The first analyst day I attended was at the Vista International Hotel in the World Trade Center. When I walked out into the hall during a break, there were long banks of pay phones jammed with analysts delivering the bad news to trading desks and clients. The price of Control Data stock probably never saw that level again, but I was so clueless that I didn’t have any idea what had happened.
The other thing I remember from that day was standing behind the rows of analysts in the ballroom and seeing a sea of gray and blue, with two splashes of color, one red dress and one brown. There were a few other women in attendance as well, but they had adopted the corporate colors of the time.
At the hundreds of conferences and large meetings I’ve attended since, there has rarely been more than ten or fifteen percent of the attendees who were women. Last week, the shoe was on the other foot at a CFA Institute conference, “Alpha and Gender Diversity: The Competitive ... continues
In the aftermath of the financial crisis, there was a great hue and cry about how we had become slaves to our models and that they had proven to be imperfect — tragically imperfect — masters.
It is, then, quite ironic (and very surprising, at least to me) that we seem to be more reliant on those models than ever before. Well, perhaps not those models, but the new-and-improved ones that have taken their place.
The investment business has gotten more quantitative and more automated, so that’s certainly part of it. It’s hard to become more qualitative in your approach and more thoughtful about the proper context in which models should be used when you’re handing off much of the decision/execution process to machines.the research puzzle | Here’s a posting that considers “programmed” versus “nonprogrammed” decisions.
The financial crisis was a watershed event for investment organizations, as you might expect. Significant ... continues
In most of our endeavors, we seek to avoid ambiguity and are quick to classify people, places, things, whatever. Those classifications make it easier for us to think in a shorthand way, taking some of the complexity out of the complex nature of everyday life (even while adding in the real possibility of errors in miscategorization).
Of course, investors are champions at this activity, breaking down our holdings into asset classes and style boxes and buckets of this and that. It all seems so precise and definite, but it really isn’t. There are lots of gray areas made to look like black and white — and the lines are drawn looking backwards rather than forwards.
Today’s classifications are soon to be out of date and, truth be told, the best money is often made by moving across the existing lines and into new territory, which is an anathema for those who like to plot out the landscape according to the current map and have carefully prescribed percentages of assets ... continues
Every industry has its lingo, its jargon, and its favorite phrases. In the investment world, you can see that in spades, even though the words sometimes don’t enlighten as you would expect.
For example, think of the terms that have come to be used to label an asset category — like “hedge funds” or “smart beta” — without really describing the category accurately at all. If you need air quotes and repeated clarifications when using the terms, perhaps we could come up with something better, but those ones have stuck.
Language is a function of the culture that spawns it, so it’s interesting to watch it develop over time and to see what phrases become an inescapable part of the dialogue (even as they become relatively meaningless through repetition and sloppy application). Today’s example: “high conviction.”
If you read the materials of organizations that are involved in investment manager selection, you can’t ... continues
I came across a handout from an information systems class that I took more than forty years ago. The front page had a grid that was based upon the work of Nobel laureate Herbert Simon from 1960. Here it is:
As I looked at it, I started to think about investment decision making. Using this grid, are investment decisions programmed or nonprogrammed? Are they more often “routine and repetitive” or “one-shot, ill-structured, and novel”? There are different camps of belief. For example, someone who believes in indexation has chosen to own “the market” today, tomorrow, and forever. That’s as straightforward and programmed as it gets.
But the categorization as presented primarily made me ponder the boundaries of quantitative investment management (programmed) versus fundamental management (nonprogrammed). Quantitative approaches have been around a long time — thirty years ago there were simple versions of much of what is ... continues