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Tear sheet of a Live Algo

Is there a way to obtain a tear sheet of an algo that is trading live?

5 responses

Any other ways to achieve the same thing would be appreciated.

Hi Peyman,

If you have a live algorithm that's been running for 6 months or longer, you can generate a tearsheet for it by using get_live_results().

You can do something like this in research:

lr = get_live_results('<id>')  
lr.create_full_tear_sheet()  

where the is the ID of your live algorithm obtainable from the URL of your live algorithm dashboard (https://www.quantopian.com/live_algorithms/<id>).

Let me know if this helps.

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Thank you Jamie I was not aware of the 6 months lower bound. I guess there is really no good way of pulling stats and performance metrics before 6 months other than to look at what the dashboard gives you.

Update: just saw that all the data is actually there when using get_live_results(''). I will write the metrics myself. Thanks for your help.

Jamie, is there way to get the results of an algo from all of it's different runs (due to unavoidable restarts and crashes?). I have some algos which have been trading since last November, but they've all been required to be restarted a handful of times, so I don't have a contiguous trading history for them...

Hi Simon,

Interesting point/question. Currently, there's no straightforward way to do this, but I just submitted a feature request internally for the ability to concatenate live algo results in research.

In the meantime, here are a couple of workarounds that you could try:

1) Manually format the data for pyfolio. This would require you to get all of the live algo results, get the data that you need, reformat it, and input it to pyfolio. It may require some time, but it should work.

2) Run a backtest your strategy and specify the live_algo_start_date to be the date that your first live algo started (see create_full_tear_sheet docs). The downside to this one is that it's a backtest, but the upside is that it won't require much work.

Again, neither of these is ideal and we'll see if we can come up with a better way to achieve the same thing.