Unfortunately, "the market is irrational" doesn't imply "you can name the ways in which it is irrational" nor does it imply even that there exists any single entity that is capable of correctly naming the way in which it is irrational. It is perfectly capable of having, and indeed almost certainly has, a chaotic, highly-information-packed, very fast-moving irrationality that is beyond any human or human institution's ability to understand, quantify, express, predict, control, harness, or "fix". I do not mean that figuratively or metaphorically... there's no reason to believe the market's irrationality is even remotely comprehensible.
So the argument shouldn't be phrased in terms of whether the market is efficient or not... everybody knows it isn't. So let's cut to the chase... why do you (for generalized values of "you") think you know better, and if you do know better, why aren't you using it to make a killing, or, alternatively, how about you write down some interesting predictions about what's going to happen in three or four years and demonstrate the rightness of your theories? Say something interesting and verifiable, and let's see how you do.
In the meantime, merely making the tedious observation that the market isn't "really" rational gets you no points, and I perceive no obligation on my part to change any of my political beliefs merely because "the market isn't rational". On the other hand, make correct predictions years in advance, especially if you can do so reliably, and I will sit up and take notice, I promise you. But, be warned, I'm very familiar with the process of bending a prediction to fit the data and that's not going to cut it... I demand that you be right, full stop. If you can't do that... welcome to the group of people who know the economy is irrational but can do nothing meaningful about it, population: entire rest of humanity.
Absolutely. The number of players involved and the level of information asymmetry mean that it's not even knowable how the market is or isn't irrational.
You're basically arguing that "alpha" is an illusion borne out of the quirks of distributed probability. I (along with many leading minds in finance) also believe this to be true. What many hedge funds call "alpha" is often just dumb luck. In the few cases that it isn't, policy changes at central banks are often involved (this is why it's taken the fed several years to choreograph the wind-down of QE).
But the irony here is that the fact that everyone believes they can beat the market is what makes the market as efficient and liquid as it is. If everyone traded with the same strategy, you'd see massive swings in volatility and information asymmetry would be an even bigger issue than it is. Because there are so many different trading strategies built to hunt out arbitrage in certain pockets, the market as a whole is incredibly efficient - or at least more efficient than it would otherwise be.
Whether or not they are capable of guessing the direction of the markets is irrelevant: if you take a portfolio strategy and make equal bets on enough different assets, you'll end up with something that is probably close to the market rate of return anyway. Note that this only applies to the "professional investor" class (as defined by the SEC); everyone else is simply better off in mutual funds. Professional investors have access to classes of securities with a higher average rate of return than normal citizens do, so they likely can beat the market as long as they're also able to absorb big losses in the years they don't beat the market.
I don't think this is true. Plenty of smart people who worked with various models knew their data wasn't solid and reflected just a few years of a benign market, and plenty of people understood the rather obvious idea of a Black Swan.
The reason they kept at it was systemic: they were paid to sit and cheer the market up, continue to sell product, and generally not question the business model.
The people who made a lot of money off the crash tended to be people who were able to sit out the upswing in some way, without being punished too hard. Hedge fund managers with either new funds or long track records, like Paulson and Andrew Lahde.
The crash was always coming. I remember going to a luncheon at GS where that was the major point. This was in 2006, and they predicted it would start in 2007 and culminate in 2008.
Most models assume financial markets are a continuous function, when in reality markets are mostly continuous with periodic step functions. When you hit a period with a step function, the market is either being irrational or correcting prior irrationality. You can't predict these step functions with any accuracy; though many of the big investment banks knew it was coming a year or two in advance. But even if you can predict them, there is no good way to model them.
Goldman Sachs, for all its faults, is run by exceptionally competent people. They came out of the downturn stronger than they went in. They understand the models well because they built most of them. But there were plenty of large market players at Lehman, Merrill, Nationwide, etc. who were ignorant of the problems until it was too late. These are the people who just did what the model told them to because it was making them money, and they didn't understand the risk exposure they really had.
Do you think all these guys with fancy degrees did not think about this? Come on, of course they did. You don't even need to know about any model in particular to understand that models rest on assumptions. It's a high school concept they teach you in any TOK class.
The reason GS was able to react is IMO they have a great network. The culture is geared towards finding out what other people are thinking. They're the only firm I've been out to dinner with where the guys cared to hear my opinion, in depth. The same salesguy at another shop reverted back to type.
So they found out through their feedback that many, many people did not think the models were correct and acted on it.
The problem was that models assumed some risks were uncorrelated and in 2008 they became highly correlated.
A lot of major wall street institutions got destroyed by it.
2008 was not the first time correlation shot to 1. Sure, it's hard to model, I'll admit that. But to think that nobody had considered this is wrong.
I saw a bunch of people who knew the models were wrong, but nobody had the balls to say so while the spreadsheets still worked.
But it turns out that it's still a good idea to teach Newtonian mechanics -- it's a useful model, as long as you know its limitations.
Theories and models aren't just right or wrong. Some are more wrong than others. Isaac Asimov summed it up better than I could:
http://chem.tufts.edu/answersinscience/relativityofwrong.htm
Newtonian mechanics isn't so much wrong as it is incomplete. Is anything in economics like that? It doesn't seem so.
It turns that it produces results that are close enough to reality to be good enough in lots of scenarios. (And, similarly to how you can ignore relativity in lots of scenarios, you can also ignore lots of other complexifying bits of physics some of the time -- plenty of mechanical equations will give you "good enough" results without taking into account air resistance, for example).
Yes, much of economics is like that. Economics is studying an inherently more complicated problem than simple billiard-ball mechanics, but the idea that economics has nothing useful to say about the real world is an agenda sold by people who don't like the implications of orthodox economics.
You are attempting to measure the objective truth inherent in some model. Be careful with this (or at least be explicit about it).
Newtonian mechanics is pretty accurate to an astonishing degree[0]. To call it "wrong in all scenarios" is saying that because it is wrong in one scale, it is wrong in another. At which point every physics theory we have is "wrong in all scenarios". The standard model can't predict or talk about planck level physics, and thus, it is "wrong in all scenarios". GR can't talk about quantum gravity and thus is "wrong in all scenarios". Hell, the Schrödinger equation is "wrong in all scenarios".
If you believe in a fundamental truth inherent in some equation or model of some system, that is fine. But I think that is far from an accepted point of view.
[0]http://www.npl.washington.edu/eotwash/sites/www.npl.washingt...
Imagine a yardstick that is only marked at full inches. You can use it to measure things in the scale of a couple of yards, a few feet, and many inches. You can't use it to measure anything smaller than an inch because it's not marked for that scale. You can't use it to measure anything more than a couple of yards because that's unwieldy. That doesn't mean that the yard stick is "wrong".
The yardstick analogy was set up by the parent to be 'because the yardstick doesn't have marks less than an inch'
Then yardstick is always an approximation that is useful within a particular domain, just as newtonian mechanics are always an approximation that is useful within a particular domain. So far we are in agreement.
Newtonian mechanics always produces an incorrect result, however when the error is small enough to be neglected, because our measurements are noisy or we have no requirement for greater precision, then we can say that they are accurate for our purposes. This is pretty much the definition of an approximation.
It also must be pointed out that in order to know whether our application falls within the domain of values for which Newtonian mechanics are accurate enough, we must also understand something about relativity and quantum mechanics.
Newtonian mechanics alone can't tell you anything about when it is grossly inaccurate, and when it gives you a value that is indistinguishable from experiment. You must understand its limits in order to use in in the general case. It is therefore not 'perfectly accurate', but merely a good approximation based on limited data.
And what investors try to do would be akin to asking a physicist to examine two cars before a Nascar race and tell you who was going to win the race.
Newtonian mechanics may not be 100% accurate but it's extremely accurate for a wide range of real-world, useful scenarios, to the extent that any discrepancy with reality is often beyond what can be measured. For example, the Pioneer Anomaly was a discrepancy of a few thousand kilometers in distance, over a total distance of more than a billion kilometers. This was still enough to prompt a lot of investigation, and the problem was finally solved by properly accounting for photon pressure from thermal emissions from the spacecraft itself. This is a discrepancy on the order of parts per million that could not only be detected but was considered extremely significant.
I get the impression that economists, on the other hand, are ecstatic if their theories are within even 1% of reality. That's a whole different class of wrongness.
In 99.9% of use cases, Newtonian physics are completely accurate, not a decimal out of place.
Market explanations of 'efficiency'? Way out of whack.
If you're doing orbital calculations, it's often wrong.
In the vast majority of real world calculations, it's not approximate. It gives the same answer as relativistic calculations.
Oh, I have an analogy. It's like using 64 bit integers instead of bigints. Any time you input real world numbers, they never go above ten million. Both models give you the correct answer, no error.
No model ever captures the entire nuance of reality. Even a notion of speed is misleading when your objects contain heat. So don't peek inside the model and judge it based on how the pieces interact inside. Judge it based on the results. And Newtonian physics typically give you ideal perfect results.
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Or maybe I should put it a different way:
Newtonian physics are an approximation for the question "In a counterfactual thought experiment where my measurement had infinite precision in trailing zeroes, what would the answer be?"
Newtonian physics are exact for the question "What is the answer based on my measurement?"
Problems occur when people expect the model to correspond 100% to reality, which it was never intended to do. It is confusing the map for the territory. Unfortunately most journalists have this tendency.
IMHO there's nothing wrong with economic bubbles, there's no economic law that I know of which says that economic growth should only happen linearly.
What was wrong with the financial bubble of 2008 was the way it was handled, starting with the Bear Stearns bailout in early 2008 (of which not many people speak anymore, is like everything started with Lehman Brothers in September).
Yes, banks had made some very wrong assumptions and they should have paid dearly for them, like in any free market. That didn't happen.
Problem is, the companies selling said securities have no interest in identifying the downside. Nor are they legally obligated to since they are selling these products to "professional investors" who ostensibly should know better.
Just because the assumption is wrong doesn't mean it's not useful: without it, you can't even build a reasonable model of financial markets. But because the assumption is core to financial modeling, this means that all financial models are wrong. In fact, that's exactly how my financial modeling professor opened up the first class: by explicitly stating that all models are wrong in some way. You have to understand the ways that the model can be wrong in order to make any substantive claims about it. The Black-Shoals options pricing model assumes market liquidity; it's not very useful if you're talking about an asset that isn't very liquid.
Misunderstanding when models should and should not be applied is one of the core reasons we got into an asset bubble in the mid-2000s. Banks were pricing financial products using models whose assumptions did not hold over the long-term. They didn't understand how their models were wrong until it was too late, and it ended up losing them (but ultimately the American taxpayers) a lot of money. But because the assumption that markets are always rational and efficient is wrong, it doesn't follow that markets are never rational or efficient. Markets can be rational and efficient, but it depends on the relative timeframe and the structure of the market involved.