Topics created by buyers_are_back

@buyers_are_back Hi,

You can use is_liquid field from spx dataset to filter out weights allocated to not members of S&P500 at given point in time:

from qnt.data import stocks_load_spx_data spx_data = stocks_load_spx_data(min_date="2006-01-01") is_liquid = spx_data.sel(field="is_liquid") final_weights = your_weights * is_liquid ### weights for given date (weights_spec) date = "2026-02-24" weights_spec = final_weights.sel(time=date)

The number 842 represents total number of assets that have been members of S&P500 index at some point in time (from given dataset), and 658 shows number of assets that are still active on market (have OHLC prices), but only ~500 are index constituents in that point in time.

To get the list of index members on certain date, just filter is_liquid field:

### liquidity field values for given date is_liquid_spec = is_liquid.sel(time=date) members_spec = is_liquid_spec.coords["asset"][is_liquid_spec == 1.0].asset.values

@commanderangle Dear commanderangle,

If you use ML in your strategy but not select that option we can't guarantee for how your strategy will be evaluated and it could be filtered out.

Regards

@buyers_are_back Hello.
Here is a new example of stock prediction using index data.
I recommend using the single-pass version.
https://quantiacs.com/documentation/en/data/indexes.html

@support

Thank you, I noticed some changes on the rules so I have to reimplement the strategy anyway.

@buyers_are_back Hi,
the update was related to market_capitalization field availability and correctness, as vyacheslav_b described. Unfortunately, at the moment we cannot provide missing fundamental data, like number of ordinary shares, for some stocks (e.g. META). We are going to investigate potential new data sources in order to improve our datasets.
Regards,

@buyers_are_back Hi, more info of course can be found here:

https://indexes.nasdaqomx.com/docs/Nasdaq_Index_Weight_Calculations.pdf

and here:

https://indexes.nasdaq.com/docs/Methodology_NDX.pdf

Pages 4 and 5 give more details on the weights and caps.

For example, no security weight may exceed 14% of the index value.

@buyers_are_back Hi, yes, that is ok, data will be updated in the next days.

@buyers_are_back We reprocessed the submission, it is formally correct and passes all the filters. Sorry for the issue, evidently on our side.