- Joined
- 11/16/13
- Messages
- 4
- Points
- 13
Hey folks,
I posted this question to another forum and didn't seem to garner much informed response. I realize quant net isn't too big on algo trading, but maybe some of you can steer me the right way here.
For a long time I've been fascinated with the idea of writing my own backtesting software. I've seen quite a few of the retail offerings and they don't seem to give me the transparency or flexibility that I want to have. So far the best retail solution I've seen is deltix, but I still don't think a retail solution is really what I'm looking for. I want to understand and also be able to customize every element of the backtesting process. I've done quite a few vectorized backtests in MATLAB which is great, but I really want to come up with an event-driven solution in C++ (and maybe build an event-driven MATLAB version or plug in as well later). My basic structure so far is a pretty much just a for loop that loops over time and my data and a header file of functions that are close to the functions you can find the IB TWS API. I also have made the commissions and some characteristics of the account management rules scriptable.
My question to you folks is what can I do to make this better? How do the big prop firms/funds etc. backtest? What can I add to improve the accuracy of this and make my tests more accurate? What omissions have I made?
In terms of optimization: Currently I just use a brute force parameter sweep. I split my data into a training and testing set. I bet there's an ideal way to split it up instead of just first 75% training, last 25% testing, because that obviously opens me up to the possibility or regime shifts, etc. I've been reading a lot about genetic optimization and am working on including something like that instead of just a big parameter sweep for optimization.
In terms of data and data storage: I'm lucky to have very good millisecond level data on certain assets made available to me by my school, which I'm learning how to store in the free version of kdb+ from my database. I've been using MySQL, but it's obviously not optimal.
In terms of the next steps I'm considering: I want to make it multithreaded to run multiple tests at a time or improve the performance of my future genetic algorithms. I've been looking into the possibility of using CUDA on my GPU as well but maybe that isn't so well suited to this task. I also want to add portfolio level functionality (that I don't have to code up each time).
So let's hear about some other ideas, pointers, and gotchas you've experienced that might help an aspiring algo trader out!
I posted this question to another forum and didn't seem to garner much informed response. I realize quant net isn't too big on algo trading, but maybe some of you can steer me the right way here.
For a long time I've been fascinated with the idea of writing my own backtesting software. I've seen quite a few of the retail offerings and they don't seem to give me the transparency or flexibility that I want to have. So far the best retail solution I've seen is deltix, but I still don't think a retail solution is really what I'm looking for. I want to understand and also be able to customize every element of the backtesting process. I've done quite a few vectorized backtests in MATLAB which is great, but I really want to come up with an event-driven solution in C++ (and maybe build an event-driven MATLAB version or plug in as well later). My basic structure so far is a pretty much just a for loop that loops over time and my data and a header file of functions that are close to the functions you can find the IB TWS API. I also have made the commissions and some characteristics of the account management rules scriptable.
My question to you folks is what can I do to make this better? How do the big prop firms/funds etc. backtest? What can I add to improve the accuracy of this and make my tests more accurate? What omissions have I made?
In terms of optimization: Currently I just use a brute force parameter sweep. I split my data into a training and testing set. I bet there's an ideal way to split it up instead of just first 75% training, last 25% testing, because that obviously opens me up to the possibility or regime shifts, etc. I've been reading a lot about genetic optimization and am working on including something like that instead of just a big parameter sweep for optimization.
In terms of data and data storage: I'm lucky to have very good millisecond level data on certain assets made available to me by my school, which I'm learning how to store in the free version of kdb+ from my database. I've been using MySQL, but it's obviously not optimal.
In terms of the next steps I'm considering: I want to make it multithreaded to run multiple tests at a time or improve the performance of my future genetic algorithms. I've been looking into the possibility of using CUDA on my GPU as well but maybe that isn't so well suited to this task. I also want to add portfolio level functionality (that I don't have to code up each time).
So let's hear about some other ideas, pointers, and gotchas you've experienced that might help an aspiring algo trader out!
