Tuesday, July 28, 2009
I have 3 former students (that I know of) who took the exam, and a couple more that were considering it. I expect the three I know of did well (hopefully, they'll let me know sometime today).
update: So far, two have reported in, and one passed - still waiting on the thrid.
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Sunday, July 26, 2009
click for larger image (courtesy of investmentpostcards.com)
Wednesday, July 22, 2009
Tuesday, July 21, 2009
Monday, July 20, 2009
Well, I just re-upped and re-registered for the 2010 exam. So, I'm once again a Level 3 Candidate. At least this time I'm already familiar with well over half the material, so it shouldn't be nearly as stressful.
I might even start early and keep with it this time around. With luck, I might be done with my first pass through he material by January 1. While that seems early, if I shoot for January 1, I'll probably actually finish by March or so, and then I can focus on actually locking this stuff down. After all, the material is interesting, but I don;t want to take any more exams for a while after this.
And yet, some conspiracy theory whack jobs still doubt that it happened. One moonbat (sarcasm intended) named Bart Sibrel systematically harassed the Apollo crewmembers to see if they'd admit that the landing was a hoax. He made the mistake of calling Buzz Aldrin a liar. Click below to see what happened.
Man - I could easily keep clicking this all day like one of those experiments where they gave mice crack.
Sunday, July 19, 2009
Unfortunately, the data typically used to measure consumption (the US Government's figures for personal expenditure on nondurable goods and services category in the National Income and Product Account) don't have a lot of variation. So, they don't work very well as an explanatory variable. Savov finds that whe he uses EPA records on aggregate garbage production, they're exhibit a correlation with equity returns that are twice as high as the NIPA/Equity returs correlations. Here's the abstract of his paper (downloadable from the SSRN):In theory, one way to explain the premium would be to look at consumption, a broad measure of wealth. People should demand a premium from an investment that goes down when consumption goes down. That’s because the alternative — bonds — hold on to their value when consumption declines. Another way to put it: When you are making lots of garbage, you are rich. When you stop making garbage, you are poor. Unlike bonds, which continue to pay out whether you produce lots of garbage (and are rich) or not, stocks are likely to lose their value during bad times. Therefore, investors should want a large reward for putting their money in something whose value decreases at the same time as their overall wealth decreases.
Read the whole thing here.A new measure of consumption -- garbage -- is more volatile and more correlated with stocks than the standard measure, NIPA consumption expenditure. A garbage-based CCAPM matches the U.S. equity premium with relative risk aversion of 17 versus 81 and evades the joint equity premium-risk-free rate puzzle. These results carry through to European data. In a cross section of size, value, and industry portfolios, garbage growth is priced and drives out NIPA expenditure growth.
Monday, July 13, 2009
Correlation is a statistical measure of the degree to which investment returns move together. Between 1991 and 1994, the correlation between the S&P 500 index and high-yield bonds was low, at 0.2 or 0.3, according to Pimco statistics. (A correlation of 1 means returns move in perfect sync.) International stocks had a correlation with the S&P 500 of 0.3 or 0.4, and real-estate investment trusts had a correlation of 0.3, according to Pimco data. Commodities showed little correlation to U.S. stocks. By early 2008, investment categories of just about every stripe were moving significantly more in sync with the S&P 500. The correlation on international stocks and high-yield bonds rose to 0.7 or 0.8, and real-estate investment trusts to 0.6 or 0.7, according to Pimco's data for the previous three yearsRead the whole thing here (note: subscription required).
The problem with portfolio diversification is that it is typically implemented using historical correlations (actually, on covariances, but the two are essentially the same). To provide optimal diversification, portfolio allocations should be made based on "forward looking" correlations. In practice, some managers adjust historical correlation estimates to reflect their views of future relationships. But that becomes far more complicated than simply using historical estimates and assuming that they'll continue unto the future.
Note: if you don't have an online subscription to the Journal, try searching for the article using Google News - if you click on the link there, it works around the WSJ subscription filter (however, not all WSJ articles can be accessed this way).
Friday, July 10, 2009
Unfortunately, my data wasn't straight - I realized that I had used the wrong data code (a certain type of dividend distribution) from CRSP. So, my previous analysis was basically crap (that's a technical term for the unitiated) and had to be redone using the proper data set.
Luckily, it looks like my primary results after using the proper code, but with a few minor changes. For now, I'm still doing the preliminary descriptive stuff. Since I did the initial version of the paper in a hurry (hey - it was a conference deadline), I took a few shortcuts. This time, I'm going back to step 1 and going over every line of code, and (just as important), making sure I know how the sample changes at each point. As a result, I'm much more confident with my data this time around.
But doing the descriptive statistics is still (to me) about the most boring part of the paper. Still, it's gotta be done.
Thursday, July 9, 2009
What the models failed to capture was that humans don’t behave in simple, predictable and uncorrelated ways. It’s impossible to overstate the importance of the way these models cope with correlation of peoples’ psychology. To sum it up: they don’t. Let me know if that’s too complex an analysis for the mathematical masters of the universe.Read the whole thing here.
Anyone who’s ever been to a nightclub, a football game or even a very loud party will know that there are situations where we don’t act as individuals, buzzing about doing our own thing. These are occasions when we all suddenly stop being individuals and start doing the same thing – usually involving large quantities of drugs and some very bad singing. Although these sorts of events are specifically designed to trigger this behaviour – which is probably a deep evolutionary adaptation to sponsor group behaviour, useful when it comes to running down tasty antelope and dealing with giant, carnivorous sabre toothed beavers – it can also happen in other situations. Most stockmarket booms and busts are generated by similar group effects.
In general, people behave in an uncorrelated fashion right up until the point they don’t.
Tuesday, July 7, 2009
The momentum profits are realized through price adjustments reflecting shocks to firm fundamentals after portfolio formation. In particular, there is a consistent cross - sectional trend, from short-term momentum to long-term reversal, that happens to earnings shocks, to revisions to expected future cash flows at all horizons, and to prices. The evidence suggests that investors myopically extrapolate current earnings shocks as if they were long lasting, which are then incorporated into prices and cash flow forecasts. Accordingly, the realized momentum profits can be completely explained by the cross - sectional variation of contemporaneous earnings shocks or revisions to future cash flows. Importantly, these cash flow variables dominate the lagged returns in explaining the realized momentum profits. As a result, the realized momentum profits represent cash flow news that has little to do with the ex ante expected returns. In fact, the ex ante expected momentum profits are significantly negative.
On an unrelated note, the Unknown Family will be traveling the next few days for a family reunion in West Virginia (the Unknown Wife's father grew up their, and that fork in the family tree has a get-together every year). So, unless I schedule a few pieces to post automatically, posting will likely be slim for the next few days.
Monday, July 6, 2009
Saturday, July 4, 2009
Now we're getting ready to grill some critters, followed by fireworks. In the meanwhile, here are some links. They're from a previous year's post, but they.re worth repeating (after all at Financial Rounds, we're all about the efficiency thing):
The Declaration of Independence most people have never read it through. So take a few minutes and do so before going about your day.Now go grill some meat, light some fireworks, and have a happy 4th of July.
Our Sacred Honor - a piece that recounts what happened to the signers of the Declaration
The Pledge of Allegiance - 'nuff said.
The Star Spangled Banner - the words to our national anthem and a video of Whitney Houston singing it.
Thursday, July 2, 2009
In all seriousness, thanks for reading. I'm humbled.
Imagine an aeronautics engineer designing a state-of-the-art jumbo jet. In order for it to fly, the engineer has to rely on the same aerodynamics equation devised by physicists 150 years ago, which is based on Newton's second law of motion: force equals mass times acceleration. Problem is, the engineer can't reconcile his elegant design with the equation. The plane has too much mass and not enough force. But rather than tweak the design to fit the equation, imagine if the engineer does the opposite, and tweaks the equation to fit the design. The plane still looks awesome, and on paper, it flies. The engineer gets paid, the plane gets built, and soon thousands just like it are packed full of people and sent out onto runways. They fly for a while, but eventually, because of that fatal tweak, they all end up crashing.Read the whole thing here. It's long, but well worth it.
In a way, this is what's happened in quantitative finance. The planes are the complex derivatives—like collateralized debt obligations—that now lie smoldering on the balance sheets of banks. The engineers are the "quants": those math and science Ph.D.s who flocked to Wall Street over the past decade and used mathematical models to build these new investment products. These are the people Warren Buffett was talking about when he said, "Beware of geeks bearing formulas" in his letter to shareholders this year. The quants aren't entirely to blame for the financial meltdown; there's plenty of guilt to be shared by regulators, top executives and the investors who bought the instruments the quants created. Yet while aeronautical engineers who willfully designed a faulty plane might be on trial for criminal negligence, Wall Street's math gurus are, for the most part, still employed. Strangely, the banks need quants more than ever right now. If anyone's going to figure out how to price these toxic assets, it's them. Quantitative finance isn't going away, but it is in desperate need of reform. And one man—a math geek himself—thinks he knows where to start.
Paul Wilmott is a 49-year-old Oxford-trained mathematician and arguably the most influential quant today, the brightest star in their insular, nerdy universe. The Financial Times calls him a "cult derivatives lecturer."
Wednesday, July 1, 2009
Caution: SAS Geekspeak ahead
One of the data sets is pretty large (it was about 70 gigabytes, but with the updates and indexing I've done, it's almost 100 gig). So, adding the new data and checking it took quite a while (no matter how efficiently you code things, SAS simply takes a long time to read a 70 gigabyte file). I thought I had everything done except for the final step. Unfortunately, the program kept crashing due to "insufficient resources."
For the unitiated, when manipulating data (sorting, intermediate steps on SQL select statements, etc...) SAS sets up temporary ("scratch") files. They're supposed to be released when SAS terminates, but unfortunately, my system wasn't doing that. So, I had over 180 gigabytes of temporary files clogging up my hard drive. This means that there wasn't enough disk space on my 250 gigabyte drive for SAS to manipulate the large files I'm using.
Of course, I only realized this when my program crashed AFTER EIGHT HOURS OF RUNNING! TWICE!
I've now manually deleted all the temporary files, and I'm running the program overnight to see if this fixes the problem.
Ah well - if it was easy, anyone could do it.
update (next morning): Phew! It ran - it seems the unreleased temporary files were the issue. On to the next problem.