Three things worth remembering

Nice charts from Dresdner Kleinwort Wasserstein:

I personaly agree with all above. Charts are from 2004, but they are and will be actual for a long time. Analysts are bullish most of the time. Because in the long term... stock and also GDP is rising.


One more note from Dresdner:


Look at the chart below.  In a study by Torngren and Montgomery, two groups of participants, lay people and professionals, were asked to choose which stock was going to outperform each month.  The laypeople were undergrads in psychology and the professional investors were portfolio managers, analysts and brokers.

They would chose between two stocks (well known blue chip names).  They were all given the name, the industry and previous 12 months performance for each stock.

The students were 59% confident in their stock picking abilities on average and the professionals averaged 65% confidence.  Obviously the lay people outperformed the professionals by a large margin.

When the professionals were 100% sure they were correct, they were actually right less than 15% of the time!  Look below at how, as the "perfect calibration" line (confidence level) moves up, performance declined -- dramatically for the professionals.  Also notice how lay people never said they were 100% confident.

You might think these studies are flawed or that I'm cherry picking the studies, but I have tons of research on this with a number of other studies that show the same thing.  The point is you don't want to be overly confident when positioning yourself.

It's always important to know what the indicators that you're following actually mean, to get as good of a grip on market action as possible.  But no matter what, always remain humble and avoid the cycle described above, and avoid having an ego at all costs.

It's no wonder 85% - 90% of fund managers underperform the market.

And what is "The Market" anyway?  Not what most people think ...



Hat Tip Chris Rowe

The Dark Magic of Structured Finance

I read somewhere last week that you can make from $100 bn portfolio of BBB rated securities brand new portfolio of $90 bn triple A rated securities... Amazing stuff.

Too bad I cant find a link. Anyway, this story from Marginal Revolution is also very interesting.

Marginal Revolution:

In Too Big To Save Robert Pozen gives a clever example, based on an excellent paper by Coval, Jurek and Stafford, which explains both the lure of structured finance and why the model exploded so quickly.

Suppose we have 100 mortgages that pay $1 or $0. The probability of default is 0.05 (assume independence). We pool the mortgages and then prioritize them into tranches such that tranche 1 pays out $1 if no mortgage defaults and $0 otherwise, tranche 2 pays out $1 if 1 or fewer mortgages defaults, $0 otherwise. Tranche 10 then pays out $1 if 9 or fewer mortgages default and $0 otherwise. Tranche 10 has a probability of defaulting of 2.82 percent. A fortioritranches 11 and higher all have lower probabilities of defaulting. Thus, we have transformed 100 securities each with a default of 5% into 9 with probabilities of default greater than 5% and 91 with probabilities of default less than 5%.

Now let's try this trick again. Suppose we take 100 of these type-10 tranches and suppose we now pool and prioritize these into tranches creating 100 new securities. Now tranche 10 of what is in effect a CDO will have a probability of default of just 0.05 percent, i.e. p=.000543895 to be exact. We have now created some "super safe," securities which can be very profitable if there are a lot of investors demanding triple AAA.

To review we have assumed that the underlying mortgages each have a probability of default of p=.05 and by pooling and prioritizing we have created a tranche with a probability of default of just p=.0282 and a CDO with a probability of default of p=.0005. In this way, structured finance was able to create many triple AAA securities from a pool of securities none of which were triple AAA. This point is widely understood. Now here is a much less well understood consequence.

Suppose that we misspecified the underlying probability of mortgage default and we later discover the true probability is not .05 but .06. In terms of our original mortgages the true default rate is 20 percent higher than we thought--not good but not deadly either. However, with this small error, the probability of default in the 10 tranche jumps from p=.0282 to p=.0775, a 175% increase. Moreover, the probability of default of the CDO jumps from p=.0005 to p=.247, a 45,000% increase!

The dark magic of structured finance conjured many low-risk securities out of many risky securities. Like all dark magic, however, the conjuring came at a price because if you didn't get the spell exactly correct it was easy to create something much more risky and dangerous than you were likely to have ever imagined.

Here is an excel file, StructuredFinanceMath, with the calculations.

Addendum: Adding in correlation among mortgage defaults makes the math more difficult but doesn't change the bottom line that I wanted to illustrate which is that small changes in the underling default risk (or correlation) are highly amplified in the tranches and CDOs.

Complexity in Financial Systems

The Psy-Fi Blog:

What's Complexity?

We can probably all agree that modern day financial systems are complex, but what that actually means isn’t something that everyone agrees on. Typically, though, a system characterised by complexity isn’t something that anyone’s designed – it emerges, it adapts spontaneously and it produces stunningly unexpected outcomes when no one’s expecting them.

Which, let’s face it, sounds a lot like modern finance. The problem is that many economists are focusing on how they manage this system when, in reality, it’s impossible to do so. It’s like trying to contain swine flu using a butterfly net.

Complexity Is Not Engineering

When many people, including economists, discuss complex systems they often use analogies with complicated engineered systems like aircraft or nuclear power systems. Now these are definitely complicated, with many, many interacting parts, the failure of any of which may compromise their integrity. However, complicated human engineered systems are not truly complex. For the most part the designers of these systems go out of their way to make sure that they don’t exhibit the trademark unpredictability and non-linear outcomes of complexity.

Indeed, the very fact that these systems have a designer is a sure sign that they’re not truly complex. This was the problem that Charles Darwin solved – how do complex things like human beings come into existence if not through the guidance of a designer? The answer, of course, is that complexity can arise through interaction with the environment as long as there’s some means of adaptation. These are the trademarks of complex adaptive systems. Darwin was concerned with biological evolution, but the global financial system is of the same type.

Complex Means Adaptive

There are two noteworthy things about complex adaptive systems. The first is that they’re complex. The second is that they’re adaptive.

And while that may be a statement of the bloody obvious it’s one that seems to escape many financiers studying the subject. The ability of the system to adapt, often in completely unpredictable ways, means that you can’t model it and you can’t foresee the outcomes of any strategy of intervention. It’s all completely unknowable in advance.

Once you accept this it becomes suddenly apparent that a huge swathe of modern finance is complete rubbish. For example, in a complex system you expect to see “tipping points” or phase transitions when the system suddenly and unpredictably switches from one stable state to another. As Caballero and Krishnamurthy have documented this appears to be exactly what happens during the episodes of liquidity hoarding and flights to quality associated with financial crises. People suddenly switch from a belief that they’re in a state where risk is measurable based on probability to one characterised by fear in the face of absolute uncertainty, so called Knightian uncertainty.

So, in the depths of the panic of 2008 we saw investors selling Collateralised Debt Obligations at almost any price largely because they didn’t know how to analyse them. What it looks like is that they bought these sub-prime backed securities because they’d been given the highest rating possible by the credit rating agencies. When some of these went bad the investors – many of them supposedly high powered institutions – belatedly recognised that they hadn’t got a clue about what they’d bought and sold, virtually at any price. One day they had nice risk models giving default probabilities, the next day they had junk.

The Theory of Rational Ignorance

In fact the problem is slightly worse than this. Many of these institutions had rationally decided not to invest in understanding the products they were investing in because they figured out that it was too expensive to employ the people capable of analysing the issues, an example of The Theory of Rational Ignorance. As Steven L. Schwarcz has remarked in Regulating Complexity in Financial Markets:

“The complexities of modern investment securities can lead to a failure of investing standards and financial-market practices for several reasons: these complexities impair disclosure; they obscure the ability of market participants to see and judge consequences; and they make financial markets more susceptible to financial contagion and also more susceptible to fraud.”

Our problem is that most of the time we’re not prepared to invest as though everything’s about to go wrong. We’re habitually biased to look at the upside, not the downside so we build portfolios without hedges, because they’ll restrict our short-term profits and we’ll always take the view we can get out before it all goes wrong. This is where an understanding of the instability of the global financial system can help investors: it spends its life permanently tip-toeing across a shaky wire over a gorge populated with extremely hungry crocodiles.

And it's got vertigo.

The Next Cause Will Be Different

There’s quite a lot of work now going into figuring out how we prevent the next crisis, much of it looking at how the financial system is re-engineered to prevent these types of failures. It’s a pointless exercise, because as fast as one set of rules is created the system will mutate to find ways around it. In so doing it’ll create all manner of unexpected connections, invisible to the overseers. Who, for instance could have predicted that badly designed mortgage schemes in middle America could have led to the collapse of the Icelandic government? Hidden links and invisible chains of consequence are everywhere in global finance.

Because the global financial system isn’t engineered and doesn’t have a designer there’s no way of controlling it. Those industrious academics trying to figure out how to use engineering concepts used to manage risk on complicated systems like aircraft are wasting their time. The failure of the global financial system isn’t like a single airplane unexpectedly crashing, it’s more like every single aircraft crashing simultaneously. It’s not the problems we can see, like the design of the avionics computer, that are the issue, it’s the fact that air-traffic control systems are dependent on a small number of global positioning satellites each of which happen to use the same specialised microprocessor, which has an unknown bug which is triggered by a combination of a certain date and freak sunspot activity.

Or something else, equally unpredictable.

Punks

Taken together the complexity of the global financial system, and the way that it’s often linked by tight but unappreciated couplings such that a small perturbation in one area can lead to devastating consequences elsewhere, makes it fundamentally unstable. Worse, however, is that even if you can get a handle on the risks today by tomorrow they’ll have changed. In such circumstances believing any prediction is an act of faith, rather than an intelligent assumption.

Equally any set of economic theories or financial models or loudmouthed gurus that claim to be able to foresee the future are hopelessly lost in their own rhetoric. There is no designer, there is no plan, there is no predictability. There’s just stuff, which happens. The best we can do either is plan with a margin of safety or just get lucky.

So, do you feel lucky, punks?