## Models

This is my first ever handwritten post. Wrote this using a Natraj 621 pencil in a notebook while involved in an otherwise painful activity for which I thankfully didn’t have to pay much attention to. I’m now typing it out verbatim from what I’d written. There might be inaccuracies because I have a lousy handwriting. I begin

People like models. People like models because it gives them a feeling of being in control. When you observe a completely random phenomenon, financial or otherwise, it causes a feeling of unease. You feel uncomfortable that there is something that is beyond the realm of your understanding, which is inherently uncontrollable. And so, in order to get a better handle of what is happening, you resort to a model.

The basic feature of models is that they need not be exact. They need not be precise. They are basically a broad representation of what is actually happening, in a form that is easily understood. As I explained above, the objective is to describe and understand something that we weren’t able to fundamentally comprehend.

All this is okay but the problem starts when we ignore the assumptions that were made while building the model, and instead treat the model as completely representative of the phenomenon it is supposed to represent. While this may allow us to build on these models using easily tractable and precise mathematics, what this leads to is that a lot of the information that went into the initial formulation is lost.

Mathematicians are known for their affinity towards precision and rigour. They like to have things precisely defined, and measurable. You are likely to find them going into a tizzy when faced with something “grey”, or something not precisely measurable. Faced with a problem, the first thing the mathematician will want to do is to define it precisely, and eliminate as much of the greyness as possible. What they ideally like is a model.

From the point of view of the mathematician, with his fondness for precision, it makes complete sense to assume that the model is precise and complete. This allows them to bringing all their beautiful math without dealing with ugly “greyness”. Actual phenomena are now irrelevant.The model reigns supreme.

Now you can imagine what happens when you put a bunch of mathematically minded people on this kind of a problem. And maybe even create an organization full of them. I guess it is not hard to guess what happens here – with a bunch of similar thinking people, their thinking becomes the orthodoxy. Their thinking becomes fact. Models reign supreme. The actual phenomenon becomes a four-letter word. And this kind of thinking gets propagated.

Soon the people fail to  see beyond the models. They refuse to accept that the phenomenon cannot obey their models. The model, they think, should drive the phenomenon, rather than the other way around. The tails wagging the dog, basically.

I’m not going into the specifics here, but this might give you an idea as to why the financial crisis happened. This might give you an insight into why obvious mistakes were made, even when the incentives were loaded in favour of the bankers getting it right. This might give you an insight as to why internal models in Moody’s even assumed that housing prices can never decrease.

I think there is a lot more that can be explained due to this love for models and ignorance of phenomena. I’ll leave them as an exercise to the reader.

Apart from commenting about the content of this post, I also want your feedback on how I write when I write with pencil-on-paper, rather than on a computer.

## Division of Labour

Some six of us have planned for a vacation for next month. And so far, the “labour” of planning the vacation has been divided unevenly. So far, it has been three of us who have been doing a lot of the work – talking with tour operators, drawing up schedules, planning transport and accommodation, booking tickets, etc.

Now with a large part of the work having been done, the three of us who have been doing the work have decided to put NED and have left it to the other three “freeriders” to complete the rest of the work. As you might expect, the other three continue putting NED and in the last few days not much work has been done.

The question is this – what is the optimal strategy for the three of us who have been so far doing work? We think we’ve done more than enough of our share and so the others should take over now. On the other hand, the more we leave it to the other three, the more procrastination that will happen which might come back to hit all of us in terms of higher rates, etc.

It is dilemmas like this that allow freeriders to freeride – they know that by freeriding, they are not the only ones who are losing out, and that there are people who are more driven than them who will also end up losing out if these guys freeride. And the freeriders know that the driven guys won’t let things drift and will positively do something about it, and that encourages them to freeride further. And so forth.

Is there a solution to this problem? When there is a common objective, how should incentives be structured in order to make the freeriders work, while also not making it obvious that these are artificially tailored incentives?

## Scissors

It was our third term in IIMB. The institute had come up with this concept called “core electives” which no one had a clue about. These courses were neither core nor elective. And one of them happened to be Investments, taught by the excellent and entertaining Prof. R Vaidyanathan.

This was around the time when Kodhi and I had been trying hard to introduce the word “blade” (in the context of “putting blade” meaning “hitting on someone”) to campus. This word had been long established in Bangalore Slanguage, and we were trying to make IIMB also adopt the same. In order to further our efforts towards introducing this words, we even picked a batchmate each and actually started putting blade (ok I made that last one up).

So during the course of the class, Prof Vaidya said “the difference between a blade and scissors is that a blade cuts one way while a scissors cuts both ways”. I forget the context in which he said that, but it doesn’t matter. What matters is that a collective bulb lit up in the first row, where Kodhi and I had been sitting. “Blade” now had a logical extension. A new slang-word had been born at that moment, and later that day at lunch we introduced it to the general public at IIMB.

So that is the origin of the term “scissors”. Now the title of my blog post series in “arranged scissors” might make sense for you. Scissors happens when louvvu “cuts both ways”. When a pair of people put blade on each other- they are effectively “putting scissors” with each other. So in most cases, the objective of blade is to convert it to “scissors”. And so forth.

While in the frontbenches of Prof Vaidya’s class Kodhi and I were inventing the term “scissors”, Neha Jain was in the backbenches actually putting scissors with Don. Now she has come up with a nice poem on this topic. Do read it. And I want to make a Death Metal song out of it. So if you have any nice ideas regarding the tune and appropriate umlauts, do leave a comment.