CONFIDENCE GAME

AN INTERVIEW WITH JAMES RICKARDS

Octavian Report: Could you take us through what you see happening to the monetary system? 

James Rickards: The dollar, the yen, the euro — all are forms of money. I would say gold is a form of money. Bitcoin is a form of money. In times past, feathers and clam shells have been money. One of the criticisms of many  modern forms of money, of central bank money and Bitcoin in particular, is that they are not backed by anything.

I make the point — and I’m not the first one to say this, I actually learned this from Paul Volcker — that it is backed by one thing, which is confidence. Meaning if we have confidence that something is money, then it’s money. If you and I think something’s money, and you’re willing to take it from me in exchange for goods and services, and furthermore you believe that you can give it to someone else in exchange for goods and services and make investments, then it’s money. It functions as money. But the problem with confidence is that it’s fine as long as it lasts, but it’s very fragile and it’s very easily lost. Once it’s lost, it’s impossible to get back, or at least extremely difficult to get back.

When I talk about the collapse of the international monetary system, people think I must be an apocalyptic doom-and-gloomer. End of the world, we’re all going to be living in caves, eating canned goods. I say no, not at all. I don’t think it’s the end of the world, I just think it’s the end of a system that has in fact collapsed three times in the past 100 years. There’s nothing unusual about breakdowns in the international monetary system. When it happens, the major trading financial powers get together, sit around a table, and rewrite what they call the rules of the game. “Rules of the game” is actually a phrase, a term of art in international finance, for the operating system (just to use modern jargon) of the international monetary system.

All I’m doing is looking at the system dynamics. It’s very easy to see the collapse coming based on that, and then ask the question: when the collapse comes, what will the new system look like? That is, what will it look like after the next Bretton Woods, or the next Smithsonian agreement, or for that matter Genoa in 1922? The next time the powers sit around the table, what deal will they come up with? Then I work backwards from that to today, and ask: what can I or should I do with my portfolio now  to prepare for this new deal?

That’s the scenario. Now, I have the view that basically all the central-bank models, all the risk-management models used on Wall Street and in capital markets around the world are obsolete. There are much better tools available today. The three that I use most frequently — not the only three — are complexity theory, behavioral psychology, and causal inference. Causal inference also goes by the name inverse probability, and it’s also known as Bayes’ theorem. Three branches of science: one’s physics, one’s applied mathematics, and one’s social-psychological. That’s my tool kit, along with some other things.

Using those tools, it’s very easy to see the collapse coming for two reasons. One, in complex systems — and I would make the case that capital markets are complex systems nonpareil — the worst thing that you can have happen is an exponential function of scale. Meaning that as you scale up the system, you don’t increase the risk in a linear way, you increase it in an exponential way. To take a simple example, let’s say that J.P. Morgan tripled the gross notional value of its derivatives. You go to Jamie Dimon and say, “Okay, Mr. Dimon, you tripled your balance sheet. How much did the risk go up?” He would say: “Yeah, we tripled the balance sheet, but it’s long, short, long, short, long, short. The longs offset the shorts. You net it down, the actual risk is quite small relative to the gross notional value. That’s not the way to think about it. We tripled the balance sheet, but the risk went up a little bit.”

If you ask the everyday citizen, they would probably use intuition and say, “Well, if you tripled the balance sheet, sounds like you tripled the risk.” The correct answer is that Jamie Dimon’s wrong, and the everyday citizen using intuition is wrong. The correct answer is if you triple the scale of the system, you increase the risk by a factor of 10 or 100, some X-factor based on the slope of the curve, which is a power curve. It’s basically the degree, the distribution of severity and frequency of risk.

You go back to 2008: what did we hear about? Too big to fail, too big to fail, too big to fail. Today, the five largest banks in the United States are bigger than they were in 2008. They have a larger percentage of all the banking assets, and their derivative books are much bigger. Everything that was too big to fail in 2008 is much bigger today. Given the exponential function I just described, the risk is exponentially greater than 2008. Whatever you saw in 2008, get ready. A much bigger collapse is coming. Probably sooner than later.

I was general counsel of Long-Term Capital Management. I negotiated their bailout, so I had a front row seat for that. I was on the phone with the heads of the major banks. Jon Corzine at Goldman Sachs,  Sandy Warner at J.P. Morgan, David Komansky at Merrill Lynch, Herb Allison and others, and Bill McDonough and Gary Gensler from the Treasury in Washington. I basically negotiated that bailout and saw exactly how close the global system came to complete collapse. We were hours away from shutting every stock and bond exchange in the world. Literally hours away, and the bailout got done. Four billion dollars changed hands. The balance sheet was supported. A press release was issued and the crisis passed. But it was extremely close, and not a foregone conclusion at all that we could get that done.

Having witnessed that, and knowing the team at LTCM — we had sixteen Ph.D.s from MIT, Harvard, Chicago, Stanford, and Yale, and two Nobel Prize winners — I said, well, if the smartest people in the world in this field with 160-plus IQ’s can get it that badly wrong, they must be missing something. There must be something wrong with the theory, because they’re not stupid. Nobody likes to lose their own money, so there must be something wrong with the theory.

I spent the next 10 years working on this, about five years figuring out what was wrong, where the flaws were, and another five years figuring out what actually works to remedy them. I refined my models enough that in 2005 and 2006 I was warning people that a collapse was coming again. That it would be worse.

Now, I didn’t say, Bear Stearns’ hedge fund is going to fail at the end of July 2007. I didn’t say that Lehman Brothers was going to collapse in mid-September 2008. It wasn’t necessary. It was sufficient to say that the collapse was coming because none of the lessons of 1998 had been learned. I’m in the same state today: the lessons of 2008 have not been learned. I’m watching the dynamics, I’m watching it play out, and you can see the next collapse coming. Here’s the tempo. In 1998, Wall Street bailed out a hedge fund to save the world. In 2008, central banks bailed out Wall Street to save the world. Move forward 10 years — let’s say 2018, to pick a number — and who’s going to bail out the central banks? Each bailout gets bigger than the one before. Each collapse is bigger than the one before, which is exactly what complexity theory would forecast based on the scaling metrics and the dynamics I described.

So who bails out the central banks? There’s only one clean balance sheet left in the world. There’s only one source of liquidity. After all, the Fed took their balance sheet from $800 billion approximately in 2008 to a little over $4 trillion dollars today. The problem is they haven’t normalized. Now that the crisis is long over, they haven’t gone back to the $800-billion-dollar level, which would be a more normal balance sheet. They stayed at $4 trillion; they’re stuck there. They’re not doing more QE, but they are rolling over what they have and they can’t reduce the size of the balance sheet.

What are they going to do in the next crisis? Go to $8 trillion? To $12 trillion? What is the outer boundary of how much money they can actually print? Legally, there is no boundary. They could actually print $12 trillion if they wanted to. At some point, however, you cross this intangible, invisible confidence boundary that I described earlier — and that goes back to the original problem of confidence in any form of money. And all the other central banks are in the same situation. The People’s Bank of China, the Bank of England, the Bank of Japan, the European Central Bank. It’s not unique to the U.S. If the central banks don’t have the wherewithal to liquefy the world in the next panic, and if the next panic is coming and you can see it a mile away, where will the liquidity come from? There’s only one source of liquidity left in the world, which is the IMF. They can print world money, which are the special drawing rights or SDRs.

When you get to the endgame, they’re going to have to print trillions of SDRs (each SDR is worth about $1.50) to re-liquefy the world in a global financial panic. Will that work? In theory it could work, but I expect if it works, it will only be because nobody understands it, like something’s happening and, as Bob Dylan sang in “Ballad of a Thin Man,” “Something’s happening here and you don’t know what it is.” At best, it will be highly inflationary.

Now, maybe it won’t work. Maybe people will say, “I’ve lost confidence in Federal Reserve money and European Central Bank money and Bank of Japan money. Why should I have any more confidence in IMF money? It’s just another form of currency, and I’ve lost confidence in all of them and I’m going to go get some gold.”  If that actually happens, the world may have to go to a gold standard. Now, I guarantee there’s not a central bank in the world that wants a gold standard. They may have to go to one, not because they want to, but because they have no choice, because it’s the only way to restore confidence. That raises an interesting question: if you go to a gold standard, what’s the price of gold? I talk about this in The New Case for Gold, about the blunder of 1925 with Churchill taking the U.K. back to a gold standard at a price that Keynes warned him was deflationary. Keynes didn’t favor a gold standard at the time. He did in 1944 and he did in 1914. He didn’t in 1925, but he did tell Churchill if you’re going to do this, you need a much higher price to avoid deflation. Churchill ignored him and threw the U.K. into a depression.

So question is: what is the implied non-deflationary price of gold today? I’ll use M1 of China, U.S., and the ECB, just as a frame. The answer’s $10,000 now if you have 40 percent backing — and over $50,000 if you have 100 percent backing of M2, which is a broader money supply. I don’t think you have to use M2. I don’t think you need 100 percent. It’s a judgement that’s debatable. But even on the modest assumptions of M1 using 40 percent backing, gold would have to be $10,000 an ounce to support the money supply. You may or may not have a gold standard, but if you do gold will be $10,000 an ounce.

Now, if you don’t, if the SDR thing actually works, gold will get to $10,000 an ounce the other way, which is inflation. Gold is going to shoot much higher. In the SDR scenario it will shoot much higher because of inflation, and in the gold-standard scenario it will shoot much higher because it has to, to avoid deflation. It’s not really the price of gold going up, it’s the devaluation of the paper currency. It’s the same thing. The dollar price of gold is just the inverse of the value of the dollar.

OR: Why do you say gold has to be part of a new system? What do you say to the people who think it’s an anachronism?

Rickards: The flaw in that — and I think this is one of the biggest problems today, and certainly an issue with everyone from Milton Friedman to Janet Yellen — is that they take confidence for granted. If you assume that confidence in paper money is infinitely elastic, then there’s no reason why the money supply cannot be infinitely elastic.

There are a lot of gold bashers out there who will be very quick to tell you that gold’s a barbarous relic, blah blah blah. But there are some more thoughtful people out there, among whom I would include Stephanie Kelton, Warren Mosler, Richard Duncan, and others. They’re all different, but they’re smart people. I’ve met a lot of them. Paul McCulley, formerly of PIMCO and a close associate of Bill Gross. They call themselves modern monetary theorists.

I think Adair Turner is coming out this way in his new book, Between Debt and the Devil, and even Larry Summers in some ways. What they’re saying is that there’s nothing you cannot print yourself out of. You get too much deflation? Print more money. Deflation won’t go away? Print more. People won’t spend? The government can spend. Maybe you cannot force people to spend it, but the government loves to spend money, they know how to do that really well. If it increases the deficit, so what? Just issue more debt to cover the deficit, and if people don’t want your debt, the central bank can buy it. Don’t worry about paying it back because the central bank can convert the treasury bonds into perpetual bonds. The whole thing just goes away. You don’t have to worry about the national debtthe Fed can just buy the whole $19 trillion of it, sock it away on their balance sheet, make it a perpetual note, and go play golf. What’s the problem?

This is sometimes called “helicopter money.” It’s called “people’s QE” by Jeremy Corbyn, it’s called “fiscal dominance” by Rick Mishkin. It has different names, but it always says the same thing: there’s no outer boundary on how much money you can print, so what’s the problem?

My thesis — and here I’ll flip over to the behavioral-psychology side a little bit — is that it’s not a problem until it is. In other words, confidence can be sustained until it can’t. You can lose this very quickly, so I don’t believe that confidence is infinitely elastic. There’s nothing in human nature or history that says that. If you’re relying on confidence to say that money can be infinitely elastic, then you’re wrong. The concern is that the elites will go down this road — having been wrong about the wealth effect, about QE1, QE2, and QE3, about Operation Twist — and then they’ll somehow wake up and see they’re wrong again. But they’ll find out the hard way because confidence in the entire system will collapse. At which point, your only two remedies are SDRs and gold.

OR: What’s your take on central banks and gold?

Rickards: With regard to central banks and gold, I always say watch what they do, not what they say. If the U.S. has a budget problem, and we’re sitting on about $380 billion in gold, why don’t you just sell the gold and get some money? That’s what Canada did. That’s what the U.K. did. Why are we hanging onto it?

The question answers itself. Obviously, it has some value. Obviously, it has some role in the monetary system. In my book, I write about a discovery I made — one of those discoveries that’s hiding in plain sight. I had been working on a thesis that the Fed is, at least on occasion, insolvent. My basis for that was to look at the Fed’s balance sheet. They’re leveraged today about 113 to one. That’s unheard of. I’ve been in the hedge-fund business, I’ve been in the investment-banking business, I’ve been in the banking business for decades. Banks leverage maybe 12 to one, broker-dealers and investment banks leverage maybe 15 to one, a hedge fund will lever two or three to one (although that’s getting a little risky). Even Long-Term Capital Management was never leveraged more than 20 to one, and we were very aggressive about leverage. 113 to one is way, way off the charts.

Now, just to be clear, the Fed does not mark its value sheet to market. My thought experiment is: what if they did? There’s a lot of data out there about the composition of the bond holdings of the Fed, particularly those held at the New York Fed. It’s not difficult to get that information, to do some bond math, and mark it to market. Doing that, I discovered that they were in fact insolvent at various times along the way. I had this conversation with several Fed officials. One member of the board of governors, another individual who was not a member of the board, but a very, very close advisor to Bernanke and Yellen, a true insider, a Ph.D. economist, a friend of mine. I was able to have this conversation with him. Interestingly, the member of the board of governors more or less conceded my point, but her rejoinder was, “Well, maybe we’re insolvent, but it doesn’t matter.” In other words, central banks don’t need capital. That’s a point of view.

The other conversation was with the insider: he was adamant that they’ve never been insolvent, ever. Regardless of bond-market moves. He wouldn’t tell me why, so I got to thinking about it. I went back to the balance sheet to see what I was missing. And lo and behold, there was this gold item valued at $42 an ounce. I said, “Well I should mark that to market. If I’m going to mark the bonds to market, I need to mark the gold to market.”

Now, as I was doing this I noticed a couple things. The Fed’s gold holdings are approximately 8,000 tons exactly. Close to exactly the amount held by the U.S. Treasury. In intelligence work, the first rule is there are no coincidences, and this non-coincidence explains why the Treasury stopped selling gold in 1980. Bven as late as the late 70’s, the Treasury was still dumping gold to suppress the price. That’s not speculation; there’s declassified correspondence among President Ford, Henry Kissinger, Arthur Burns, and the Chancellor of Germany that lays this out. The Treasury was actually dumping thousands of tons of gold in the late 1970s, but then in 1980 it just stopped on a dime. The U.S. has sold almost no gold since. Instead, we got everyone else to dump their gold. We got the U.K. to dump six hundred tons in the beginning of 1999. We got Switzerland to dump over a thousand tons in the early 2000s. We got the IMF to dump four hundred tons in 2010. The U.S. has been prevailing upon all these other people to sell their gold, but we won’t sell any ourselves. Why? They can’t. The Treasury has to hold the gold they’ve got in order to honor, on legal and constitutional grounds, the certificate held by the Fed. This was received in exchange for the gold (with an explicit guarantee that the gold was there to backstop the Fed’s balance sheet).

So I was wrong the first time. The Fed has never been insolvent; my insider friend was correct. The reason I was wrong was not because of the bond portfolio, which would have made them insolvent, but because of the gold, which adds about $350 billion to the balance sheet. When you add that to capital on a mark-to-market basis, the leverage ratio drops from 113 to one to about 13 to one, which is pretty healthy for a normal bank. On top of everything else we’re discussing, you find that the Federal Reserve has a hidden asset, which is the value of gold, and that it’s well capitalized — if you count the gold. What does it mean when central bankers and public officials disparage gold, tell you it’s an anachronism, tell you it’s a tradition, tell you it’s a barbarous relic, tell you that you’re a fool to own it — and yet they themselves are propped up and made solvent by gold?

OR: More and more physical gold is leaving the tradable system as China and Russia stockpile it, yet huge derivatives are still being written on it. Can you talk about that disconnect?

Rickards: Well, there is a world of paper gold and there’s a world of physical gold. Now, paper gold to me is not paper gold. It’s paper, but it references the price of gold. There’s not going to be any actual large difference between the paper price and the physical price quoted whether it’s in London or Beijing, because of the arbitrages.

I just recently returned from Switzerland where I met with the head of the country’s biggest gold refinery, who told me that he’s seeing severe shortages in supply. This guy, he knows who all the big sellers are, he knows who all the big buyers are because he’s the biggest gold refiner and he takes it in and ships it out. He knows who all the players are and this is, again, in the physical world. He said that with regard to his selling side, he has more demand than he can handle. He’s sending the Chinese 10 tons a week; they want 20 tons. He won’t provide it because he doesn’t have that much gold and he has other customers to take care of.

The physical shortages are already showing up and they’re getting worse. I’ve heard similar things from wholesale dealers — people who deal directly with London Bullion Market Association members and Comex-approved warehouses. These are the large holders of gold in the world, and they are saying that it is taking longer and longer to fill deliveries. The supply situation is stretched and probably about to break.

Meanwhile, the paper gold market continues to expand with 100-to-one leverage. Warehouses continue to get drawn down, contracts continue to be written. You have a very, very large inverted pyramid, with a broad base of paper gold on top and a tiny sliver of physical gold supporting the whole thing. It’s becoming wobbly, and it’s about to tip over.

Any break in that market — coming back to the issue of confidence — would lead directly to what I would call the mother of all short squeezes and a buying panic. What would I mean by a break? Well, most likely a failure to deliver. Suppose some dealer, some large bank, some exchange, some intermediary somewhere has sold a lot of paper gold and has been called upon by the buyers to deliver. They say, “I don’t want to roll over my contract, I don’t want cash settlement, I want the gold, please. Give me the gold.”

They’re not going to be able to get it. That failure will become public, because it always does, and will create a crisis of confidence. Everyone will run down to their dealers, their exchanges, and their brokers all at once and say, “Give me my gold!”  They’ll then discover that there’s only about one percent of what’s needed to fulfill that demand, and there’s nowhere near enough gold in the world at anything close to today’s prices (even if you could find it, which you probably will not be able to) to satisfy those contracts.

What would happen next? The answer is that, since you cannot deliver the gold, you’re going to have to terminate the contract, and it will come as a surprise to a lot of paper gold buyers that such terminations are totally legal. If you actually read the contracts gold buyers sign you’ll find what are called force majeure clauses or material adverse change clauses, meaning gold exchanges have the power to suspend delivery.  There’s also what’s called trading for liquidation only, which means you can roll over your contract or close it out, but you cannot take delivery. They have emergency powers to do, really, whatever they want to maintain orderly markets. So what they’ll do is they’ll terminate all these contracts using these contractual and governance provisions. They won’t steal your money, they’ll send you a cash settlement for yesterday’s price. But meanwhile the price of gold today will be going up $200, $300, $400, $500 an ounce. Day after day you’ll be sitting there, watching the exact hyperbolic price movements that were the reason you bought the gold in the first place — and you will not be participating in them.

You will be closed out at exactly the time when you most want the contract. That always happens. That’s the conditional correlation effect. The time you most want it is the time you won’t have it, because it doesn’t work for the other guy. They close you out, send you a check for yesterday’s price, and you’ll miss the move. And by the way, even if you want to jump back in, you won’t be able to buy any. Dealers will be sold out, mints will be backlogged, refiners will be backlogged. They won’t even take your calls. That’s what my friend in Switzerland told me. He said if I didn’t know you and you weren’t already a customer, I wouldn’t take your call. I’m not taking any new business because I cannot supply it.

OR: Can you talk about the so-called war on cash and the potential confiscation of gold?

Rickards: The war on cash is over. The government won. We hear about the cashless society and I think Sweden may be the first to get there. Others are considering it. Larry Summers writes an op-ed on abolishing the 100-dollar bill, and there’s a movement in Europe to get rid of the 500-euro note, so there are a lot of significant legal and political trends against cash. It’s really irrelevant, because we don’t use cash anywhere. You might have a few bucks in your wallet, but people get their paychecks from direct deposit, they get their retirement checks from direct deposit, they pay their bills online, they use their credit cards, they use their debit cards, and there hasn’t been a paper Treasury security issue, I think, since the late 1970’s. The dollar is already a digital currency, and so are all the other major currencies.

To the extent we have any paper money at all, it’s a token. To the point where you buy a two-dollar candy bar, you don’t even reach in your pocket and get out a five, you just swipe your debit card. We already live in a world of digital currencies, with respect to the dollar, the major currencies.

People say, “Yeah, but it’s still legal. I can go down to the bank and get $10,000 or $20,000 and stick it in a safe to avoid negative interest rates or have it for an emergency.” They’re wrong. It’s not that easy. If you go actually do it, actually go down to the bank and ask them for $15,000 or $20,000, you will be treated like a drug dealer or a tax evader. Some banks will tell you to come back in a couple days, that they have to order the cash. There’ll be reams of paperwork to fill out. They’ll file a report with the Treasury.

People are kidding themselves about the ease with which they can get cash. They are locked into a digital system. The war on cash is over and the government won. That’s just the prelude to negative interest rates. It’s like slaughtering pigs: you don’t chase the pigs around a field. You get them into a pen and then you slaughter them. What’s happening with savers is that everyone’s being rounded up into one of four or five digital pens, i.e. Citi and J.P. Morgan and Wells Fargo, and they’re going to be led to the slaughterhouse of negative interest rates.

OR: Do you think we are seeing a currency war going on internationally at the moment?

Rickards: About currency wars, let me say I’m always amused when I see a journalist or someone write a story saying “Oh gee, there’s a currency war. Look at this. China’s weakening against the yen.” I make the point that the most recent currency war started in 2010. I talk about it in my book on the subject which came out in 2011. It’s the same currency war. Wars consist of many battles, wars are not continuous fighting all the time. There are big battles and little battles; there are quiet periods and then a new battle erupts. You have an occasional D-Day or Battle of the Bulge, but some episodes are more intense than others.

Currency wars are the same. There are quiet periods, but it’s the same war. What I call Currency War One lasted from 1921 to 1936. What I call Currency War Two lasted from 1967 to 1987. I make the point that the world is not always in a currency war, but when we are they can go on for a very long time because they have no logical conclusion. It’s just back and forth, with a race to the bottom via competitive devaluations. The only conclusion to a currency war is either systemic reform or systemic collapse. Either the system breaks down completely or people get together, as they did at the Plaza Hotel in 1985, to give the system some coherence.

I don’t see the leadership, I don’t see the giants today. I don’t see people like James Baker, Bob Rubin, George Schultz, or John Maynard Keynes. I don’t see people like that on the landscape. I see a lot of people not of that stature in positions of power. I don’t see any awareness that this collapse is coming. So given the two possible outcomes — systemic reform or systemic collapse — I think systemic collapse is the more likely. But we are in a currency war and have been since 2010. We will be perhaps until 2025. Unless the system collapses earlier, which is what I expect.

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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.
14:26
There’s a mother, father, sister, brother safe house operator, car driver, cook.
14:32
Somebody in that social network who knows enough about the attack and they’re like,
14:36
if I had $5,000, I could make 50, just buy a put option.
14:40
The crooks and terrorists, they always go to options because they have the most leverage,
14:44
and the SEC knows where to look.
14:47
So that’s how it happens.
14:49
And then the question was, could you detect it.
14:52
So we started out.
14:53
There are about 6,000 tickers on the New York Stock Exchange and the NASDAQ.
14:57
And we’re talking about second by second data for years on 6,000 tickers.
15:03
That’s an enormous, almost unmanageable amount of data.
15:06
So what we did is we reduced the targets.
15:08
We said, well, look, there’s not going to be any impact on Ben and Jerry’s ice cream
15:12
if there’s a terrorist attack.
15:14
You’re looking at cruise ships, amusement parks, hotels, landmark buildings.
15:18
there’s a set of stocks that would be most effective.
15:22
So we’re able to narrow it down to about 400 tickers, which is much more manageable.
15:26
Second thing you do, you establish a baseline.
15:28
Say, what’s the normal volatility, the normal average daily volume, normal correlation in
15:35
the stock market.
15:36
So-called beta and so forth.
15:37
And then you look for abnormalities.
15:39
So the stock market’s up.
15:42
The transportation sector is up.
15:43
Airlines are up, but one airline is down.
15:46
What’s up with that?
15:47
So that’s the anomaly you look for.
15:48
And then the third thing you do.
15:49
You look for news.
15:50
Well, OK, the CEO just resigned because of some scandal.
15:54
OK, got it, that would explain why the stock is down.
15:57
But when you see the anomalous behavior, and there’s no news, your reference is, somebody
16:03
knows something I don’t.
16:04
People aren’t stupid, they’re not crazy.
16:06
There’s a reason for that, just not public.
16:08
That’s the red flag.
16:09
And then you start to, OK, we’re in the target zone.
16:12
We’re in these 400 stocks most affected.
16:15
We see this anomalous behavior.
16:17
Somebody is taking a short position while the market is up and there’s no news.
16:21
That gets you a red light.
16:23
And then you drill down.
16:24
You use what in intelligence work we call all source fusion, and say, well, gee, is
16:28
there some pocket litter from a prisoner picked up in Pakistan that says cruise ships or something
16:34
along– you sort of get intelligence from all sources at that point drilled down So
16:38
that was the project.
16:40
We built a working model.
16:41
It worked fine.
16:42
It actually worked better than we expected.
16:44
I told the agency, I said, well, we’ll build you a go-kart, but if you want a Rolls Royce,
16:48
that’s going to be a little more expensive.
16:50
The go-kart actually worked like a Rolls Royce.
16:52
Got a direct hit in August 2006.
16:55
We were getting a flashing red signal on American Airlines three days before MI5 and New Scotland
17:04
Yard took down that liquid bomb attack that were going to blow up 10 planes in midair
17:09
with mostly Americans aboard.
17:11
So it probably would have killed 3,000 Americans on American Airlines and Delta and other flights
17:16
flying from Heathrow to New York.
17:18
That plot was taken down.
17:20
But again, we had that signal based on– and they made hundreds of arrests in this neighborhood
17:26
in London.
17:27
So this worked perfectly.
17:30
Unfortunately, the agency had their own reasons for not taking it forward.
17:37
They were worried about headline risk, they were worried about political risk.
17:41
You say, well, we were using all open source information.
17:45
You can pay the Chicago Mercantile Exchange for data feed to the New York Stock Exchange.
17:48
This is stuff that anybody can get.
17:49
You might to pay for it, but you can get it.
17:52
But the agency was afraid of the New York Times headline, CIA trolls through 401(k)
17:58
accounts, which we were not doing.
18:00
It was during the time of waterboarding and all that, and they decided not to pursue the
18:06
project.
18:07
So I let it go, there were plenty of other things to do.
18:09
And then as time went on, a few years later, I ended up in Bahrain at a wargame– financial
18:14
war game– with a lot of thinkers and subject matter experts from around the world.
18:20
Ran into a great guy named Kevin Massengill, a former Army Ranger retired Major in the
18:27
US army, who was working for Raytheon in the area at the time was part of this war game.
18:32
We were sort of the two American, little more out of the box thinkers, if you want to put
18:36
it that way.
18:38
We hit it off and I took talked him through this project I just described.
18:42
And we said, well look, if the government doesn’t want to do it, why don’t we do it
18:45
privately?
18:46
Why don’t we start a company to do this?
18:47
And that’s exactly what we did.
18:49
Our company is, as I mentioned, Meraglim.
18:51
Our website, Meraglim.com, and our product is Raven.
18:55
So the question is, OK, you had a successful pilot project with the CIA.
19:01
It worked.
19:02
By the way, this is a new branch of intelligence in the intelligence.
19:06
I-N-T, INT, is short for intelligence.
19:08
And depending on the source, you have SIGINT, which is signal intelligence, you have HUMINT
19:14
which is human intelligence, and a number of others.
19:17
We created a new field called MARKINT, which is market intelligence.
19:20
How can you use market data to predict things that are happening.
19:24
So this was the origin of it.
19:26
We privatized it, got some great scientists on board.
19:30
We’re building this out ourselves.
19:31
Who partnered with IBM, and IBM’s Watson, which is the greatest, most powerful plain
19:38
language processor.
19:40
Watson can read literally millions of pages of documents– 10-Ks, 10-Qs, AKs, speeches,
19:47
press releases, news reports.
19:51
More than a million analysts could read on their own, let alone any individual, and process
19:57
that in plain language.
19:58
And that’s one of our important technology partners in this.
20:02
And we have others.
20:04
What do we actually do?
20:07
What’s the science behind this.
20:09
First of all, just spend a minute on what Wall Street does and what most analysts do,
20:13
because it’s badly flawed.
20:15
It’s no surprise that– every year, the Fed does a one year forward forecast.
20:22
So in 2009, they predict 2010.
20:24
In 2010, they predict 2011.
20:27
So on.
20:28
Same thing for the IMF, same thing for Wall Street.
20:30
They are off by orders of magnitude year after year.
20:34
I mean, how can you be wrong by a lot eight years in a row, and then have any credibility?
20:38
And again, the same thing with Wall Street.
20:41
You see these charts.
20:43
And the charts show the actual path of interest rates or the actual path of growth.
20:48
And then along the timeline, which is the x-axis, they’ll show what people were predicting
20:52
at various times.
20:54
The predictions are always way off the actual path.
20:57
There’s actually good social science research that shows that economists do worse than trained
21:02
monkeys on terms of forecasting.
21:04
And I don’t say that in a disparaging way– here’s the science.
21:07
A monkey knows nothing.
21:08
So if you have a binary outcome– up, down, high, low, growth, recession– and you ask
21:17
a monkey, they’re going to be right half the time and wrong half the time, because they
21:20
don’t know what they’re doing.
21:21
So you’re to get a random outcome.
21:24
Economists are actually wrong more than half the time for two reasons.
21:28
One, their models are flawed.
21:29
Number two, what’s called herding or group behavior.
21:32
An economist would rather be wrong in the pack than go out on a limb and maybe be right,
21:37
but if it turns out you’re not right, you’re exposed.
21:40
But there are institutional constraints.
21:42
People want to protect their jobs.
21:44
They’re worried about other things than getting it right.
21:47
So the forecasting market is pretty bad.
21:48
The reasons for that– they use equilibrium models.
21:52
The capital markets are not in equilibrium system, so forget your equal equilibrium model.
21:57
They use the efficient market hypothesis, which is all the information is out there,
22:01
you can’t beat the market.
22:02
Markets are not efficient, we know that.
22:05
They use stress tests, which are flawed, because they’re based on the past, but we’re outside
22:12
the past.
22:13
The future could be extremely different.
22:16
They look at 9/11, they look at long term capital management, they look at the tequila
22:20
crisis.
22:21
Fine, but if the next crisis is worse, there’s nothing in that history that’s going to tell
22:25
you how bad it can get.
22:27
And so they assume prices move continuously and smoothly.
22:30
So price can go from here to here or from here to here.
22:34
But as a trader, you can get out anywhere in between, and that’s for all these portfolio
22:38
insurance models and stop losses come from.
22:41
That’s not how markets behave.
22:42
That go like this– they just gap up.
22:44
They don’t hit those in between points.
22:45
Or they gap down.
22:46
You’re way underwater, or you missed a profit opportunity before you even knew it.
22:51
So in other words, the actual behavior of markets is completely at odds with all the
22:56
models that they use.
22:57
So it’s no surprise the forecasting is wrong.
23:00
So what are the good models?
23:01
What are the models that do work?
23:03
What is the good science?
23:04
The first thing is complexity theory.
23:07
Complexity theory has a long pedigree in physics, meteorology, seismology, forest fire management,
23:13
traffic, lots of fields where it’s been applied with a lot of success.
23:18
Capital markets are complex systems.
23:20
The four hallmarks of a complex system.
23:24
One is their diversity of actors, sure.
23:26
Two is their interaction– are the actors talking to each other or are they all sort
23:30
of in their separate cages.
23:31
Well, there’s plenty of interaction.
23:33
Is there communication and is there adaptive behavior?
23:37
So yeah, there are diverse actors, there’s communication.
23:40
They’re interacting.
23:42
And if you’re losing money, you better change your behavior quickly.
23:45
That’s an example of adaptive behavior.
23:47
So capital markets are four for four in terms of what makes a complex system.
23:51
So why not just take complexity science and bring it over to capital markets?
23:55
That’s what we’ve done, and we’re getting fantastic results.
23:57
So that’s the first thing.
23:58
The second thing we use is something called Bayesian statistics.
24:03
It’s basically a mathematical model that you use when you don’t have enough data.
24:08
So for example, if I’ve got a million bits of data, yeah, do your correlations and regressions,
24:14
that’s fine.
24:15
And I learned this at the CIA, this is the problem we confronted after 9/11.
24:19
We had one data point– 9/11.
24:20
Janet Yellen would say, wait for 10 more attacks, and 30,000 dead, and then we’ll have a time
24:26
series and we can figure this out.
24:28
No.
24:29
To paraphrase Don Rumsfeld, you go to war with the data you have.
24:33
And so what you use is this kind of inferential method.
24:37
And the reason statisticians dislike it is because you start with a guess.
24:41
But it could be a smart guess, it could be an informed guess.
24:44
The data may be scarce.
24:45
You make the best guess you can.
24:47
And if you have no information at all, just make it 50/50.
24:50
Maybe Fed is going to raise rates, maybe they’re not.
24:53
I think we do better than that on the Fed.
24:55
But if you didn’t have any information, you just do 50/50.
24:58
But then what you do is you observe phenomena after the initial hypothesis, and then you
25:05
update the original hypothesis based on the subsequent data.
25:07
You ask yourself, OK this thing happened later.
25:10
What is the conditional correlation that the second thing would happen if the first thing
25:14
were true or not?
25:16
And then based on that, you’d go back, and you either increase the probability of the
25:19
hypothesis being correct, or you decrease it.
25:21
It gets low enough, you abandon it, try something else.
25:24
If it gets high enough, now you can be a lot more confident in your prediction.
25:27
So that’s Bayesian statistic.
25:29
You use it to find missing aircraft, hunt submarines.
25:32
It’s used for a lot of things, but you can use it in capital markets.
25:36
Third thing, behavioral psychology.
25:38
This has been pretty well vetted.
25:40
I think most economists are familiar with it, even though they don’t use it very much.
25:43
But humans turn out to be a bundle of biases.
25:48
We have anchoring bias, we get an idea in our heads, and we can’t change it.
25:52
We have recency bias.
25:54
We tend to be influenced by the last thing we heard.
25:57
And anchoring bias is the opposite, we tend to be influenced by something we heard a long
26:01
time ago.
26:03
Recency bias and anchoring bias are completely different, but they’re both true.
26:07
This is how you have to get your mind around all these contradictions.
26:11
But when you work through that, people make mistakes or exhibit bias, it turns out, in
26:16
very predictable ways.
26:18
So factor that in.
26:19
And then the fourth thing we use, and economists really hate this, is history.
26:23
But history is a very valuable teacher.
26:26
So those four areas, complexity theory, Bayesian statistics, behavioral psychology, and history
26:33
are the branches of science that we use.
26:35
Now what do we do with it?
26:37
Well, we take it and we put it into something that would look like a pretty normal neural
26:41
network.
26:42
You have nodes and edges and some influence in this direction, some have a feedback loop,
26:47
some influence in another direction, some are influenced by others, et cetera.
26:51
So for Fed policy for example, you’d set these nodes, and it would include the things I mentioned
26:55
earlier– inflation, deflation, job creation, economic growth, capacity, what’s going on
27:02
in Europe, et cetera.
27:03
Those will be nodes and there will be influences.
27:05
But then inside the node, that’s the secret sauce.
27:08
That’s where we have the mathematics, including some of the things I mentioned.
27:12
But then you say, OK, well, how do you populate these nodes?
27:15
You’ve got math in there, you’ve got equations, but where’s the news come from?
27:19
That’s where Watson comes in.
27:20
Watson’s reading all these records, feeding the nodes, they’re pulsing, they’re putting
27:24
input.
27:25
And then we have these actionable cells.
27:26
So the euro-dollar cross rate, the Yuandollar cross rate, yen, major benchmark, bonds, yields
27:36
on 10 year treasury notes, bunds, JGBs, et cetera.
27:41
These are sort of macro indicators, but the major benchmark bond indices, the major currency
27:46
across rates, the major policy rates, which are the short term central bank rates.
27:50
And a basket of commodities– oil, gold, and a few others– they are the things we watch.
27:55
We use these neural networks I described, but they’re not just kind of linear or conventional
28:06
equilibrium models.
28:07
They’re based on the science I describe.
28:09
So all that good science, bringing it to a new field, which is capital markets, using
28:13
what’s called fuzzy cognition, neural networks, populating with Watson, this is what we do.
28:19
We’re very excited about it, getting great results.
28:21
And this is what I use.
28:23
When I give a speech or write a book or write an article, and I’m making forecast.
28:28
This is what’s behind it.
28:32
So we talked earlier about business cycles, recessions, depressions.
28:37
And that’s conventional economic analysis.
28:40
My definition of depression is not exactly conventional, but that’s really thinking in
28:44
terms of growth, trend growth, below trend growth, business cycles, et cetera.
28:50
Collapse or financial panic is something different.
28:52
A financial panic is not the same as a recession or a turn in the business cycle.
28:57
They can go together, but they don’t have to.
28:59
So let’s talk about financial panics as a separate category away from the business cycle
29:04
and growth, which we talked about earlier.
29:06
Our science, the science I use, the science that we use with Raven, at our company, Meraglim,
29:12
involves complexity theory.
29:14
Well, complexity theory shows that the worst thing that can happen in a system is an exponential
29:21
function of scale.
29:23
Scale is just how big is it.
29:24
Now you have to talk about your scaling metrics.
29:27
We’re talking about the gross notional value derivatives.
29:28
We’re talking about average daily volume on the stock market.
29:31
We’re talking about debt.
29:33
We could be talking about all of those things.
29:35
This is new science, so I think it will be years of empirics to make this more precise.
29:39
But the theory is good, and you can apply it in a sort of rough and ready way.
29:43
So you go to Jamie Dimon, and you say, OK, Jamie, you’ve tripled your gross notional
29:50
value derivatives.
29:51
You’ve tripled your derivatives book.
29:53
How much did the risk go up?
29:54
Well, he would say, not at all, because yeah, gross national value is triple, but who cares?
29:59
It’s long, short, long, short, long, short, long, short.
30:01
You net it all down.
30:02
It’s just a little bit of risk.
30:04
Risk didn’t go up at all.
30:06
If you ask my 87-year-old mother, who is not an economist, but she’s a very smart lady,
30:10
say, hey mom, I tripled the system, how much did the risk go up?
30:14
She would probably use intuition and say, well, probably triple.
30:17
Jamie Dimon is wrong, my mother is wrong.
30:21
It’s not the net, it’s the gross.
30:22
And it’s not linear, it’s exponential.
30:24
In other words, if you triple the system, the growth went up by a factor of 10, 50,
30:28
et cetera.
30:29
There’s some exponential function associated with that.
30:32
So people think, well gee, in 2008, we learned our lesson.
30:36
We’ve got debt under control, we’ve got derivatives under control.
30:39
No.
30:40
Debt is much higher.
30:41
Debt to GDP ratios are much worse.
30:44
Total notional value, gross notional values of derivatives is much higher.
30:47
Now people look at the BIS statistics and say, well, the banks, actually, gross national
30:52
value derivatives has been going down, which it has, but that’s misleading because they’re
30:57
taking a lot of that, moving it over to clearing houses.
30:59
So it’s never been on the balance sheet, it’s always been off balance sheet.
31:02
But even if you use the footnotes, that number has gone down for banks, but that’s only because
31:07
they’re putting it over clearing houses.
31:09
Who’s guaranteeing the clearing house?
31:10
The risk hasn’t gone away, it’s just been moved around.
31:12
So given those metrics– debt, derivatives, and other indices, concentration, the fact
31:21
that the five largest banks in America have a higher percentage of total banking assets
31:26
than they did in 2008, there’s more concentration– that’s another risk factor.
31:31
Taking that all into account, you can say that the next crisis will be exponentially
31:37
worse than the last one.
31:38
That’s an objective statement based on complexity theory.
31:41
So you either have to believe that we’re never going to have a crisis.
31:44
Well, you had one in 1987, you had one in 1994, you had one in 1998.
31:49
You had the dotcom crash in 2000, mortgage crash in 2007, Lehman in 2008.
31:55
Don’t tell me these things don’t happen.
31:56
They happen every five, six, seven years.
31:59
It’s been 10 years since the last one.
32:02
Doesn’t mean it happens tomorrow, but nobody should be surprised if it does.
32:05
So the point is this crisis is coming because they always come, and it will be exponentially
32:11
worse because of the scaling metrics I mentioned.
32:14
Who’s ready for that?
32:15
Well, the central banks aren’t ready.
32:17
In 1998, Wall Street bailed out a hedge fund long term capital.
32:23
In 2008, the central banks bailed out Wall Street.
32:25
Lehman– but Morgan Stanley was ready to fail, Goldman was ready to fail, et cetera.
32:31
In 2018, 2019, sooner than later, who’s going to bail out the central banks?
32:35
And notice, the problem has never gone away.
32:37
We just get bigger bailouts at a higher level.
32:40
What’s bigger than the central banks?
32:42
Who can bail out the central banks?
32:43
There’s only one institution, one balance sheet in the world they can do that, which
32:46
is the IMF.
32:48
The IMF actually prints their own money.
32:51
The SDR, special drawing right, SDR is not the out strawberry daiquiri on the rocks,
32:55
it’s a special drawing right.
32:56
It’s world money, that’s the easiest way to think about it.
32:58
They do have a printing press.
33:00
And so that will be the only source of liquidity in the next crisis, because the central banks,
33:07
if they don’t normalize before the crisis– and it looks like they won’t be able to, they’re
33:11
going to run out of runway, and they can expand the balance sheet beyond the small amount
33:17
because they’ll destroy confidence, where does the liquidity come from?
33:20
The answer, it comes from the IMF.
33:23
So that’s the kind of global monetary reset, the GMR, global monetary resety.
33:28
You hear that expression.
33:31
There’s something very new that’s just been called to my attention recently, and I’ve
33:36
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
33:51
ounce of gold.
33:52
This is not the IMF.
33:53
The IMF is not doing this.
33:55
The Federal Reserve, the Treasury is not doing it.
33:58
The ECB is not doing it.
33:59
If they were, you’d see it.
34:00
It would show up in the gold holdings.
34:02
You have to conduct open market operations in gold to do this.
34:05
But the Chinese appear to be doing it, and it starts October 1, 2016.
34:11
That was the day the Chinese Yuan joined the SDR.
34:15
The IMF admitted the Yuan to the group was four, now five currencies that make up the
34:21
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.