[GH-141] Add BOP (#142)

Add Balance of Power.

Balance of Power (BOP) measures the strength of the bulls vs. bears.

Formular:
```
BOP = (close - open) / (high - low)
```

Example:
* `df['bop']` returns the Balance of Power

README.md

@@ -57,6 +57,7 @@ Supported statistics/indicators are:
 * Aroon: Aroon Oscillator
 * Z: Z-Score
 * AO: Awesome Oscillator
+* BOP: Balance of Power
 
 ## Installation
 
@@ -682,7 +683,9 @@ There is no default column name or window for Z-Score.
 The statistical formula for a value's z-score is calculated using
 the following formula:
 
-```z = ( x - μ ) / σ```
+```
+z = ( x - μ ) / σ
+```
 
 Where:
 
@@ -710,6 +713,18 @@ Examples:
 * `df['ao']` returns the Awesome Oscillator with default windows (5, 34)
 * `df['ao_3,10']` returns the Awesome Oscillator with a window of 3 and 10
 
+#### [Balance of Power](https://school.stockcharts.com/doku.php?id=technical_indicators:balance_of_power)
+
+Balance of Power (BOP) measures the strength of the bulls vs. bears.
+
+Formular:
+```
+BOP = (close - open) / (high - low)
+```
+
+Example:
+* `df['bop']` returns the Balance of Power
+
 ## Issues
 
 We use [Github Issues](https://github.com/jealous/stockstats/issues) to track

stockstats.py

@@ -1203,15 +1203,27 @@ def _get_ao(self, windows=None):
         ao = self._sma(median_price, fast) - self._sma(median_price, slow)
         self[column_name] = ao
 
+    def _get_bop(self):
+        """ get balance of power
+
+        The Balance of Power indicator measures the strength of the bulls.
+        https://school.stockcharts.com/doku.php?id=technical_indicators:balance_of_power
+
+        BOP = (close - open) / (high - low)
+        """
+        dividend = self['close'] - self['open']
+        divisor = self['high'] - self['low']
+        self['bop'] = dividend / divisor
+
     def _get_kama(self, column, windows, fasts=None, slows=None):
         """ get Kaufman's Adaptive Moving Average.
         Implemented after
         https://school.stockcharts.com/doku.php?id=technical_indicators:kaufman_s_adaptive_moving_average
 
         :param column: column to calculate
         :param windows: collection of window of exponential moving average
-        :param fasts: fastest EMA constant
-        :param slows: slowest EMA constant
+        :param fasts: faster EMA constant
+        :param slows: slower EMA constant
         :return: None
         """
         window = self.get_int_positive(windows)
@@ -1382,6 +1394,7 @@ def handler(self):
              'supertrend_ub'): self._get_supertrend,
             ('aroon',): self._get_aroon,
             ('ao',): self._get_ao,
+            ('bop',): self._get_bop,
         }
 
     def __init_not_exist_column(self, key):

test.py

@@ -681,6 +681,12 @@ def test_ao(self):
         assert_that(ao1[idx], equal_to(ao[idx]))
         assert_that(ao2[idx], near_to(-0.071))
 
+    def test_bop(self):
+        stock = self.get_stock_30day()
+        bop = stock['bop']
+        assert_that(bop[20110104], near_to(0.5))
+        assert_that(bop[20110106], near_to(-0.207))
+
     def test_drop_column_inplace(self):
         stock = self._supor[:20]
         stock.columns.name = 'Luke'