An educational blog which supplements subscriber service Chart Patterns are nothing but Footprints of the Greenbacks.
Friday, May 08, 2009
On the upside it still has room to 36 until next major resistance and on the down-side, selling might pick-up on any hard break of the 200 SMA or break of the 2 day low around 33.85. Our thoughts are that sentiment is still very bullish and any significant selling in tech (for example a move to 32) would be a good buying opportunity.
Thursday, May 07, 2009
Tuesday, May 05, 2009
Bull litmus test
We're surprised at the news (as is the market with futures down 1.2% as we write this post) as we assumed the stress test had the bars set very low, since after all, it was created by the government.
Tomorrow should test the bull's resolve; we'll be watching for down-side momentum, volume, and how broad the potential pull-back will be. We'll also be focusing on possible divergences between financials and commodities.
If we sell-off hard tomorrow (and more importantly Thursday when the details and not just the headline leaks come out), and on good volume, then most likely it will be a start of at least an intermediate pull-back. If the market pulls back only with mild losses, or no losses, or even gains (!) then chances are that the S&P will be going to 1000 with ease.
Update: it seems that the BAC news has now been interpreted differently (not a big surprise since we would have been shocked to see these quasi tests actually produce bad news) and futures rallied on better than expected economic news.
We'll see how they close them -- any mild pull-back this week would be bullish to base under resistance, especially in the QQQQ and IWM.
Saturday, May 02, 2009
Our thoughts
If you see the trend continuing and want a pair trade then go short IYR XLF, and go long USO OIH XME MOO. Our feeling is that the aforementioned commodity ETFs will not only outperform the financials and REITs but also the small-caps (IWM), the Nasdaq (QQQQ) and the S&P 500 (SPY).
Hopefully we'll find out this week whether Friday was an anomaly or the start of a new trend. Stay tuned.
HCPG
Sector D: Steel and Iron
Sector C: Crude Oil and Oil Services
The two ETF's we like to use when focusing on crude and oil companies are USO and OIH. The other popular one, XLE, is also a good trading vehicle but the daily on OIH is much cleaner than in XLE.
We had USO long on the trend-line break of 29 in our newsletter on Friday. We still like it but want confirmation as the volume on the break was questionable.
OIH same story -- price looks good and it wouldn't surprise us if OIH rallied 10 points within 10 days but it needs to confirm as volume on Friday was weak.
SU looks good to go for run to 30.
Lots of clean air for COG as it sits above its 200 SMA.
EOG could be in for a good move through 67.
Sector B: Metals and Minerals
Here are our favorite trading stocks within the sector:
MEE might need a few days to consolidate the Wednesday earning's move but it looks good to go for at least another 6 points. If you're a swing trader look to buy dips on this stock.
Huge volume break-out move on JRCC on Friday -- a bit of digestion under the 200 SMA would be excellent for this runner.
We had CNX in our newsletter with 33 alert for Friday. Stock looks good to 38.
We had BTU long alert for Friday at 27.5. The stock blew through our spot and now is basing under 30. Looks good to go for another 4 points.
This sector looks even better than the Ag-Chem in that a) it has less congestion (compare to MON) and b) has more up-side potential in that resistance is further away.
Sector A: Ag-Chems
There's no ETF we love for this sector (not liquid enough) but MOO seems to be the best of the bunch.
Clear break-out on increased volume (not difficult though as stock normally trades thin so a bit of day-trader attention would get the volume spike) but has 200 SMA to deal with relatively soon.
Angle of ascent is a big part of the way we trade. Note the increased angles of ascent in AGU (versus the more flat nature of S&P 500 in April versus March). This means that there could be fast up-move coming in the stock. Possible top? Maybe, but before then there should be an excellent long opportunity, at least to the October gap area.
CF is the leader of the group; excellent price action but possibly needs a bit of rest ahead of the 200SMA (at least that is what would happen in a rational market :-)
MON messier than the rest but important enough to be mentioned -- could easily run to 88, especially if it rests for one day.
POT looking good under 92.
Stay Tuned for this evening's post, Sector B: Metals
Friday, May 01, 2009
Commodity Rip
Metals:
Oil Service:
Crude:
And the poor Treasuries:
Gold lagging -- let's see if they catch up.
Update: today was one of the clearest change of leadership days we have seen in a long time. One day a trend does not make -- however, if we get continuation on Monday then it's a good bet we're going to get a very good run in the commodities with money flowing from the REITS and financials into metals, ags, coal, and oil.
Today's triggers
These are day-trade entries but often our subscribers swing-trade many of our trigger spots. We ourselves are primarily day-traders and look for 1-4% moves with stops around 0.3%-0.5%.
Thursday, April 30, 2009
Comp 200 SMA tag and reverse
Sunday, April 12, 2009
Financial Fun
XLF closed right at resistance. As much as we think this bank rally is overdone, we have to admit that this actually is a very bullish chart IF it can base under resistance for a few days and then have a high-volume breakout. We always tell each other that we think/feel is irrelevant; we feel bearish but we've been trading this rally long because that is clearly what the charts have shown in the last month. Opinions are fun and we talk to each other about how we "feel" all the time, however when it comes to actually putting our money on the line, we always defer to the charts.
If we had followed what we felt (our emotions) instead of what we saw (charts) we would have, without a doubt, given back all our ytd gains by buying FAZ SRS over the last few weeks. Decouple your emotions from your trading. Allow yourself to feel/voice/cry over whatever you want, but when it comes to actually pulling the trigger, always follow your system and not what you want/feel. If the two fall into synch, wonderful, if not, too bad, but do not even give yourself the option of following your emotions over what you see ahead of you (chart trends).
The bears will have their day in the sun again and we'll join them on the dark side; once the charts confirm the break of the rally.
Saturday, April 04, 2009
We see what we want to see
Recipe for Disaster: The Formula That Killed Wall Street
A year ago, it was hardly unthinkable that a math wizard like David X. Li might someday earn a Nobel Prize. After all, financial economists—even Wall Street quants—have received the Nobel in economics before, and Li's work on measuring risk has had more impact, more quickly, than previous Nobel Prize-winning contributions to the field. Today, though, as dazed bankers, politicians, regulators, and investors survey the wreckage of the biggest financial meltdown since the Great Depression, Li is probably thankful he still has a job in finance at all. Not that his achievement should be dismissed. He took a notoriously tough nut—determining correlation, or how seemingly disparate events are related—and cracked it wide open with a simple and elegant mathematical formula, one that would become ubiquitous in finance worldwide.
For five years, Li's formula, known as a Gaussian copula function, looked like an unambiguously positive breakthrough, a piece of financial technology that allowed hugely complex risks to be modeled with more ease and accuracy than ever before. With his brilliant spark of mathematical legerdemain, Li made it possible for traders to sell vast quantities of new securities, expanding financial markets to unimaginable levels.
His method was adopted by everybody from bond investors and Wall Street banks to ratings agencies and regulators. And it became so deeply entrenched—and was making people so much money—that warnings about its limitations were largely ignored.
Then the model fell apart. Cracks started appearing early on, when financial markets began behaving in ways that users of Li's formula hadn't expected. The cracks became full-fledged canyons in 2008—when ruptures in the financial system's foundation swallowed up trillions of dollars and put the survival of the global banking system in serious peril.
David X. Li, it's safe to say, won't be getting that Nobel anytime soon. One result of the collapse has been the end of financial economics as something to be celebrated rather than feared. And Li's Gaussian copula formula will go down in history as instrumental in causing the unfathomable losses that brought the world financial system to its knees.
How could one formula pack such a devastating punch? The answer lies in the bond market, the multitrillion-dollar system that allows pension funds, insurance companies, and hedge funds to lend trillions of dollars to companies, countries, and home buyers.
A bond, of course, is just an IOU, a promise to pay back money with interest by certain dates. If a company—say, IBM—borrows money by issuing a bond, investors will look very closely over its accounts to make sure it has the wherewithal to repay them. The higher the perceived risk—and there's always some risk—the higher the interest rate the bond must carry.
Bond investors are very comfortable with the concept of probability. If there's a 1 percent chance of default but they get an extra two percentage points in interest, they're ahead of the game overall—like a casino, which is happy to lose big sums every so often in return for profits most of the time.
Bond investors also invest in pools of hundreds or even thousands of mortgages. The potential sums involved are staggering: Americans now owe more than $11 trillion on their homes. But mortgage pools are messier than most bonds. There's no guaranteed interest rate, since the amount of money homeowners collectively pay back every month is a function of how many have refinanced and how many have defaulted. There's certainly no fixed maturity date: Money shows up in irregular chunks as people pay down their mortgages at unpredictable times—for instance, when they decide to sell their house. And most problematic, there's no easy way to assign a single probability to the chance of default.
Wall Street solved many of these problems through a process called tranching, which divides a pool and allows for the creation of safe bonds with a risk-free triple-A credit rating. Investors in the first tranche, or slice, are first in line to be paid off. Those next in line might get only a double-A credit rating on their tranche of bonds but will be able to charge a higher interest rate for bearing the slightly higher chance of default. And so on.
The reason that ratings agencies and investors felt so safe with the triple-A tranches was that they believed there was no way hundreds of homeowners would all default on their loans at the same time. One person might lose his job, another might fall ill. But those are individual calamities that don't affect the mortgage pool much as a whole: Everybody else is still making their payments on time.
But not all calamities are individual, and tranching still hadn't solved all the problems of mortgage-pool risk. Some things, like falling house prices, affect a large number of people at once. If home values in your neighborhood decline and you lose some of your equity, there's a good chance your neighbors will lose theirs as well. If, as a result, you default on your mortgage, there's a higher probability they will default, too. That's called correlation—the degree to which one variable moves in line with another—and measuring it is an important part of determining how risky mortgage bonds are.
Investors like risk, as long as they can price it. What they hate is uncertainty—not knowing how big the risk is. As a result, bond investors and mortgage lenders desperately want to be able to measure, model, and price correlation. Before quantitative models came along, the only time investors were comfortable putting their money in mortgage pools was when there was no risk whatsoever—in other words, when the bonds were guaranteed implicitly by the federal government through Fannie Mae or Freddie Mac.
Yet during the '90s, as global markets expanded, there were trillions of new dollars waiting to be put to use lending to borrowers around the world—not just mortgage seekers but also corporations and car buyers and anybody running a balance on their credit card—if only investors could put a number on the correlations between them. The problem is excruciatingly hard, especially when you're talking about thousands of moving parts. Whoever solved it would earn the eternal gratitude of Wall Street and quite possibly the attention of the Nobel committee as well.
To understand the mathematics of correlation better, consider something simple, like a kid in an elementary school: Let's call her Alice. The probability that her parents will get divorced this year is about 5 percent, the risk of her getting head lice is about 5 percent, the chance of her seeing a teacher slip on a banana peel is about 5 percent, and the likelihood of her winning the class spelling bee is about 5 percent. If investors were trading securities based on the chances of those things happening only to Alice, they would all trade at more or less the same price.
But something important happens when we start looking at two kids rather than one—not just Alice but also the girl she sits next to, Britney. If Britney's parents get divorced, what are the chances that Alice's parents will get divorced, too? Still about 5 percent: The correlation there is close to zero. But if Britney gets head lice, the chance that Alice will get head lice is much higher, about 50 percent—which means the correlation is probably up in the 0.5 range. If Britney sees a teacher slip on a banana peel, what is the chance that Alice will see it, too? Very high indeed, since they sit next to each other: It could be as much as 95 percent, which means the correlation is close to 1. And if Britney wins the class spelling bee, the chance of Alice winning it is zero, which means the correlation is negative: -1.
If investors were trading securities based on the chances of these things happening to both Alice and Britney, the prices would be all over the place, because the correlations vary so much.
But it's a very inexact science. Just measuring those initial 5 percent probabilities involves collecting lots of disparate data points and subjecting them to all manner of statistical and error analysis. Trying to assess the conditional probabilities—the chance that Alice will get head lice if Britney gets head lice—is an order of magnitude harder, since those data points are much rarer. As a result of the scarcity of historical data, the errors there are likely to be much greater.
In the world of mortgages, it's harder still. What is the chance that any given home will decline in value? You can look at the past history of housing prices to give you an idea, but surely the nation's macroeconomic situation also plays an important role. And what is the chance that if a home in one state falls in value, a similar home in another state will fall in value as well?
Here's what killed your 401(k) David X. Li's Gaussian copula function as first published in 2000. Investors exploited it as a quick—and fatally flawed—way to assess risk. A shorter version appears on this month's cover of Wired.
ProbabilitySpecifically, this is a joint default probability—the likelihood that any two members of the pool (A and B) will both default. It's what investors are looking for, and the rest of the formula provides the answer. | Survival timesThe amount of time between now and when A and B can be expected to default. Li took the idea from a concept in actuarial science that charts what happens to someone's life expectancy when their spouse dies. | EqualityA dangerously precise concept, since it leaves no room for error. Clean equations help both quants and their managers forget that the real world contains a surprising amount of uncertainty, fuzziness, and precariousness. |
CopulaThis couples (hence the Latinate term copula) the individual probabilities associated with A and B to come up with a single number. Errors here massively increase the risk of the whole equation blowing up. | Distribution functionsThe probabilities of how long A and B are likely to survive. Since these are not certainties, they can be dangerous: Small miscalculations may leave you facing much more risk than the formula indicates. | GammaThe all-powerful correlation parameter, which reduces correlation to a single constant—something that should be highly improbable, if not impossible. This is the magic number that made Li's copula function irresistible. |
Enter Li, a star mathematician who grew up in rural China in the 1960s. He excelled in school and eventually got a master's degree in economics from Nankai University before leaving the country to get an MBA from Laval University in Quebec. That was followed by two more degrees: a master's in actuarial science and a PhD in statistics, both from Ontario's University of Waterloo. In 1997 he landed at Canadian Imperial Bank of Commerce, where his financial career began in earnest; he later moved to Barclays Capital and by 2004 was charged with rebuilding its quantitative analytics team.
Li's trajectory is typical of the quant era, which began in the mid-1980s. Academia could never compete with the enormous salaries that banks and hedge funds were offering. At the same time, legions of math and physics PhDs were required to create, price, and arbitrage Wall Street's ever more complex investment structures.
In 2000, while working at JPMorgan Chase, Li published a paper in The Journal of Fixed Income titled "On Default Correlation: A Copula Function Approach." (In statistics, a copula is used to couple the behavior of two or more variables.) Using some relatively simple math—by Wall Street standards, anyway—Li came up with an ingenious way to model default correlation without even looking at historical default data. Instead, he used market data about the prices of instruments known as credit default swaps.
If you're an investor, you have a choice these days: You can either lend directly to borrowers or sell investors credit default swaps, insurance against those same borrowers defaulting. Either way, you get a regular income stream—interest payments or insurance payments—and either way, if the borrower defaults, you lose a lot of money. The returns on both strategies are nearly identical, but because an unlimited number of credit default swaps can be sold against each borrower, the supply of swaps isn't constrained the way the supply of bonds is, so the CDS market managed to grow extremely rapidly. Though credit default swaps were relatively new when Li's paper came out, they soon became a bigger and more liquid market than the bonds on which they were based.
When the price of a credit default swap goes up, that indicates that default risk has risen. Li's breakthrough was that instead of waiting to assemble enough historical data about actual defaults, which are rare in the real world, he used historical prices from the CDS market. It's hard to build a historical model to predict Alice's or Britney's behavior, but anybody could see whether the price of credit default swaps on Britney tended to move in the same direction as that on Alice. If it did, then there was a strong correlation between Alice's and Britney's default risks, as priced by the market. Li wrote a model that used price rather than real-world default data as a shortcut (making an implicit assumption that financial markets in general, and CDS markets in particular, can price default risk correctly).
It was a brilliant simplification of an intractable problem. And Li didn't just radically dumb down the difficulty of working out correlations; he decided not to even bother trying to map and calculate all the nearly infinite relationships between the various loans that made up a pool. What happens when the number of pool members increases or when you mix negative correlations with positive ones? Never mind all that, he said. The only thing that matters is the final correlation number—one clean, simple, all-sufficient figure that sums up everything.
The effect on the securitization market was electric. Armed with Li's formula, Wall Street's quants saw a new world of possibilities. And the first thing they did was start creating a huge number of brand-new triple-A securities. Using Li's copula approach meant that ratings agencies like Moody's—or anybody wanting to model the risk of a tranche—no longer needed to puzzle over the underlying securities. All they needed was that correlation number, and out would come a rating telling them how safe or risky the tranche was.
As a result, just about anything could be bundled and turned into a triple-A bond—corporate bonds, bank loans, mortgage-backed securities, whatever you liked. The consequent pools were often known as collateralized debt obligations, or CDOs. You could tranche that pool and create a triple-A security even if none of the components were themselves triple-A. You could even take lower-rated tranches of other CDOs, put them in a pool, and tranche them—an instrument known as a CDO-squared, which at that point was so far removed from any actual underlying bond or loan or mortgage that no one really had a clue what it included. But it didn't matter. All you needed was Li's copula function.
The CDS and CDO markets grew together, feeding on each other. At the end of 2001, there was $920 billion in credit default swaps outstanding. By the end of 2007, that number had skyrocketed to more than $62 trillion. The CDO market, which stood at $275 billion in 2000, grew to $4.7 trillion by 2006.
At the heart of it all was Li's formula. When you talk to market participants, they use words like beautiful, simple, and, most commonly, tractable. It could be applied anywhere, for anything, and was quickly adopted not only by banks packaging new bonds but also by traders and hedge funds dreaming up complex trades between those bonds.
"The corporate CDO world relied almost exclusively on this copula-based correlation model," says Darrell Duffie, a Stanford University finance professor who served on Moody's Academic Advisory Research Committee. The Gaussian copula soon became such a universally accepted part of the world's financial vocabulary that brokers started quoting prices for bond tranches based on their correlations. "Correlation trading has spread through the psyche of the financial markets like a highly infectious thought virus," wrote derivatives guru Janet Tavakoli in 2006.
The damage was foreseeable and, in fact, foreseen. In 1998, before Li had even invented his copula function, Paul Wilmott wrote that "the correlations between financial quantities are notoriously unstable." Wilmott, a quantitative-finance consultant and lecturer, argued that no theory should be built on such unpredictable parameters. And he wasn't alone. During the boom years, everybody could reel off reasons why the Gaussian copula function wasn't perfect. Li's approach made no allowance for unpredictability: It assumed that correlation was a constant rather than something mercurial. Investment banks would regularly phone Stanford's Duffie and ask him to come in and talk to them about exactly what Li's copula was. Every time, he would warn them that it was not suitable for use in risk management or valuation.
In hindsight, ignoring those warnings looks foolhardy. But at the time, it was easy. Banks dismissed them, partly because the managers empowered to apply the brakes didn't understand the arguments between various arms of the quant universe. Besides, they were making too much money to stop.
In finance, you can never reduce risk outright; you can only try to set up a market in which people who don't want risk sell it to those who do. But in the CDO market, people used the Gaussian copula model to convince themselves they didn't have any risk at all, when in fact they just didn't have any risk 99 percent of the time. The other 1 percent of the time they blew up. Those explosions may have been rare, but they could destroy all previous gains, and then some.
Li's copula function was used to price hundreds of billions of dollars' worth of CDOs filled with mortgages. And because the copula function used CDS prices to calculate correlation, it was forced to confine itself to looking at the period of time when those credit default swaps had been in existence: less than a decade, a period when house prices soared. Naturally, default correlations were very low in those years. But when the mortgage boom ended abruptly and home values started falling across the country, correlations soared.
Bankers securitizing mortgages knew that their models were highly sensitive to house-price appreciation. If it ever turned negative on a national scale, a lot of bonds that had been rated triple-A, or risk-free, by copula-powered computer models would blow up. But no one was willing to stop the creation of CDOs, and the big investment banks happily kept on building more, drawing their correlation data from a period when real estate only went up.
"Everyone was pinning their hopes on house prices continuing to rise," says Kai Gilkes of the credit research firm CreditSights, who spent 10 years working at ratings agencies. "When they stopped rising, pretty much everyone was caught on the wrong side, because the sensitivity to house prices was huge. And there was just no getting around it. Why didn't rating agencies build in some cushion for this sensitivity to a house-price-depreciation scenario? Because if they had, they would have never rated a single mortgage-backed CDO."
Bankers should have noted that very small changes in their underlying assumptions could result in very large changes in the correlation number. They also should have noticed that the results they were seeing were much less volatile than they should have been—which implied that the risk was being moved elsewhere. Where had the risk gone?
They didn't know, or didn't ask. One reason was that the outputs came from "black box" computer models and were hard to subject to a commonsense smell test. Another was that the quants, who should have been more aware of the copula's weaknesses, weren't the ones making the big asset-allocation decisions. Their managers, who made the actual calls, lacked the math skills to understand what the models were doing or how they worked. They could, however, understand something as simple as a single correlation number. That was the problem.
"The relationship between two assets can never be captured by a single scalar quantity," Wilmott says. For instance, consider the share prices of two sneaker manufacturers: When the market for sneakers is growing, both companies do well and the correlation between them is high. But when one company gets a lot of celebrity endorsements and starts stealing market share from the other, the stock prices diverge and the correlation between them turns negative. And when the nation morphs into a land of flip-flop-wearing couch potatoes, both companies decline and the correlation becomes positive again. It's impossible to sum up such a history in one correlation number, but CDOs were invariably sold on the premise that correlation was more of a constant than a variable.
No one knew all of this better than David X. Li: "Very few people understand the essence of the model," he told The Wall Street Journal way back in fall 2005.
"Li can't be blamed," says Gilkes of CreditSights. After all, he just invented the model. Instead, we should blame the bankers who misinterpreted it. And even then, the real danger was created not because any given trader adopted it but because every trader did. In financial markets, everybody doing the same thing is the classic recipe for a bubble and inevitable bust.
Nassim Nicholas Taleb, hedge fund manager and author of The Black Swan, is particularly harsh when it comes to the copula. "People got very excited about the Gaussian copula because of its mathematical elegance, but the thing never worked," he says. "Co-association between securities is not measurable using correlation," because past history can never prepare you for that one day when everything goes south. "Anything that relies on correlation is charlatanism."
Li has been notably absent from the current debate over the causes of the crash. In fact, he is no longer even in the US. Last year, he moved to Beijing to head up the risk-management department of China International Capital Corporation. In a recent conversation, he seemed reluctant to discuss his paper and said he couldn't talk without permission from the PR department. In response to a subsequent request, CICC's press office sent an email saying that Li was no longer doing the kind of work he did in his previous job and, therefore, would not be speaking to the media.
In the world of finance, too many quants see only the numbers before them and forget about the concrete reality the figures are supposed to represent. They think they can model just a few years' worth of data and come up with probabilities for things that may happen only once every 10,000 years. Then people invest on the basis of those probabilities, without stopping to wonder whether the numbers make any sense at all.
As Li himself said of his own model: "The most dangerous part is when people believe everything coming out of it."
— Felix Salmon (felix@felixsalmon.com) writes the Market Movers financial blog at Portfolio.com.
USA: Banana Republic
Take a minute or two and read the article in its entirety. We've highlighted the parts that held the most interest to us:
The Quiet Coup
One thing you learn rather quickly when working at the International Monetary Fund is that no one is ever very happy to see you. Typically, your “clients” come in only after private capital has abandoned them, after regional trading-bloc partners have been unable to throw a strong enough lifeline, after last-ditch attempts to borrow from powerful friends like China or the European Union have fallen through. You’re never at the top of anyone’s dance card.The reason, of course, is that the IMF specializes in telling its clients what they don’t want to hear. I should know; I pressed painful changes on many foreign officials during my time there as chief economist in 2007 and 2008. And I felt the effects of IMF pressure, at least indirectly, when I worked with governments in Eastern Europe as they struggled after 1989, and with the private sector in Asia and Latin America during the crises of the late 1990s and early 2000s. Over that time, from every vantage point, I saw firsthand the steady flow of officials—from Ukraine, Russia, Thailand, Indonesia, South Korea, and elsewhere—trudging to the fund when circumstances were dire and all else had failed.
Every crisis is different, of course. Ukraine faced hyperinflation in 1994; Russia desperately needed help when its short-term-debt rollover scheme exploded in the summer of 1998; the Indonesian rupiah plunged in 1997, nearly leveling the corporate economy; that same year, South Korea’s 30-year economic miracle ground to a halt when foreign banks suddenly refused to extend new credit.
But I must tell you, to IMF officials, all of these crises looked depressingly similar. Each country, of course, needed a loan, but more than that, each needed to make big changes so that the loan could really work. Almost always, countries in crisis need to learn to live within their means after a period of excess—exports must be increased, and imports cut—and the goal is to do this without the most horrible of recessions. Naturally, the fund’s economists spend time figuring out the policies—budget, money supply, and the like—that make sense in this context. Yet the economic solution is seldom very hard to work out.
No, the real concern of the fund’s senior staff, and the biggest obstacle to recovery, is almost invariably the politics of countries in crisis.
Typically, these countries are in a desperate economic situation for one simple reason—the powerful elites within them overreached in good times and took too many risks. Emerging-market governments and their private-sector allies commonly form a tight-knit—and, most of the time, genteel—oligarchy, running the country rather like a profit-seeking company in which they are the controlling shareholders. When a country like Indonesia or South Korea or Russia grows, so do the ambitions of its captains of industry. As masters of their mini-universe, these people make some investments that clearly benefit the broader economy, but they also start making bigger and riskier bets. They reckon—correctly, in most cases—that their political connections will allow them to push onto the government any substantial problems that arise.
In Russia, for instance, the private sector is now in serious trouble because, over the past five years or so, it borrowed at least $490 billion from global banks and investors on the assumption that the country’s energy sector could support a permanent increase in consumption throughout the economy. As Russia’s oligarchs spent this capital, acquiring other companies and embarking on ambitious investment plans that generated jobs, their importance to the political elite increased. Growing political support meant better access to lucrative contracts, tax breaks, and subsidies. And foreign investors could not have been more pleased; all other things being equal, they prefer to lend money to people who have the implicit backing of their national governments, even if that backing gives off the faint whiff of corruption.
But inevitably, emerging-market oligarchs get carried away; they waste money and build massive business empires on a mountain of debt. Local banks, sometimes pressured by the government, become too willing to extend credit to the elite and to those who depend on them. Overborrowing always ends badly, whether for an individual, a company, or a country. Sooner or later, credit conditions become tighter and no one will lend you money on anything close to affordable terms.
The downward spiral that follows is remarkably steep. Enormous companies teeter on the brink of default, and the local banks that have lent to them collapse. Yesterday’s “public-private partnerships” are relabeled “crony capitalism.” With credit unavailable, economic paralysis ensues, and conditions just get worse and worse. The government is forced to draw down its foreign-currency reserves to pay for imports, service debt, and cover private losses. But these reserves will eventually run out. If the country cannot right itself before that happens, it will default on its sovereign debt and become an economic pariah. The government, in its race to stop the bleeding, will typically need to wipe out some of the national champions—now hemorrhaging cash—and usually restructure a banking system that’s gone badly out of balance. It will, in other words, need to squeeze at least some of its oligarchs.
Squeezing the oligarchs, though, is seldom the strategy of choice among emerging-market governments. Quite the contrary: at the outset of the crisis, the oligarchs are usually among the first to get extra help from the government, such as preferential access to foreign currency, or maybe a nice tax break, or—here’s a classic Kremlin bailout technique—the assumption of private debt obligations by the government. Under duress, generosity toward old friends takes many innovative forms. Meanwhile, needing to squeeze someone, most emerging-market governments look first to ordinary working folk—at least until the riots grow too large.
Eventually, as the oligarchs in Putin’s Russia now realize, some within the elite have to lose out before recovery can begin. It’s a game of musical chairs: there just aren’t enough currency reserves to take care of everyone, and the government cannot afford to take over private-sector debt completely.
So the IMF staff looks into the eyes of the minister of finance and decides whether the government is serious yet. The fund will give even a country like Russia a loan eventually, but first it wants to make sure Prime Minister Putin is ready, willing, and able to be tough on some of his friends. If he is not ready to throw former pals to the wolves, the fund can wait. And when he is ready, the fund is happy to make helpful suggestions—particularly with regard to wresting control of the banking system from the hands of the most incompetent and avaricious “entrepreneurs.”
Of course, Putin’s ex-friends will fight back. They’ll mobilize allies, work the system, and put pressure on other parts of the government to get additional subsidies. In extreme cases, they’ll even try subversion—including calling up their contacts in the American foreign-policy establishment, as the Ukrainians did with some success in the late 1990s.
Many IMF programs “go off track” (a euphemism) precisely because the government can’t stay tough on erstwhile cronies, and the consequences are massive inflation or other disasters. A program “goes back on track” once the government prevails or powerful oligarchs sort out among themselves who will govern—and thus win or lose—under the IMF-supported plan. The real fight in Thailand and Indonesia in 1997 was about which powerful families would lose their banks. In Thailand, it was handled relatively smoothly. In Indonesia, it led to the fall of President Suharto and economic chaos.
From long years of experience, the IMF staff knows its program will succeed—stabilizing the economy and enabling growth—only if at least some of the powerful oligarchs who did so much to create the underlying problems take a hit. This is the problem of all emerging markets.
In its depth and suddenness, the U.S. economic and financial crisis is shockingly reminiscent of moments we have recently seen in emerging markets (and only in emerging markets): South Korea (1997), Malaysia (1998), Russia and Argentina (time and again). In each of those cases, global investors, afraid that the country or its financial sector wouldn’t be able to pay off mountainous debt, suddenly stopped lending. And in each case, that fear became self-fulfilling, as banks that couldn’t roll over their debt did, in fact, become unable to pay. This is precisely what drove Lehman Brothers into bankruptcy on September 15, causing all sources of funding to the U.S. financial sector to dry up overnight. Just as in emerging-market crises, the weakness in the banking system has quickly rippled out into the rest of the economy, causing a severe economic contraction and hardship for millions of people.
But there’s a deeper and more disturbing similarity: elite business interests—financiers, in the case of the U.S.—played a central role in creating the crisis, making ever-larger gambles, with the implicit backing of the government, until the inevitable collapse. More alarming, they are now using their influence to prevent precisely the sorts of reforms that are needed, and fast, to pull the economy out of its nosedive. The government seems helpless, or unwilling, to act against them.
Top investment bankers and government officials like to lay the blame for the current crisis on the lowering of U.S. interest rates after the dotcom bust or, even better—in a “buck stops somewhere else” sort of way—on the flow of savings out of China. Some on the right like to complain about Fannie Mae or Freddie Mac, or even about longer-standing efforts to promote broader homeownership. And, of course, it is axiomatic to everyone that the regulators responsible for “safety and soundness” were fast asleep at the wheel.
But these various policies—lightweight regulation, cheap money, the unwritten Chinese-American economic alliance, the promotion of homeownership—had something in common. Even though some are traditionally associated with Democrats and some with Republicans, they all benefited the financial sector. Policy changes that might have forestalled the crisis but would have limited the financial sector’s profits—such as Brooksley Born’s now-famous attempts to regulate credit-default swaps at the Commodity Futures Trading Commission, in 1998—were ignored or swept aside.
The financial industry has not always enjoyed such favored treatment. But for the past 25 years or so, finance has boomed, becoming ever more powerful. The boom began with the Reagan years, and it only gained strength with the deregulatory policies of the Clinton and George W. Bush administrations. Several other factors helped fuel the financial industry’s ascent. Paul Volcker’s monetary policy in the 1980s, and the increased volatility in interest rates that accompanied it, made bond trading much more lucrative. The invention of securitization, interest-rate swaps, and credit-default swaps greatly increased the volume of transactions that bankers could make money on. And an aging and increasingly wealthy population invested more and more money in securities, helped by the invention of the IRA and the 401(k) plan. Together, these developments vastly increased the profit opportunities in financial services.
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Not surprisingly, Wall Street ran with these opportunities. From 1973 to 1985, the financial sector never earned more than 16 percent of domestic corporate profits. In 1986, that figure reached 19 percent. In the 1990s, it oscillated between 21 percent and 30 percent, higher than it had ever been in the postwar period. This decade, it reached 41 percent. Pay rose just as dramatically. From 1948 to 1982, average compensation in the financial sector ranged between 99 percent and 108 percent of the average for all domestic private industries. From 1983, it shot upward, reaching 181 percent in 2007.
The great wealth that the financial sector created and concentrated gave bankers enormous political weight—a weight not seen in the U.S. since the era of J.P. Morgan (the man). In that period, the banking panic of 1907 could be stopped only by coordination among private-sector bankers: no government entity was able to offer an effective response. But that first age of banking oligarchs came to an end with the passage of significant banking regulation in response to the Great Depression; the reemergence of an American financial oligarchy is quite recent.
Of course, the U.S. is unique. And just as we have the world’s most advanced economy, military, and technology, we also have its most advanced oligarchy.
In a primitive political system, power is transmitted through violence, or the threat of violence: military coups, private militias, and so on. In a less primitive system more typical of emerging markets, power is transmitted via money: bribes, kickbacks, and offshore bank accounts. Although lobbying and campaign contributions certainly play major roles in the American political system, old-fashioned corruption—envelopes stuffed with $100 bills—is probably a sideshow today, Jack Abramoff notwithstanding.
Instead, the American financial industry gained political power by amassing a kind of cultural capital—a belief system. Once, perhaps, what was good for General Motors was good for the country. Over the past decade, the attitude took hold that what was good for Wall Street was good for the country. The banking-and-securities industry has become one of the top contributors to political campaigns, but at the peak of its influence, it did not have to buy favors the way, for example, the tobacco companies or military contractors might have to. Instead, it benefited from the fact that Washington insiders already believed that large financial institutions and free-flowing capital markets were crucial to America’s position in the world.
One channel of influence was, of course, the flow of individuals between Wall Street and Washington. Robert Rubin, once the co-chairman of Goldman Sachs, served in Washington as Treasury secretary under Clinton, and later became chairman of Citigroup’s executive committee. Henry Paulson, CEO of Goldman Sachs during the long boom, became Treasury secretary under George W.Bush. John Snow, Paulson’s predecessor, left to become chairman of Cerberus Capital Management, a large private-equity firm that also counts Dan Quayle among its executives. Alan Greenspan, after leaving the Federal Reserve, became a consultant to Pimco, perhaps the biggest player in international bond markets.
These personal connections were multiplied many times over at the lower levels of the past three presidential administrations, strengthening the ties between Washington and Wall Street. It has become something of a tradition for Goldman Sachs employees to go into public service after they leave the firm. The flow of Goldman alumni—including Jon Corzine, now the governor of New Jersey, along with Rubin and Paulson—not only placed people with Wall Street’s worldview in the halls of power; it also helped create an image of Goldman (inside the Beltway, at least) as an institution that was itself almost a form of public service.
Wall Street is a very seductive place, imbued with an air of power. Its executives truly believe that they control the levers that make the world go round. A civil servant from Washington invited into their conference rooms, even if just for a meeting, could be forgiven for falling under their sway. Throughout my time at the IMF, I was struck by the easy access of leading financiers to the highest U.S. government officials, and the interweaving of the two career tracks. I vividly remember a meeting in early 2008—attended by top policy makers from a handful of rich countries—at which the chair casually proclaimed, to the room’s general approval, that the best preparation for becoming a central-bank governor was to work first as an investment banker.
A whole generation of policy makers has been mesmerized by Wall Street, always and utterly convinced that whatever the banks said was true. Alan Greenspan’s pronouncements in favor of unregulated financial markets are well known. Yet Greenspan was hardly alone. This is what Ben Bernanke, the man who succeeded him, said in 2006: “The management of market risk and credit risk has become increasingly sophisticated. … Banking organizations of all sizes have made substantial strides over the past two decades in their ability to measure and manage risks.”
Of course, this was mostly an illusion. Regulators, legislators, and academics almost all assumed that the managers of these banks knew what they were doing. In retrospect, they didn’t. AIG’s Financial Products division, for instance, made $2.5 billion in pretax profits in 2005, largely by selling underpriced insurance on complex, poorly understood securities. Often described as “picking up nickels in front of a steamroller,” this strategy is profitable in ordinary years, and catastrophic in bad ones. As of last fall, AIG had outstanding insurance on more than $400 billion in securities. To date, the U.S. government, in an effort to rescue the company, has committed about $180 billion in investments and loans to cover losses that AIG’s sophisticated risk modeling had said were virtually impossible.
Wall Street’s seductive power extended even (or especially) to finance and economics professors, historically confined to the cramped offices of universities and the pursuit of Nobel Prizes. As mathematical finance became more and more essential to practical finance, professors increasingly took positions as consultants or partners at financial institutions. Myron Scholes and Robert Merton, Nobel laureates both, were perhaps the most famous; they took board seats at the hedge fund Long-Term Capital Management in 1994, before the fund famously flamed out at the end of the decade. But many others beat similar paths. This migration gave the stamp of academic legitimacy (and the intimidating aura of intellectual rigor) to the burgeoning world of high finance.
As more and more of the rich made their money in finance, the cult of finance seeped into the culture at large. Works like Barbarians at the Gate, Wall Street, and Bonfire of the Vanities—all intended as cautionary tales—served only to increase Wall Street’s mystique. Michael Lewis noted in Portfolio last year that when he wrote Liar’s Poker, an insider’s account of the financial industry, in 1989, he had hoped the book might provoke outrage at Wall Street’s hubris and excess. Instead, he found himself “knee-deep in letters from students at Ohio State who wanted to know if I had any other secrets to share. … They’d read my book as a how-to manual.” Even Wall Street’s criminals, like Michael Milken and Ivan Boesky, became larger than life. In a society that celebrates the idea of making money, it was easy to infer that the interests of the financial sector were the same as the interests of the country—and that the winners in the financial sector knew better what was good for America than did the career civil servants in Washington. Faith in free financial markets grew into conventional wisdom—trumpeted on the editorial pages of The Wall Street Journal and on the floor of Congress.
From this confluence of campaign finance, personal connections, and ideology there flowed, in just the past decade, a river of deregulatory policies that is, in hindsight, astonishing:
• insistence on free movement of capital across borders;
• the repeal of Depression-era regulations separating commercial and investment banking;
• a congressional ban on the regulation of credit-default swaps;
• major increases in the amount of leverage allowed to investment banks;
• a light (dare I say invisible?) hand at the Securities and Exchange Commission in its regulatory enforcement;
• an international agreement to allow banks to measure their own riskiness;
• and an intentional failure to update regulations so as to keep up with the tremendous pace of financial innovation.
The mood that accompanied these measures in Washington seemed to swing between nonchalance and outright celebration: finance unleashed, it was thought, would continue to propel the economy to greater heights.
The oligarchy and the government policies that aided it did not alone cause the financial crisis that exploded last year. Many other factors contributed, including excessive borrowing by households and lax lending standards out on the fringes of the financial world. But major commercial and investment banks—and the hedge funds that ran alongside them—were the big beneficiaries of the twin housing and equity-market bubbles of this decade, their profits fed by an ever-increasing volume of transactions founded on a relatively small base of actual physical assets. Each time a loan was sold, packaged, securitized, and resold, banks took their transaction fees, and the hedge funds buying those securities reaped ever-larger fees as their holdings grew.
Because everyone was getting richer, and the health of the national economy depended so heavily on growth in real estate and finance, no one in Washington had any incentive to question what was going on. Instead, Fed Chairman Greenspan and President Bush insisted metronomically that the economy was fundamentally sound and that the tremendous growth in complex securities and credit-default swaps was evidence of a healthy economy where risk was distributed safely.
In the summer of 2007, signs of strain started appearing. The boom had produced so much debt that even a small economic stumble could cause major problems, and rising delinquencies in subprime mortgages proved the stumbling block. Ever since, the financial sector and the federal government have been behaving exactly the way one would expect them to, in light of past emerging-market crises.
By now, the princes of the financial world have of course been stripped naked as leaders and strategists—at least in the eyes of most Americans. But as the months have rolled by, financial elites have continued to assume that their position as the economy’s favored children is safe, despite the wreckage they have caused.
Stanley O’Neal, the CEO of Merrill Lynch, pushed his firm heavily into the mortgage-backed-securities market at its peak in 2005 and 2006; in October 2007, he acknowledged, “The bottom line is, we—I—got it wrong by being overexposed to subprime, and we suffered as a result of impaired liquidity in that market. No one is more disappointed than I am in that result.” O’Neal took home a $14 million bonus in 2006; in 2007, he walked away from Merrill with a severance package worth $162 million, although it is presumably worth much less today.
In October, John Thain, Merrill Lynch’s final CEO, reportedly lobbied his board of directors for a bonus of $30 million or more, eventually reducing his demand to $10million in December; he withdrew the request, under a firestorm of protest, only after it was leaked to The Wall Street Journal. Merrill Lynch as a whole was no better: it moved its bonus payments, $4 billion in total, forward to December, presumably to avoid the possibility that they would be reduced by Bank of America, which would own Merrill beginning on January 1. Wall Street paid out $18 billion in year-end bonuses last year to its New York City employees, after the government disbursed $243 billion in emergency assistance to the financial sector.
In a financial panic, the government must respond with both speed and overwhelming force. The root problem is uncertainty—in our case, uncertainty about whether the major banks have sufficient assets to cover their liabilities. Half measures combined with wishful thinking and a wait-and-see attitude cannot overcome this uncertainty. And the longer the response takes, the longer the uncertainty will stymie the flow of credit, sap consumer confidence, and cripple the economy—ultimately making the problem much harder to solve. Yet the principal characteristics of the government’s response to the financial crisis have been delay, lack of transparency, and an unwillingness to upset the financial sector.
The response so far is perhaps best described as “policy by deal”: when a major financial institution gets into trouble, the Treasury Department and the Federal Reserve engineer a bailout over the weekend and announce on Monday that everything is fine. In March 2008, Bear Stearns was sold to JP Morgan Chase in what looked to many like a gift to JP Morgan. (Jamie Dimon, JP Morgan’s CEO, sits on the board of directors of the Federal Reserve Bank of New York, which, along with the Treasury Department, brokered the deal.) In September, we saw the sale of Merrill Lynch to Bank of America, the first bailout of AIG, and the takeover and immediate sale of Washington Mutual to JP Morgan—all of which were brokered by the government. In October, nine large banks were recapitalized on the same day behind closed doors in Washington. This, in turn, was followed by additional bailouts for Citigroup, AIG, Bank of America, Citigroup (again), and AIG (again).
Some of these deals may have been reasonable responses to the immediate situation. But it was never clear (and still isn’t) what combination of interests was being served, and how. Treasury and the Fed did not act according to any publicly articulated principles, but just worked out a transaction and claimed it was the best that could be done under the circumstances. This was late-night, backroom dealing, pure and simple.
Throughout the crisis, the government has taken extreme care not to upset the interests of the financial institutions, or to question the basic outlines of the system that got us here. In September 2008, Henry Paulson asked Congress for $700 billion to buy toxic assets from banks, with no strings attached and no judicial review of his purchase decisions. Many observers suspected that the purpose was to overpay for those assets and thereby take the problem off the banks’ hands—indeed, that is the only way that buying toxic assets would have helped anything. Perhaps because there was no way to make such a blatant subsidy politically acceptable, that plan was shelved.
Instead, the money was used to recapitalize banks, buying shares in them on terms that were grossly favorable to the banks themselves. As the crisis has deepened and financial institutions have needed more help, the government has gotten more and more creative in figuring out ways to provide banks with subsidies that are too complex for the general public to understand. The first AIG bailout, which was on relatively good terms for the taxpayer, was supplemented by three further bailouts whose terms were more AIG-friendly. The second Citigroup bailout and the Bank of America bailout included complex asset guarantees that provided the banks with insurance at below-market rates. The third Citigroup bailout, in late February, converted government-owned preferred stock to common stock at a price significantly higher than the market price—a subsidy that probably even most Wall Street Journal readers would miss on first reading. And the convertible preferred shares that the Treasury will buy under the new Financial Stability Plan give the conversion option (and thus the upside) to the banks, not the government.
This latest plan—which is likely to provide cheap loans to hedge funds and others so that they can buy distressed bank assets at relatively high prices—has been heavily influenced by the financial sector, and Treasury has made no secret of that. As Neel Kashkari, a senior Treasury official under both Henry Paulson and Tim Geithner (and a Goldman alum) told Congress in March, “We had received inbound unsolicited proposals from people in the private sector saying, ‘We have capital on the sidelines; we want to go after [distressed bank] assets.’” And the plan lets them do just that: “By marrying government capital—taxpayer capital—with private-sector capital and providing financing, you can enable those investors to then go after those assets at a price that makes sense for the investors and at a price that makes sense for the banks.” Kashkari didn’t mention anything about what makes sense for the third group involved: the taxpayers.
Even leaving aside fairness to taxpayers, the government’s velvet-glove approach with the banks is deeply troubling, for one simple reason: it is inadequate to change the behavior of a financial sector accustomed to doing business on its own terms, at a time when that behavior must change. As an unnamed senior bank official said to The New York Times last fall, “It doesn’t matter how much Hank Paulson gives us, no one is going to lend a nickel until the economy turns.” But there’s the rub: the economy can’t recover until the banks are healthy and willing to lend.
Looking just at the financial crisis (and leaving aside some problems of the larger economy), we face at least two major, interrelated problems. The first is a desperately ill banking sector that threatens to choke off any incipient recovery that the fiscal stimulus might generate. The second is a political balance of power that gives the financial sector a veto over public policy, even as that sector loses popular support.
Big banks, it seems, have only gained political strength since the crisis began. And this is not surprising. With the financial system so fragile, the damage that a major bank failure could cause—Lehman was small relative to Citigroup or Bank of America—is much greater than it would be during ordinary times. The banks have been exploiting this fear as they wring favorable deals out of Washington. Bank of America obtained its second bailout package (in January) after warning the government that it might not be able to go through with the acquisition of Merrill Lynch, a prospect that Treasury did not want to consider.
The challenges the United States faces are familiar territory to the people at the IMF. If you hid the name of the country and just showed them the numbers, there is no doubt what old IMF hands would say: nationalize troubled banks and break them up as necessary.
In some ways, of course, the government has already taken control of the banking system. It has essentially guaranteed the liabilities of the biggest banks, and it is their only plausible source of capital today. Meanwhile, the Federal Reserve has taken on a major role in providing credit to the economy—the function that the private banking sector is supposed to be performing, but isn’t. Yet there are limits to what the Fed can do on its own; consumers and businesses are still dependent on banks that lack the balance sheets and the incentives to make the loans the economy needs, and the government has no real control over who runs the banks, or over what they do.
At the root of the banks’ problems are the large losses they have undoubtedly taken on their securities and loan portfolios. But they don’t want to recognize the full extent of their losses, because that would likely expose them as insolvent. So they talk down the problem, and ask for handouts that aren’t enough to make them healthy (again, they can’t reveal the size of the handouts that would be necessary for that), but are enough to keep them upright a little longer. This behavior is corrosive: unhealthy banks either don’t lend (hoarding money to shore up reserves) or they make desperate gambles on high-risk loans and investments that could pay off big, but probably won’t pay off at all. In either case, the economy suffers further, and as it does, bank assets themselves continue to deteriorate—creating a highly destructive vicious cycle.
To break this cycle, the government must force the banks to acknowledge the scale of their problems. As the IMF understands (and as the U.S. government itself has insisted to multiple emerging-market countries in the past), the most direct way to do this is nationalization. Instead, Treasury is trying to negotiate bailouts bank by bank, and behaving as if the banks hold all the cards—contorting the terms of each deal to minimize government ownership while forswearing government influence over bank strategy or operations. Under these conditions, cleaning up bank balance sheets is impossible.
Nationalization would not imply permanent state ownership. The IMF’s advice would be, essentially: scale up the standard Federal Deposit Insurance Corporation process. An FDIC “intervention” is basically a government-managed bankruptcy procedure for banks. It would allow the government to wipe out bank shareholders, replace failed management, clean up the balance sheets, and then sell the banks back to the private sector. The main advantage is immediate recognition of the problem so that it can be solved before it grows worse.
The government needs to inspect the balance sheets and identify the banks that cannot survive a severe recession. These banks should face a choice: write down your assets to their true value and raise private capital within 30 days, or be taken over by the government. The government would write down the toxic assets of banks taken into receivership—recognizing reality—and transfer those assets to a separate government entity, which would attempt to salvage whatever value is possible for the taxpayer (as the Resolution Trust Corporation did after the savings-and-loan debacle of the 1980s). The rump banks—cleansed and able to lend safely, and hence trusted again by other lenders and investors—could then be sold off.
Cleaning up the megabanks will be complex. And it will be expensive for the taxpayer; according to the latest IMF numbers, the cleanup of the banking system would probably cost close to $1.5trillion (or 10percent of our GDP) in the long term. But only decisive government action—exposing the full extent of the financial rot and restoring some set of banks to publicly verifiable health—can cure the financial sector as a whole.
This may seem like strong medicine. But in fact, while necessary, it is insufficient. The second problem the U.S. faces—the power of the oligarchy—is just as important as the immediate crisis of lending. And the advice from the IMF on this front would again be simple: break the oligarchy.
Oversize institutions disproportionately influence public policy; the major banks we have today draw much of their power from being too big to fail. Nationalization and re-privatization would not change that; while the replacement of the bank executives who got us into this crisis would be just and sensible, ultimately, the swapping-out of one set of powerful managers for another would change only the names of the oligarchs.
Ideally, big banks should be sold in medium-size pieces, divided regionally or by type of business. Where this proves impractical—since we’ll want to sell the banks quickly—they could be sold whole, but with the requirement of being broken up within a short time. Banks that remain in private hands should also be subject to size limitations.
This may seem like a crude and arbitrary step, but it is the best way to limit the power of individual institutions in a sector that is essential to the economy as a whole. Of course, some people will complain about the “efficiency costs” of a more fragmented banking system, and these costs are real. But so are the costs when a bank that is too big to fail—a financial weapon of mass self-destruction—explodes. Anything that is too big to fail is too big to exist.
To ensure systematic bank breakup, and to prevent the eventual reemergence of dangerous behemoths, we also need to overhaul our antitrust legislation. Laws put in place more than 100years ago to combat industrial monopolies were not designed to address the problem we now face. The problem in the financial sector today is not that a given firm might have enough market share to influence prices; it is that one firm or a small set of interconnected firms, by failing, can bring down the economy. The Obama administration’s fiscal stimulus evokes FDR, but what we need to imitate here is Teddy Roosevelt’s trust-busting.
Caps on executive compensation, while redolent of populism, might help restore the political balance of power and deter the emergence of a new oligarchy. Wall Street’s main attraction—to the people who work there and to the government officials who were only too happy to bask in its reflected glory—has been the astounding amount of money that could be made. Limiting that money would reduce the allure of the financial sector and make it more like any other industry.
Still, outright pay caps are clumsy, especially in the long run. And most money is now made in largely unregulated private hedge funds and private-equity firms, so lowering pay would be complicated. Regulation and taxation should be part of the solution. Over time, though, the largest part may involve more transparency and competition, which would bring financial-industry fees down. To those who say this would drive financial activities to other countries, we can now safely say: fine.
To paraphrase Joseph Schumpeter, the early-20th-century economist, everyone has elites; the important thing is to change them from time to time. If the U.S. were just another country, coming to the IMF with hat in hand, I might be fairly optimistic about its future. Most of the emerging-market crises that I’ve mentioned ended relatively quickly, and gave way, for the most part, to relatively strong recoveries. But this, alas, brings us to the limit of the analogy between the U.S. and emerging markets.
Emerging-market countries have only a precarious hold on wealth, and are weaklings globally. When they get into trouble, they quite literally run out of money—or at least out of foreign currency, without which they cannot survive. They must make difficult decisions; ultimately, aggressive action is baked into the cake. But the U.S., of course, is the world’s most powerful nation, rich beyond measure, and blessed with the exorbitant privilege of paying its foreign debts in its own currency, which it can print. As a result, it could very well stumble along for years—as Japan did during its lost decade—never summoning the courage to do what it needs to do, and never really recovering. A clean break with the past—involving the takeover and cleanup of major banks—hardly looks like a sure thing right now. Certainly no one at the IMF can force it.
In my view, the U.S. faces two plausible scenarios. The first involves complicated bank-by-bank deals and a continual drumbeat of (repeated) bailouts, like the ones we saw in February with Citigroup and AIG. The administration will try to muddle through, and confusion will reign.
Boris Fyodorov, the late finance minister of Russia, struggled for much of the past 20 years against oligarchs, corruption, and abuse of authority in all its forms. He liked to say that confusion and chaos were very much in the interests of the powerful—letting them take things, legally and illegally, with impunity. When inflation is high, who can say what a piece of property is really worth? When the credit system is supported by byzantine government arrangements and backroom deals, how do you know that you aren’t being fleeced?
Our future could be one in which continued tumult feeds the looting of the financial system, and we talk more and more about exactly how our oligarchs became bandits and how the economy just can’t seem to get into gear.
The second scenario begins more bleakly, and might end that way too. But it does provide at least some hope that we’ll be shaken out of our torpor. It goes like this: the global economy continues to deteriorate, the banking system in east-central Europe collapses, and—because eastern Europe’s banks are mostly owned by western European banks—justifiable fears of government insolvency spread throughout the Continent. Creditors take further hits and confidence falls further. The Asian economies that export manufactured goods are devastated, and the commodity producers in Latin America and Africa are not much better off. A dramatic worsening of the global environment forces the U.S. economy, already staggering, down onto both knees. The baseline growth rates used in the administration’s current budget are increasingly seen as unrealistic, and the rosy “stress scenario” that the U.S. Treasury is currently using to evaluate banks’ balance sheets becomes a source of great embarrassment.
Under this kind of pressure, and faced with the prospect of a national and global collapse, minds may become more concentrated.
The conventional wisdom among the elite is still that the current slump “cannot be as bad as the Great Depression.” This view is wrong. What we face now could, in fact, be worse than the Great Depression—because the world is now so much more interconnected and because the banking sector is now so big. We face a synchronized downturn in almost all countries, a weakening of confidence among individuals and firms, and major problems for government finances. If our leadership wakes up to the potential consequences, we may yet see dramatic action on the banking system and a breaking of the old elite. Let us hope it is not then too late.