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Looking to create stock screener

Hello Q community,

I am new to python & quantopian, although i have been reading around & must say i am impressed by the diversity of ideas around here. Keep it up!

Currently i am doing some manual trading based on mostly technical factors. Sometimes i feel a bit overwhelemed when it comes to futures/ stocks to know what names i should be keeping an eye on & frankly i don't enjoy (price) screen time much. What i am looking to create is a simple screener which will list the tickers of futures/ stocks that fulfill certain criteria. I have a feeling this would probably work using the Pipeline.

For example how would i go about attaining a list of tickers which fulfil the following criteria:
1. RSI of over 50 for the last week
2. 7 day fast moving average > 30 day slow MA

Any ideas/tips or things to read would be massively appreciated!

Thanks in advance,

6 responses

Hi Florian,

Feel free to check out this example notebook I wrote for you that demonstrates proper usage of a pipeline screen. It uses the criteria you mentioned and outputs a list of securities from January-August 2017.
Reading through the pipeline tutorial which incorporates information on factors, filters, and screens can really help as well! Let me know if you have any other questions.


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Hi Robert,

I stumbled upon the thread based on searching how to build a screener in Quantopian. I am a complete novice but your code covers a lot of what I actually need. Thank you so much for that!

I wanted to ask you whether I could import the OHLC4 ((open + high + low + close)/4)) prices somehow from library because from what I understood the USEquityPricing is based only on the close prices?

And if I cannot do that, is the data_handle with get_pricing the only way to get the OHLC4 that I need? If so, can I apply that to the whole universe of Quantopian for the purposes of the screener?

Thank you!

Thank you!


Try something like this:

from quantopian.pipeline.filters import Q500US, QTradableStocksUS  
from import USEquityPricing  
from quantopian.research import run_pipeline  
from quantopian.pipeline import Pipeline  
def make_pipeline():

    O =  
    H = USEquityPricing.high.latest  
    L = USEquityPricing.low.latest  
    C =

    OHLC4 = ( O + H + L + C )/ 4     

    pipe = Pipeline( columns={'OHLC4': OHLC4}, screen = Q500US())  
    return pipe  
result = run_pipeline(make_pipeline(), '2019-05-24', '2019-05-24')  


2019-05-24 00:00:00+00:00

Equity(2 [ARNC]) 22.116750
Equity(24 [AAPL]) 179.487500
Equity(53 [ABMD]) 263.202500
Equity(62 [ABT]) 75.934750
Equity(67 [ADSK]) 170.225000
Equity(76 [TAP]) 58.847500
Equity(114 [ADBE]) 276.672500
Equity(122 [ADI]) 99.280000
Equity(128 [ADM]) 39.298750

Awesome, Vlad.

I tried to run the screener but did not manage to and do not know why. I would be extremely grateful if you have a look at it (in the attached notebook).

The idea is supersimple - the screener returns stocks with bolinger band width < 0.001, where

// basis of bolinger band = sma(OHLC4,5)

// upper band = basis + 2*basis.std() // just saw that in the notebook I have left sma_5 instead of basis but that does not solve the problem

// lower band = basis - 2*basis.std() // just saw that in the notebook I have left sma_5 instead of basis but that does not solve the problem

// bolinger band width = (upper band - lower band) / basis

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For use OHLC4 that way you need to create a custom factor.

Thanks! I think I just managed to do that but still getting errors.

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