I’m Not An Investor

Commenter DYOW, on a Berkshire and Fairfax thread writes:

This applies to concentrated bets.  If you are diversified than i consider this closer to indexing and not investing – then i get it.
But I don’t understand how anyone can call a holding “an investment” and not look at all the filings, and at the least, go through every page of the 10K.

http://www.cornerofberkshireandfairfax.ca/forum/general-discussion/do-you-read-all-of-the-filings-of-a-company-you-invest-in/

I thought quite a bit about this and I realized I am not an investor in the DYOW sense. And I don’t want to be. I refuse to waste my life holed up in a room reading financial statements. I have much better things to do.

But I have also come to realize that its pretty easy for a small investor to get excellent returns without doing much work. Net-nets are good example of a strategy that is highly effective and yet requires very little time and energy….certainly it does not require reading all disclosures.

In fact its an interesting question as to whether even Buffett himself needed to do the work he did to get the results he obtained. His early years were essentially deep value and in his later years he shifted to quality. I would argue that these asset allocations may have mattered a lot more than the particular stocks he picked.

How scientists come to agree on false facts

Lets say a bunch of different scientists around the world are measuring some factor X. And a bunch of different studies, using different methods come up with similar values. There is the common belief that the result must be right given the agreement between the different methods.

But this idea is false. Scientist can come to agreement even on things even if the fact is false. How does this happen? Lets say the first team to publish, Team T gets a result XT. The next team, Team U, tries their method and lets propose two counterfactual worlds. World A and World B.

In World A when Team U finishes their result is reasonably close to XT. Team U is pretty happy and publishes.

In World B, Team U’s result is very very different than  XT.  Team U is less happy and they therefore recheck the results again and again. They find some legitimate errors in their methods. They are now able to get a result less different than XT but still not in good agreement.

Now Team V enters the picture and when it does the world splits again. Again Team V is pressured to look for mistakes only when their results don’t agree with previously established ones. The more teams publish results the stronger the pressure and bias. Thus a scientific consensus is born.

A real world example of this phenomenon can be seen in a Nasa feature on the measurement of global ocean cooling by Josh Willis:

In 2006, he co-piloted a follow-up study led by John Lyman at Pacific Marine Environmental Laboratory in Seattle that updated the time series for 2003-2005. Surprisingly, the ocean seemed to have cooled

Not surprisingly, says Willis wryly, that paper got a lot of attention, not all of it the kind a scientist would appreciate. In speaking to reporters and the public, Willis described the results as a “speed bump” on the way to global warming,

…………….

Basically, I used the sea level data as a bridge to the in situ [ocean-based] data,” explains Willis, comparing them to one another figuring out where they didn’t agree. “First, I identified some new Argo floats that were giving bad data; they were too cool compared to other sources of data during the time period. It wasn’t a large number of floats, but the data were bad enough, so that when I tossed them, most of the cooling went away. But there was still a little bit, so I kept digging and digging.”

What I find amazing about this is that we have a NASA scientist admitting to throwing away data and its a feature on the NASA website. What is interesting about this is that he never bothered investigating the reason for the supposed “bad data”. And notice the one way nature of his corrections…he only threw away data that was “too cool”. And when he didn’t get agreement he kept digging and digging. This better than anything I have ever seen illustrates how scientists come to agreement on things.

Sometimes the ugly way is also the right way

In Episode 1 of Season 2 of Gotham, Bruce Wayne is trying to open a secret key code locked room his father created. He tries various combinations in vain. Finally he realizes that he can just use a bomb to blow the door open. Thus the title of this post:

Sometimes the ugly way is also the right way

As human beings we are used to living in a world of constraints and rules. And often we create these constraints ourselves. The ugly way violates our imposed constraints.

My good friend works at a place he hates. He often works from home because it would take him 2 hours to commute to the workplace. But he is unproductive at home and only does work at the last minute. As a result he is often rushing and sleeping late. This makes him too tired to search for jobs a new job.

He is stuck. He can’t leave his job because he is too tired to search. He can’t move closer to work because he knows he will soon switch jobs. And he doesn’t have the discipline to work from home.

Now I have suggested that he move closer to the job he hates. If only to give him the time he needs to search for a new job. He thinks this is stupid since he will only end up relocating once he finds a better job. He has imposed a set of constraints on himself that make his situation impossible to resolve.

I have found that some of my greatest ideas came to me because I started to questions the constraints I made up. Once I did this a solution was easy.