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Minute resolution in research

hi,

i'm trying to train a small NN in research envirment.

assume i have a list of symbols and a list of dates, how do i get minute resolution data for those lists?

i'm getting an error using history.

thanks, Nitay.

Update Backtest







qb.History(tickers, start_date, end_date, resolution) returns a multi-index data frame. Please see the attached notebook file.

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for some reason, the message didn't come right.

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for some reason, the message didn't come right.

i have two problems:

1. in the second cell: can't increase 'day_delta' above 10.

2. when running the third cell: i'm getting 'dead kernel'.

please help! it's so frustrating, i can't do the most basic things...

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Hi Nitay, you'll run into the timeout issue for large history request. Please try to request a small period of history price with self.History() and concatenate the data frames to obtain the entire data set you need. A large history data request will kill the kernel.

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The material on this website is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory services by QuantConnect. In addition, the material offers no opinion with respect to the suitability of any security or specific investment. QuantConnect makes no guarantees as to the accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances. All investments involve risk, including loss of principal. You should consult with an investment professional before making any investment decisions.


hi Jing Wu ,

this is the problem in the second cell, but in the third cell i'm calling history inside a loop, one symbol and one day at a time, so what's the problem there?

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Update Backtest





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The material on this website is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory services by QuantConnect. In addition, the material offers no opinion with respect to the suitability of any security or specific investment. QuantConnect makes no guarantees as to the accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances. All investments involve risk, including loss of principal. You should consult with an investment professional before making any investment decisions.


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