@stefanm said in How to get stocks in SP500 index at a given time:

is_liquid_spec = is_liquid.sel(time=date)
members_spec = is_liquid_spec.coords["asset"][is_liquid_spec == 1.0].asset.values

Thanks for the reply! I have some further questions.

Is it the case that the dataset does not contain all symbols in the index? If I plot the number of stocks it started from around 350 then increases to 500.

c80c9110-826a-4349-8125-f3641fad0e09-image.png

There are some symbols and their counterparts with suffix ~1, for instance NAS:FISV and NAS:FISV~1, what does it mean?

f16737ac-577b-44ea-b698-fdd1164f4dd9-image.png

@copper-herring ok, thanks for reporting, we will

@rubber-metapod We are not running any futures contest right now.

Hi, the progress depends on many submissions are in the queue.

@black-magmar Yes.

@optical-turtle The Q24 entries will be updated soon.

@vg2001 It has been fixed, sorry

And what if a strategy uses the following rules to select assets to trade:

the primary exchange is NAS the sector is not finance has price data for at least the previous 3 months has an average daily trading volume of at least 200 k based on the previous 3 months belongs to the top 100 of the thus far selected assets in terms of market capitalization

Would you say any of these rules violate the contest rules?

Because these are the selection criteria for the N100 constituents. The only difference in my strategy is that I'm using qnt.data.stocks_load_ndx_data.sel(field='is_liquid') instead.
Sure, the first of the rules above manually selects the exchange and the second one manually excludes a sector. But still none of these manually select assets and neither does the filter is_liquid from another dataset.

Also, lets take a look why you prohibited manual asset selection in the first place. Wasn't this to avoid lookahead bias? And isn't this also the reason for the existence of the field is_liquid in any of your datasets? Are you saying that the exact field you introduced to avoid lookahead bias is now the reason you disqualify a strategy because of lookahead bias just because it's from a dataset other than the one for the contest?

@svyable Hi,
sorry for late answer, no we don't provide that option, but we will think about adding it in future.

@wool-hypno Which codes?

@vyacheslav_b Forgive me for the late response, I have not been on the platform. Thank you for your assistance. I can report that I have had no joy in using the strategy builder. I followed what you said and went on to download Chrome and still no joy. The strategy did not even appear under My Strategies. I guess I will just have develop the strategy on my own IDE and upload. Anyway, thanks for assistance, most appreciated.
Cheers

@granite-ditto Hi, the first source of information is the documentation at:

https://quantiacs.com/documentation/en/

In addition, we recommend you to check the template notebook available at:

https://github.com/quantiacs/Q24-crypto-guide/blob/master/strategy.ipynb

Quantiacs provides a built-in filter for selecting the top crypto assets according to the "liquid" field as follows:

is_liquid = data.sel(field='is_liquid')

@green-flareon Thanks. The live phase of the Q23 is running. Quants can join any contest during the submission phase. Q24 is on.

@support thanks!!!

@tim-hub Hi,

the template processing has not finished yet, it is on day by day processing (currently beginning of 2023). The reason of the error is that helper function tries to compare stat after 2022-08-31, which is not possible if processing date is 2020-01-01 for example. It doesn't affect the output (weights), and now you don't see this error because processing date is after 2022-08-31. If you had cloned the template and run it, the error would not have occurred.

@lookman The answer we sent to your e-mail address bounced back.

@sun-73 @RoyPalo, Hi,

Q23 Leaderboard was updated several days ago, all eligible submissions are there now, sorry for late notice. Please let us know if you find any submission that is missing.