School Bus

Today, I got e-mail from a friend. There was a photo of a "typical" Japanese school bus: Then a photo of an Indian school bus: Then the comment: Where did you call when you had a technical problem with your computer? Japan or India? Did I mention that my friend is Indian?

 

Peregrine

We live on the 17th floor of an apartment, overlooking Lake Ontario: Unlike the 6 or 7 houses we've lived in, there are no song birds up here. BUT, we do get pigeons ... and (pigeon-eating) Peregrine Falcons. I reckon this is a young one.

 

Central Limit Theorem

There's this remarkable theorem that goes something like this: Suppose we record the average daily temperature (measuring the temperature every hour, for 24 hours -- then averaging these 24 readings). Suppose, too, that we record these daily averages for a few years. Finally, we plot the frequency with which certain averages occur and get the green distribution shown here: The red curve is the world famous "Bell Curve". The fact that the frequency distribution looks like the Bell Curve is interesting, eh? What's even more interesting is the fact that if we plotted the average height of people we meet each day (or their average weight), we'd still get (very nearly) a Bell Curve. We might also repeat this ritual for the average of the number of kilowatts used by a city each hour or the average length of fish we catch each day (while fishing each day in Lake Ontario ... and catching lots of fish). These averages always look like the Bell Curve if there are lots of numbers involved in the average. (That is, we meet lots of people each day or catch lots of fish.) That's the Central Limit Theorem and (after a jillion years of ignoring it) I decided to explain it ... here.

 

JibJab

I've mentioned before that I love to do them thar JibJab thingies. Yesterday, Lori & Jay celebrated their 14th wedding anniversary. (How time flies, eh?) Anyway, not being able to help meself I did this guy.

 

Levy, eh?

I have little faith in the assumption that stock returns obey some mathematically generated distribution ... like normal ... or lognormal or whatever. Them's mathematicians earning a living. Recently, R. Brown pointed out the Levy distribution. It (at least) has the efficacious property that LARGE returns are more frequent than, say, normally distributed returns. (That goes by the sexy name of fat tails.) I much prefer to use actual historical returns (over some sufficiently large time period) -- then randomly pick the returns from this collection. To put it bluntly: Use actual returns and NOT a mathematical proxy. However (I must admit) math models have fascinated me for years. What's particularly fascinating is to consider picking historical returns in a particular order - like from minimum return to maximum (or max to min). I did that once upon a time. The interesting thing is that the collection of historical returns has a particular distribution, a particular mean, a particular standard deviation, skew, kurtosis etc. etc. regardless of the order in which you select 'em.

 

more COAL

Recently, I generated a Coal Index ('cause I couldn't find none on the Internet, where I could download historical values to a spreadsheet). Thanks to Danyon, who pointed out a neat "Global" Index: the STOWE INDEX, I can compare the two. Unlike "my INDEX" (which includes a dozen U.S. coal mining companies), STOWE involves coal companies around the globe - primarily in China and the U.S. (including companies that manufacture mining equipment). Staring intently at the charts for the past year, it seems that there's been a recent divergence: Very interesting, eh? So I take a peek at the largest component of the STOWE, China Shenhua Energy (over the past six months): Mamma mia! Shenhua is China's largest coal mining company, followed by China Coal Energy (which has done equally well and is 2nd in the STOWE index.). Check out the past year. Compared to Shenhua, the largest U.S. outfit, BTU, can't get out of 1st gear!! P.S. There's also an ETF that emulates the STOWE Index: KOL:

 

Moon & Venus

When somebody sees a bright star and asks: "Whos' that?" I always say: "That's the planet Venus." Is it? Who knows, but Venus is the planet closest to earth. Anyway, early this morning (about 4 AM) I saw the Moon beside one of them very bright "stars". I said to myself: "That's the planet Venus." Alas, I'm probably just as gullible as others, so (to be sure) I looked at my very sexy SkyMap and found this: I went back to bed feeling oh so clever. Now I just have to figure out what that means. ------------------------------------------- I'm lousy at imagining the sun-moon-earth configuration. Once upon a time I convinced several people (as gullible as I) that the Moon follows the path of the Sun. Alas, it must have been lunacy on my part, 'cause I can clearly see (after hours of staring at both) that the moon does not follow the sun ... tho' it's close. In fact (after a Google or three), I discover that the Moon's path is about 5 degrees from the Sun's path (at maximum separation).

 

Coal Index

I've been looking for an Index that covers a bunch of coal stocks, like the DOW covers 30 big-name stocks and the S&P500 covers 500 of 'em. I also needed to have historical prices, available from Yahoo. Since I couldn't find such an Index, I made my own. To this end, I generated a spreadsheet, described here. Note that the Coal Index is up over 80%, beating the DOW (at least for the past six months): There's a dozen U.S. coal stocks in the Index and, if I compare that Index to my Canadian coal stocks, WTN and GCE (on the Toronto Exchange), I get this (over the past six months): It makes me very happy! Indeed, one of these coal stocks done good in a trading contest.

 

H1N1

For some time, I was tracking the cases of H1N1 Swine flu virus. I even did an analysis to predict the "eventual" number of cases, worldwide. Though I stopped doing this on July 1, 2009 (when the number of cases was just under 80,000), I did get a prediction (based upon fitting a curve to the logarithm of cases, weighting the recent cases more heavily): It's interesting to note that my "prediction" was 263,025 cases. I just looked up the latest report of the W.H.O. and find that, as of August 30, 2009, the number of cases is 254,206 . That's scary.

 

Pasta

I've always felt that pasta, of one variety or t'other, was my favourite meal. Indeed, I often ask, at a gathering of friends: "If you were stranded on a desert island and there was just one ethnic restaurant on the island, what would you want it to be?" My answer is always: Italian ... because of the pasta, of course. However, though there are a few hundred types of Italian pasta, they're (almost) all made of Semolina flour (from Durham wheat) and differ only in their shape: I recall spending a month at an Italian research centre in Southern Italy and my host was very proud of the local pasta (orecchiette, shaped like a little ears). Okay, so now my wife has convinced me that rice is good. In fact, there are tens of thousands of types of rice !!! Now, when we play the "What ethnic restaurant" game, I may still say Italian ... but it'll be for the risotto.

 

Correlations

So I was discussing what influences what, in the stock market ... with my brother-in-law. So I generated a spreadsheet that calculated correlations between pairs of assets. Some were to be expected -- but some were surprising. Here's an example: The fascinating thing is to compare daily stock returns when the returns for one asset are delayed a day ... or maybe advanced. So, I calculate the correlation between the Shanghai Index returns and the DOW returns one day later (or earlier). Then, comparing the DOW and Japan: See? The China Index has a higher correlation of daily returns when compared to the DOW returns on the previous market day. That holds, too, for Japan.

 

Contests

Since it's nearing the end of the year and since many financial discussion forums hold "investing" contests and since I've done that for several years (and now want to end that ritual), I've written a tutorial on HOW I DO IT: Click! Tho' it's been fun, I'm gettin' too lazy to continue.

 

It always surprises me to see where visitors to gummy-stuff come from and what browsers they use and what operating system. Visitors For the month of August, 2009, here's what I find: Top 10 countries Browsers Operating Systems

 

Calories

It always amazed me that you can lose a pound or two ... overnight. If you were sleeping on a bathroom scale, you'd presumably see the indicator slowly drop by a pound or two. Where does it go? So I tried doing some weight-loss arithmetic, like so: ⊗ The body "uses" about 100 Calories per hour. ⊗ At 3500 Calories per pound of body fat, that's a pound every 35 hours. ⊗ Just living and breathing (without any caloric food intake), you'd lose (very roughly) a pound every 35 hours. ⊗ Then, while sleeping for 8 hours ... would you (could you) lose a pound or two??? Aah, but the body uses less than 100 Calories per hour while sleeping. It's more like 65 Calories/hour. So how does one lose a pound or two overnight? Okay, that 100 Cal/hr is approximate. It'll depend upon your BMR or Basal Metabolic Rate which will depend upon your biological configuration. To lose a pound in 8 hours ... wouldn't that require about 3500/8 = 437 Cal.hr? Impossible. While playing with the numbers, I discover that the calorie that I'm familiar with is NOT the Calorie noted on food products. Indeed, the calorie is defined as the heat energy required to raise the temperature of 1 gram of water by 1 degree centigrade. The Calorie will raise 1 kilogram by 1 degree. See? The Calorie is really a kilocalorie ... and the word is capitalized. Get it? 1 Calorie = 1 kilocalorie.

 

Stealth bomber

Now this is funny ... or sad? In 1990, the U.S. AirForce unveiled its newest long range bomber: The B-2 "Stealth" bomber had cost billions to develop. It was characterized by its all-wing design: The analysis included a ritual for finding the volume distribution that maximized the range. The ritual involved taking a derivative and setting it equal to zero. Conclusion? The volume should be "almost all in the wing". Hence the B-2. Alas, the engineers who recommended the all-wing design neglected to test the second derivative ... to see if'n they found a maximum or a minimum. It turned out (as discovered subsequently), that the all-wing design MINIMIZED the range of the aircraft. Indeed, the flying wing was, aerodynamically, the worst possible configuration. Now, if'n I only had that story at my finger tips when I taught introductory calculus!