Predicting Terrorism with Market Intelligence: Stock Options

Jim Rickards explains why there’s a financial crisis coming, and in so doing, reviews the unusual origins of his predictive analytics tool. He also explores complexity theory and Bayesian statistics. Jim Rickards is a renowned author and the chief global strategist at Meraglim. Filmed on July 12, 2018 in New York.

 

This has roots that go back to 9/11.
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Tragic day, September 11, 2001, when the 9/11 attack took place.
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And what happened then– there was insider trading in advance of 9/11.
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In the two trading days prior to the attack, average daily volume and puts, which is short
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position, put option buying on American Airlines and United Airlines, was 286 times the average
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daily volume.
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Now you don’t have to be an option trader, and I order a cheeseburger for lunch every
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day, and one day, I order 286 cheeseburgers, something’s up.
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There’s a crowd here.
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I was tapped by the CIA, along with others, to take that fact and take it forward.
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The CIA is not a criminal investigative agency.
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Leave that to the FBI and the SEC.
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But what the CIA said was, OK, if there was insider trading ahead of 9/11, if there were
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going to be another spectacular terrorist attack, something of that magnitude, would
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there be insider trading again?
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Could you detect it?
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Could you trace it to the source, get a FISA warrant, break down the door, stop the attack,
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and save lives?
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That was the mission.
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We call this Project Prophecy.
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I was the co-project director, along with a couple of other people at the CIA.
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Worked on this for five years from 2002 to 2007.
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When I got to the CIA, you ran into some old timers.
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They would say something like, well, Al-Qaeda or any terrorist group, they would never compromise
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operational security by doing insider trading in a way that you might be able to find.
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And I had a two word answer for that, which is, Martha Stewart.
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Martha Stewart was a legitimate billionaire.
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She made a billion dollars through creativity and her own company.
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She ended up behind bars because of a $100,000 trade.
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My point is, there’s something in human nature that cannot resist betting on a sure thing.
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And I said, nobody thinks that Mohamed Atta, on his way to Logan Airport, to hijack a plane,
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stopped at Charles Schwab and bought some options.
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Nobody thinks that.
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But even terrorists exist in the social network.
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There’s a mother, father, sister, brother safe house operator, car driver, cook.
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Somebody in that social network who knows enough about the attack and they’re like,
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if I had $5,000, I could make 50, just buy a put option.
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The crooks and terrorists, they always go to options because they have the most leverage,
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and the SEC knows where to look.
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So that’s how it happens.
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And then the question was, could you detect it.
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So we started out.
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There are about 6,000 tickers on the New York Stock Exchange and the NASDAQ.
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And we’re talking about second by second data for years on 6,000 tickers.
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That’s an enormous, almost unmanageable amount of data.
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So what we did is we reduced the targets.
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We said, well, look, there’s not going to be any impact on Ben and Jerry’s ice cream
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if there’s a terrorist attack.
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You’re looking at cruise ships, amusement parks, hotels, landmark buildings.
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there’s a set of stocks that would be most effective.
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So we’re able to narrow it down to about 400 tickers, which is much more manageable.
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Second thing you do, you establish a baseline.
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Say, what’s the normal volatility, the normal average daily volume, normal correlation in
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the stock market.
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So-called beta and so forth.
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And then you look for abnormalities.
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So the stock market’s up.
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The transportation sector is up.
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Airlines are up, but one airline is down.
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What’s up with that?
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So that’s the anomaly you look for.
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And then the third thing you do.
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You look for news.
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Well, OK, the CEO just resigned because of some scandal.
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OK, got it, that would explain why the stock is down.
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But when you see the anomalous behavior, and there’s no news, your reference is, somebody
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knows something I don’t.
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People aren’t stupid, they’re not crazy.
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There’s a reason for that, just not public.
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That’s the red flag.
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And then you start to, OK, we’re in the target zone.
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We’re in these 400 stocks most affected.
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We see this anomalous behavior.
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Somebody is taking a short position while the market is up and there’s no news.
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That gets you a red light.
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And then you drill down.
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You use what in intelligence work we call all source fusion, and say, well, gee, is
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there some pocket litter from a prisoner picked up in Pakistan that says cruise ships or something
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along– you sort of get intelligence from all sources at that point drilled down So
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that was the project.
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We built a working model.
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It worked fine.
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It actually worked better than we expected.
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I told the agency, I said, well, we’ll build you a go-kart, but if you want a Rolls Royce,
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that’s going to be a little more expensive.
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The go-kart actually worked like a Rolls Royce.
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Got a direct hit in August 2006.
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We were getting a flashing red signal on American Airlines three days before MI5 and New Scotland
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Yard took down that liquid bomb attack that were going to blow up 10 planes in midair
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with mostly Americans aboard.
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So it probably would have killed 3,000 Americans on American Airlines and Delta and other flights
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flying from Heathrow to New York.
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That plot was taken down.
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But again, we had that signal based on– and they made hundreds of arrests in this neighborhood
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in London.
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So this worked perfectly.
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Unfortunately, the agency had their own reasons for not taking it forward.
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They were worried about headline risk, they were worried about political risk.
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You say, well, we were using all open source information.
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You can pay the Chicago Mercantile Exchange for data feed to the New York Stock Exchange.
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This is stuff that anybody can get.
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You might to pay for it, but you can get it.
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But the agency was afraid of the New York Times headline, CIA trolls through 401(k)
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accounts, which we were not doing.
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It was during the time of waterboarding and all that, and they decided not to pursue the
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project.
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So I let it go, there were plenty of other things to do.
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And then as time went on, a few years later, I ended up in Bahrain at a wargame– financial
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war game– with a lot of thinkers and subject matter experts from around the world.
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Ran into a great guy named Kevin Massengill, a former Army Ranger retired Major in the
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US army, who was working for Raytheon in the area at the time was part of this war game.
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We were sort of the two American, little more out of the box thinkers, if you want to put
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it that way.
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We hit it off and I took talked him through this project I just described.
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And we said, well look, if the government doesn’t want to do it, why don’t we do it
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privately?
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Why don’t we start a company to do this?
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And that’s exactly what we did.
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Our company is, as I mentioned, Meraglim.
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Our website, Meraglim.com, and our product is Raven.
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So the question is, OK, you had a successful pilot project with the CIA.
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It worked.
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By the way, this is a new branch of intelligence in the intelligence.
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I-N-T, INT, is short for intelligence.
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And depending on the source, you have SIGINT, which is signal intelligence, you have HUMINT
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which is human intelligence, and a number of others.
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We created a new field called MARKINT, which is market intelligence.
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How can you use market data to predict things that are happening.
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So this was the origin of it.
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We privatized it, got some great scientists on board.
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We’re building this out ourselves.
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Who partnered with IBM, and IBM’s Watson, which is the greatest, most powerful plain
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language processor.
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Watson can read literally millions of pages of documents– 10-Ks, 10-Qs, AKs, speeches,
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press releases, news reports.
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More than a million analysts could read on their own, let alone any individual, and process
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that in plain language.
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And that’s one of our important technology partners in this.
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And we have others.
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What do we actually do?
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What’s the science behind this.
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First of all, just spend a minute on what Wall Street does and what most analysts do,
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because it’s badly flawed.
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It’s no surprise that– every year, the Fed does a one year forward forecast.
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So in 2009, they predict 2010.
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In 2010, they predict 2011.
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So on.
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Same thing for the IMF, same thing for Wall Street.
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They are off by orders of magnitude year after year.
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I mean, how can you be wrong by a lot eight years in a row, and then have any credibility?
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And again, the same thing with Wall Street.
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You see these charts.
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And the charts show the actual path of interest rates or the actual path of growth.
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And then along the timeline, which is the x-axis, they’ll show what people were predicting
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at various times.
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The predictions are always way off the actual path.
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There’s actually good social science research that shows that economists do worse than trained
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monkeys on terms of forecasting.
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And I don’t say that in a disparaging way– here’s the science.
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A monkey knows nothing.
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So if you have a binary outcome– up, down, high, low, growth, recession– and you ask
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a monkey, they’re going to be right half the time and wrong half the time, because they
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don’t know what they’re doing.
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So you’re to get a random outcome.
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Economists are actually wrong more than half the time for two reasons.
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One, their models are flawed.
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Number two, what’s called herding or group behavior.
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An economist would rather be wrong in the pack than go out on a limb and maybe be right,
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but if it turns out you’re not right, you’re exposed.
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But there are institutional constraints.
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People want to protect their jobs.
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They’re worried about other things than getting it right.
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So the forecasting market is pretty bad.
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The reasons for that– they use equilibrium models.
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The capital markets are not in equilibrium system, so forget your equal equilibrium model.
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They use the efficient market hypothesis, which is all the information is out there,
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you can’t beat the market.
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Markets are not efficient, we know that.
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They use stress tests, which are flawed, because they’re based on the past, but we’re outside
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the past.
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The future could be extremely different.
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They look at 9/11, they look at long term capital management, they look at the tequila
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crisis.
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Fine, but if the next crisis is worse, there’s nothing in that history that’s going to tell
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you how bad it can get.
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And so they assume prices move continuously and smoothly.
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So price can go from here to here or from here to here.
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But as a trader, you can get out anywhere in between, and that’s for all these portfolio
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insurance models and stop losses come from.
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That’s not how markets behave.
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That go like this– they just gap up.
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They don’t hit those in between points.
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Or they gap down.
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You’re way underwater, or you missed a profit opportunity before you even knew it.
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So in other words, the actual behavior of markets is completely at odds with all the
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models that they use.
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So it’s no surprise the forecasting is wrong.
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So what are the good models?
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What are the models that do work?
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What is the good science?
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The first thing is complexity theory.
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Complexity theory has a long pedigree in physics, meteorology, seismology, forest fire management,
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traffic, lots of fields where it’s been applied with a lot of success.
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Capital markets are complex systems.
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The four hallmarks of a complex system.
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One is their diversity of actors, sure.
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Two is their interaction– are the actors talking to each other or are they all sort
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of in their separate cages.
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Well, there’s plenty of interaction.
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Is there communication and is there adaptive behavior?
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So yeah, there are diverse actors, there’s communication.
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They’re interacting.
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And if you’re losing money, you better change your behavior quickly.
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That’s an example of adaptive behavior.
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So capital markets are four for four in terms of what makes a complex system.
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So why not just take complexity science and bring it over to capital markets?
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That’s what we’ve done, and we’re getting fantastic results.
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So that’s the first thing.
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The second thing we use is something called Bayesian statistics.
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It’s basically a mathematical model that you use when you don’t have enough data.
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So for example, if I’ve got a million bits of data, yeah, do your correlations and regressions,
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that’s fine.
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And I learned this at the CIA, this is the problem we confronted after 9/11.
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We had one data point– 9/11.
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Janet Yellen would say, wait for 10 more attacks, and 30,000 dead, and then we’ll have a time
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series and we can figure this out.
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No.
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To paraphrase Don Rumsfeld, you go to war with the data you have.
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And so what you use is this kind of inferential method.
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And the reason statisticians dislike it is because you start with a guess.
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But it could be a smart guess, it could be an informed guess.
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The data may be scarce.
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You make the best guess you can.
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And if you have no information at all, just make it 50/50.
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Maybe Fed is going to raise rates, maybe they’re not.
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I think we do better than that on the Fed.
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But if you didn’t have any information, you just do 50/50.
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But then what you do is you observe phenomena after the initial hypothesis, and then you
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update the original hypothesis based on the subsequent data.
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You ask yourself, OK this thing happened later.
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What is the conditional correlation that the second thing would happen if the first thing
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were true or not?
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And then based on that, you’d go back, and you either increase the probability of the
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hypothesis being correct, or you decrease it.
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It gets low enough, you abandon it, try something else.
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If it gets high enough, now you can be a lot more confident in your prediction.
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So that’s Bayesian statistic.
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You use it to find missing aircraft, hunt submarines.
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It’s used for a lot of things, but you can use it in capital markets.
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Third thing, behavioral psychology.
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This has been pretty well vetted.
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I think most economists are familiar with it, even though they don’t use it very much.
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But humans turn out to be a bundle of biases.
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We have anchoring bias, we get an idea in our heads, and we can’t change it.
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We have recency bias.
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We tend to be influenced by the last thing we heard.
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And anchoring bias is the opposite, we tend to be influenced by something we heard a long
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time ago.
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Recency bias and anchoring bias are completely different, but they’re both true.
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This is how you have to get your mind around all these contradictions.
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But when you work through that, people make mistakes or exhibit bias, it turns out, in
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very predictable ways.
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So factor that in.
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And then the fourth thing we use, and economists really hate this, is history.
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But history is a very valuable teacher.
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So those four areas, complexity theory, Bayesian statistics, behavioral psychology, and history
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are the branches of science that we use.
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Now what do we do with it?
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Well, we take it and we put it into something that would look like a pretty normal neural
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network.
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You have nodes and edges and some influence in this direction, some have a feedback loop,
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some influence in another direction, some are influenced by others, et cetera.
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So for Fed policy for example, you’d set these nodes, and it would include the things I mentioned
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earlier– inflation, deflation, job creation, economic growth, capacity, what’s going on
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in Europe, et cetera.
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Those will be nodes and there will be influences.
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But then inside the node, that’s the secret sauce.
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That’s where we have the mathematics, including some of the things I mentioned.
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But then you say, OK, well, how do you populate these nodes?
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You’ve got math in there, you’ve got equations, but where’s the news come from?
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That’s where Watson comes in.
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Watson’s reading all these records, feeding the nodes, they’re pulsing, they’re putting
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input.
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And then we have these actionable cells.
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So the euro-dollar cross rate, the Yuandollar cross rate, yen, major benchmark, bonds, yields
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on 10 year treasury notes, bunds, JGBs, et cetera.
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These are sort of macro indicators, but the major benchmark bond indices, the major currency
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across rates, the major policy rates, which are the short term central bank rates.
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And a basket of commodities– oil, gold, and a few others– they are the things we watch.
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We use these neural networks I described, but they’re not just kind of linear or conventional
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equilibrium models.
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They’re based on the science I describe.
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So all that good science, bringing it to a new field, which is capital markets, using
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what’s called fuzzy cognition, neural networks, populating with Watson, this is what we do.
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We’re very excited about it, getting great results.
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And this is what I use.
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When I give a speech or write a book or write an article, and I’m making forecast.
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This is what’s behind it.
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So we talked earlier about business cycles, recessions, depressions.
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And that’s conventional economic analysis.
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My definition of depression is not exactly conventional, but that’s really thinking in
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terms of growth, trend growth, below trend growth, business cycles, et cetera.
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Collapse or financial panic is something different.
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A financial panic is not the same as a recession or a turn in the business cycle.
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They can go together, but they don’t have to.
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So let’s talk about financial panics as a separate category away from the business cycle
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and growth, which we talked about earlier.
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Our science, the science I use, the science that we use with Raven, at our company, Meraglim,
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involves complexity theory.
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Well, complexity theory shows that the worst thing that can happen in a system is an exponential
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function of scale.
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Scale is just how big is it.
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Now you have to talk about your scaling metrics.
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We’re talking about the gross notional value derivatives.
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We’re talking about average daily volume on the stock market.
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We’re talking about debt.
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We could be talking about all of those things.
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This is new science, so I think it will be years of empirics to make this more precise.
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But the theory is good, and you can apply it in a sort of rough and ready way.
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So you go to Jamie Dimon, and you say, OK, Jamie, you’ve tripled your gross notional
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value derivatives.
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You’ve tripled your derivatives book.
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How much did the risk go up?
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Well, he would say, not at all, because yeah, gross national value is triple, but who cares?
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It’s long, short, long, short, long, short, long, short.
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You net it all down.
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It’s just a little bit of risk.
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Risk didn’t go up at all.
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If you ask my 87-year-old mother, who is not an economist, but she’s a very smart lady,
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say, hey mom, I tripled the system, how much did the risk go up?
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She would probably use intuition and say, well, probably triple.
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Jamie Dimon is wrong, my mother is wrong.
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It’s not the net, it’s the gross.
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And it’s not linear, it’s exponential.
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In other words, if you triple the system, the growth went up by a factor of 10, 50,
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et cetera.
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There’s some exponential function associated with that.
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So people think, well gee, in 2008, we learned our lesson.
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We’ve got debt under control, we’ve got derivatives under control.
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No.
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Debt is much higher.
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Debt to GDP ratios are much worse.
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Total notional value, gross notional values of derivatives is much higher.
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Now people look at the BIS statistics and say, well, the banks, actually, gross national
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value derivatives has been going down, which it has, but that’s misleading because they’re
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taking a lot of that, moving it over to clearing houses.
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So it’s never been on the balance sheet, it’s always been off balance sheet.
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But even if you use the footnotes, that number has gone down for banks, but that’s only because
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they’re putting it over clearing houses.
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Who’s guaranteeing the clearing house?
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The risk hasn’t gone away, it’s just been moved around.
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So given those metrics– debt, derivatives, and other indices, concentration, the fact
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that the five largest banks in America have a higher percentage of total banking assets
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than they did in 2008, there’s more concentration– that’s another risk factor.
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Taking that all into account, you can say that the next crisis will be exponentially
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worse than the last one.
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That’s an objective statement based on complexity theory.
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So you either have to believe that we’re never going to have a crisis.
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Well, you had one in 1987, you had one in 1994, you had one in 1998.
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You had the dotcom crash in 2000, mortgage crash in 2007, Lehman in 2008.
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Don’t tell me these things don’t happen.
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They happen every five, six, seven years.
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It’s been 10 years since the last one.
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Doesn’t mean it happens tomorrow, but nobody should be surprised if it does.
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So the point is this crisis is coming because they always come, and it will be exponentially
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worse because of the scaling metrics I mentioned.
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Who’s ready for that?
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Well, the central banks aren’t ready.
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In 1998, Wall Street bailed out a hedge fund long term capital.
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In 2008, the central banks bailed out Wall Street.
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Lehman– but Morgan Stanley was ready to fail, Goldman was ready to fail, et cetera.
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In 2018, 2019, sooner than later, who’s going to bail out the central banks?
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And notice, the problem has never gone away.
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We just get bigger bailouts at a higher level.
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What’s bigger than the central banks?
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Who can bail out the central banks?
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There’s only one institution, one balance sheet in the world they can do that, which
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is the IMF.
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The IMF actually prints their own money.
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The SDR, special drawing right, SDR is not the out strawberry daiquiri on the rocks,
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it’s a special drawing right.
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It’s world money, that’s the easiest way to think about it.
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They do have a printing press.
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And so that will be the only source of liquidity in the next crisis, because the central banks,
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if they don’t normalize before the crisis– and it looks like they won’t be able to, they’re
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going to run out of runway, and they can expand the balance sheet beyond the small amount
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because they’ll destroy confidence, where does the liquidity come from?
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The answer, it comes from the IMF.
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So that’s the kind of global monetary reset, the GMR, global monetary resety.
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You hear that expression.
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There’s something very new that’s just been called to my attention recently, and I’ve
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done some independent research on it, and it holds up.
33:39
So let’s see how it goes.
33:42
But it looks as if the Chinese have pegged gold to the SDR at a rate of 900 SDRs per
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ounce of gold.
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This is not the IMF.
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The IMF is not doing this.
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The Federal Reserve, the Treasury is not doing it.
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The ECB is not doing it.
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If they were, you’d see it.
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It would show up in the gold holdings.
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You have to conduct open market operations in gold to do this.
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But the Chinese appear to be doing it, and it starts October 1, 2016.
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That was the day the Chinese Yuan joined the SDR.
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The IMF admitted the Yuan to the group was four, now five currencies that make up the
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SDR.
34:22
So almost to the day, when the Yuan got in the SDR, you see this a horizontal trend where
34:29
first, gold per ounce is trading between 850 and 950 SDRs.
34:37
And then it gets tighter.
34:38
Right now, the range is 875 to 925.
34:41
Again, a lot of good data behind this.
34:44
So it’s a very good, it’s another predictive indicator.
34:47
If you see gold around 870 SDRs per ounce, that’s a strong SDR, weak gold.
34:54
Great time to buy gold, because the Chinese are going to move back up to 900.
34:58
So that’s an example of science, observation, base and statistics, inference, all the things
35:04
we talked about that can be used today in a predictive analytic way.
35:08
A crisis is coming, because they always do.
35:10
I don’t have a crystal ball, this is plenty of history to back it up.
35:13
It’ll be exponentially worse.
35:15
That’s what the science tells us.
35:16
The central banks will not be prepared, because they haven’t normalized from the last one.
35:20
You’re going to have to turn to the IMF, and who’s waiting there but China with a big pile
35:24
of gold.

Thomas Friedman, Iraq war booster

The New York Times columnist broke down what the Iraq was really about for Charlie Rose on May 29, 2003.

Jerome Delay/AP
So that’s what that was all about?

At the end of May 2003, America was on the verge of one of its longest-running, most expensive wars in Iraq. Yet Iraq war boosters were feeling vindicated by the swift march on Baghdad, which had fallen within weeks, and the swift collapse of the regime.

New York Times columnist Thomas Friedman, a fan of the Iraq war, appeared on Charlie Rose to crow about this rousing success on May 29 2003. The brief clip below from that interview (the full interview can be found here) is a fascinating glimpse into the id of Washington insiders like Friedman before the invasion in March of that year and for the first few months, at least, of what was to prove a long occupation.

He appears to still think it was the right choice. He wrote last June, in a column on Syria, that: “You can’t go from Saddam to Switzerland without getting stuck in Hobbes — a war of all against all — unless you have a well-armed external midwife, whom everyone on the ground both fears and trusts to manage the transition. In Iraq, that was America” and “the only reason Iraq has any chance for a decent outcome today is because America was on the ground with tens of thousands of troops to act as that well-armed midwife, reasonably trusted and certainly feared by all sides, to manage Iraq’s transition to more consensual politics.”

I don’t ever remember a time in my five years in Iraq where the US was generally seen as a trusted “midwife” by a majority, or even a large minority, of people. Whether or not Iraq might have a found a better, less bloody way out from the shadow of Saddam Hussein without an invasion and occupation, is now something forever unknowable.

(I just made the below transcript from the above clip. I’ve omitted most “uhms” and the like, and may have made one or two errors since the audio is a bit compromised):

Rose: “Now that the war is over and there’s some difficulty with the peace, was it worth doing?”

After Russian trolls target black Americans, one city fights back

Friedman: “I think it was unquestionably worth doing Charlie, and I think that looking back that I now certainly feel I understand what the war was about and it’s interesting to talk about it here in silicon valley because I think looking back at the 1990s I can identify there are actually three bubbles of the 1990s, there was the Nasdaq bubble, there was the corporate governance bubble, and lastly there was what I would call the terrorism bubble, and the first two were based on creative accounting and the last two were based on moral creative accounting. The terrorism bubble that built up over the 1990s said flying airplanes into the World Trade Center, that’s Ok. Wrapping yourself with dynamite and blowing up Israelis in the pizza parlour, that’s Ok. Because we’re weak and they’re strong and the weak have a different morality. Having your preachers say that’s Ok? That’s Ok. Having your charities raise money for people who do these kinds of things? That’s Ok. And having your press call people who do these kind of things martyrs? That’s Ok. And that build up as a bubble, Charlie. And 9/11 to me was the peak of that bubble. And  what we learned on 9/11 in a gut way was that bubble was a fundamental threat to our society because there is no wall high enough no INS agent smart enough no metal detector efficient enough to protect an open society from people motivated by that bubble. And what we needed to do was to go over to that part of the world and burst that bubble. We needed to go over there basically uhm, and, uh, uhm take out a very big stick, right in the heart of that world and burst that bubble. And there was only one way to do it because part of that bubble said ‘we’ve got you’ this bubble is actually going to level the balance of power between us and you because we don’t care about life, we’re ready to sacrifice and all you care about is your stock options and your hummers. And what they needed to see was American boys and girls going house to house from Basra to Baghdad uhm, and basically saying which part of this sentence don’t  you understand. You don’t think we care about our open society, you think this bubble fantasy we’re going to just let it go, well suck on this. Ok. That, Charlie, was what this war was about. We could have hit Saudi Arabia. It was part of that bubble. We could have hit Pakistan,  We hit Iraq, because we could. And that’s the real truth. “

What’s maybe most interesting about this bizarre set of views was that they were so commonplace back then. Al Qaeda has hit the United States, so we must hit back at them. Not just at Al Qaeda, or the people who might have directly assisted them, but a much bigger “them:” A whole civilization who had started to loom in the sight of people like Thomas Friedman as an existential threat to America.

Saddam Hussein had nothing to do with 9/11. The Iraqi people had had nothing to do with 9/11. Were there people there who were delighted to see the US get a bloody nose from Osama bin Laden? Yes. The previous decade had seen a US-backed sanctions effort targeting Saddam Hussein that crippled the country. Never mind that Saddam brought that upon his people with the invasion of Kuwait. Average people were the ones who suffered the most. In 1999 UNICEF estimated that the mortality rate for children under the age of five had doubled in central and southern Iraq since sanctions were imposed, from 56 dead children per 1,000 between 1984-1989 to 131 per 1,000 between 1994-1999.

I don’t begrudge them their anger, not least because they weren’t doing anything to harm people here in the US. I never understood the terror that seemed to grip so many Americans after 9/11, perhaps because by that point I’d covered small wars and grasping poverty we haven’t seen the likes of in the US for generations across Southeast Asia. A few years prior, I covered the independence of East Timor. The murder of Monitor stringer Sander Thoenes there was what led me to getting picked up by the paper — and he was just one of over 100,000 excess deaths in the tiny country during Indonesia’s 24-year occupation. For comparison, that was one in seven people in East Timor. One in seven Americans dying as the result of war and occupation would be 44 million people.

I had schoolmates who died in the towers, one dear friend who departed from the heights of Tower Two just minutes before it would have been too late, and who struggled with survivor’s guilt about the colleagues who stayed at their desks, for years after (most reckoned the plane that had crashed into the first tower was an accident, not a terrorist attack). It effected me, as it effected almost all Americans.

But it didn’t seem that hard to keep some perspective. And having lived in Muslim majority Indonesia since 1993 and spending the years after 9/11 covering Al Qaeda and aligned militant groups in the region, I’d learned enough to know that a war that could be painted as against Muslims in general would suit Al Qaeda right down to the ground – such a reaction is what they wanted, since they reckoned that would yield them a bonanza of new recruits.

Mr. Friedman has gone from strength to strength in the years since, with handsome speakers fees for him to explain his theories about how the world is changing and evolving. But that brief clip above shows a man whose analysis is easily swayed by emotion, by sentiment.

“What they needed to see was American boys and girls going house to house from Basra to Baghdad and basically saying which part of this sentence don’t you understand. You don’t think we care about our open society, you think this bubble fantasy we’re going to just let it go, well suck on this” is not the sort of comment that comes from dispassionate, reasoned analysis. It comes from fear.

We learned in a “gut way (that) bubble was a fundamental threat to our society?” That’s not really learning. As horrible as that attack on us was, there was no fundamental threat to our society. We have done a good job in the years since increasing security (to the point that, in some views, we have actually threatened our own open society ourselves) and preventing any further major attacks on our soil. Did the invasion of Iraq and taking out “a very big stick” accomplish that? No.

Finally, even the notion of a “terrorism bubble” in the 1990s was a bit of a myth. The decade that the 9/11 attacks began so horrifically was among the safest ones when terrorism in the skies is considered ever (since supplanted by the last decade). There were 469 fatalities for passengers, crews and passengers for commercial fliers in the 2000s, 256 of those on 9/11. In the 1990s, there were just under 400 fatalities. In the 1980s, there were about 1,400 and in the 1970s, there were just over 800 killed. When total number of commercial flights are included to make apples to apples comparisons, the most dangerous decade was the 1930s, with 616 fatalities per billion passenger flights. The 2000s had 22 per billion flights taken.

If there has been a “terrorism” bubble it appeared to have burst around 1991judging by this graph at the Global Terrorism Database maintained at the University of Maryland with funding from the Department of Homeland Security. Terrorism, though, surged again after 2003, largely with a rise in terrorist incidents in Afghanistan and Iraq associated with the wars being fought in those lands.

At this time of looking back, let’s try to remember the track records and quality of argument presented by people whose views and advice are sought before the wars of our future.

How Russia and China are preparing to exploit a warming planet

POLITICO’s latest Global Translations podcast explores how climate change is reshaping power dynamics among America’s adversaries.

Hurricanes, floods, and wildfires aside, climate change is delivering another threat: a remaking of geopolitics that stands to empower some of America’s adversaries and rivals.

As Arctic ice melts, Russia stands to gain access to oil and gas fields historically locked beneath northern ice — and is building up capability to launch cruise missiles from newly navigable waters to threaten America’s coastlines.

As polar seaways open up, China is eyeing a new “Polar Silk Road” — shorter shipping routes that could cut weeks off of shipping times from Asia to Europe.

And as drought drives more farmers and herders off their lands, extremist groups in Africa and the Middle East are finding fresh recruits.

These are just some of the ways climate change stands to reshape the power dynamics between nations that emerged from interviews for POLITICO’s Global Translations podcast.

Climate change is “making all of our challenges — whether it’s

  • terrorism,
  • weapons of mass destruction,
  • violent extremism or
  • great power competition between China and Russia —

that much more challenging,” said Sherri Goodman, a former deputy undersecretary of defense who led studies of climate impacts on national security for the Center for Naval Analyses.

Some of the biggest power shifts are around the Arctic, which Goodman called “ground zero for the nexus of national security and climate change. In our lifetime, a whole new ocean has opened up because with climate change the sea ice is retreating, the oceans are warming and the permafrost is collapsing.”

A global quest for resources is already underway in the Arctic, said Goodman, now a senior fellow at the Woodrow Wilson Center Polar Institute. “There are thought to be vast stores of fossil fuels, oil and gas and minerals across the Arctic that have not yet been tapped. Russia is doing so today across its vast Arctic coastline with the help of China,” she said.

Russia is vying for control of Arctic seaways and has built some 40 icebreakers — ships that can channel through ice. “Russia envisions under Putin a northern sea route that is essentially a toll road that requires Russian Arctic escorts in the form of icebreakers or other patrol boats, escorting not only the Chinese but others who want to ship across the Arctic,” she said. By contrast, the U.S. has only two icebreakers, she said.

Meanwhile, China, which is not a polar country, has launched aggressive Arctic diplomacy and gained non-voting observer status for itself at the Arctic Council, the international forum that addresses policy in the Arctic. Last year, China issued its first arctic policy.

“It envisions a Polar Silk Road that stretches from Shanghai across potentially to Hamburg and Reykjavik and parts of Europe across Russia’s vast northern sea route hugging the Russian coastline and both exploiting the energy resources there, potential transport opportunities, shipping, research,” Goodman said.

President Donald Trump’s interest in buying Greenland was driven in part by resources newly available because of melting ice. The Danish government quickly rebuffed the idea, but the incident could be seen as an acknowledgment of climate change from a leader who has derided global warming as a hoax.

Climate change poses additional security consequences. U.S. military bases at home and abroad have already been strained by destructive hurricanes and flooding that have cost billions of dollars to repair — and extreme weather has stretched thin the disaster response capabilities of the military. When hurricanes hit Florida and Puerto Rico and the East Coast of the United States in 2017 and 2018, the military had to slow the flow of forces to Afghanistan in order to be able to provide relief at home. Meanwhile, troops have to operate in higher temperatures across Asia and the Middle East, where temperatures now regularly are over 100 degrees and face a broader array of infectious diseases.

Florida’s Tyndall Air Force Base incurred billions of dollars in damage from Hurricane Michael in 2018 when winds tore through the roofs of hangars and destroyed buildings. Congress has in recent years directed the Department of Defense to address the climate resilience of military bases and climate risks to operating forces.

“The Department of Defense is beginning to integrate these risks into its strategy plans and plans,” Goodman said.

Another geopolitical threat is migration — whether from low-lying island states that stand to lose fresh water drinking supply or coastal areas susceptible to typhoons. Prolonged drought is believed to contribute to conflicts in the Middle East.

“We know that in Syria the prolonged drought that preceded the civil unrest there was a contributing factor to that unrest, which became instability, which led to the violent extremism, which has become the deadliest civil war in modern times,” she said.

Elsewhere, drought-prone countries are buying up land to grow water-intensive crops in what is called the “virtual water” trade. For example, China has been buying agricultural land in the U.S. and Europe to harvest water-intensive crops such as alfalfa.

Simon Dalby, a professor of geography and environmental studies at Wilfrid Laurier University, told the podcast that the geopolitical consequences can be difficult to predict. He cited the impacts of a 2010 drought in Russia which led the Kremlin to limit wheat exports, setting off a chain reaction.

“International markets panicked. The price went up quickly — and it is indeed suggested that in fact part of the Arab Spring was partly a response to those price fluctuations. So political disturbances across the Middle East might indeed have been related to the drought in Russia, which was probably at least partly caused by climate fluctuations. So this is where we see how dramatically the global economy and the ecology is interconnected,” he said.

The world will need emergency stockpiles of food and disaster relief aid, he said.

And, he noted, while warming may open up certain regions to new agriculture, unpredictable rainfall and flooding can wreak havoc on crops. “This is much trickier than simply saying, ‘Oh because it’s warmer, Russia will do better.’ It’s not that simple,” he said.

Climate change is transforming agriculture itself.

Increased concentration of carbon dioxide in the atmosphere ramps up photosynthesis and makes crops grow more quickly. But the phenomenon has been shown to reduce nutrient density in some crops, like rice. Researchers have begun studying how many people might be at risk for iron or zinc deficiency as a result.

Like governments, businesses are studying how to address long-term risks to their business models, said Gary Litman, vice president for global initiatives at the U.S. Chamber of Commerce.

“We definitely need to prepare, to adjust, to adapt to climate change to mitigate the impact of the industry on climate,” he said. But he added that it’s part of a broader pressure on companies to address long-term environmental sustainability and compete for increasingly scarce resources. “We’re dealing with finite resources. There’s not going to be more cobalt on this planet. There is not going to be new soil on this planet. There is not going to be a new oxygen on this planet,” he said.

He noted that advanced technologies, such as batteries, require rare metals. “You cannot address the climate issue — you cannot prepare, for example, for the rise of the oceans — if you don’t invest in new construction materials. How do you build the dam? If you use the current resources, you’ll run out of gravel before you build anything. If you don’t have access to reliable supply of cobalt, you won’t be able to switch to e-mobility,” he said.

Synagogue Attacker Who Killed Two Had Planned Far Bigger Massacre

German authorities charge suspect with murder after Wednesday’s live-streamed assault in country’s east

BERLIN-—The German man detained after a live-streamed and ultimately botched attack on a synagogue that left two dead in Germany’s east was charged with murder on Thursday after what authorities described as a terror attack.

But as more details about the 27-year-old suspect and his plan emerged, it became clear that Germany had narrowly escaped a far bigger massacre.

Witness accounts, information from authorities and the suspect’s own writings and recorded statements, painted a portrait of a determined extremist who was, by his own admission, ultimately thwarted in his plans for globally broadcast carnage by shoddy preparations.

“What we witnessed yesterday was terror,” General Federal Prosecutor Peter Frank told journalists as he unveiled the charges. The accused, he said, “had intended to cause a massacre.”

Mourners gathered around a makeshift memorial of flowers and candles in the market square in Halle on Thursday, a day after the attack. PHOTO: HENDRIK SCHMIDT/AGENCE FRANCE-PRESSE/GETTY IMAGES

The man, identified by a security official on Wednesday as Stephan Balliet from the state of Saxony-Anhalt, tried and failed to enter the locked gate of the synagogue in the city of Halle around midday on Wednesday, according to authorities and witnesses.

He then turned around, shooting dead a passerby and killing a patron at a fast-food restaurant, streaming the entire episode on the Twitch online service using a camera fixed to his helmet.

The live-streaming of the attack showed the suspect wanted to cause a global impact, Mr. Frank said, following the example of recent attackers such as Australian Brenton Tarrant, who allegedly killed 50 at two mosques in Christchurch, New Zealand. He was inspired by others and wanted to inspire others, Mr. Frank said.

In written documents that security experts said they believed Mr. Balliet had posted online before the assault, the suspect describes his motivations, his tactics and the makeshift weapons he had built to execute his attack.

In the documents, written in English and seen by The Wall Street Journal, the author uses familiar far-right tropes, expressing hatred of Jews, Muslims and liberals. The bulk of the documents, however, detail plans to attack the Halle synagogue and the various handmade guns and explosives created for the operation.

The author lists three objectives:

  1. Prove the viability of improvised weapons,”
  2. Increase the moral [sic] of other suppressed Whites by spreading the combat footage,” and
  3. Kill as many anti-Whites as possible, jews preferred.”

Florence Keen, a research fellow at the International Centre for the Study of Radicalisation and Political Violence in London, said the documents bore similarities to manifestos of other hate-crime perpetrators, including conspiracy theories about alleged threats against whites.

Blyth Crawford, a fellow research fellow at the center, said “the end of the manifesto, detailing his ‘achievements’ and tasks, really exemplifies the ’gamification’ of these kinds of killings.”

The suspect’s reliance on handmade weapons, including two automatic guns and a shotgun, and sketchy planning seems to have played a role in limiting the toll victims.

In a recording of the live-streamed video seen by The Journal, the man can be heard swearing as his guns repeatedly jam and fail to fire. Earlier in the sequence, he expresses surprise at finding the gates of the synagogue locked and frustration after 15 minutes of trying and failing to force his way in.

After the bungled attack, authorities said, the suspect shot dead a woman on the street and drove to a nearby kebab shop where he killed a customer who can be heard on the video crying for his life. The attacker is repeatedly shown aiming at passersby but failing to fire his makeshift guns.

I will die like the loser I am,” he explains at one point, apologizing to viewers for not causing more casualties.

According to German officials, Mr. Balliet killed a 40-year-old German woman from Halle and a 20-year-old German man from Merseburg, who was identified by the fan club of local soccer team HFC as Kevin S.

After a brief shootout with a police car more than 20 minutes into the attack, the suspect drove off, stopping on the outskirts of the city where he tried to swap his car, and shooting and wounding two people in the process, according to a witness.

Kai Henze, 36, owner of an auto shop, Kai’s Garage, in Landsberg, east of Halle, said he was working when he heard a shot outside. Two minutes later, a man entered, pointing a gun and saying he was a wanted criminal, had just shot two people and needed a car.

“I threw him the keys of a taxi that I had just here for repair. Then he said ‘I know you will call the police now, but please give me 10 minutes,’ and threw two €50 bills on the street for me and then quickly drove away with the taxi.”

Mr. Henze said he then attended to the two victims nearby, a couple around 40, before calling the police. Mr. Balliet was arrested soon after.

Details of the suspect are slowly emerging.

Ursula Siebenhüner, 68, from the village of Ahldorf, said Mr. Balliet lived alone with his mother, a teacher, in the neighboring hamlet of Helbra.

A German official who declined to be named said Mr. Balliet had been among the last Germans to do compulsory military service before it was abolished. He had served six months to the end of March 2011 in Hagenow, where he didn’t stand out in any way.

Holger Stahlknecht, state interior minister of Saxony-Anhalt, said the suspect wasn’t known to German intelligence agencies prior to the attack.

A man described as Mr. Balliet’s father told the Bild tabloid that Mr. Balliet had been a loner with few friends and spent most of his time online. “He was always blaming others for everything,” the man said.

Neither Mr. Balliet’s mother nor his father could be reached for comment.

Mr. Balliet faces two murder charges, nine counts of attempted murder and several charges related to other crimes, the prosecutor said.

While the attacker appeared to have acted on his own, authorities said they were still investigating whether he had support or if anyone had prior knowledge of the attack. The suspect was due to appear in the Federal Court of Justice in Karlsruhe later Thursday.

German Justice Minister Christine Lambrecht said the attack had shown that far-right extremism was “one of the biggest threats we are currently facing.”