How my IIMB Class explains the 2008 financial crisis

I have a policy of not enforcing attendance in my IIMB class. My view is that it’s better to have a small class of dedicated students rather than a large class of students who don’t want to be there. One of the upsides of this policy is that there has been no in-class sleeping. Almost. I caught one guy sleeping last week, in what was session 16 (out of 20). Considering that my classes are between 8 and 9:30 am on Mondays and Tuesdays, I like to take credit for it.

I also like to take credit for the fact that despite not enforcing attendance, attendance has been healthy. There have usually been between 40 and 50 students in each class (yes, I count, when I’ve bamboozled them with a question and the class has gone all quiet), skewed towards the latter number. Considering that there are 60 students registered for the course, this translates to a pretty healthy percentage. So perhaps I’ve been doing something right.

The interesting thing to note is that where there are about 45 people in each class, it’s never the same set of 45. I don’t think there’s a single student who’s attended all of my classes. However, people appear and disappear in a kind of random uncoordinated fashion, and the class attendance has remained in the forties, until last week that is. This had conditioned me into expecting a rather large class each time I climbed up that long flight of stairs to get into class.

While there were many causes of the 2008 financial crisis, one of the prime reasons shit hit the fan then was that CDOs (collateralised debt obligations) blew up. CDOs were an (at one point in time) innovative way of repackaging receivables (home loans or auto loans or credit card bills) so as to create a set of instruments of varying credit ratings.

To explain it in the simplest way, let’s say I’ve lent money to a 100 people and each owes me a rupee each month. So I expect to get a hundred rupees each month. Now I carve it up into tranches and let’s say I promise Alice the “first 60 rupees” I receive each month. In return she pays me a fee. Bob will get the “next 20 rupees”, again for a fee. Note that if fewer than 60 people pay me this month, Bob gets nothing. Let’s say Eve gets the next 10 rupees, so in case less than 80 people pay up, Eve gets nothing. So this is very risky, and Eve pays much less for her tranche than Bob pays for his which is in turn much less than what Alice pays for hers. The last 10 rupees is so risky that no one will buy it and so I hold it.

Let’s assume that about 85 to 90 people have been paying on their loans each month. Not the same people, but different, like in my class. Both Alice and Bob are getting paid in full each month, and the return is pretty impressive considering the high ratings of the instruments they hold (yes these tranches got rated, and the best tranche (Alice’s) would typically get AAA, or as good as government bonds). So Alice and Bob make a fortune. Until the shit hits the fan that is.

The factor that led to healthy attendance in my IIMB class and what kept Alice and Bob getting supernormal returns was the same – “correlation”. The basic assumption in CDO markets was that home loans were uncorrelated – my default had nothing to do with your default. So both of us defaulting together is unlikely. When between 10 and 15 people are defaulting each month, that 40 (or even 20) people will default together in a given month has very low probability. Which is what kept Alice and Bob happy. It was similar in my IIMB class – the reason I bunk is uncorrelated to the reason you bunk, so lack of correlation in bunking means there is a healthy attendance in my class each day.

The problem in both cases, as you might have guessed, is that correlations started moving from zero to one. On Sunday and Monday night this week, they had “club selections” on IIMB campus. Basically IIMB has this fraud concept called clubs (which do nothing), which recruiters value for reasons I don’t know, and so students take them seriously. And each year’s officebearers are appointed by the previous year’s officebearers, and thus you have interviews. And so these interviews went on till late on Monday morning. People were tired, and some decided to bunk due to that. Suddenly, there was correlation in bunking! And attendance plummeted. Yesterday there were 10 people in class. Today perhaps 12. Having got used to a class of 45, I got a bit psyched out! Not much damage was done, though.

The damage was much greater in the other case. In 2008, the Federal Reserve raised rates, thanks to which banks increased rates on home loans. The worst borrowers defaulted, because of which home prices fell, which is when shit truly hit the fan. The fall in home prices meant that many homes were now worth less than the debt outstanding on them, so it became rational for homeowners to default on their loans. This meant that defaults were now getting correlated! And so rather than 85 people paying in a month, maybe 45 people paid. Bob got wiped out. Alice lost heavily, too.

This was not all. Other people had bet on how much Alice would get paid. And when she didn’t get paid in full, these people lost a lot of money. And then they defaulted. And it set off a cascade. No one was willing to trade with anyone any more. Lehman brothers couldn’t even put a value on the so-called “toxic assets” they held. The whole system collapsed.

It is uncanny how two disparate events such as people bunking my class and the 2008 financial crisis are correlated. And there – correlation rears its ugly head once again!

 

Tranche of wallet

One of the buzzwords in marketing in the last few years has been “share of wallet”. “We don’t aim for market share in any particular segment”, they say. “What we are aiming for is a larger portion of the customer’s share of wallet”. Basically what marketers try to do is to design their products such that a larger portion of customers’ spending comes to them rather than go to competitors (again – they claim they have no direct competitors and everyone else who competes for the customer’s spending is a competitor).

So far so good. But the problem with looking at things from a “share of wallet” pespective is that it assumes that the wallet is homogeneous. That each part of the wallet is similar to the other, and spending for different items comes uniformly from all parts of the wallet. This isn’t usually very well recognized, but what matters more than “share of wallet” (of course that matters) is the “tranche of wallet” that this particular product sits in.

I don’t think I need to give a rigorous proof for this – but some spending is more equal than others. For example, if you are dirt poor and have only ten rupees left in your pocket, you would rather buy a loaf of bread than buy a tube of lipstick. Some goods are more important than the others. “Necessities” they call them. The rest become “luxuries”. Even the “luxuries” are not homogeneous – there are various tranches in that.

So the aim for the product manager should be to get into the deeper tranches of the customer’s wallet (assuming that the top tranche is the “equity tranche” – the one that takes the first hit when spending has to be cut). Targeting the top tranche may be a good business in good times, but when things go even slightly bad, spending on this product is likely to take a hit and thus the “share of wallet” falls dramatically. Getting into a deeper tranche means more insurance, so to say.

In the world of  CDOs (from where I borrow this tranche, equity, etc. terminology), people who take on the equity tranche and other more risky tranches do so only in exchange for a premium – basically that you need to be paid a premium amount (compared to lower tranches) during good times so that it compensates for lack of income in the bad times. So this means that if you are trying to target the most disposable part of the wallet (i.e. the part of wallet that takes the first hit when spending has to be cut), you better be a premium player and make enough money during good times.

So the basic insight is that. The more disposable spending on your product is for your customer, the more the premium that you have to charge. Some products such as high end fashion accessories seem to have got it right. Extremely disposable spending, which leads to volatility of income; balanced by extremely high margins which make good money in good times.

Certain other products, however, don’t seem to have got it right. One example that comes to mind is Indian IT. Some of the offerings of Indian IT companies come near the disposable end of their customers’ wallets. However, to compensate for this, they don’t seem to charge enough of a premium. So they make “normal” profits during good times, and sub-normal profits during bad times – leading to an average of sub-par performance.

So before you enter a business, see which part of your customer’s wallet you are targeting. See if the returns that you will get out of this business in good times will be enough to tide you over during bad times. And only then invest. Of course, before the 2007-present downturn happened, people had no idea what bad times were, and thus entered into risky businesses without enough of a risk premium.