@support
Cool, thanks very much! 👍

@anthony_m we patched with spot BTC data see answer: https://quantiacs.com/community/topic/6/btc-contest-start-date

@support I see, need to push them to submit then....

@captain-nidoran hi, all your strategies which will take part to the contest should be under the "In Contest" tab in the "Competition" section.

The migration "Candidates" -> "In Contest" was not immediate as we released minor improvements to the front-end side once the submission phase was over.

@anshul96go Sorry for the late answer, we missed it somehow. Yes, all submissions sent before deadline will be processed and accepted.

@support
Thanks.
You guys are the best!🏆

@rezhak21 Rules are defined at: https://quantiacs.com/contest and more details for the current contests (submission time till end of May) can be found at: https://quantiacs.com/contest/15

For Futures the in sample period starts on January 1st 2006, for the BTC Futures on January 1st, 2014

@nosaai Hello

Spyder should be run under conda environment

conda activate qntdev conda install spyder spyder

an alternative way is to clone the library from https://github.com/quantiacs/toolbox
and develop strategies inside qnt. But I recommend using the approach from the documentation.

@newbiequant96 Hi, the template is a "working code" still to be finalized and published among the templates in the account area, however the logic behind is strictly multi-pass and a conversion to single pass is not really so straightforward.

Dear @quani42,

Your submissions are in the queue and will be processed. Also, all submissions that are sent to the contest before the deadline will be eligible to take part in it.

Regards

@antinomy wow, thank you so much, this is awesome!

@support thanks, yes....

@support Thanks. Works fine now.

@gjhernandezp Hello, you can use them for local development. Unfortunately, we do not support yet external datafeeds after submission...it is on our to-do list.

@vg2001 Dear vg2001,
There were some problems with the servers, thank you for your patience.
Regards

@maxime Yes, of course, you can use our optimizer:

https://quantiacs.com/community/topic/29/optimizing-and-monitoring-a-trading-system-with-quantiacs

Be careful with optimization as it will lead to overfitting....

@support
Actually, I've write the weights to the output function.
螢幕擷取畫面 2024-04-24 235034.png
I think the reason might be that the data was out-of-date when the strategy received at the weekend. After the data update in the next day, it failed to pass the test.

@multi_byte-wildebeest Hello.

How to get the Sharpe Ratio is in the Quick Start template.
https://github.com/quantiacs/strategy-q20-nasdaq100-quick-start/blob/master/strategy.ipynb

import qnt.stats as qnstats def get_sharpe(market_data, weights): rr = qnstats.calc_relative_return(market_data, weights) sharpe = qnstats.calc_sharpe_ratio_annualized(rr).values[-1] return sharpe sharpe = get_sharpe(data, weights) # weights.sel(time=slice("2006-01-01",None))

or

import qnt.output as qnout qnout.check(weights, data, "stocks_nasdaq100")

or

stat = qnstats.calc_stat(data, weights) display(stat.to_pandas().tail())

or

import qnt.graph as qngraph statistics = qnstats.calc_stat(data, weights) display(statistics.to_pandas().tail()) performance = statistics.to_pandas()["equity"] qngraph.make_plot_filled(performance.index, performance, name="PnL (Equity)", type="log") display(statistics[-1:].sel(field=["sharpe_ratio"]).transpose().to_pandas()) qnstats.print_correlation(weights, data)

Please look at this post
https://quantiacs.com/community/topic/515/what-is-forward-looking-and-why-it-s-effective-badly-to-strategy/6?_=1711712434795

@support Thank you, yes, this is what I was looking for

Dear magenta.kabuto,

It appears to be a pandas version mismatch. You can try using different pandas version but it's not documented nor supported and our library could behave in an unexpected manner.