ENH #215 hwma indicator TST added DOC readme

README.md

@@ -496,7 +496,7 @@ print(bothhl2.name)  # "pre_HL2_post"
 |:--------:|
 | ![Example MACD](/images/SPY_MACD.png) |
 
-### **Overlap** (30)
+### **Overlap** (31)
 
 * _Double Exponential Moving Average_: **dema**
 * _Exponential Moving Average_: **ema**
@@ -506,6 +506,7 @@ print(bothhl2.name)  # "pre_HL2_post"
 * _High-Low-Close Average_: **hlc3**
     * Commonly known as 'Typical Price' in Technical Analysis literature
 * _Hull Exponential Moving Average_: **hma**
+* _Holt-Winter Moving Average_: **hwma**
 * _Ichimoku Kinkō Hyō_: **ichimoku**
     * Use: help(ta.ichimoku). Returns two DataFrames.
     * Drop the Chikou Span Column, the final column of the first resultant DataFrame, remove potential data leak.
@@ -686,6 +687,7 @@ result = ta.cagr(df.close)
 * _Drawdown_ (**drawdown**) shows the peak-to-trough decline during a specific period for an investment,
 trading account, or fund. See: ```help(ta.drawdown)```
 * _Gann High-Low Activator_ (**hilo**) was created by Robert Krausz in a 1998. See: ```help(ta.hilo)```
+* _Holt-Winter Moving Average_ (**hwma**) is a three-parameter moving average by the Holt-Winter method.
 * _McGinley Dynamic_ (**mcgd**) is an overlap indicator developed by John R. McGinley, a Certified Market Technician. See: ```help(ta.mcgd)```
 * _Price Volume Rank_ (**pvr**) was created by Anthony J. Macek. See: ```help(ta.pvr)```
 * _Quantitative Qualitative Estimation_ (**qqe**) is like SuperTrend for a Smoothed RSI. See: ```help(ta.qqe)```

pandas_ta/overlap/hwma.py

@@ -1,5 +1,4 @@
 # -*- coding: utf-8 -*-
-# import numpy as np
 from pandas import Series
 from pandas_ta.utils import get_offset, verify_series
 
@@ -16,8 +15,8 @@ def hwma(close, na=None, nb=None, nc=None, offset=None, **kwargs):
     # Initialize ..
     m = close.size
     last_f = close[0]
-    last_v = 0
-    last_a = 0
+    # last_a, last_v = 0, 0
+    last_a = last_v = 0
     result = []
 
     # Calculate ..
@@ -25,14 +24,10 @@ def hwma(close, na=None, nb=None, nc=None, offset=None, **kwargs):
         F = (1.0 - na) * (last_f + last_v + 0.5 * last_a) + na * close[i]
         V = (1.0 - nb) * (last_v + last_a) + nb * (F - last_f)
         A = (1.0 - nc) * last_a + nc * (V - last_v)
-        # print('F|V|A:', F, V, A)
         result.append((F + V + 0.5 * A))
         # update values
-        last_a = A
-        last_f = F
-        last_v = V
+        last_a, last_f, last_v = A, F, V
 
-    # Serialize ..
     hwma = Series(result, index=close.index)
 
     # Offset
@@ -45,8 +40,8 @@ def hwma(close, na=None, nb=None, nc=None, offset=None, **kwargs):
     if "fill_method" in kwargs:
         hwma.fillna(method=kwargs["fill_method"], inplace=True)
 
-    # Name & Category    
-    suffix = f'{na}_{nb}_{nc}'
+    # Name & Category
+    suffix = f"{na}_{nb}_{nc}"
     hwma.name = f"HWMA_{suffix}"
     hwma.category = "overlap"
 
@@ -58,8 +53,11 @@ hwma.__doc__ = \
 """HWMA (Holt-Winter Moving Average)
 
 Indicator HWMA (Holt-Winter Moving Average) is a three-parameter moving average
-by the Holt-Winter method; the three parameters should be selected to obtain a forecast.
-This version has been implemented for Pandas TA by rengel8 based on a publication for MetaTrader 5. 
+by the Holt-Winter method; the three parameters should be selected to obtain a
+forecast.
+
+This version has been implemented for Pandas TA by rengel8 based
+on a publication for MetaTrader 5.
 
 Sources:
     https://www.mql5.com/en/code/20856

tests/test_ext_indicator_overlap_ext.py

@@ -53,6 +53,11 @@ class TestOverlapExtension(TestCase):
         self.assertIsInstance(self.data, DataFrame)
         self.assertEqual(self.data.columns[-1], "HMA_10")
 
+    def test_hwma_ext(self):
+        self.data.ta.hwma(append=True)
+        self.assertIsInstance(self.data, DataFrame)
+        self.assertEqual(self.data.columns[-1], "HWMA_0.2_0.1_0.1")
+
     def test_kama_ext(self):
         self.data.ta.kama(append=True)
         self.assertIsInstance(self.data, DataFrame)

tests/test_indicator_overlap.py

@@ -99,6 +99,13 @@ class TestOverlap(TestCase):
         self.assertIsInstance(result, Series)
         self.assertEqual(result.name, "HMA_10")
 
+    def test_hwma(self):
+        result = pandas_ta.hwma(self.close)
+        self.assertIsInstance(result, Series)
+        self.assertEqual(result.name, "HWMA_0.2_0.1_0.1")
+        print(f"\n{result.head(30)}")
+        print(f"\n{result.tail(30)}")
+
     def test_kama(self):
         result = pandas_ta.kama(self.close)
         self.assertIsInstance(result, Series)