Evidence of Intent

Income from an asset, , depends on manager decision and random factor , so . Assume that managers are motivated by personal income , such that the action taken where is the manager’s utility function and is the incentive-compensation scheme.

The problem in incentive compensation (principle-agent theory) is that of finding , the incentive compensation scheme under which payoff to the owners is maximized. The inputs considered are the utility (including risk adversity) of the manager, , and the relationship of effort to outcome, .

By designing , you want to maximize the incentive (the responsiveness of compensation to managerial effort) while minimizing the actual payoff, all while sharing risk so that the manager is not crippled by the risk involved.

Net-net, it seems to suggest that we don’t want managers that are too rich, since the manager needs to have a significant proportion of his wealth vested in the company (to align risk interests and prevent moral hazard) at the same time the owners are trying not to pay him too much, and hence limit his ownership of the company. In fact, it seems to me that an equitable arrangement always results in the manager’s percentage ownership of the company growing with time, an effect only partially offset by the growth in asset value as a whole. After all, what good reason can a manager give for not wanting to own more of the company they have control of?

The possibility of separating ownership from management is made possible by knowledge of responsiveness of managerial effort to reward (motivation, ) and the responsiveness of asset income to managerial effort (). This knowledge cannot be guaranteed to always be of a form that makes the separation possible.

Bought Brooks Brothers shirts for the first time today. Very curious pricing structure — 1 shirt for $80, 3 shirts for $200, $60 off for going above $300.

The marginal prices of the 6 shirts I got were then $80, $80, $40, $80, $20, $40, making for an average price of $56.

There’s something awful about thinking that personal capabilities are strongly ordered – that for every two people with different capabilities, one of the two can do everything that the other can. This feeling is behind the aversion to taking money too seriously, because money is definitely strongly ordered. If money were everything, I’d either be better or worse than you, with no other possibility.

Thank god money isn’t everything then. More accurately, thank god prices do not completely represent my desire for things. If everyone had the same desires and productive abilities, then prices would indeed represent desires, but because of the different desires (demands) and productivities (supplies), there is much to gain from exchanging goods I produce with other people.

To the extent that people conform in their desire for scarce items, however, prices are inevitably accurate measures of personal demand, and it’s an endless rat race. To the extent to which prices of things are aligned with the degree what I want them, there is only one way to become happier – to make more money.

Drawing 5 cards out of a deck 100,000 times, I got

      1 SF
     23 4K
    110 FH
    220 FL
    412 ST
   2144 3K
   4706 2P
  42322 1P
  50062 HC

Drawing 7 cards out of a deck 100,000 times, I got

      5 SF
    181 4K
   2595 FH
   3016 FL
   4633 ST
   4907 3K
  17251 HC
  23565 2P
  43847 1P

One-pair becomes the most common hand!

See also: http://en.wikipedia.org/wiki/Poker_probability

Hat tip: CMoh

http://www.playwinningpoker.com/poker/betting/

In heads-up poker games, if both 22 and AK were to go all-in pre-flop, they would be evenly (very close to 50/50) matched. In real play, however, 22 loses to AK by a big margin. This is because the  betting and folding options are worth a lot more to AK than to 22, which is to say that the unknown flop, turn and river introduce big variances into the AK’s expected return.

In that sense, AKs are preferable because their riskiness boosts the value of options possessed.

Lesson: seek risk with respect to which you possess options!

The more I think about poker, the more apt of a metaphor for life it becomes. Roommate chris informed me that high level matches go to showdown about one in 200 times on the site he plays on. My first reaction was that of distaste, that there was a huge barrier to newcomers learning anything since they have precious little objective evidence to learn from. I then thought that maybe there were players out there with mentors, and that you would be outcompeted by rule-following rote-learners if you tried to learn the game from scratch.

Then I realized that I had been going about it the wrong way, and I had been too bent on my own definition of reality, which involved knowing what cards the other players have, or having some theory about them, in order to learn. That is, after all, the objective reality on which winning or losing the game was based on.

Or is it? This is really a complex question, the objectivity of a situation, when the underlying reality percolates up to observed reality in such a convoluted manner that you might as well make up a fresh theory for what happens on the surface. Which, I think might just be the case here, that poker (barring certain obtusities) depends on understanding the manners in which others seek patterns as much as, or even more than, the underlying mechanics of shuffling cards and objective odds.

The stock market is the same. The long time it takes for earnings to prove themselves surely makes the movement of prices analogous to a showdown only one-in-200 times, and yet is the ultimate reality on which every other movement is based. Reality is mixed here, neither objective nor arbitrary.

Why animal rights? Because we think of animals on a continuum with humans, and having animal rights forms a buffer for human rights. It is difficult for someone to grant animal rights without granting human rights, and so pushing for animal rights makes human rights more dependable. Sensible moves based on using the structure of the world. Fruitarians go too far though.

This post is a warning about UPS in New York. I missed a UPS delivery 3 times, called the 1800 number and was told to pick it up at 522 Greenwich in downtown Manhattan. The pickup center could not find my package, and was staffed by rude and unmotivated personnel. They were also looking for the package by hand, without any type of computer help. The UPS call center has no connection with the pickup center, you have to call the pickup center itself to confirm that your package is there.

By setting up their central call center this way, UPS shows a blatant disregard for the worth of customer time. The disparity between the delivery logistics (which are quite good) and the end-point exception handling (absolutely terrible) is amazing.

Econtalk this week mentioned an incredible fact, that the US GDP has a very tight growth band around 3%:

I was surprised that I’ve never known this before. The reason, I think, is that usually we see plots of year on year GDP growth, which look like this:

It is difficult to see that not only does the average (well, the geometric mean of 1+growth, to be exact) come to 3%, but also that the averages for shorter intervals of time also come to 3%; the deviations are highly anti-correlated and cancel themselves out fairly quickly, but this is not visually obvious.

Additional reading:

http://www.econbrowser.com/archives/2009/03/trend_stationar.html

http://econlog.econlib.org/archives/2009/03/greg_mankiw_get.html

The reductionist analytic modeling recipe goes like this:

1. Pick a system to study, choosing a boundary around a region in the world and mentally sectioning it off – everything inside that boundary is the system and everything outside is the environment.
2. Simplify the system by picking a few details to pay attention to, ignoring everything else. Divide the system into components with defined states and define interactions between components. Some parts have defined interactions that reach through the boundary defined in step 1, and interact with the environment.
3. Assemble those parts back into the whole, building up complexity by computing how the various combinations of states of the various parts interact with each other.

Step 2 simplifies while step 3 complexifies. Step 2 is semantic while step 3 is syntactical. If the results from step 3 successfully predict the behavior of the system, then the simplifications in step 2 are said to capture the essential details of the problem.

By thinking of the work accomplished by analysis as due to these three types of work, you could find the limiting reagent and spend more time on that. The analytic engine you are improving could be personal, collective, flow or even batch-oriented.

Your strength as a rationalist is your ability to be more confused by fiction than by reality.  If you are equally good at explaining any outcome, you have zero knowledge.

– Eliezer

Logic is equally valid in all universes, and hence cannot tell you which of those universes you are in. Applying logic does not give you new information, it merely aligns your decisions better to the information you already have, by either reducing bias or increasing the efficiency of your estimators.

It is good to distinguish when you are getting new information and when you are processing existing information better, because knowing explicitly how the validity of your ideas flows allows you to make corrections faster and easier.