Are there any integrated framework that I can back-test and paper/live trading in one place?

External question — Quantitative Finance Stack Exchange Author: Hao Original post: https://quant.stackexchange.com/questions/25224 License: CC BY-SA 3.0 — https://creativecommons.org/licenses/by-sa/3.0/ Adaptation: HTML converted to plain text; contact email addresses removed. I'm trying to start working on a fully automated algorithmic trading system, and I'm a little struggling with the framework to use. The requirements I have in my mind are: Needs to support back-testing. Needs to be able to do paper/live trading with Interactive Brokers, without rewriting the code with their API. Needs to support most security types, like stock, option, future, Forex, etc. For 1 and 2 I know there's quantopian. For 2 and 3 I know there are frameworks like pyalgotrade. But I can't find anything that support all the three. If there is one solution can you give me some recommendations? Or if there's no such thing exists, can you tell me how you handle these problems, with minimum efforts? Thanks a lot!

External answer — Quantitative Finance Stack Exchange Author: Thomas Johnson Original post: https://quant.stackexchange.com/a/25307 License: CC BY-SA 3.0 — https://creativecommons.org/licenses/by-sa/3.0/ Adaptation: HTML converted to plain text; contact email addresses removed. Remember that all back testing is full of lies assumptions. Latency (both line latency and latency internal to the exchanges), adverse selection, market impact (yes, even you have market impact), etc, are all based on assumptions. These assumptions are educated guesses at best, but more often terrible models are used (you always get filled at at mid!) and they're totally hidden from you. The best choice, if you have the capability, is to choose your execution platform and then tweak an existing backtesting framework to match the behavior you observe in live trading (or build a backtesting framework from scratch if necessary). If you're worried about API compatibility, use a facade or adapter to make the backtesting and execution APIs look the same..

External answer — Quantitative Finance Stack Exchange Author: mementum Original post: https://quant.stackexchange.com/a/25508 License: CC BY-SA 3.0 — https://creativecommons.org/licenses/by-sa/3.0/ Adaptation: HTML converted to plain text; contact email addresses removed. Edit (2016-06-21) : Now with live data/trading integration with Interactive Brokers. It has taken a while but it has finally arrived. backtrader ( https://github.com/mementum/backtrader ) can do 1 and 3 and is in the process of getting 2 ironed out. A live data feed from IB will make it into the next release (due in the next few days) and it will then be down to mapping of orders. On the project page you can see a list of other similar (some more, some less) python projects and may prove to be closer to be your cup of tea, or maybe not. Disclaimer : I am the author of backtrader Filling: Quick explanation as Thomas Johnson is right in the need to make assumptions. Volume is not used. I only trade in markets and assets which are liquid enough Pricewise ... it depends on the order type with the following assumption in place: the bar which the system is evaluating is gone ... no match can be done against it Market : The order gets filled with the opening price of the next bar Close : meant for intraday systems and gets matched with the last bar of the session at the close price Limit : starting with next bar the system looks at the open/high/low/close prices to try to give a "better" price (example: open is better than the limit, open is chosen) or limit StopLimit : similar to limit, but looking again at the 4 prices components to see if the stop trigger price and limit prices can be executed in the same bar.