Kx released a 32bit, free-for-commercial-use version in 2014 and then reversed course around a year later after banks and hedge funds surprised them by flocking to it for a large subset of their developers / dev machines.
Hopefully they stick to it this time around. It's an incredible system. It's the only thing I've ever used, including Pandas, dplyr & Matlab, where someone could stand over my shoulder asking data analysis questions and I could answer them, on the fly.
LLM's, though notoriously bad (so far) at KDB+/Q compared to other languages, are still a godsend for folks getting started. I recently returned to writing Q after being away from it for 8 years and I've been amazed how good even Google's AI suggestions have been at helping with functions & queries.
Getting started tip: try using Q strictly as a query language, avoid K. Do everything else (data shoveling, devops,...) with a different language.
I'm always stunned to see the level of VB6 expertise that remains in the world even two decades after Microsoft left it for dead.
Just look at the effort and knowhow that went into this VBA function that resolves the local file system path from the https url of workbooks synced to OneDrive/SharePoint:
I've been surprised to see many pro devs using Excel/VBA as a secondary tool.
One example: a couple years ago I was working with a big hedge fund and one of their data analysts sent me an Excel model he had built and I was tickled to see the .xlsm extension (i.e., VBA code on board).
"Ahh ha", I thought, "Let's see what these macro-recording cowboys have been up to."
There was a lot of VBA inside, all written by this Caltech comp sci data analyst who was a Python superstar. The VBA was for pulling data from a database, putting it on a sheet, building some formulas, and some pretty formatting. There were even a few userforms!
I teased him, "VBA? What else are you guys using over there? A cotton gin and a steam shovel?"
I was startled to hear him heap praise upon Excel and VBA instead of the usual complaints.
He said something that stuck with me, "Excel makes it easy to understand the dependency structure that is implied by computations. If I had done this in Python, I'd be answering questions about it all day long."
He has a younger sister. As for other outlets for making friends and socializing, team sports are indispensable. Also great, and surprisingly underutilized -- in my observation -- are playgrounds.
With playgrounds you get the best part of school, recess, without the rest of it.
If parents would look up from their phones for a minute and watch what's going on in playgrounds they'd be amazed.
Recently I saw about 20 kids, across a wide age range, hold a spontaneous, well-organized game of Among Us.
You won't just make friends there; you'll run in Draco Malfoys too; and that's also valuable.
We started homeschooling by happenstance when it turned out that kindergarten was going to conflict with our son's beloved jiu-jitsu class. The class was a bit of a drive and we weren't going to be able to get there in time for his favorite part: the 30 minutes of horsing around on the mats before class started.
We thought, "Well, it's only kindergarten". It worked out well enough (knock on wood) that we just kept going.
Compared to my own harried "THE BUS IS COMING!!!" sleep-deprived school days, it has been a wonderful change.
If I could go back in time, I'd put my mom in an ankle lock until she agreed to do the same for me.
Especially since I learned that in my home state homeschoolers can participate in high-school sports. In high school I had to wake up at 4AM for 5AM hockey practice. If I could have returned home afterwards and slept, rather than going straight to school, I would have thanked the Gods.
I agree that insider trading is an unlikely explanation for the reason you mention.
It could be that an early algorithmic advantage compounded into an incumbency advantage: better research tools; better data; better pay for better scientists.
The 'secret sauce' may have started out as novel discoveries and, over time, become 'just being RenTec'.
Particularly when these analytical advantages may compound over time rather than dissipate. For instance, suppose a firm was exceptionally good at pairing world-class mathematicians with a team of mathematically-exceptional programmers who could reconceptualize the math wizard's insights as financial time series models and steer them towards areas of applicability. Now, when the next world-class mathematician comes to the office on a recruiting trip, he recognizes a higher expected value & better colleagues, joins, and the engine gets more repetitions with which to improve itself.
I worked on an Excel\vba swat team at an investment bank. Whenever someone in the various business units got themselves into more trouble than they could handle with an Excel model, we'd try to set things right. We saw a lot of wonderfully creative vba code from industrious programming beginners (or, as we liked to call them, "Macro Recording Cowboys". The most amusing I saw was a model where the vba code used a Greek mythology variable naming convention:
Dim Hermes As String, Artemis As Long, Odin As Range
Hopefully they stick to it this time around. It's an incredible system. It's the only thing I've ever used, including Pandas, dplyr & Matlab, where someone could stand over my shoulder asking data analysis questions and I could answer them, on the fly.
LLM's, though notoriously bad (so far) at KDB+/Q compared to other languages, are still a godsend for folks getting started. I recently returned to writing Q after being away from it for 8 years and I've been amazed how good even Google's AI suggestions have been at helping with functions & queries.
Getting started tip: try using Q strictly as a query language, avoid K. Do everything else (data shoveling, devops,...) with a different language.