I worked for a large investment bank, was paid well, but was also rather unhappy. I'm not a fan of office politics and also hated the fact that what we were doing was actually quite unsophisticated, yet we dressed it up like the most complicated thing ever to clients.
We were using wavelets for analysing market micro-structure and using any generated signals to influence our trades. Wavelets were the topic of my thesis, so I was a good fit for the team. I know it sounds complicated, but if you looked at the signals we generated, they looked awfully similar to a rather basic trend-following style regression model. I believe we found a very complicated way to compute signals that a simple trend follower would compute in far fewer CPU cycles.
Anyway, I got a fairly decent bonus one year (because markets were trending nicely), and decided I want to set up my own tech company. I was always a nerdy guy, and I thought I could contribute more in the tech space. With hindsight it was a good move, and financially I believe I am now better off than most of my trading colleagues.
My advice to new guys joining our desk (maybe it helps you a bit): focus on your exit, more than your entry, and if you can help it, be really, really, really lucky :P
Doesn't this describe nearly all of the financial industry? Do you happen to know of any exceptions?
The market is, in theory, not a zero sum game. Algorithmic systems, in practice, are. In theory the only way you can genuinely beat the market is when you find an inefficiency in it. And inefficiencies are generally based on a lack of knowledge. If everybody knows what you know, that inefficiency will no longer exist. And now pair this with the reality that most (and it's probably safe to say all) algorithmic systems are not really especially complex. That doesn't mean they're easy to make though. The 'secret sauce' is in exactly what data is used, how the pieces you have interoperate, the way inputs and outputs are massaged, and so on. But this drives a huge need for secrecy. Nobody who is successful is going to want to talk about how their system is designed largely because most would not be especially difficult to replicate if they provided more than very abstract details.
And given some metric like trading volume how much does that affect that number?
I've heard of some hedge funds raising way less than they could have, maybe because their strategies would be killed much faster with 500mm than with 50mm ?
You know those books that show you how to get rich doing X? Those writers make far more money from the book than they do from X.
No doubt you can find corners of the investing internet that will discuss these things, but you'll probably find an awful lot of chaff in your wheat, because the successful ones won't be chatting about it on forums.
Now on a more constructive note, optimising your long term investment strategy is probably best achieved by getting a pension with some cheap trackers, and a savings account. If you're already doing that then great because that's 95% of your optimisations there.
I wont recommend any web sites, because the details will depend on the country where you live.
I'm right now working on optimizing my long term investment strategy, but the hardest thing is that there's nobody to talk to it about it (unlike when I have other coding problems), and I have no idea when I'm doing something totally stupid in my code base. Getting the right metrics to optimize is really hard, as mostly I'm just looking at numbers and graphs.