Posts made by Sun-73

Hi @support,

The JupyterLab run of new strategies for Q23 contest is giving the message below regarding max exposure:

Check max exposure for index stocks (nasdaq100, s&p500)…
ERROR! The max exposure is too high.
Max exposure: [0.10520976 0.10536531 0.1051576 ... 0.09200489 0.09211786 0.09212628] Hard limit: 0.1
Use qnt.output.cut_big_positions() or normalize_by_max_exposure() to fix.

However, the strategy already cuts the abs(weight) if above 0.10.

Besides, module 'qnt.output' has no attribute 'cut_big_positions'.

Thanks!

Hi @support, thank you! The box is now working fine!

I have a simple suggestion regarding the charts created for each strategy:

Besides the equity curve (strategy, SPX and Nasdaq100), Logarithmic scale, Long/Short, Underwater, and Bias, it would be nice to see an additonal chart (with two lines) showing the number of assets in each day that have a positive weight (long position), as well as the number of assets in each day that have a negative weight (short position).

This will help us developing the strategies, since we can better track the outcomes generated by different algorithms being constructed.

Also, this can help you identify asset hand-picking with buy-and-hold positions.

Thanks!

Hi @support, the box “Show only my results” in the Q23 Global Leaderboard is not working. Thanks!

Hi @support, everything is all right now. Thank you!

Hi @support, last week, a set of previously submitted (and accepted) strategies were moved from the Q22 competition (from the “Candidates” area, in the website, to the “Filtered” area).

Some strategies were submitted more recently while others several months ago.

In the “Filtered” area, there is no comment attached to each strategy to justify the mentioned exclusion from Q22.

The strategies are the following: Sun73_Q22_6a, Sun73_Q22_5a_v3, Sun73_Q22_4a, Sun73_Q22_2e, Sun73_Q22_2d, Sun73_Q22_2c

Could you please check this issue? I noticed that it also happened to other users as well.

Many thanks!

Hi @angusslq, the same thing happened to me (ex: with my strategy Sun73_Q22_6a).

Hi @support, can you please check this issue for us? Thank you!

Hi @support, thank you once again!

Hi @support, regarding the upcoming Q22 contest on S&P500 (long-short), a couple of questions:

• How can one upload stocks data for S&P500? For NASDAQ-100, we use qndata.stocks_load_ndx_data(tail=period)

• Is there a maximum limit of stocks to be traded on a given day (or, in principle, one can use all available liquid stocks for that day)?

• Is there a limit for the weights? In Q21 contest, the limit was a maximum of 10% of capital to be invested in a given stock in a given day.

Thank you!

@support Thank you!

Hi @support,

System Sun73_Q21_6aaa #17158009 is not being updated in the Q21 leaderboard. The "Date End" for this system seems to be stucked at 2024-06-12.

Could you please check it?

Many thanks!

Hi @support,

When do you expect to start the Q22 contest?

Any information on the asset class (NASDAQ-100, Futures...) of this new contest? Long-short or long-only?

Thanks!

Hi @support, my strategies still do not appear in the Q21 Leaderboard.

Also, I submitted 6 new systems on 2024-06-29 that are still 0% checking. Could you please verify if everthing is all right?

Thanks a lot!

@support Thank you very much once again!

Hi @support,

(1) Regarding rejection of system “Sun73_Q21_8e”, indeed the message in the website says that: “The strategy has a high correlation with standard templates or your strategy from the past competition: #9645444 - 0.91 (IS )”.

Could you please inform which system is #9645444? I could not identify it in my systems submitted to past competitions.

(2) In respect to the missing “sell weights” it seems that current Q21 Leaderboards is somehow “killing” the negative weights. For instance, system “Sun73_Q21_8e” in Quantiacs website shows only positive weights, whereas when I run this system in JupyterLab I got both positive and negative weights (as designed).

Please see the comparison below (since 2022) between the outputs from the website and JupyterLab.

Could you please check what is going on? I believe this issue is happening to other users as well.

Thank you once again!

Hi @support, the system “Sun73_Q21_8e” submitted to Q21 was recently rejected, possibly due to its in-sample Sharpe ratio (0.89). However, in the Q21 competition updates, you informed us that the required Sharpe ratio for contest participation has been adjusted to 0.70.

Could you please check? If the in-sample Sharpe was not the reason for rejection, could you please inform what was the reason?

Other question: I noticed that both Q20 and Q21 Leaderbords have been modified in recent days. For instance, many systems of mine that trade in a buy/sell approach are now only considering the buy weights. Could you please clarify?

Thank you!

@support Thank you once again!

Hi @support, two quick questions:

(1) Does the limit of 10% for the weight of each asset apply for both (buy and/or sell) positions?

In other words, a vector of weights (0.10, 0.02, -0.10, -0.05...) is OK, but the vector (0.50, 0.20, 0.01, -0.30, -0.05...) will be modified to (0.10, 0.10, 0.01, -0.10, -0.05...)?

(2) This "10% rule" will already be in place during the Live Contest Evaluation Period (July 1, 2024 - October 31, 2024), right?

I asked this question because the current "Out-of-sample Sharpe" column displayed in the "Q21 Global Leaderboard" seems to not include the "10% rule", since some leading systems show high Sharpe ratios using only a few assets, and apparently investing all available capital in them (instead of limiting the individual positions to 10% of capital).

Many thanks again!

Hi @support, a suggestion to reduce the overall processing time is to adjust the "Running Time" rule: instead of 5 minutes of time per each point in time, I would limit it to 1 minute per observation.

Besides reducing submission processing time for ALL users, it would stimulate us to produce parsimonious systems (more focused on results), instead of building huge models with tons of data that generate a severe computational burden without effective gains.

This would also guide users to shift the discussion from "big data" to "good data", in the sense that finding high-quality data is much more important than the quantity of data itself (Ng, A., 2015. Advice for applying machine learning).

Hi @support, could you please check if submission of system "Sun73_Q21_6e" is ok? I submitted it 8 days ago and "checking progress" is still at 0%. Long queue? Many thanks!

@support Hi, is the Q21 Global Leaderboard currently considering the limit of 10% of capital per asset?

Since this rule is binding for all systems submitted to the Q21 contest, it would be interesting to also see the current sharpe ratios when the rule is in place (to better simulate the live phase and help us adapt and optimize the systems to this new rule).

Maybe just adding an extra column (such as "Out-of-Sample Sharpe, lim. 10%") would be enough.

Thanks once again!