Posts made by buyers_are_back

@support Thank you for clarification!

@vyacheslav_b

This was the last page. If I set it to show 1000 rows per page I still only see results from 2023-05-15.

Did I miss something?

Hi,

I was playing around with strategies and found that the evaluation only starts from one year back? I remember previously it started from 2016-01-01. This kinda breaks my submission.

I'd love to know if this is intentional. Thanks

@vyacheslav_b Thank you! I'll have a look

Hi, I'd like to access to access both market and index data in strategy(). Would the following code work? It worked locally but when submitted the "checking" progress does not move at all.

# load data
data = qndata.stocks.load_ndx_data(min_date="2005-01-01")

def strategy(data):
    # get index data
    index_name = 'NDX'
    index_data = qndata.index.load_data(assets=[index_name], min_date='2005-01-01', forward_order=True)
    index_data = xr.align(index_data.sel(asset=index_name), data.isel(field=0), join='right')[0]
    ndx_values = index_data.values

I also tried a load_data function where I load both datasets and use load_data=load_data in qnbt.backtest() , but it quickly leads to a memory leak.

@support

Thank you, I noticed some changes on the rules so I have to reimplement the strategy anyway.

Hi I have a strategy in q20 but I want to reuse it in q21.

I reuploaded it as # 16543405 but it says

"The strategy has a high correlation with standard templates or your strategy from the past competition:
#15136749 money-launderer-q20-test01-b - 1.00 (IS null)"

This is the one I want to reuse. Would it be possible?

Best regards

@vyacheslav_b

Thanks for the reply. I know "market cap = #shares * price". The real issue is that #shares is not available for some stocks (e.g. META) so I have to rely on other data sources like yahoo finance.

@support

Do you have an update? Thanks!

@support I have 3 more questions regarding adjusted close.

(1) I have not checked the source code but I assume your backtest / online evaluation is based on split- and divident-adjusted close prices?

(2) In qnt.qndata.stocks only close is provided. I checked it is split-adjusted properly but not dividend-adjusted (see attached screenshot). Should we retroactively compute the adjusted close based on divs? It would be nice to have it in the data so we don't have to compute it every time.

(3) The split_cumprod column is always 1. What does it mean? It's probably not important.

@support Thank you, looking forward to your update.

@support Thank you for the information. Is there a way to get the market cap of each stock in your framework?

Furthermore what is your data source? I see for example Shares Outstanding / Implied Shares Outstanding of "NAS:ABNB" is available on yahoo finance. https://finance.yahoo.com/quote/ABNB/key-statistics

Hi,

could you please check the fundamental data? I want to access shares but for some stocks they are nan or 0. I just list the result of the last day (liquidity is checked). There are probably more in the data before.

Thanks!

import qnt.data.secgov_fundamental as fundamental
indicators_data = fundamental.load_indicators_for(market_data, indicator_names=['shares'])

for symbol in symbols:
    if market_data.sel(asset=symbol, field='is_liquid').values[-1] == 1:
        print(symbol, indicators_data.sel(asset=symbol, field='shares').values[-1])

NAS:META nan
NAS:LULU 56574615254.22
NAS:CDW 33285349512.0
NAS:MDB 25767646010.4
NAS:FANG 34372380817.46
NAS:GFS 28094353231.94
NAS:AVGO 573720125618.37
NAS:AMD 293136048694.22
NAS:CSX 72448787967.15999
NAS:LRCX 122063448150.0
NAS:MSFT 3131260131262.89
NAS:QCOM 183135600000.0
NAS:CDNS 84897732150.0
NAS:BIIB 31780231266.739998
NAS:INTU 177660674450.0
NAS:ASML 374502070437.11
NAS:TTWO 24769146877.199997
NAS:MAR 72319227139.16
NAS:NFLX 268631184172.16
NAS:MDLZ 97282992944.75
NAS:EXC 36793013731.020004
NAS:TSLA 545618293897.8
NAS:KDP 40670292503.1
NAS:WBA 17859797164.170002
NAS:CCEP 32580298037.100002
NAS:MRNA 40159714892.88
NAS:DASH nan
NAS:GEHC 41337329248.62
NAS:INTC 177787400000.0
NAS:ADI 94490338901.0
NAS:AMAT 167292873657.04
NAS:CTAS 63627808606.45
NAS:PEP 236126948757.80002
NAS:SBUX 103698198000.0
NAS:MNST 63000117666.9
NAS:VRTX 107249405203.2
NAS:SNPS 89193820979.90001
NAS:ORLY 66984680438.55
NAS:CPRT 54101457174.100006
NAS:DLTR 27929003604.03
NAS:TXN 151632812349.47998
NAS:AMZN 1827140369086.9001
NAS:BKNG 119802937241.46
NAS:DXCM 51724604035.56999
NAS:ON 31639413394.08
NAS:TMUS 190777094005.5
NAS:WBD 20737341514.5
NAS:VRSK 34046494056.96
NAS:CRWD nan
NAS:KHC 42786029487.490005
NAS:TTD nan
NAS:AEP 43841699622.2
NAS:MU 103767434720.0
NAS:PAYX 43552833819.04
NAS:ROST 49298041330.380005
NAS:ADSK 54802967111.75
NAS:ADP 100286301121.70999
NAS:IDXX 44404626994.02
NAS:AZN nan
NAS:ANSS 29792286582.59
NAS:CSGP 38431317106.1
NAS:CTSH 37163907688.8
NAS:CHTR 0.0
NAS:FTNT 51725867964.920006
NAS:PANW 90655398000.0
NAS:WDAY 0.0
NAS:NXPI 60621839878.799995
NAS:GOOGL nan
NAS:PDD nan
NAS:AMGN 145625242968.73
NAS:KLAC 92102230350.06
NAS:AAPL 2719006406480.0
NAS:EA 35546917294.560005
NAS:XEL 29106817021.1
NAS:ADBE 235577880000.00003
NAS:FAST 43609858258.549995
NAS:CSCO 198977053111.2
NAS:REGN 0.0
NAS:ODFL 46154568504.22
NAS:GILD 91452314560.56
NAS:ILMN 21159124000.0
NAS:ABNB nan
NAS:DDOG nan
NAS:PYPL 67530454850.64
NAS:TEAM nan

@dark-pidgeot said in Q20 contest results:

@support said in Q20 contest results:

That is also a good observation. In general, we would like a long-only system with low turnover to beat the Nasdaq index for example. But still, we see a lot of problems with hand-picking stocks and survivorship-bias affected systems.

if I understand correctly

if I initially select 10 stocks, and even if I have a good sharpe ratio, my strategy can make long and short positions. I could be disqualified

That's my understanding too. If you initially select 10 stocks, that already implies survivorship-bias, and is in fact "forward looking" because in for instance year 2010 you could not foresee which 10 stocks would still exist in the index in 2024.

Hi all,

I am wondering is there a way to get the weights of the constitutes of the index from the data? I need not only the current weights but also historical ones for the strategy.

To be honest I am not sure how the index value is calculated. I thought it was just a weighted sum, then I can just do a matrix inverse to get the weights. However Wikipedia gives some more complexed definition:

It is a modified capitalization-weighted index. The stocks' weights in the index are based on their market capitalizations, with certain rules capping the influence of the largest components.

I am not sure how this capping works and would appreciate it if someone has an idea. Thanks.

Best regards

Hi all,

I am doing some test for q21 now and found the data from qndata package is not up-to-date (today is Jan 26 but I can only get data till Jan 19). I am using the online environment.

Best regards

@support I just checked again and saw one of my strategies magically showed up in the "candidates" lol (which was previously in "filtered"). I was totally absent these days and wonder if something has changed? anyway happy that I made the first step.

Hi @support , thanks! gonna check the format again when I've got time

Hi all,

I'm fairly new just trying to learn. I wanted to submit some test strategy which was all good locally and in the online environment with sr>1 with multipass test. However when I submitted it seemed it was not even executed? Here are the logs (which is obscure tbh)

INFO: 2023-09-11T23:35:42Z: pass started: 15136753
INFO: 2023-09-11T23:35:44Z: nxt: 2006-01-03T00:00:00Z
INFO: 2023-09-11T23:35:44Z: next date: 2006-01-03T00:00:00Z
INFO: 2023-09-11T23:35:47Z: nxt: 2006-01-03T00:00:00Z
INFO: 2023-09-11T23:35:47Z: next date: 2006-01-03T00:00:00Z
INFO: 2023-09-12T00:15:45Z: stats received light=false
INFO: 2023-09-12T00:15:45Z: progress: 0.0
INFO: 2023-09-12T00:15:45Z: checking: first pass
INFO: 2023-09-12T00:15:45Z: filter passed: source exists
INFO: 2023-09-12T00:15:45Z: filter passed: output html exists
FAIL: 2023-09-12T00:15:45Z: filter failed: output missed
INFO: 2023-09-12T00:37:46Z: pass completed: 15136753

server log

statistics:
{"id":14162495,"series":[],"submission_id":"15136749","output_exists":false,"source_exists":true,"last_data":true,"non_liquid":null,"trades_only_btc":null,"output_dates_missed":false,"exposure_check_succeed":null,"ref_output":null,"html_gz":null,"correlated_list":[],"ref_date":1136073600000,"last_date":null,"light":false,"state":null}

Can you please help me know what was the issue?