@Mukund, this isn't currently available in the Quantopian backtester, you will have to manually kick off a full backtest for each iteration. Note that your data is saved in a full backtest. You can start it, close your laptop, walk away, and come back when the full backtest is finished to view the returns, logs, and performance. Parameter optimization will be easier in the upcoming research environment. This features hosted IPython notebooks where you can analyze datasets and run these calculations. Here's a demo sneak peak.
@Joe Zipline is Quantopian's backtesting engine. The code is entirely open sourced and available on Github. You're welcome to develop algorithms locally on your machine and then port them to Quantopian for further backtesting and to start live trading with the broker. If you're feeling ambitious, you can submit a pull request!
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