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Hi,
Is there a way to get backtest results into the research environment?
This is what I was using on Quantopian to run pyfolio from the research environment:
import pyfolio
bt = get_backtest('59ba65befb066a54cb82b031')
bt.create_full_tear_sheet()
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Felipe Palhares Hampshire
This will be very helpful.
+ 1
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Alexandre Catarino
Hi Lexx7 ,
We have created a GitHub issue to implement this feature:
[Research] QuantBook Retrieves Backtest Results For Analysis #4580
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Bruce Vanstone
Hi,
any update on this feature, or an example of how to access the backtest results for an algorithm for further analysis?
Cheers,
Bruce
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Laurent Crouzet
Bruce Vanstone A lot was added to analyse backtests. See:
https://github.com/QuantConnect/Lean/pull/4898I still need to do additionnal research to check that every data is available from this method...
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.
Shile Wen
Hi Bruce,
This was answered in this thread.
Best,
Shile Wen
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.
Shile Wen
Hi Bruce,
Under the Console, you should see "Backtesting Project ID: ..." and "Algorithm Id: ..." for the Project and Backtest IDs respectively.
Best,
Shile Wen
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.
Tarquinius Superbus
Hi QC team,
I am fairly new to the platform and has a question on accessing backtest result from research notebook. I was able to import the backtest object by using the command mentioned above. However I am not sure how to access the contents/values in the backtest object. Specifically, I want to see daily return/daily portfolio position from the backtest.
I tried to go over detailed documentation here:
https://www.quantconnect.com/lean/docsHowever this doc seems outdated and incomplete. I'd really appreciate any help/pointer on this.
Best,
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.
Derek Melchin
Hi Tarquinius Superbus,
To get the backtest results into the Research environment, we can use
api.ReadBacktest(projectID, backtestID)See the attached notebook for reference.
A list of all the backtest attributes that are returned from this call are available here. Note daily return and daily portfolio positions are not included. A workaround is to save them in the ObjectStore while backtesting, then load them into the Research environment.
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.
Tarquinius Superbus
Hi Derek,
Thanks for the explanation.
For anyone who wonders into this thread in the future, note that you can extract portfolio NAV with this code snippet. It extracts NAV value from the strategy equity chart.
# To extract portfolio NAV from backtest results backtest = api.ReadBacktest(projectID, backtestID) chartpoint_ls = backtest.Charts["Strategy Equity"].Series["Equity"].Values nav = [x.y for x in chartpoint_ls] date = [datetime.fromtimestamp(x.x) for x in chartpoint_ls] nav = pd.Series(nav,index=date)Best,
Tarquinius Superbus
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.
Jonathan Evans
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.
Michael Handschuh
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.
Max_leverage_yolo
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.
Michael Handschuh
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.
Nat Miletic
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.
Jared Broad
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.
Travis Teichelmann
When I add the top method to Initialize I receive a message that OneBillion doesn't exist in the current context. I've tried changing it to an integer and looking for members that in DollarVolume property but couldn't find anything. Any thoughts?
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Michael Handschuh
You can add
const decimal OneBillion = 1000m*1000m*1000m;. It's just a constant to find stocks with volumes over a billion, Likewise, you could change the volume filter to anything you like!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.
Travis Teichelmann
Perfect! Thank you for updating the code. I modified what you provided to filter the securities based on price. Now all I need to do is implement a gap up and gap percentage method then I can move on to other parts of my algo. Here's what I did.
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.
Stephen Oehler
So this might be a dumb question, but can you apply indicators to the coarse universe selection function? Wondering if I could say, for example, "grab all stocks whose 1-year momentum percent is greater than 10%". :-) Excellent work guys!
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.
Stephen Oehler
Ah found it in an older thread, sorry about that! For those who come here wondering the same thing, here is how you conduct technical analysis in the Coarse Universe filter: https://github.com/QuantConnect/Lean/blob/master/Algorithm.CSharp/EmaCrossUniverseSelectionAlgorithm.cs
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.
Travis Teichelmann
Stephen - You can use indicators on the universe selection, that's actually what I'm working on right now. I've been using the link you provided in another post. https://github.com/QuantConnect/Lean/blob/master/Algorithm.CSharp/EmaCrossUniverseSelectionAlgorithm. Community - I've been looking at the LogReturns indicator and found a way to compare the difference in the current price with yesterday's close. Translating those findings into the coarse universe selection is a bit more tricky. Similar to what Stephen was saying, I want to scan the entire universe for stocks that have gapped up. Then scan those to find ones that have the highest gain. This is one of the biggest parts of my strategy and I've been working on it for a while. So if you could point me in the right direction or give me an example that would be fantastic. Best, -Travis
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.
Michael Handschuh
Hey Travis, you don't need to copy all of your indicators into the project. They should be available without adding the file. Sadly the gap open condition requires open and close prices, but the coarse universe data set only has the daily closing price, so I'm not sure you can detect gap up/down on open. If you're just looking for stocks that had the largest one day gains, take a look at this example algorithm. I used the WSJ top gainers page to find stocks that gained the most in one day... and then shorted them!
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.
Stephen Oehler
Hi Michael, Quick question for ya: If you have indicators that are being used within the Coarse Universe Linq statement, are your indicators updated daily or are they updated at the pace of the Universe Resolution? Example of the indicators being declared and updated within the Linq statement: https://github.com/QuantConnect/Lean/blob/master/Algorithm.CSharp/EmaCrossUniverseSelectionAlgorithm.cs I'm getting too-good-to-be-true results in my algorithm. It uses a certain indicator that requires 20 days of daily data. My Universe resolution is set to minute though, and I'm wondering if I'm getting a self-fulfilling prophecy problem here (maybe benefiting from fill-forwarding?).
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.
Travis Teichelmann
Micheal - Can you backtest live data or is it exclusive to live mode? I've tried to run this algorithm live and made sure the links to WSJ were functional though no trades are being made. I was also inspecting the HTML on the site to find more data to parse. It doesn't seem to be pulling in any data even after I left it running overnight. Trying to run a price filter where d.Price
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.
Stephen Oehler
Hi Travis, I thought I saw someone use custom data with their backtest. Is that the same as "live data" in this case? https://www.quantconnect.com/forum/discussion/418/bubble-algorithm-using-cape-ratio-macd-and-rsi#Item_12 Hopefully I'm not misunderstanding you!
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.
Michael Handschuh
When using indicators in any universe selection function, they will be updated at the same frequency as the universe gets updated. In the case of coarse universes, they will update on a daily time frame. Another thing to note is that we do not apply fill forward to universe selection. If you need more help please post an algorithm demonstrating your issue/concern.
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.
Michael Handschuh
Travis - I'll run the algorithm over this evening with some debugging to see if things are working as expected. Did you make any changes to the example algorithm? I'm not sure what you mean by 'backtest live data.' The NyseTopGainers custom data type is written to support both live and backtesting cases. It supports the backtest case by hitting dropbox (I made a small script to scrape the pages and built a csv from it)
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.
Stephen Oehler
Great, thanks for the validation, Michael!
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.
Michael Handschuh
Clarification on my above statement: We don't apply fill forward to the universe selection data itself, but subscriptions added via universe selection can be set to have fill forward data using the UniverseSettings.FillForward property. This is set to true by default.
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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