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Disneyland 1955 (Video)

As a parent, I truly came to appreciate the magic of The Magic Kingdom. Thus this I found this video, nicely set to music, enjoyable to watch. It is also interesting to see how different the 1955 park was, and how people in attendance looked and acted.

If you like this, also check more details about it at the Disney History Institute.

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The Surprising Truth About What Motivates Us (Video)

This video changed how I view the world. Essentially it served to turn some of my basic assumptions about people on their head. In particular, this video questions whether incentives, in fact, incent. I would not go far as to say it kills the idea (of incentives) completely, but it certainly adds a new twist to it.

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Venture Capital Financings per Capita by State

PriceWaterhouseCoopers recently released their Money Tree Report, which among other things provides the dollar amount of venture capital money raised by state.  Below is data from this report, but with each state considered on a per capita basis (2012 VC$ / 2010 population).  The last column is percentage of the highest per capita rate as a measure of relative activity.

State 2012 VC$ 2010 Pop  Per Cap VC$ % of Highest
MA     3,126,968,400     6,547,629              477.57 100.0%
CA   14,194,421,800   37,253,956              381.02 79.8%
WA        907,508,100     6,724,540              134.95 28.3%
CO        585,433,300     5,029,196              116.41 24.4%
UT        318,397,200     2,763,885              115.20 24.1%
DC          64,201,200        601,723              106.70 22.3%
NY     1,863,532,100   19,378,102                96.17 20.1%
RI          85,059,100     1,052,567                80.81 16.9%
NJ        444,135,500     8,791,894                50.52 10.6%
MD        284,252,600     5,773,552                49.23 10.3%
MN        253,183,800     5,303,925                47.74 10.0%
VA        372,380,200     8,001,024                46.54 9.7%
NH          60,672,000     1,316,470                46.09 9.7%
IL        570,432,100   12,830,632                44.46 9.3%
CT        157,577,300     3,574,097                44.09 9.2%
PA        520,744,100   12,702,379                41.00 8.6%
TX        934,421,200   25,145,561                37.16 7.8%
AZ        221,938,100     6,392,017                34.72 7.3%
OR        124,267,800     3,831,074                32.44 6.8%
GA        261,840,300     9,687,653                27.03 5.7%
OH        285,750,500   11,536,504                24.77 5.2%
MI        236,805,900     9,883,640                23.96 5.0%
NC        196,918,300     9,535,483                20.65 4.3%
NM          35,732,000     2,059,179                17.35 3.6%
WI          95,311,900     5,686,986                16.76 3.5%
KS          47,201,700     2,853,118                16.54 3.5%
TN          87,160,600     6,346,105                13.73 2.9%
IN          84,161,300     6,483,802                12.98 2.7%
FL        199,110,400   18,801,310                10.59 2.2%
DE            9,489,900        897,934                10.57 2.2%
ID          15,150,000     1,567,582                  9.66 2.0%
ME          12,787,200     1,328,361                  9.63 2.0%
OK          34,036,000     3,751,351                  9.07 1.9%
SC          39,499,900     4,625,364                  8.54 1.8%
WV          14,568,000     1,852,994                  7.86 1.6%
VT            4,415,000        625,741                  7.06 1.5%
NE          10,615,000     1,826,341                  5.81 1.2%
MT            5,575,100        989,415                  5.63 1.2%
KY          23,543,000     4,339,367                  5.43 1.1%
AL          23,106,000     4,779,736                  4.83 1.0%
ND            2,400,000        672,591                  3.57 0.7%
MO          21,316,000     5,988,927                  3.56 0.7%
MS            9,776,000     2,967,297                  3.29 0.7%
NV            7,095,100     2,700,551                  2.63 0.6%
LA          10,508,400     4,533,372                  2.32 0.5%
AR            5,000,000     2,915,918                  1.71 0.4%
IA            5,000,000     3,046,355                  1.64 0.3%
HI               645,000     1,360,301                  0.47 0.1%
PR               100,000     3,725,789                  0.03 0.0%
SD                           –        814,180                       – 0.0%
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On Black Swan Probability and Tail Obesity

For a long while now, having watched bubbles form and pop, I have found it frustrating how people pile into assets with straight line trajectories. I first noticed it in the time of the dot-com bubble of the late 1990s. During that time, as I recall, returns in the market were frighteningly close to straight line, not only highly positive, but with a low volatility of returns from month to month.

A more frightening version of this, in terms of risk to our way of life, was in residential real estate. Prior to the popping of the real estate bubble, residential real estate in the United States had also had fairly straight line appreciation over a considerable number of years. Again, not only was the appreciation significantly positive, it had little variance.

It reminds me of a favorite “simple wisdom that is obvious but that we tend to forget” type quote:

 

“If something cannot go on forever, it will stop.”
~ Herbert Stein

 

I’ll not be at all surprised if what I’m about to propose has been done before, as it seems so simple. If so, forgive me.

It would seem that one can represent the degree to which a return has been straight line fairly easily as R/V, where R is some measure of return and V is some measure of volatility, likely for the same period of time, but not necessarily so. As this ratio increases, I propose that tail probability, the probability of a significant move, call it a black swan or gray swan event to use Nassim Taleb’s term, increases (tail obesity). My theory is that significant moves become more probable as tension increases, similar to how a major earthquake becomes more likely as tension grows between tectonic plates, and that in some situations this tension increases following periods of straight line appreciation.

It might also be that a formula like (R / R2) / (V / V2), where R is some return, R2 is some return prior, V is some measure of volatility, and V2 is this measure for some period prior (again, likely for the same periods, but not necessarily so), would identify this tail probability more accurately, as it would serve to measure the change in return versus the change in volatility over a period of time.

This, to some degree, goes against conventional wisdom that higher volatility implies higher risk. Note that I’m not proposing that lower volatility implies higher risk, but that high returns over a period of time, when combined with low volatility of those returns, serves to change the shape of the parabola of possible returns. In other words, I’m merely proposing that there may be a way to identify a time when a black swan or gray swan type price movement, to use Nassim Taleb’s term, is more probable than usual.

Also note that I’ve concentrated on straight line positive returns, ignoring similar moves downward, likely to the chagrin of statistical purists. Intuitively, I feel that the tail probability increase is more likely with straight line appreciation, and that the increase in probability at the tail is isolated or at least heavily weighted to the down side. Capitulation happens both ways, of course, but given that there is no limit to upside, while the downside always has to contend with zero, there is simply more opportunity for straight line returns to the upside.

If this is some sort of common knowledge, which I fear as it seems to simple, then egads, and sorry. If not, call it the Hawkins Ratio; my kids will think it is cool.
Originally published 7/7/11 in Science 2.0.
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The Socialism Paradox

I find myself fascinated how similar people, with similar values, can feel so differently about social engineering. This comes out in political discourse, and certainly is a hot topic today, with those more in favor of socialism, which I’ll refer to in this article as socialism inclined, having dramatically increased momentum for putting their more socialistic policies in place.

I’ve paid attention to this for a while, inquiring of people who feel differently that I (I believe in little or no socialism) why they felt the way that they did. Over time, I’ve come up with a theory, which is that they generally perceive the effects of some socialism differently.Fairly well all people, whether more capitalistic and or more socialism inclined, would agree that an entirely socialist system would result in a drastically smaller, less productive economy, so much so that everyone suffers. Spectacular and catastrophic failures of socialism dot history. The reason for this is human nature; take incentive away from those capable (for whatever reason) of producing and they stop producing, leading toward a subsistence like economy. The reality is that people don’t produce to give; they produce to get.Where those more vs. less socialism inclined begin to disagree is in the effect of a little bit of socialism, frequently referred to as social engineering. The socialism inclined, in the United States generally considered to be most represented by The Democratic Party, believe that there is little if any effect of some socialism. The anti socialism crowd, generally fiscal Republicans (some Republicans, as well as Democrats, vote based on other reasons such as their opinion on abortion, religion, gay rights, etc., and don’t care about or concern themselves with economic policy), instead believe that the effect of a little bit of socialism is immediate and significant. The difference in this perception could be represented graphically as follows:

Socialism Effect Perception
I personally believe more like the red line, that a little bit of socialism has an immediate and significantly negative impact, and that we would be better off over all with negligible socialism. This is what I refer to as The Socialism Paradox. In the process of trying to help those on the bottom, those in favor of socialism actually instead negatively affect them, as well as everybody else. At least this is what I believe is likely the case.

This is based in part on the way I find things tend to work. In general, it seems that if a lot of something has a given effect, a little will have some, and the incremental effect actually tends to be greater early on than later.

The good news is that we are on the same team, and have the same goal. We all want to go the same direction, and as far as possible. It is simply, to use a football analogy, that one person thinks we should throw a pass, while another thinks we should rush it up the middle; but we all want to get to the goal line. Frankly, given some of the animosity over the past few years, believing this grants me some comfort.

A Plug For My Convictions

Nevertheless, I get the feeling that we are, as a society, losing track of the fact that stuff does not appear out of thin air. You can’t just give someone something without an effect somewhere else. Stimulus, for example, is borrowing. To use an analogy, if you max out your credit cards, you’ll have more stuff in the short term, but you’ll pay for it big time later. Isn’t this essentially the same thing? Worse yet, aren’t we really simply borrowing money that we will not begin to start paying back, if ever, until those in grade school today are in the workforce? Thus, instead of owning up to our failures and enduring some pain, are we not instead saddling these children with debt so that we can avoid pain ourselves (as if they will have no problems of their own to deal with)? Is it not possible that the pendulum could swing too far?