Leaderboard

Generally, for backtesting you have a few options. -Quantopian : Cloud based, aimed at algorithm development. -Zipline: Local version of Quantopian, tad complex to get setup and running right. -Backtrader: Open Source Python backtester with ability to trade live via the IB API. Learning curve, but probably the best of the free bunch. -Amibroker: Powerful backtest software but expensive ($400 for the complete package). They all will do what you want if you know how to program for them, that's where it gets tricky, as you have to set them up to load in your executions and how to handle the In-trade procedure. The tool I'm developing (and will eventually release to the community) loads your exported trades, caches the minute data for the stock, and then runs a bunch of simulations against that data before producing a report of comparisons to the baseline. For example if you wanted to compare what your PnL looked like if you never moved to breakeven and sold at R.5, R1, R1.5, and R2 levels, it'd do it. The report crunches the benchmark numbers and adds some meta data about each trade (e.g. calculated stop too close, risk reward ratio not adequate, scaled too early, didn't let run) - the goal is to give a broad brush idea to people about areas they may be able to hone their edge (a few trades flagged as scaled-too-early is just noise, a large percentage might be something to look at). The difficult part about this is making it user friendly. Not sure when I'll have it in a state to release, lots of projects at the moment so the passion development has to go on the back burner.