Another issue is that the toolbox relies on a NumPy version older than 2.0, which is incompatible with the current environment in Colab: https://colab.research.google.com/drive/1N0xxcVUdZr3m179XeS_OyK1y_d90M0EW

@support Thx for ur reply

Dear @angusslq,

The ranking is calculated based on contest sharpe ratio only. The situation that you saw at that time was only temporary because at that point the calculations for new day were ongoing, so some strategies were processed before others, and their contest sharpe was updated, but the ranking is only updated after every single strategy from that contest has been processed and updated.

Regards

Dear @silverstar1003,

There was a temporary problem with our servers which has been resolved, and your strategy should be calculated soon.

Regards

Dear @angusslq,

Once the competition ends its live period (currently 4 months for Q22), the prizes are given. That means that at the end of those 4 months we sort all strategies and only the top 7 by sharpe ratio are eligible for prize and get allocation: 1st place 1M, second place 500k etc. and this cannot be changed afterwards. The prizes are not given on the daily basis and certainly not during the contest live period. You can find more info in the contest rules page on our website.

For your second question, we assume risk-free rate to be zero. You can find additional information about how we use sharpe ratio here.

Regards

Dear @angusslq,

Allocations are set at the end of the contest, and they take into account the strategies ranking at that time. We update the rankings as we process the participating strategies with the new available data, which happens 5 times a week for 5 working days. The allocations that you refer are probably in the systems page and they take into account the current ranking in the contest but that doesn't mean anything until the contest ends and prizes are given.

Regards

Dear @svyable,

If you use our backtest function, the liquidity filter will applied automatically, you can just ignore that warning.
On the other hand, if you decide to use single-pass strategy option you should apply that filter manually or just use clean function that has that option included.

Regards

@angusslq Hi. Try cloning the template or restarting JupyterLab. The error was fixed in the new version of the qnt library.

Dear @angusslq

Yes, there is a large queue currently as we are nearing the end of the submission period for the following contest. All submissions submitted before the deadline will be eligible for participating in the contest, including yours.

Regards

@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