@rezhak21 Hi, the lookback period used in the builtin backtest function is expressed in calendar days, while indicators are computed in trading days. As a rule of thumb, add 2 more days every 5 trading days to take weekends into account.

@anshul96go Just to give you more context: when you submit a strategy to the contest, the strategy is queued. Depending on the current load, the processing can take some time. If you submit when many other users are submitting, then processing will take more time.

Moreover, when you develop on the notebook, processing is instantaneous because no particular checks are done (well, it depends on the complexity of the strategy). You just run your code and get the result.

If you code it using a single-pass approach the processing will be very fast. If you use our backtesting function (which prevents forward looking), processing will be a bit slower.

When you submit the strategy, however, several sanity checks are run on the strategy. The system checks if allocations are defined for all datapoints, if your strategy is performing looking forward operations, if it stops producing the output before current day, it computes the Sharpe ratio and other statistical indicators, and moreover it computes the correlation of your strategy with all examples we provide, as we do not allow an example to win a contest...so the processing is slower.

For quick development, please refer to the results you get in the notebook, submit the strategy and then it will be ok.

@spancham Hi, yes, understood. The 10% rule applies to the contest entries and to the prizes (1M USD invested, 500k USD invested, etc, see https://quantiacs.com/contest).

However, strategies can get funded by investors even if they do not win contests. In this case 2 schemes are possible:

1. a fixed management fee, i.e. the quant earns a monthly fixed fee.

2. a performance fee, i.e. the quant earns a monthly performance fee.

It is already happening with quants who submitted systems which developed a long track record. In both cases, there is a mutual agreement between Quantiacs, the investor and the quant on the level of the fees.

Hi.

When you submit the strategy, the evaluator checks the strategy using data isolation and runs the notebook each day during the in-sample period.

This is necessary because there is a very common issue - looking forward.

The evaluator can parallelize this process, but anyway it takes more time.

@spancham Hello, the management fee is order of magnitude of a performance fee. Imagine that you get 1m USD allocated, the system has 10% volatility, a Sharpe ratio of 1 for 1 year, and you make 10% in performance fees per year. Instead of choosing a performance fee (which could be zero in bad months) you could choose at the very beginning a fixed fee. In this case, it would be order of 1k USD per month.

The length of the track record depends on the strategy and many factors, let us say no less than some months, longer time for a larger capacity.

@sheikh Hi Sheikh, we are busy preparing the new contest.

The algorithm you mention actually has a lot of flat phases also in sample, why do you think the problem is an external library?

If you run the system in a notebook and plot the equity chart, do you get the same result or not?

Thank you

@spancham The performance fee is a yearly performance fee as per industry standard. If system makes 100k USD in profits per year (1 Sharpe, volatility 10%, 1M USD invested), then the quant will receive 10k USD per year.

@spancham Currently there is no investor tab, it is part of our roadmap and we are working on that. At the moment we are focusing on improving the software and the data, the new version of Quantiacs is up and running since 3 months only. As soon as the fund is up, we will announce it.

We published a summary of the past 14 contests on the home page, with quant names and allocations made by Quantiacs (own money). Quantiacs has private agreements with investors allocating their money to selected systems, and with quants who developed systems and are getting fees.

If you/your family have enough capital and want to invest in your own algo and bear the risk of downside losses, well, you will be able to do it with Quantiacs (once we start the fund) if you want.

@magenta-grimer yes, correct, and it does not have to win a contest, we monitor all submitted systems and will contact the quants who wrote interesting systems.

But if you implemented a stateful strategy, the evaluator can't parallelize the checking. It will take much more time. You can see the time of the one-day evaluation in the log and estimate how long it will take.

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 @captain-prairie_dog,

Yes, that's right. We will announce next contest soon, but roughly, the deadline period will be a couple of months away, so the users get enough time to develop their strategies.

Regards

@dark-pidgeot yes

Dear @dark-pidgeot,

There are two ways of how you can select your strategies to participate in the contest.
The first way is to use our auto-select feature. If it's turned on, then the top 15 strategies by performance will be automatically selected for participation.
The second way is to disable auto-select feature and use manual selection, after which you will have to hand-pick the strategies that you would like to participate.

It appears that you used manual selection at that time but didn't select any strategy manually. After careful review we concluded that you didn't break any other rule and your strategies are eligible for participation, and because this is a mistake users often make, we will add your submissions to the Q22 contest.

Regards

Dear @captain-prairie_dog,

Each contest has it's deadline period, for Q22 it was 31st of January. The live period is 4 months during which strategies will be evaluated and at the end of that period the prizes will be given to the winners. So to answer your question, yes, user needs to backtest and submit the strategy before the submission deadline and pass the filters (sharpe ratio, liquidity etc.) in order to participate in the contest. After that, all participating strategies are evaluated on real data in the following contest period (usually 4 months) and the score is calculated as a sharpe ratio. You can check what it is and how is it calculated in the documentation page on our website.
Hopefully this will clear up the confusion, and if you have any further questions, please feel free to ask.

Best 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

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

@auxiliary-snail Hi,

unfortunately, this is not allowed and in accordance with the rules. Using hard-coded time periods in which trading algorithm will work differently, is not a quantitative method (just like manual asset selection, e.g. "trade only Apple or Microsoft"). We still haven't implemented a mechanism for automatic recognition of such behaviors in trading strategies, and even though a strategy could be successfully submitted, it will not be eligible for prize winning.
What we are searching for, is well performing strategy over entire in_sample period (SR>0.7), robust to all market movements 2006-2025, so we can expect it will perform well in future, too.

Dear @lookman,
can you please share part of code where secgov_load_indicators() functions is called and throws error (with full exception)? Keep in mind that this function is actually load_indicators() function from secgov_indicators.py,and can be imported and used as:

from qnt.data import secgov_load_indicators

or

from qnt.data.secgov_indicators import load_indicators

Kind regards