Backtesting is only 1/2 to 1/3 of the actual task of algorithmic trading. When it comes to actually trading money, if you're not careful and cover every corner case, you really could lose your shirt. I can't believe that 100 lines of code is all that you would need to cover all the edge and failure cases that could lose yourself a lot of money.
What happens if the network drops while you're in a trade, or in the middle of executing an order? What if you have a partial fill, and you have a partial buy order hanging around and a full sell order out there? What if you have a stop limit order to exit a trade, and it blows through your limit? Do you have a backup stop order just in case? There are a lot of issues that you can't backtest that can only be learned once you start trading real money. I've had situations where I ran my algos on the DAX overnight, and I woke up to find that the exit order never executed, and I was 1000 euros away from where I should have gotten out. Luckily, this trade was in my favor, but it scared the shit out of me because it could have easily gone the other way. I've also had my internet connection drop overnight, and I had to scramble to figure out how to get out of a trade I was in.
The other issue is interpreting backtesting data, and knowing the difference between over-optimized data (ie. curve fitting) vs something with an actual edge. You can make almost any algo profitable if you curve-fit, even a simple MA cross-over can show extremely profitable results, if you over-optimize the data. But it won't work in real life. So being able to sift between falsely good algos and actually profitable algos is very, very hard, and takes experience. This is the biggest problem with trying to find an actual algo with an edge, it's very very hard.
I wrote my own backtester and I download my own data nightly, and that definitely takes a lot of time and effort, but the hardest part is the actual trading, by far. The psychology involved with trading is an order of magnitude harder than coding, and the hardest thing I've ever done in my life. I blew through a shitload of money, just to learn the ropes.
In terms of algo trading books, I really don't have any recommendations. I found most of the algo trading books are similar, telling you to watch out for curve fitting, etc. Where they lack is helping you come up with actual trades. My recommendation is a book called "Mastering the Trade" by John Carter. He gives out trade setups that he actually used. They may no longer be profitable, but it's the closest thing you can get to actually learning various day trading techniques, and you can implement those to get an idea, and then work your way from there.
I'm not hating on Quantopian, it looks pretty nicely done, and hopefully it takes off. But from experience, I know that algorithmic trading is by far the hardest thing I've done. If inexperienced traders jump in, they'll spend a lot of money on "tuition" for sure.
What happens if the network drops while you're in a trade, or in the middle of executing an order? What if you have a partial fill, and you have a partial buy order hanging around and a full sell order out there? What if you have a stop limit order to exit a trade, and it blows through your limit? Do you have a backup stop order just in case? There are a lot of issues that you can't backtest that can only be learned once you start trading real money. I've had situations where I ran my algos on the DAX overnight, and I woke up to find that the exit order never executed, and I was 1000 euros away from where I should have gotten out. Luckily, this trade was in my favor, but it scared the shit out of me because it could have easily gone the other way. I've also had my internet connection drop overnight, and I had to scramble to figure out how to get out of a trade I was in.
The other issue is interpreting backtesting data, and knowing the difference between over-optimized data (ie. curve fitting) vs something with an actual edge. You can make almost any algo profitable if you curve-fit, even a simple MA cross-over can show extremely profitable results, if you over-optimize the data. But it won't work in real life. So being able to sift between falsely good algos and actually profitable algos is very, very hard, and takes experience. This is the biggest problem with trying to find an actual algo with an edge, it's very very hard.
I wrote my own backtester and I download my own data nightly, and that definitely takes a lot of time and effort, but the hardest part is the actual trading, by far. The psychology involved with trading is an order of magnitude harder than coding, and the hardest thing I've ever done in my life. I blew through a shitload of money, just to learn the ropes.
In terms of algo trading books, I really don't have any recommendations. I found most of the algo trading books are similar, telling you to watch out for curve fitting, etc. Where they lack is helping you come up with actual trades. My recommendation is a book called "Mastering the Trade" by John Carter. He gives out trade setups that he actually used. They may no longer be profitable, but it's the closest thing you can get to actually learning various day trading techniques, and you can implement those to get an idea, and then work your way from there.
I'm not hating on Quantopian, it looks pretty nicely done, and hopefully it takes off. But from experience, I know that algorithmic trading is by far the hardest thing I've done. If inexperienced traders jump in, they'll spend a lot of money on "tuition" for sure.