Exercises: Universe Selection

Lecture Link

This exercise notebook refers to this lecture. Please use the lecture for explanations and sample code.

https://www.quantopian.com/lectures#Universe-Selection

Part of the Quantopian Lecture Series:



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import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from quantopian.pipeline.classifiers.morningstar import Sector
from quantopian.pipeline import Pipeline
from quantopian.pipeline.data.builtin import USEquityPricing
from quantopian.pipeline.filters import QTradableStocksUS, AtLeastN
from quantopian.research import run_pipeline
from quantopian.pipeline.data import morningstar
from quantopian.pipeline.factors import CustomFactor, AverageDollarVolume

Helper Functions



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def calculate_daily_turnover(unstacked):
    return (unstacked
            .diff()        # Get True/False showing where values changed from previous day.
            .iloc[1:]      # Drop first row, which is meaningless after diff().
            .astype(bool)  # diff() coerces from bool -> object :(.  Undo that.
            .groupby(axis=1, level=0)  
            .sum())

Exercise 1: Examining the QTradableStocksUS Universe

a. Initializing the Universe

Set the QTradableStocksUS as your universe by using the QTradableStocksUS() function.



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# Your code goes here

b. Finding Asset Composition

Use the pipeline API with the QTradableStocksUS as a screen to find and print the list of equities included in the QTradableStocksUS on 2016-07-01.



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# Your code goes here

c. Sector Exposure

Use the pipeline API with the QtradableStocksUS as a screen to find and print the sector composition of the universe on 2016-07-01.



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SECTOR_CODE_NAMES = {
    Sector.BASIC_MATERIALS: 'Basic Materials',
    Sector.CONSUMER_CYCLICAL: 'Consumer Cyclical',
    Sector.FINANCIAL_SERVICES: 'Financial Services',
    Sector.REAL_ESTATE: 'Real Estate',
    Sector.CONSUMER_DEFENSIVE: 'Consumer Defensive',
    Sector.HEALTHCARE: 'Healthcare',
    Sector.UTILITIES: 'Utilities',
    Sector.COMMUNICATION_SERVICES: 'Communication Services',
    Sector.ENERGY: 'Energy',
    Sector.INDUSTRIALS: 'Industrials',
    Sector.TECHNOLOGY: 'Technology',
    -1 : 'Misc'
}

# Your code goes here

d. Turnover Rate

Use the pipeline API with the QtradableStocksUS as a screen and the calculate_daily_turnover helper function to find and plot the turnover of the universe during 2016.



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# Your code goes here

Exercise 2: Examining Tradability

a. NetIncome 1500

Create a universe consisting of the top 1500 equities by net income then find and print the list of equities included in the universe on 2016-07-01.



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# Your code goes here

b. Measuring Tradability

Find the average 200 day average dollar volume of the NetIncome 1500 universe using the AverageDollarVolume built in factor and compare to that of the QTradableStocksUS.



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# Your code goes here

Exercise 3: Sector Balance

a. Dividend 1500

Create a universe consisting of the top 1500 equities by dividend yield then find and print the list of equities included in the this universe on 2016-07-01.



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# Your code goes here

b. Dividend 1500 Sector Composition

Find and print the sector composition of the universe on 2016-07-01.



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SECTOR_CODE_NAMES = {
    Sector.BASIC_MATERIALS: 'Basic Materials',
    Sector.CONSUMER_CYCLICAL: 'Consumer Cyclical',
    Sector.FINANCIAL_SERVICES: 'Financial Services',
    Sector.REAL_ESTATE: 'Real Estate',
    Sector.CONSUMER_DEFENSIVE: 'Consumer Defensive',
    Sector.HEALTHCARE: 'Healthcare',
    Sector.UTILITIES: 'Utilities',
    Sector.COMMUNICATION_SERVICES: 'Communication Services',
    Sector.ENERGY: 'Energy',
    Sector.INDUSTRIALS: 'Industrials',
    Sector.TECHNOLOGY: 'Technology',
    -1 : 'Misc'
}

# Your code goes here

Exercise 4: Turnover Smoothing

a. PE 1500

Create a universe consisting of the top 1500 equities by price to earnings ratio then find and print the list of equities included in the this universe on 2016-07-01.



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# Your code goes here

b. PE 1500 Turnover

Use the calculate_daily_turnover helper function to find and plot the turnover of the PE 1500 universe during 2016. Compare the average to that of the QTradableStocksUS.



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# Your code goes here

c. Smoothing the PE 1500

Using AtLeastN, apply a smoothing function to the PE 1500 to reduce turnover noise and find the new mean turnover.



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# Your code goes here

Congratulations on completing the Universe Selection exercises!

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