[GH-143] Retrieve Chande Momentum Oscillator (#144)

The Chande Momentum Oscillator (CMO) is a technical momentum
indicator developed by Tushar Chande.
https://www.investopedia.com/terms/c/chandemomentumoscillator.asp

```
CMO = 100 * ((sH - sL) / (sH + sL))
```

where:
* sH=the sum of higher closes over N periods
* sL=the sum of lower closes of N periods

README.md

@@ -4,7 +4,7 @@
 [![codecov](https://codecov.io/gh/jealous/stockstats/branch/master/graph/badge.svg?token=IFMD1pVJ7T)](https://codecov.io/gh/jealous/stockstats)
 [![pypi](https://img.shields.io/pypi/v/stockstats.svg)](https://pypi.python.org/pypi/stockstats)
 
-VERSION: 0.5.4
+VERSION: 0.5.5
 
 ## Introduction
 
@@ -725,6 +725,30 @@ BOP = (close - open) / (high - low)
 Example:
 * `df['bop']` returns the Balance of Power
 
+#### [Chande Momentum Oscillator] (https://www.investopedia.com/terms/c/chandemomentumoscillator.asp)
+
+The Chande Momentum Oscillator (CMO) is a technical momentum 
+indicator developed by Tushar Chande.
+
+The formula calculates the difference between the sum of recent 
+gains and the sum of recent losses and then divides the result 
+by the sum of all price movements over the same period.
+
+The default window is 14.
+
+Formular:
+```
+CMO = 100 * ((sH - sL) / (sH + sL))
+```
+
+where:
+* sH=the sum of higher closes over N periods
+* sL=the sum of lower closes of N periods
+
+Examples:
+* `df['cmo']` returns the CMO with a window of 14
+* `df['cmo_5']` returns the CMO with a window of 5
+
 ## Issues
 
 We use [Github Issues](https://github.com/jealous/stockstats/issues) to track

stockstats.py

@@ -99,6 +99,8 @@ class StockDataFrame(pd.DataFrame):
 
     WR = 14
 
+    CMO = 14
+
     WAVE_TREND_1 = 10
     WAVE_TREND_2 = 21
 
@@ -728,9 +730,9 @@ def _get_um_dm(self):
 
         initialize up move and down move
         """
-        hd = self['high_delta']
+        hd = self._col_delta('high')
         self['um'] = (hd + hd.abs()) / 2
-        ld = -self['low_delta']
+        ld = -self._col_delta('low')
         self['dm'] = (ld + ld.abs()) / 2
 
     def _get_pdm(self, windows):
@@ -1215,6 +1217,37 @@ def _get_bop(self):
         divisor = self['high'] - self['low']
         self['bop'] = dividend / divisor
 
+    def _get_cmo(self, window=None):
+        """ get Chande Momentum Oscillator
+
+        The Chande Momentum Oscillator (CMO) is a technical momentum
+        indicator developed by Tushar Chande.
+        https://www.investopedia.com/terms/c/chandemomentumoscillator.asp
+
+        CMO = 100 * ((sH - sL) / (sH + sL))
+
+        where:
+        * sH=the sum of higher closes over N periods
+        * sL=the sum of lower closes of N periods
+        """
+        if window is None:
+            window = self.CMO
+            column_name = 'cmo'
+        else:
+            window = self.get_int_positive(window)
+            column_name = 'cmo_{}'.format(window)
+
+        close_diff = self['close'].diff()
+        up = close_diff.clip(lower=0)
+        down = close_diff.clip(upper=0).abs()
+        sum_up = self._mov_sum(up, window)
+        sum_down = self._mov_sum(down, window)
+        dividend = sum_up - sum_down
+        divisor = sum_up + sum_down
+        res = 100 * dividend / divisor
+        res.iloc[0] = 0
+        self[column_name] = res
+
     def _get_kama(self, column, windows, fasts=None, slows=None):
         """ get Kaufman's Adaptive Moving Average.
         Implemented after
@@ -1298,6 +1331,9 @@ def _get_rate(self):
         """
         self['rate'] = self['close'].pct_change() * 100
 
+    def _col_delta(self, col):
+        return self[col].diff()
+
     def _get_delta(self, key):
         key_to_delta = key.replace('_delta', '')
         self[key] = self[key_to_delta].diff()
@@ -1395,6 +1431,7 @@ def handler(self):
             ('aroon',): self._get_aroon,
             ('ao',): self._get_ao,
             ('bop',): self._get_bop,
+            ('cmo',): self._get_cmo,
         }
 
     def __init_not_exist_column(self, key):

test.py

@@ -687,6 +687,19 @@ def test_bop(self):
         assert_that(bop[20110104], near_to(0.5))
         assert_that(bop[20110106], near_to(-0.207))
 
+    def test_cmo(self):
+        stock = self.get_stock_30day()
+        cmo = stock['cmo']
+        assert_that(cmo[20110104], equal_to(0))
+        assert_that(cmo[20110126], near_to(7.023))
+        assert_that(cmo[20110127], near_to(-16.129))
+
+        cmo_14 = stock['cmo_14']
+        assert_that(cmo_14[20110126], near_to(7.023))
+
+        cmo_5 = stock['cmo_5']
+        assert_that(cmo_5[20110126], near_to(7.895))
+
     def test_drop_column_inplace(self):
         stock = self._supor[:20]
         stock.columns.name = 'Luke'