ENH: Add Rate of change Percentage indicator

tests/pipeline/test_technical.py

@@ -15,6 +15,7 @@ from zipline.pipeline.factors import (
     Aroon,
     FastStochasticOscillator,
     IchimokuKinkoHyo,
+    RateOfChangePercentage,
 )
 from zipline.testing import ExplodingObject, parameter_space
 from zipline.testing.fixtures import WithAssetFinder, ZiplineTestCase
@@ -354,3 +355,19 @@ class IchimokuKinkoHyoTestCase(ZiplineTestCase):
             str(e.exception),
             '%s must be <= the window_length: 53 > 52' % arg,
         )
+
+
+class TestRateOfChangePercentage(ZiplineTestCase):
+    def test_rate_of_change_per(self):
+        rocp = RateOfChangePercentage(
+            inputs=(USEquityPricing.close,),
+            window_length=10
+        )
+        today = pd.Timestamp('2014')
+        assets = np.arange(5, dtype=np.int64)
+
+        data = np.ones((10, 5))
+        data[0, :] = np.full((1, 5), 2.0)
+        out = np.zeros(data.shape[1])
+        rocp.compute(today, assets, out, data)
+        assert_equal(out, np.full((5,), -50.0))

zipline/pipeline/factors/__init__.py

@@ -24,6 +24,7 @@ from .technical import (
     FastStochasticOscillator,
     IchimokuKinkoHyo,
     MaxDrawdown,
+    RateOfChangePercentage,
     Returns,
     RSI,
     SimpleMovingAverage,
@@ -47,6 +48,7 @@ __all__ = [
     'IchimokuKinkoHyo',
     'Latest',
     'MaxDrawdown',
+    'RateOfChangePercentage',
     'RecarrayField',
     'Returns',
     'RollingLinearRegressionOfReturns',

zipline/pipeline/factors/technical.py

@@ -590,3 +590,33 @@ class IchimokuKinkoHyo(CustomFactor):
         out.senkou_span_a = (tenkan_sen + kijun_sen) / 2
         out.senkou_span_b = (high.max(axis=0) + low.min(axis=0)) / 2
         out.chikou_span = close[chikou_span_length]
+
+
+class RateOfChangePercentage(CustomFactor):
+    """
+    Rate of change Percentage
+    ROC measures the percentage change in price from one period to the next.
+    The ROC calculation compares the current price with the price `n`
+    periods ago.
+    Formula for calculation: ((price - prevPrice) / prevPrice) * 100
+    price - the current price
+    prevPrice - the price n days ago, equals window length
+
+    **Default Inputs**: [USEquityPricing.close]
+    **Default Window Length**: 10
+
+    """
+    inputs = (USEquityPricing.close,)
+    window_length = 10
+
+    def compute(self, today, assets, out, close):
+        today_close = close[-1]
+        prev_close = close[0]
+        evaluate('((tc - pc) / pc) * 100',
+                 local_dict={
+                     'tc': today_close,
+                     'pc': prev_close
+                 },
+                 global_dict={},
+                 out=out,
+                 )