerful tools we use in the intelligence community goes by technical-sounding names like “causal inference” or “inverse probability.” These are methods based on a mathematical equation that’s two centuries old.
The idea behind it is basic, though. You form a hypothesis based on experience, common sense, and whatever data are available. Then you test the hypothesis not by what has happened before but by what comes after.
Instead of reasoning from cause to effect, you reverse the process. You watch the effects to determine the cause. This will validate or invalidate the “cause” you have hypothesized.
Other times the effects contradict the hypothesis, in which case you modify or abandon it and adopt another. Often, the effects confirm the hypothesis, in which case you know you’re on the right track and keep going.
Courtesy of Bill Bonner, Bonner & Partners

The views and opinions expressed herein are the author's own, and do not necessarily reflect those of EconMatters. © EconMatters All Rights Reserved | Facebook | Twitter | Free Email | Kindle

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