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Fundamental Historical Data

I'm trying to return the a historical set of some number of days of historical data. I only need the data for the filtered set from pipeline. Here is an algo that prints out the type of data I want from pipeline and how I ideally would like the data like the history data comes back.

Has anyone had success returning a number of days worth of fundamental data for a given set of equities? Am I missing something really simple?

Thanks for the help!

John

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Backtest from to with initial capital
Total Returns
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Alpha
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Beta
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Sharpe
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Sortino
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Max Drawdown
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Benchmark Returns
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Volatility
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Returns 1 Month 3 Month 6 Month 12 Month
Alpha 1 Month 3 Month 6 Month 12 Month
Beta 1 Month 3 Month 6 Month 12 Month
Sharpe 1 Month 3 Month 6 Month 12 Month
Sortino 1 Month 3 Month 6 Month 12 Month
Volatility 1 Month 3 Month 6 Month 12 Month
Max Drawdown 1 Month 3 Month 6 Month 12 Month
from quantopian.algorithm import attach_pipeline, pipeline_output
from quantopian.pipeline import Pipeline
from quantopian.pipeline.factors import CustomFactor, AverageDollarVolume
from quantopian.pipeline.data import morningstar

import pandas as pd
import numpy as np

class PeRatio(CustomFactor):
    inputs = [morningstar.valuation_ratios.pe_ratio]
    window_length = 10
    
    def compute(self, today, assets, out, pe_ratio):
        out[:] = pe_ratio[-1]
            
class Roe(CustomFactor):
    
    inputs = [morningstar.operation_ratios.roe]
    window_length = 10
    
    def compute(self, today, assets, out, roe):       
        out[:] = roe[-1]
            

def before_trading_start(context, data):
    results = pipeline_output('factors').dropna()
    
    #either want the peRatio and quality to return a set of the window length
    print results
    
    #ideally something with a date key like data.history is set up
    print data.history(results.index, 'high', 10, '1d')    
    
def initialize(context):
    pipe = Pipeline()
    pipe = attach_pipeline(pipe, name='factors')
        
    roe = Roe()
    pipe.add(roe, "roe")
    
    peRatio = PeRatio()
    pipe.add(peRatio, "peRatio")
    
    dollar_volume = AverageDollarVolume(window_length=20)    
    pipe.set_screen(dollar_volume.rank(ascending=False) < 5)
    
There was a runtime error.
2 responses

So pipeline allows you to get historical fundamental data through the window_length argument, the idea being that you would do what ever calculations on that historical data within the custom factor, and surfacing the final value of your computations through the pipeline_output.

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James,

Yeah but I wouldn't want to do machine learning on every stock in the universe, it would be too costly. I think it would work to first filter but even so the amount of compute is still restricted to before the trading starts. Thats why I was trying to return a set of historical values that could then be used in the first couple minutes of the day. Is there no possible way of retrieving a historical set of fundamental data outside of pipeline?

Thanks for the response.

John