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Documentation discussion algorithm-reference/consolidating-data

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Hello,

I am new to QuantConnect.  I was wondering if there is a way to develope our custom Consolidators? (Sorry if the solution is so obvious, I tried to scan through the whole docs but cant figure out the solution.)

For example, I have tick data from some exchanges, apart from the standard 'price' and 'volume' information. There is also an additional field indicating the agressive side of the trade (taker buy or taker sell).  I assume that current implemented TickConsolidator will return Time | Open | High | Low | Close | Volume. Is there any way we can include an additional field using the taker side information. For example Total Taker Buy Volume during the aggregated time?

Thanks,

HP

 

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Hi, just noticed your question as I came here looking for some insights to troubleshoot fillForward for quoteBars as I also customized my tickProcessing. Anyways,
(1) For backtesting, you can download a ts-indexed python df you show up there. Utilize data by df.loc[<TimeStamp from OnData()]>] such as Time(). That's how I backtest with precomputed data in QC.
(2) Obviously, for live trading/processing, you'd need another solution.
(3) Regarding this:
volume_pos = data_df.volume.apply(lambda x: x if x >0 else 0).sum() # only take trade volume resulted from a taker buy order
Not sure how the Bitfinex Brokerage is setup these, but volume is potentially never negative. And regarding 'only take trade' - well, two makers cant be matched. There's always 1 side that's taking. Perhaps you wanna differentiate Buy vs. Sell rather? Such as PlusTick, MinusTick, ZeroPlusTick, ZeroMinusTick.... That has some insights when analyzed...

 

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Hi hieppham please start a new thread with an example algorithm attached.

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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.


Thanks Jared. I started a new thread with an example algorithm here

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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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