I was an ex-quant/trader before doing prop trading. This is how Wall St or big hedge funds or pure quant trading firms view trading. The actual activity of "trading" like hitting bids or offers or whatever is NOT looked upon very highly. It's considered very mechanical and simplistic. The important thing is having a statistically valid, backtested, forward-tested, out-of-sample working strategy.
Now, in order to do that, you need someone who is pretty quantitative AND be able to implement/program up the ideas. Programming isn't that hard, but good programs are harder to create than at first look. You don't need a hacker to implement, b/c most hackers are just hackers they aren't interested in math, finance, or modelling. But they are hella good programmers.
So, it's a very delicate balance of a person they are looking for. They are looking for someone who is SMART enough to actually think of good quantitative trading strategies YET at the same time wouldn't be bored with implementation details. Like debugging, interface with various electronic exchanges,etc. To find both of these in one person is NOT as easy as you might think. That's why quants are highly paid.
Because usually the super top phds guys CAN program, but that's not what he likes to do. He's more of a theorectical math/physics person who is dreamy about CONCEPTS and likes to think of abstract models. Then he hires a cs phd or good ms cs/ee type to implement. But the implementor has to be pretty decent in math too, not just a pure programmer/hacker in order to properly implement the models.
And one last note, the way quants approach trading is very different than the average investors. They aren't interested in one stock acting in a particular way. They generate a portfolio that trades hundreds if not THOUSANDS of stocks at once. Going long and short or abritraging a small discrepancy. So, they aren't going to find it too useful if you tell them, "Oh, I went long EBAY at 34 and it went up to 100." For them, there are so many names in their portfolio that it's impossible for them to even know the individual names. As long as these names are triggered by their trading signals they are included.
So, the problem of quant trading is very general. How do you find a strategy that produce positive alpha above transaction cost and scalable over a few hundred millions or possibly a billion? And once you do find that how do you implement it and automate it so that it's like a black box trading algorithm. Totally hands-off.
That's why the ideal quant has to be good at math, stat, finance, understanding market behaviours, programming, implementation details,etc.
