This caught my eye this morning: “10 ways to improve your programming skills”
Since I’m learning how to program (has it been two months!?), and I want to get better at it, I should try to follow some of this advice. Here’s the list:
1. Learn a new programming language
Um. It’s all new!
2. Read a good, challenging programming book
Ok, bit advanced.
3. Join an open source project
Yeah, right.
4. Solve programming puzzles
Possible candidate here. Sounds like a lot of work, though.
5. Program
Got enough of that to do!
6. Read and study code
Ugh.. no time.
7. Hang out at programming sites and read blogs
No “hanging out”, but I read.
8. Write about coding
Hmm….
9. Learn low-level programming
Nope.
10. Don’t rush to StackOverflow. Think!
Meh.
-=-=-=-=-
So maybe writing about programming is the low-hanging fruit here.
Ok, so here’s what I did today at work.
There’s this company called AM Best who are an insurance-specialist rating agency, like S&P but much narrower in focus. I go there periodically for financial information on our clients and markets and for the industry in general.
Anyway, I noticed that there is a press release archive going back to 2000. The thought struck me that it would be neat to have a database of all these press releases to crunch and see if there are any patters in the rating actions taken on companies.
THEN it would be neat to link these rating actions to stock prices, to see whether the ratings actually, um, you know, work.
For instance: how good of a predictor are they of default? Is there an immutable ‘snowball effect’ where a rated entity just keeps getting downgraded until it fails or merges with someone else?
So this project has been bubbling around in my head for a few weeks and this morning I finally had enough spare time in which to implement it.
I’ve put together a scraping routine (busily ‘scraping’ as I type) that is pulling down all 10,000+ press releases and dropping them into a database.
I considered doing all the actual data mining today, too, but that’s going to take a bit too much time. I’m happy with just sitting on the data for now.
My next objectives:
1. Parse the text to figure out what the various categories of press releases are.
I know there are downgrades and upgrades of companies, but what about actions against subsidiaries only? What about debt ratings? Most of this crap is useless to me.
2. Figuring out a system for identifying companies that matter.
There is going to be a ton of mergers, defaults, spin-offs and goodness knows what going on that I’ll need to work out. That will be tricky.
3. Isolating the rating actions associated with corporates and building a more ordered database of actions over time.
This is the ‘real work’, obviously. How ironic that it’s going to by far be the easiest step once everything’s organized. Regular Expressions, baby. Cinch.
3. Figuring out how money has been made or lost in this process.
I want to link these names to stock symbols and see if there is any perceived contagion (by the market) and, even more importantly, whether there is any ACTUAL contagion. I suspect not.
Not Unreasonable 