Topics created by antinomy

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?

Dear @antinomy,

There has been some lag in processing, thanks for pointing it out.

Regards

@antinomy Hello, ok, we will do. Please note that for this contest we focus on Nasdaq-100 stock market data. The other market data set you have access to is an "experimental" set we usded for testing. Please use nasdaq-100 data.

Support for fundamental data from secgov is experimental also.

@antinomy Hello, sorry for delay again. We found a problem with the data provider, sorry.

@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

@jeppe_and Ok, thanks for the quick reply!

@antinomy Hello, sorry for the delay in the answer, the problem has been fixed in the meanwhile. If correlations are too high, you will get a warning. Note that correlations will be checked against template code and submissions to past contests of the same kind (which are not present currently as this is the 1st crypto long-only contest we run).

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 It's working now, thanks!

@support
oh I see now what you mean.
15 strategies PER USER are selected.
At first, I thought you were only going to select 15 strategies total for all users.
Thanks.

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