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.
The Limits of Models
Here's an excellent piece on the Psi-Fi Blog, titled "Quibbles With Quants." Here's a choice part:
Momentum Effects and Firm Fundamentals
The more Long Chen's work I read, the more I like it. I recently mentioned one of his pieces on a new 3-factor model. Here's another, on the momentum effect, titled "Myopic Extrapolation, Price Momentum, and Price Reversal." In it, he links the well-known momentum effect to patterns in firm fundamentals. Here's the abstract:
So, in essence, he finds that investors ignore mean-reverting patterns in firm earnings, and over-weight recent earnings shocks.
Very nice.
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.
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.
Very nice.
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.
Updating a Dataset Always Takes Longer Than Expected
I'm still working on updating my data. As usual, what I thought would be a "simple" three to four-day jobhas stretched out to almost two weeks of work. At least I'm not this person.
Happy 4th of July
We're just got back from a trip to Wal-Mart (what could be more American) to buy some clothes for the Unknown Daughter (she's grown enough that her old bathing suit no longer fits). The Unknown Wife and Unknown Daughter tried on clothes, while I wheeled the Unknown Baby Boy around the store until he went to sleep. Not surprisingly, the large-screen flat-panel TVs did the trick (based on initial indications, he's definitely a boy-child to the core).
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):
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.
A Quarter Million Hits
Shortly after 2 today, Financial Rounds had its 250,000th visitor. Man - I never imagined there were so many people out there with Internet connections and this much free time on their hands.
In all seriousness, thanks for reading. I'm humbled.
In all seriousness, thanks for reading. I'm humbled.
Profile of Paul Wilmott
Newsweek recently ran a profile of Paul Wilmott, one of the biggest names in the "quant" world. Here are the opening paragraphs
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."
Arrrrggghh! SAS is Evil!
Just another day (or two) of torturing data. Like I mentioned a couple of days ago, a week back I decided to update a data set to include the last year or so of data (the data sources I use were recently updated). Like most "simple" jobs, it's turned out to be much more of a hairball than I expected. Although the program I used was fairly simple to rewrite, I realized that I had to update not one, not tWo, but THREE datasets in order to bring everything up to the present.
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.
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.
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