Q500US and Q1500US Market Cap Breakdown¶
In [1]:
from quantopian.pipeline import Pipeline
from quantopian.pipeline.data.builtin import USEquityPricing
from quantopian.research import run_pipeline
from quantopian.pipeline.filters.morningstar import Q500US, Q1500US
from quantopian.pipeline.data import morningstar
pipe = Pipeline(
columns={
'Market Cap': morningstar.valuation.market_cap.latest,
'Q500US' : Q500US(),
'Q1500US' : Q1500US(),
}
)
In [2]:
results = run_pipeline(pipe, '2016-01-01', '2016-01-01')
In [3]:
Q500US_results = results[results['Q500US'] == True]
Q1500US_results = results[results['Q1500US'] == True]
In [5]:
import matplotlib.pyplot as plt
fig, [ax500, ax1500] = plt.subplots(2, sharex=True)
Q500US_results.hist(['Market Cap'], bins=50, ax=ax500)
Q1500US_results.hist(['Market Cap'], bins=50, ax=ax1500)
ax500.set_xscale('log')
ax1500.set_xscale('log')
ax500.set_ylabel('Freq')
ax1500.set_ylabel('Freq')
ax500.set_title('Market Cap Breakdown of Q500US')
ax1500.set_title('Market Cap Breakdown of Q1500US');
While these histograms do not look very pretty, their logarithmic scale better displays the large value of market caps in the universes.