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My understanding is that if you want to create an indicator using the morningstar fundamental data then you must use a Fine Fundamental Universe and that the SetWarmUp functionality is not available when using fundamental data for say PE Ratio or Total Revenue.
The algorithm I am working on needs 5 quarters of data pumped into the indicators deque to start making trading decisions. If I run the backtest the results overview trading graph shows 5 quarters of the algorithm doing nothing and then it starts trading a bit after that. Is there a way to exclude the first 5 quarters (year and 3 months) from the results calculations since we don't have a way to do it with the warm-up functionality? Is there a good workaround? I want to see results like Annual Returns based on the time I trade and not including the time I am preparing data to trade.
One idea I saw was to write an algorithm that generates the indicator for the first year and 3 months and then saves it in an object store and then starts another seperate program that would read in this first year and 3 months to the indicator from the object store and then start from after the year and 3 months. Does this make the most sense in this case?
Greg Kendall
It just struck me that I could generate the data I need from the fundamental morningstar data in the research environment and save it to an object store and then in a backtest algorithm I could read in this object store into an indicator and then let the algorithm do its thing on this earlier saved data.
I seem easier to deal with fundamental data in the research environment anyway, so why not? Why not save all the quarterly data I need for 1500 stocks or so and just use that instead of pulling the fundamental data out of the fine universe data in the backtest environment? Then I don't need to "warm up" the indicators ... the research environment can warm them up! (I am assuming you can save to an object store from the research environment.)
Greg Kendall
I just realized the problem with the research environment. It can't dynamically generate a list of stocks based on criteria like the fine universe can. You need to specify a fixed list, as I understand things.
Derek Melchin
Hi Greg,
Universe selection doesn't not currently run during the warm-up period.
In addition, it's not currently possible to gather historical fundamental data in the backtesting environment. We are in the process of adding this functionality though. Subscribe to our progress here.
For a temporary workaround, consider using a QuantBook inside of the backtester as demonstrated in this related thread.
Best,
Derek Melchin
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.
Greg Kendall
" this related thread" does not link to QuantBook info. I think you repeated the link from github.
Derek Melchin
Hi Greg,
We've updated the link above to point to the related thread.
Best,
Derek Melchin
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.
Greg Kendall
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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