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    • S

      Submission failure
      Support • • Sun-73

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      support

      @antinomy great! Sorry, there were many submissions on the last day.

    • S

      Please advise on p settings. Thanks.
      Strategy help • • spancham

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      S

      Hi @support
      Thank you, I'll try that.

    • magenta.grimer

      More color on contest rules
      General Discussion • • magenta.grimer

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      support

      @magenta-grimer Hello, the 34 M USD have been allocated to the winning strategies according to the contest rules.

      Other strategies have been funded, and agreements are in place between quantiacs, investors and quants. We cannot disclose more details now, sorry.

      5M USD is a reasonable capacity a strategy could handle, yes.

    • S

      Machine Learning Strategy
      Strategy help • • spancham

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      S

      @vyacheslav_b
      Thank you! 🎉 🎉

    • S

      Strategy Funding
      General Discussion • • spancham

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      support

      @sheikh Hi,

      it simply means that your system should make a new global high before you are entitled for a payment. If your system makes 1000 at the end of January, 800 at the end of Februray, 900 at the end of March and 1100 at the end of April, your profit will be generated at the end of April and they will amount to 1100-100=100;

      no, once the system starts being traded, it will be traded in the form it was at submission time, i.e. the quant will not be allowed to update parameters/change details. Of course a submitted system can have an adaptive logic, by changing parameters according to the value of some meta-indicator. If the quant believes there is some big change to be made, it is ok to re-submit the changed system, but it will need again to accumulate a track record before being traded.

    • S

      Files disappeared from online env
      Support • • Sheikh

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      support

      @antinomy Hi, sorry for the late answer. The problem is the size of files, we are working on a solution for avoiding this issue in the future.

    • A

      Submission Issue
      Support • • antinomy

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      A

      Just out of curiousity I did some testing and it looks like the class actually was the culprit.
      I submitted a simple strategy in 2 versions, one with a class and the other with a dictionary as state. The class version was rejected (exaclty like the one from my 1st post) and the dictionary version got accepted.

    • support

      Share the state between iterations
      Request New Features • • support

      12
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      S

      @support
      ok I did what @antinomy said below and the 'state' strategy worked.
      https://quantiacs.com/community/topic/46/macroeconomic-data-with-quantiacs/3?_=1619554449031

      However, it broke my old strategies. So he further suggested to:
      https://quantiacs.com/community/topic/46/macroeconomic-data-with-quantiacs/5?_=1619556376479
      And my old strategies are running again.

      Ok, so looks like for now for all strategies without a state I have to output and pass None to weights for the state & pass a state variable to the strategy.
      Will keep you updated. Thanks for looking into the issue.

    • news-quantiacs

      The Q16 Contest is open!
      News and Feature Releases • • news-quantiacs

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      support

      @antinomy In the end we followed your advise and changed a little bit the algorithm for adding data, once a cryptocurrency is in the top10 we include it with its past history and go on with the update (now DASH and XMR are being updated). Of course once the crypto is not among the top 10, the liquidity tag for the filter is "zero". Thank you!

    • A

      Different Sharpe ratios in backtest and competition filter
      Support • • antinomy

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      C

      @support Thank you very much for the clarification, and once again congratulations for the great job you are doing 😉

    • S

      Different Sharpe ratios in backtest and after submission
      Support • • Sun-73

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      Hi @support,

      I modified the retraining interval to 1 day and it worked. Thank you for the help.

      You guys rock!

    • S

      Suggestions for the Q17 contest.
      News and Feature Releases • • Sun-73

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      support

      @theflyingdutchman Hi, each system is tested for correlations against the templates we provide and with all systems submitted to the past crypto contest.

      Sorry for the confusion when you run the notebook, we are working on improving the correlation messages.

      We already changed the information displayed in the submission area. If you want to get more infos on correlations, please submit your code (it does not matter the message about correlations you get in the notebook, the system will be processed). After processing, the submission will appear in your submission area as a "non-eligible" submission because of high correlations, and you will see to which template the correlation is high; and to which past submission you made (to the Q16) the correlation is high. Moreover, you will get some infos about correlations to systems you are submitting to the Q17 contest.

    • S

      Optimizer still running
      Strategy help • • spancham

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      @support
      Thank you! I'll try that and let you know.

    • S

      Issue with the In-sample Sharpe
      Support • • Sun-73

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      99
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      S

      @support Thank you once again. You guys are the best!

    • magenta.grimer

      Help in developing a strategy
      Strategy help • • magenta.grimer

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      support

      @magenta-grimer Hi, the lookback period in the backtester function is expressed in calendar days, and the indicators are expressed in trading days. So as far as the lookback period is long enough to include all indicator needed periods, all choices are fine.

      If the longest period needed for an indicator is 10 trading days (2 weeks), a lookback period of (for example) 20, 50 or 100 for the backtester function will deliver the same results. The shorter the better for efficiency.

    • news-quantiacs

      Data for Futures
      News and Feature Releases • • news-quantiacs

      8
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      support

      @captain-nidoran

      Hello.

      We are making some changes before starting competitions, it affected the statuses of some submissions and they became invisible on the client side. Now it should be ok.

      We carefully preserve users' data, we are making backups every day. So in the worst case of data loss, we are able to restore most data from these backups. Don't worry a lot. And thank you for the report.

      Regards.

    • P

      How to do sliding window of test/train
      Strategy help • • Penrose-Moore

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      support

      @penrose-moore We finally released a template which allows you to perform a retraining, it is available in the "Examples" section of your private space or publicly in the Documentation:

      https://quantiacs.com/documentation/en/examples/machine_learning_with_a_voting_classifier.html

    • A

      External Libraries
      Support • • antinomy

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      @support
      Yes, pip is way faster. Thanks!
      I might have found an even faster solution but I guess I have to wait a few hours to find out if it really works.

      Here's what I did:

      I created a folder in /root/books called "modules" to install cvxpy there to make it persistent: !mkdir modules && pip install --target=modules cvxpy Then if the import fails in the strategy, it creates symbolic links in /usr/local/lib/python3.7/site-packages/ that point to the content of /root/books/modules/ try: import cvxpy as cp except ImportError: import os source = '/root/book/modules/' target = '/usr/local/lib/python3.7/site-packages/' for dirpath, dirnames, filenames in os.walk(source): source_path = dirpath.replace(source, '') target_path = os.path.join(target, source_path) if not os.path.exists(target_path) and not os.path.islink(target_path): os.symlink(dirpath, target_path) continue for file in filenames: source_file = os.path.join(dirpath, file) target_file = os.path.join(target, source_path, file) if not os.path.exists(target_file) and not os.path.islink(target_file): os.symlink(source_file, target_file) import cvxpy as cp

      Creating the symlinks only takes 0.07 seconds, so fingers crossed 🙂

      UPDATE (a few hours later):
      It actually worked. When I just reopened the strategy, the environment was newly initialized. First I tried just importing cvxpy and got the ModuleNotFoundError. Then I ran the strategy including the code above: cvxpy was imported correctly and the strategy ran.

      I'm not sure if that solution works for every module because I don't know if pip might also write something to other directories than site-packages.

      Anyway, I'm happy with this solution.
      Regards

    • magenta.grimer

      Modify an example strategy to trade on the futures market
      Strategy help • • magenta.grimer

      8
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      magenta.grimer

      @support Thank you very much!

      I hope to don't disturb you so often in the future @support , but before that I need help to "get going".

    • A

      Issue with Future and Crypto Spot data
      Support • • anshul96go

      8
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      @support Thanks, mailing you!

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