@support Great news, thanks!
Posts made by Sun-73
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Q18 Contest
Hi @support,
Regarding the new contest (NASDAQ-100 Stock Long-Short), could you please provide us a Quick Start example to show how to properly read the NASDAQ-100 data?
Thanks!
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RE: Different Sharpe ratios in backtest and after submission
Hi @support,
I modified the retraining interval to 1 day and it worked. Thank you for the help.
You guys rock!
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RE: Different Sharpe ratios in backtest and after submission
By the way, I submitted another system yesterday, called "Sun73_Q17_1b", with an in-sample SR=2, but today the system is online in the website with an in-sample SR=0.7
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RE: Different Sharpe ratios in backtest and after submission
Hi @support, I backtested the system in JupyterLab two days ago and submitted on the same day. The submission went online yesterday.
Since I am trying to use a multi-pass strategy based on the function "qnbt.backtest_ml", maybe the difference is due to difference parameters of this function considered in Jupyter and the online filters of the quantiacs website.
Are the parameters of the function "qnbt.backtest_ml" exactly the same in those cases?
For example, I run the code using retrain_interval=90 days. When the system is evaluated online is it retrained every day since 2014 (or every 90 days in this example)? In other words, the parameter "retrain_interval" is forced to 1 when evaluated online?
Many thanks again!
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RE: Different Sharpe ratios in backtest and after submission
I am using the "in-sample Sharpe" in the comparison above.
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Different Sharpe ratios in backtest and after submission
Hi @support,
The SR of the system "Sun73_Q17_1a" is above 1 in JupyterLab (SR = 1.08), but almost half of it (SR=0.50) after submission to the Q17 contest.
Do you have any clue on that? I am using a modified version of the example "Q17 Supervised Learning".
Many thanks!
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RE: Suggestions for the Q17 contest.
@support Great news! Thank you!!
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RE: Systems selection for the Q16 contest
Hi @support,
Thank you for the prompt response. My set of Q16 systems displayed on the website https://quantiacs.com/leaderboard/16 is the following: Sun73_Q16_1c , Sun73_Q16_1d , Sun73_Q16_1e , Sun73_Q16_2b , Sun73_Q16_2b_v2 , Sun73_Q16_2b_v3 , Sun73_Q16_2c , Sun73_Q16_2e , Sun73_Q16_2f , Sun73_Q16_3a , Sun73_Q16_3b , Sun73_Q16_3c , Sun73_Q16_3d , Sun73_Q16_3g , Sun73_Q16_3h.
However, my chosen set of selected systems is the following: Sun73_Q16_2c , Sun73_Q16_2e , Sun73_Q16_2f , Sun73_Q16_3a , Sun73_Q16_3b , Sun73_Q16_3c , Sun73_Q16_3d , Sun73_Q16_3e , Sun73_Q16_3f , Sun73_Q16_3g , Sun73_Q16_3h , Sun73_Q16_3i , Sun73_Q16_3j , Sun73_Q16_4d , Sun73_Q16_4f.
All systems above were submitted before the Q16 deadline. Since there is an issue with the auto/manual selection, could you please select the 15 systems above for the Q16 contest? Many thanks once again!
Regards,
Sun73 -
Systems selection for the Q16 contest
Hi there,
The set of 15 selected systems displayed on page: https://quantiacs.com/personalpage/submissions/tab_in_contest
or on page: https://quantiacs.com/leaderboard
is not the same that I have selected (before October 31, 2021) on page: https://quantiacs.com/personalpage/submissions/tab_candidates
to be my final set of systems to compete on the Q16 contest (for example: Sun73_Q16_4f).Also, there are systems not listed anymore on the latter page (such as: Sun73_Q16_3a) which I have previously selected to compete on Q16.
Could you please check this (selection) issue? Many thanks!
Kind regards,
Sun73 -
Suggestions for the Q17 contest.
Hi there,
Since we're approaching the end of the submission phase for the Q16 contest, is it possible for us quants to already know a little bit about the upcoming competitions?
Will the Q17 contest be designed similarly to Q16? In other words, will Q17 be based only on crypto trading (or will it allow for futures trading too)? Only long-positions allowed (or short-positions too)?
I would suggest (if feasible) to put in place a new contest allowing to trade both cryptos and futures, besides trading long and short in any asset, but limiting the overall leverage of the portfolio. For example, adopting a 130/30 portfolio structure, which is a structure with a net long position, but permits leverage with long and short positions up to a maximum amount of leverage. In the case of a 130/30 portfolio, the leverage is 30%.
This broader and combined setup would allow us to design enhanced portfolios and might (potentially) increase the out-of-sample Sharpe ratios. Thank you!
Best regards,
Sun73 -
RE: How to getting start in Quantiacs
@qida1995 Hi qida1995, please take a look at the documentation available in the Quantiacs' website (https://quantiacs.com/documentation/en/), which is very useful not only for beginners but also for experienced users. Best of luck!
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RE: Quanticas Legacy webpage
@support The webpage is fine now. Thank you for the prompt response!
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Quanticas Legacy webpage
Hi there,
The Quantiacs Legacy webpage seems to be offline.
I've received the following message when trying to access it:
NET::ERR_CERT_DATE_INVALID
Subject: legacy.quantiacs.com
Issuer: R3
Expires on: 18 de jun. de 2021
Current date: 21 de jun. de 2021Is there an ongoing maintenance?
Many thanks!
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RE: Submission failure
@support Hi, the strategy Sun73_Q15_BTC_1f was accepted and the IS Sharpe looks fine. Could you please include it in the contest (since I submitted it before the deadline)? Many thanks again!
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RE: Submission failure
@support Thank you for the prompt response. I appreciate if you could reprocess the strategy Sun73_Q15_BTC_1f after solving this cache issue. You guys are the best!
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Submission failure
Hi there,
I submitted a strategy for crypto-futures, called Sun73_Q15_BTC_1f that was not accepted in the contest due to a Sharpe ratio lower than 1.
However, the in-sample Sharpe ratio obtained with the JupyterLab does not match the one displayed online. Both prints are shown below.
It seems that the online system almost does not trade Bitcoin after March 2017 (please see the first graph below), whereas the original system from JupyterLab trades Bitcoin on a regular basis since 2014 (as shown in last graph).
Could you please verify this mismatch?
Thanks a lot!!
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RE: backtest_ml()
@support Great! This route opens new possibilities in terms of model design. Thanks a lot!
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RE: Issue with the In-sample Sharpe
@support Thank you once again. You guys are the best!
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RE: Stocks data
@support Yes, I can load now the stocks data. Thank you once again!