The theory that caused the financial crisis gets a Nobel prize

alfred nobelVivek Kaul
Do financial markets have bubbles? Like most things in economics, the answer to what seems like a rather straightforward question, is yes and no. It depends on which economist you are talking to.
Eugene Fama and Robert Shiller are two of the three economists(the third being Peter Hansen) who have won the Nobel Prize in Economics this year.
When it comes to the bubble question Fama feels there are no bubbles. Shiller, on the other hand, has done some of his best work in economics around financial market bubbles. In fact, he was one of the few economists, who predicted both the dotcom bubble as well as the real estate bubble. Ironically enough, both of them have won the Nobel Prize in the same year.
Eugene Fama, who teaches at the University of Chicago, came up with the efficient market hypothesis(EMH), sometime in the 1960s. A lot of financial theory that followed was built around EMH.
Benoit Mandelbrot, a mathematician who did some pioneering work in economics, was Fama’s thesis advisor. As Mandelbrot (along with Richard Hudson) writes in The (Mis) Behavior of Markets – A Fractal View of Risk, Ruin and Reward “It (i.e. EMH) became the intellectual bedrock on which orthodox financial theory sits.”
So what is the EMH? As Mandelbrot and Hudson write “At its heart: In an ideal market, security prices fully reflect all relevant information…Given that, the price at any particular moment must be the “right” one.”
And how is that possible? How can the price of a financial security( lets say a stock or a bond) at any point of time incorporate all the information?
Mark Buchanan explains this through a small thought experiment in his book Forecast – What Physics, Meteorology and Natural Sciences Can Teach Us About Economics “Let’s do a thought experiment, which I’ll call the 5 percent problem. Suppose that on Tuesday morning everyone knew for sure that the markets would recover, stocks gaining 5 percent(on average) in a big rally in the final half hour at the end of the day. Everyone in the market would expect this rise, and lots of people on that morning would be eager to pay up to 5 percent more than current values to buy stock, as they would profit by selling at the day’s very end. Knowledge of the coming afternoon rise would make the market rise immediately in the morning, violating the assumption we made to start this thought experiment; the prediction of a late rally would be totally wrong.” Hence, information about the market rising by 5% towards its close, would be incorporated into the price of the stocks immediately.
Mandelbrot and Hudson give another similar example to explain EMH. “Suppose a clever chart-reader thinks he has spotted a pattern in old price records – say, every January, stocks prices tend to rise. Can he get rich on that information by buying in December and selling in January? Answer: No. If the market is big and efficient then others will spot the trend, too, or at least spot his trading on it. Soon, as more traders anticipate the January rally, more people are buying in December – and then, to beat the trend for a December rally, in November. Eventually, the whole phenomenon is spread out over so many months that it ceases to be noticeable. The trend has vanished, killed by its very discovery,” write Mandelbrot and Hudson.
And this happens primarily because the market is made up of many investors, who are all working towards spotting a trend and trading on it. As Buchanan explains in 
Forecast “In this view, a market is a vast crowd of investors with diverse interests and skills all working hard to gather information on every kind of manufacturing company, bank, nation, technology, raw material, and so on. They use that information to make best investments they can, jumping on any new information that might affect prices as it comes along, and using that information to profit. They sell currently valued stocks, bonds, or other instruments, and buy undervalued ones. These very actions act to drive the prices back toward their proper, realistic, or “intrinsic” values.”
Given this financial markets are correctly priced all the time. Robert Shiller summarises this argument best in 
Irrational Exuberance. As he writes “The efficient markets theory asserts that all financial prices accurately reflect all public information at all times. In other words, financial assets are always priced correctly, given what is publicly known, at all times.”
And if financial assets are correctly priced, there is no question of any speculative bubbles occurring. As John Cassidy writes in 
How Markets Fail – The Logic of Economic Calamities “During the 1960s and ’70s, a group of economists, many of them associated with the University of Chicago, promoted the counter-intuitive idea…that speculative bubbles don’t exist. The efficient market hypothesis…states that financial markets always generate the correct prices, taking into account all of the available information…In short financial prices are tied to economic fundamentals: they don’t reflect any undue pessimism..If markets rise above the levels justified by fundamentals, well informed speculators step in and sell until prices return to their correct levels. If prices fall below their true values, speculators step in buy.”
This ensures that all the available information is priced in. Hence, at any point of time, the market price is the correct price. And given that where is the question of any bubbles popping up? As Fama put it in a 2010 interview, “I don’t even know what a bubble means. These words have become popular. I don’t think they have any meaning.”
Robert Lucas, another University of Chicago economist who won the Nobel prize in 1995, reflected Fama’s sentiment when he said “The main lesson we should take away from the EMH for policy-making purposes is the futility of trying to deal with crises and recessions by finding central bankers and regulators who can identify and puncture bubbles. If these people exist, we will not be able to afford them.”
And this is the view that came to dominate much of the prevailing economic establishment since the 1960s. It is surprising that economists have had so much confidence in a theory for which the evidence is at best sketchy. Raj Patel makes this point in 
The Value of Nothing “The problem with efficient market hypothesis is that it doesn’t work. If it were true, there’d be no incentive to invest in research because the market would, by magic, have beaten you to it. Economists Sanford Grossman and Joseph Stiglitz demonstrated this in 1980, and hundreds of subsequent studies have pointed out quite how unrealistic the hypothesis is, some of the most influential were written by Eugene Fama himself.”
Also, if EMH were true, prices of financial assets would be right all the time, which is clearly not the case. As Buchanan writes “In November 2010, the 
New York Times reported on a dozen “mini flash crashes” in which individual stocks plunged in value over a few seconds recovering shortly thereafter. In one episode, for example, stock of Progress Energy – a company with eleven thousand employees – dropped 90 percent in few seconds. There was no news released about the business prospects of Progress Energy either before or after the event…On May 13(2011), Enstar, an insurer, fell from roughly $100 a share to $0 a share, then zoomed back to $100 in just a few seconds.”
Shiller gives the example of eToys and Toys “R” Us, two companies which were into selling toys. As he writes “Consider, for example, eToys a firm established in 1997 to sell toys over the Internet. Shortly after its initial public offering in 1999, eToys’ stock value was $8 billion, exceeding the $6 billion value of the long established “brick and mortar” retailer Toys “R” Us. And yet in fiscal 1999 eToys’ sales were $30 million, while the sales of Toys “R” Us were $11.2 billion, almost 400 times larger. And eToys’ profits were a negative $28.6 million, while the profits of Toys “R” Us were a positive $376 million.”
So a company with no profits had a greater market capitalization in comparison to a company making substantial profits. Now as per the EMH this should have never happened. Investors would have sold the eToys’ stock and driven down its price. But that did not happen, at least for a few years. And the stock price of eToys went from strength to strength.
But despite the weak evidence in support of EMH, the prevailing economic thinking since the 1960s has been that market prices of financial assets reflect the fundamentals, and hence, there was no chance of bubbles popping up. And even if bubbles did pop up, now and then, there was no chance of identifying them in advance. Alan Greenspan, the Chairman of the Federal Reserve of United States between 1987 and 2006, believed that a central bank could not spot a bubble, but could hope to mitigate its fallout, once it burst.
This led to him letting the dotcom bubble run. A few years later he let the real estate bubble run as well. He was just following the economic theory that has dominated over the last few decades. As Patel writes “ Despite ample economic evidence to suggest it was false, the idea of efficient markets ran riot through governments. Alan Greenspan was not the only person to find the hypothesis a convenient untruth. By pushing regulators to behave as if the hypothesis were true, traders could make their titanic bets…Governments enabled the finance sector’s binge by promising to be there to pick up the pieces, and they were as good as their word.”
In the end, Greenspan did find out that the model did not work and that bubbles did occur, now and then. As he admitted to before a committee of the House of Representatives in October 2008, “I found a flaw in the model that I perceived is the critical functioning structure that defines how the world works, so to speak…I had been going for 40 years or more with very considerable evidence that it was working exceptionally well.”
So Eugene Fama’s EMH doesn’t really work and has caused the world a lot of harm.
Now compare this to Robert Shiller who in the first edition of 
Irrational Exuberance, which released some time before the dotcom bubble burst, compared the stock market to a Ponzi scheme. As he wrote “Ponzi schemes do arise from time to time without the contrivance of a fraudulent manager. Even if there is no manipulator fabricating false stories and deliberately deceiving investors in the aggregate stock market, tales about the market are everywhere. When prices go up a number of times, investors are rewarded sequentially by price movements in these markets just as they are in Ponzi schemes. There are still many people (indeed, the stock brokerage and mutual fund industries as a whole) who benefit from telling stories that suggest that the markets will go up further. There is no reason for these stories to be fraudulent; they need to only emphasise the positive news and give less emphasis to the negative.”
Hence, financial markets at times degenerate into Ponzi schemes, where prices are going up simply because prices are going up. These bubbles can keep running for a while, just as the dotcom bubble in the US and the real estate bubble all over the developed world, did. When these bubbles burst, they caused huge economic problems, as we have seen over the last few years.
The trouble is that the dazzle of efficient market hypothesis has blinded economists so much that they cannot spot bubbles anymore. Hence, it is important that economists junk the efficient market hypothesis, and start looking at a world where bubbles are possible and keep popping up all the time. Else, we will have more trouble ahead.

The article originally appeared on on October 15, 2013
(Vivek Kaul is a writer. He tweets @kaul_vivek) 

Why most economists did not see the rupee crash coming

rupeeVivek Kaul
Economists and analysts have turned bearish on the future of the rupee, over the last couple of months. But very few of them predicted the crash of the rupee. Among the few who did were,SS Tarapore, a former deputy governor of the Reserve Bank of India, and Rajeev Malik of CLSA.
Tarapore felt that the rupee should be closer to 70 to a dollar. As he pointed out in a column published in The Hindu Business Line on January 24, 2013 “
With the inflation rate persistently above that in the major industrial countries, the rupee is clearly overvalued. Adjusting for inflation rate differentials, the present nominal dollar-rupee rate of around $1 = Rs 54 should be closer to $1 = Rs 70. But our macho spirits want an appreciation of the rupee which goes against fundamentals.”
Rajeev Malik of CLSA said something along similar lines in a column published on Firstpost on January 31, 2013. “
The worsening current account deficit is partly signalling that the rupee is overvalued. But the RBI and everyone else are missing that clue,” he wrote. The current account deficit is the difference between total value of imports and the sum of the total value of its exports and net foreign remittances
What Tarapore and Malik said towards the end of January turned out to be true towards the end of May. The rupee was overvalued and has depreciated 20% against the dollar since then. The question is why did most economists and analysts not see the rupee crash coming, when there was enough evidence available pointing to the same?
One possible explanation lies in what Nassim Nicholas Taleb calls the turkey problem (something I have talked about in a slightly different context earlier). As Taleb writes in his latest book
Anti Fragile “A turkey is fed for a thousand days by a butcher; every day confirms to its staff of analysts that butchers love turkeys “with increased statistical confidence.” The butcher will keep feeding the turkey until a few days before thanksgiving. Then comes that day when it is really not a very good idea to be a turkey. So, with the butcher surprising it, the turkey will have a revision of belief—right when its confidence in the statement that the butcher loves turkeys is maximal … the key here is such a surprise will be a Black Swan event; but just for the turkey, not for the butcher.”
The Indian rupee moved in the range of 53.8-55.7 to a dollar between November 2012 and end of May 2013. This would have led the ‘economists’ to believe that the rupee would continue to remain stable against the dollar. The logic here was that rupee will be stable against the dollars in the days to come, because it had been stable against the dollar in the recent past.
While this is a possible explanation, there is a slight problem with it. It tends to assume that economists and analysts are a tad dumb, which they clearly are not. There is a little more to it. Economists and analysts essentially feel safe in a herd. As Adam Smith, the man referred to as the father of economics, once asserted,
“Emulation is the most pervasive of human drives”.
An economist or an analyst may have figured out that the rupee would crash in the time to come, but he just wouldn’t know when. And given that he would be risking his reputation by suggesting the obvious. As John Maynard Keynes once wrote
“Worldly wisdom teaches us that it’s better for reputation to fail conventionally than succeed unconventionally”.
An economist/analyst predicting the rupee crash at the beginning of the year would have been proven wrong for almost 6 months, till he was finally proven right. This is a precarious situation to be in, which economists/analysts like to avoid. Hence, they tend to go with what everyone else is predicting at a particular point of time.
Research has shown this very clearly. As Mark Buchanan writes in
Forecast – What Physics, Meteorology and the Natural Sciences Can Teach Us About Economics “Financial analysts may claim to be weighing information independently when making forecasts of things like inflation…but a study in 2004 found that what analysts’ forecasts actually follow most closely is other analysts’ forecasts. There’s a strong herding behaviour that makes the analysts’ forecasts much closer to one another than they are to the actual outcomes.” And that explains to a large extent why most economists turned bearish on the rupee, after it crashed against the dollar. They were just following their herd.
There is another possible explanation for economists and analysts missing the rupee crash. As Dylan Grice, formerly an analyst with Societe Generale, and now the editor of the Edelweiss Journal, put it in a report titled
What’s the point of the macro? dated June 15, 2010 “Perhaps a more important thought is that we’re simply not hardwired to see and act upon big moves that are predictable.”
A generation of economists has grown up studying and believing in the efficient market hypothesis. It basically states that financial markets are largely efficient,meaning that at any point of time they have taken into account all the information that is available. Hence, the markets are believed to be in a state of equilibrium and they move only once new information comes in. As Buchanan writes “the efficient market theory doesn’t just claim that information should move markets. It claims that
only information moves markets. Prices should always remain close to their so called fundamental values – the realistic value based on accurate consideration of all information concerning the long-term prospects.”
What does this mean in the context of the rupee before it crashed? At 55 to a dollar it was rightly priced and had incorporated all the information from inflation to current account deficit, into its price. And given this, there was no chance of a crash or what economists and analysts like to call big outlier moves.
Benoit Mandlebrot, a mathematician who spent considerable time studying finance, distinguished between uncertainty that is mild and that which is wild. Dylan Grice explains these uncertainties through two different examples.
As he writes “Imagine taking 1000 men at random and calculating the sample’s average weight. Now suppose we add the heaviest man we can find to the sample. Even if he weighed 600kg – which would make him the heaviest man in the world – he’d hardly change the estimated average. If the sample average weight was similar to the American average of 86kg, the addition of the heaviest man in the world (probably the heaviest ever) would only increase the average to 86.5kg.”
This is mild uncertainty.
Then there is wild uncertainty, which Dylan Grice explains through the following example. “For example, suppose instead of taking the weight of our 1000 American men, we took their wealth. And now, instead of adding the heaviest man in the world we took one of the wealthiest, Bill Gates. Since he’d represent around 99.9% of all the wealth in the room he’d be massively distorting the measured average so profoundly that our estimates of the population’s mean and standard deviation would be meaningless…If weight was wildly distributed, a person would have to weight 30,000,000kg to have a similar effect,” writes Grice.
Financial markets are wildly random and not mildly random, like economists like to believe. This means that financial markets can have big crashes. But given the belief that economists have in the efficient market hypothesis, most of them can’t see any crash coming.
In fact, when it comes to worst case predictions it is best to remember a story that Howard Marks writes about in his book The Most Important Thing (and which Dylan Grice reproduced in his report titled Turning “Minimum Bullish” On Eurozone Equities dated September 8,2011). As Marks writes “We hear a lot about “worst case” projections, but they often turn out not to be negative enough. I tell my father’s story of the gambler who lost regularly. One day he heard about a race with only one horse in it, so he bet the rent money. Halfway around the track the horse jumped over the fence and ran away. Invariably things can get worse than people expect. Maybe “worse case” means “the worst we have seen in the past”. But it doesn’t mean things can’t be worse in the future.” 
Disclosure: The examples of SS Tarapore and Rajeev Malik were pointed out by the Firstpost editor R Jagannathan in an earlier piece. You can read it here)
The article originally appeared on on August 26, 2013
(Vivek Kaul is a writer. He tweets @kaul_vivek)