Looking to create stock screener

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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,
Florian

6 responses

Robert Petteruti

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.

Thanks,
Robert

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Mihail Bukov

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 quantopian.pipeline.data.builtin 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!

Vladimir

Mihail,

Try something like this:

from quantopian.pipeline.filters import Q500US, QTradableStocksUS  
from quantopian.pipeline.data.builtin import USEquityPricing  
from quantopian.research import run_pipeline  
from quantopian.pipeline import Pipeline

def make_pipeline():

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

    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')

OHLC4

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

Mihail Bukov

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

Vladimir

Mihail,

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

Mihail Bukov

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

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