@support Hi again guys, I think the leaderboard is not updating again 😳

@support Thanks for your respond. Now I understand the cause and fixed it

@eddiee Dear eddiee, no, please, for the moment do not resubmit. The timed out submissions are stored as timed out submissions and we can reprocess them. In case you need resubmission, we will let you know.

@support Thanks for the detailed answer, that seems to be it, here is the final code:

import xarray as xr import qnt.stats as qns import qnt.output as qnout import qnt.data as qndata # single-stock trading data = qndata.futures.load_data(min_date="2005-01-01", assets=["F_ES"]) # attempting an optimal (unrealistic) long-only strategy # by looking at future prices, and investing only if there will be profit next_price_open = data.sel(field="open").shift(time=-1) next2_price_open = data.sel(field="open").shift(time=-2) weights = xr.where(next_price_open < next2_price_open, 1.0, 0.0) # sell short when optimal: # weights = xr.where(next_price_open > next2_price_open, -1.0, weights) weights = qnout.clean(weights, data) qnout.check(weights, data) qnout.write(weights) stats = qns.calc_stat( data, weights, # ignoring slippage for simplicity slippage_factor=0, roll_slippage_factor=0) stats.loc[:, "equity"].plot.step();

@support Great help! Thank you so much!

@eddiee

Hello.

This code looks to the future.
It is needed to train the model.
Pay attention to the name of the variable.

@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.

@xiaolan Ok, but please note that you can work all the time with xarray, the documentation is very good:

http://xarray.pydata.org/en/stable/

@yonasbo Hi, sorry for delay, we will start soon a new contest, in the next 2 weeks

@theflyingdutchman Yes, we are integrating new data sources for a new asset class, once we are done (next week) the data and leaderboard updates will start again.

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

@lookman Hello. Try cloning your strategy and running it again. It should work correctly with the new version of the qnt library.

import qnt.data as qndata import qnt.data.secgov_fundamental as fundamental market_data = qndata.stocks.load_spx_data(min_date="2005-01-01") indicators_data = fundamental.load_indicators_for(market_data, indicator_names=['roe']) display(indicators_data.sel(field="roe").to_pandas().tail(2)) display(indicators_data.sel(asset='NAS:AAPL').to_pandas().tail(2)) display(indicators_data.sel(asset=['NAS:AAPL']).sel(field="roe").to_pandas().tail(2))

https://quantiacs.com/documentation/en/data/fundamental.html

@algotime Hello, on 1st November allocations will start, you will receive a mail soon today!

@omohyoid Dear omohyoid,

Yes, that's right. After submitting your strategy shouldn't override environment variables.

Regards

@vyacheslav_b Thank you so much.

I have one more question for you to answer. I ran the precheck and the result was nan value the first time, but I set the min_date to 2005 - 01 - 01. I would like to ask, why is there a nan value problem? Is it because the ticker I chose had some companies that weren't listed at that time? My strategy id code is # 16767242. Thank you so much

Screenshot 2024-04-09 173002.png
Screenshot 2024-04-09 173012.png

@support Thank you !

@gjhernandezp yes, correct, 2/(n+1), sorry for the typo, thanks for correcting

@eddiee

This code works for me. I can give you ideas on what to try.

Update the qnt library or reinstall.

If it doesn't help, clone the repository

https://github.com/quantiacs/toolbox

git clone https://github.com/quantiacs/toolbox.git

run
qnt/examples/005-01-optimizer.py
and other examples.

You may need to specify API_KEY

You might be able to see exactly where the error occurs in the code.
And you can modify the library code by adding logging for optimize_strategy

@gjhernandezp Thank you for sharing your solution!

@illustrious-felice Hi, just insist and test other ideas, it is not easy but you will manage!