Combining Factors¶

Factors can be combined, both with other Factors and with scalar values, via any of the builtin mathematical operators (+, -, *, etc). This makes it easy to write complex expressions that combine multiple Factors. For example, constructing a Factor that computes the average of two other Factors is simply:

>>> f1 = SomeFactor(...)
>>> f2 = SomeOtherFactor(...)
>>> average = (f1 + f2) / 2.0

In this lesson, we will create a pipeline that creates a relative_difference factor by combining a 10-day average factor and a 30-day average factor.

As usual, let's start with our imports:

In [1]:

from zipline.pipeline import Pipeline, EquityPricing
from zipline.research import run_pipeline
from zipline.pipeline.factors import SimpleMovingAverage

For this example, we need two factors: a 10-day mean close price factor, and a 30-day one:

In [2]:

mean_close_10 = SimpleMovingAverage(inputs=EquityPricing.close, window_length=10)
mean_close_30 = SimpleMovingAverage(inputs=EquityPricing.close, window_length=30)

Then, let's create a percent difference factor by combining our mean_close_30 factor with our mean_close_10 factor.

In [3]:

percent_difference = (mean_close_10 - mean_close_30) / mean_close_30

In this example, percent_difference is still a Factor even though it's composed as a combination of more primitive factors. We can add percent_difference as a column in our pipeline. Let's define make_pipeline to create a pipeline with percent_difference as a column (and not the mean close factors):

In [4]:

def make_pipeline():

    mean_close_10 = SimpleMovingAverage(inputs=EquityPricing.close, window_length=10)
    mean_close_30 = SimpleMovingAverage(inputs=EquityPricing.close, window_length=30)

    percent_difference = (mean_close_10 - mean_close_30) / mean_close_30

    return Pipeline(
        columns={
            'percent_difference': percent_difference
        }
    )

Let's see what the new output looks like:

In [5]:

result = run_pipeline(make_pipeline(), start_date='2010-01-05', end_date='2010-01-05')
result

Out[5]:

		percent_difference
date	asset
2010-01-05	Equity(FIBBG000C2V3D6 [A])	0.021425
	Equity(QI000000004076 [AABA])	0.050484
	Equity(FIBBG000BZWHH8 [AACC])	0.059385
	Equity(FIBBG000V2S3P6 [AACG])	-0.079614
	Equity(FIBBG000M7KQ09 [AAI])	0.068811
	...	...
	Equity(FIBBG011MC2100 [AATC])	-0.047524
	Equity(FIBBG000GDBDH4 [BDG])	NaN
	Equity(FIBBG000008NR0 [ISM])	NaN
	Equity(FIBBG000GZ24W8 [PEM])	NaN
	Equity(FIBBG000BB5S87 [HCH])	0.045581

7841 rows × 1 columns