Market bubbles are called bubbles for good reason. They form, they inflate, they grow to an unstably distorted size, and ultimately they undergo the effects of rapid decompression in search of equilibrium. In a word … they pop. And generally speaking, the bigger the bubble the bigger the bang. … Most of us are pretty good by now, we think, at spotting bubbles. After all, we know what they look like; we recognize their characteristics, don’t we? Maybe. Maybe not. Not all bubbles look or act the same. … Is there a bubble inflating again? … people often shrug their shoulders, scratch their heads, and simply accept that there must be good reasons why stocks have been on a roll. The average investor, after all, is at least one step removed from the markets for intangible assets and therefore has comparatively little experience to help avoid becoming their occasional Venus flytrap dinner. … When it comes to assessing the state of the real economy, on the other hand, most people are more circumspect and not so easily taken in. … this bubble was born of desperation, first by the misguided monetary policy regime and then by investors who are sure to become its unsuspecting victims as they look for return—any return—in all the wrong places. … Railing against Fed policy, of course, doesn’t change it. … we continue to believe it is possible—and necessary—to see both the forest and the trees in order to fulfill our highest obligation: to continue acting in the best interests of our clients. As noted investment manager Francois Sicart said recently: “The attitude of many professional investors toward the current market makes me think of a crowd enjoying a dance party on top of an active volcano. They know it is going to erupt but, instead of planning an exit, they keep dancing while trying to guess the exact date and time of the eruption.”
While the rest of the country has spent the past year debating gay marriage, policing tactics, Obamacare, and Deflate-gate, the inescapable topic of discussion in Silicon Valley is whether we are in a technology bubble. Marc Andreessen, the co-founder of his eponymous venture firm, is perhaps the leading advocate against the bubble chatter. On his Twitter feed, he has referenced the word “bubble” more than 300 times, repeatedly mocking or refuting anyone on his radar who even hints at such a possibility. One of his arguments, as the slides in the Rosewood ballroom suggested, is the exponential growth of mobile phones, which have fundamentally changed the way we buy and sell virtually everything, from groceries to taxi-like services, and created unprecedented disruption. Also, in contrast to the days of the dot-com boom, many tech companies are creating revenue—in some instances, lots of it. ... there may be no greater monument to what’s going on in the Valley than the 1,070-foot edifice under construction at 415 Mission Street. The new, glassy Salesforce Tower is slated to soon become the tallest building in San Francisco, rising more than 200 feet above the Transamerica Pyramid. ... Snapchat has offered Stanford undergrads as much as $500,000 a year to work for the company. Jana Rich, founder of Rich Talent Group, a well-regarded tech recruiting firm, told me that she hasn’t seen such bidding wars since the late 90s. “I’ve seen two of these life cycles, where things are going fabulously well,” she said. “Then we have the bust. We are now, in my opinion, at the height of the demand curve.” ... “You know there’s a bubble,” the saying goes, “when the pretty people show up.” ... All across the Valley, the majority of big start-ups are actually glorified distribution companies that are trying, in some sense, to copy what Domino’s Pizza mastered in the 1980s when it delivered a hot pie to your door in 30 minutes or less. ... Or maybe it’s simpler than that. As one technologist overheard and posted on Twitter, “SF tech culture is focused on solving one problem: What is my mother no longer doing for me?” ... Either you can go public, which is inadvisable without a lot of revenue, or you can sell, which is difficult given the paucity of companies that can afford to make such an offer. So, for many, the choice becomes fairly simple. You continue to raise more and more money, or you die. ... countless people from all over want this to be a bubble and they want it to burst.
Known for their calm temperaments and soft fleece, alpacas looked like the next hot thing to backyard farmers. The market was frenetic, with some top of the line animals selling for hundreds of thousands of dollars. ... But the bubble burst, leaving thousands of alpaca breeders with near-worthless herds. Today, craigslist posts across the country advertise “herd liquidations” and going out of business deals on alpacas, some selling for as low as a dollar. ... They bought in at the height of the bubble, when it was commonplace for alpacas to sell for several thousand dollars. The couple started breeding and selling the offspring. ... Back in the 1980s you’d really only find them in zoos. Now there’s close to 150,000 in the U.S. ... Even late night TV commercials, sandwiched between infomercials, touted the animals’ ability to pad a retiree’s income. ... “The fundamental fact is that in this country, an alpaca, as an asset, an income-producing asset, is worthless. It has no value at all,” Sexton says. “The product it produces, 6 to 8 pounds of alpaca fiber a year, is worth less than what it costs to feed, medicate, and house the animal.”
Xu had consistently produced returns that were truly unbelievable: His worst-performing fund had grown by nearly 800 percent in five years. He had also survived countless corruption investigations, market falls, purges and other scares. Yet even as his legend grew, Xu remained intensely secretive. ... That equilibrium seemed certain to crumble on June 12, when the Chinese stock market began a free-fall. In the span of three weeks, the market lost a third of its value. ... Unlike in the United States, where institutional investors dominate the market, China’s 200 million mom-and-pop investors make roughly 85 percent of all trades. ... “All these small individual investors are called ‘chives’ in the market,” says Hong Yan, a finance professor at the Shanghai Advanced Institute of Finance. “They get cut over and over again, but they come back every time, like little weeds.” ... By the late 1990s, he became the unofficial captain of a group popularly known as the Ningbo Death Squad. The squad made its reputation by manipulating cheap, relatively unknown stocks, which in the Chinese market are not allowed to rise or fall more than 10 percent in a single trading day. To game the system, the squad devised a strategy: Out of nowhere, it would place a gigantic order for a chosen stock. Other traders, seeing the sudden upward movement in price, would flood in, pushing the stock toward its daily 10-percent limit. Once the stock hit the limit on the first day, the momentum became self-perpetuating. Eager traders rushed to buy the stock as soon as the market opened the next day, propelling it toward the 10-percent limit once again. The movement generated its own publicity and easy profits. After a few days, the squad would sell out, and the stock would tumble back to a lower price as other traders followed. ... “Xu Xiang is always trading,” a longtime friend said. “If he’s not trading, he’s thinking about trading.” ... Nearly every one of the experts I spoke with repeated some version of the same rumor: that Xu was less a financial genius than a puppet of even larger powers. Most often, this explanation was deployed in response to a question that had been troubling observers of the Chinese financial world for months: Why hadn’t Xu stopped earlier? Rumors of his illegal methods were an open secret, and he had already built the most successful hedge fund in China, reaping billions of dollars in personal wealth in the process. Why keep going and risk a reckoning?
In the classical account of a financial market bubble, the price of an asset rises dramatically over the course of a few months or even years, reaching levels that appear to far exceed reasonable valuations of the asset’s future cash flows. These price increases are accompanied by widespread speculation and high trading volume. The bubble eventually ends with a crash, in which prices collapse even more quickly than they rose. Bubble episodes have fascinated economists and historians for centuries (e.g., Mackay 1841, Bagehot 1873, Galbraith 1954, Kindleberger 1978, Shiller 2000), in part because human behavior in bubbles is so hard to explain, and in part because of the devastating side effects of the crash. ... At the heart of the standard historical narratives of bubbles is the concept of extrapolation— the formation of expected returns by investors based on past returns. In these narratives, extrapolators buy assets whose prices have risen because they expect them to keep rising. According to Bagehot (1873), “owners of savings . . . rush into anything that promises speciously, and when they find that these specious investments can be disposed of at a high profit, they rush into them more and more.” ... In this paper, we present a new model of bubbles based on extrapolation. In doing so, we seek to shed light on two key features commonly associated with bubbles. The first is what Kindleberger (1978) called “displacement”—the fact that nearly all bubbles from tulips to South Sea to the 1929 U.S. stock market to the late 1990s internet occur on the back of good fundamental news. ... Second, we would like to explain the crucial fact that bubbles feature very high trading volume (Galbraith 1954, Carlos, Neal, and Wandschneider 2006, Hong and Stein 2007). At first sight, it is not clear how extrapolation can explain this: if, during a bubble, all extrapolators have similarly bullish views, then they would not trade with each other.
Financial crises pose challenges for macroeconomists. Schularick and Taylor (2012) show that credit booms precede crises. Mendoza and Terrones (2008) claim that not all credit booms end in crises. Herrera et al. (2014) argue that crises are not necessarily the result of large negative shocks, but also of political considerations. There is a need for models displaying financial crises that are preceded by credit booms and that are not necessarily the result of large negative shocks. ... In a recent paper (Gorton and Ordonez 2016), we show that credit booms are indeed not rare, that some end in crises (bad booms) but others do not (good booms). Are these two types of booms intrinsically different in their evolution, or do they just differ in how they end? We show that all credit booms start with a positive shock to productivity on average ten years before the end of the boom, but that in bad booms this increase dies off rather quickly while this is not the case for good booms. This suggests that a crisis is the result of an exhausted credit boom. We then develop a simple framework that rationalises these empirical findings and highlight several shortcomings of standard macroeconomic models that tend to neglect the interplay between macroeconomic and financial variables.