Fix Chande-Kroll stop #256, and #257

Add an optional "tvmode" parameter that controls the behaviour of the
Chande-Kroll volatility stop. The default, True, retains the used
behaviour, compatibility with Trading View. When False however, the
moving average mode used is now a simple moving average instead of the
Welles Wilder moving average and the periods used are different as well,
(10/1/9 vs 10/3/20).

Update the unit tests to account for the optional parameter, though
sadly we have no TA-lib implementation to compare with, and the Japanese
Yen Futures 09/93 contract used in figure 7.4 page 95 of the book, has
no freely available OHLC data i could find.

pandas_ta/trend/cksp.py

@@ -4,27 +4,32 @@ from pandas_ta.volatility import atr
 from pandas_ta.utils import get_offset, verify_series
 
 
-def cksp(high, low, close, p=None, x=None, q=None, offset=None, **kwargs):
+def cksp(high, low, close, p=None, x=None, q=None, offset=None, tvmode=None, **kwargs):
     """Indicator: Chande Kroll Stop (CKSP)"""
     # Validate Arguments
+    # TV defaults=(10,1,9), book defaults = (10,3,20)
     p = int(p) if p and p > 0 else 10
-    x = float(x) if x and x > 0 else 1
-    q = int(q) if q and q > 0 else 9
+    x = float(x) if x and x > 0 else 1 if tvmode is True else 3
+    q = int(q) if q and q > 0 else 9 if tvmode is True else 20
+
     _length = max(p, q, x)
+
     high = verify_series(high, _length)
     low = verify_series(low, _length)
     close = verify_series(close, _length)
-    offset = get_offset(offset)
 
     if high is None or low is None or close is None: return
 
-    # Calculate Result
-    atr_ = atr(high=high, low=low, close=close, length=p)
+    offset = get_offset(offset)
+    tvmode = tvmode if isinstance(tvmode, bool) else True
+
+    mamode = "rma" if tvmode is True else "sma"
+    atr_ = atr(high=high, low=low, close=close, length=p, mamode = mamode)
 
     long_stop_ = high.rolling(p).max() - x * atr_
     long_stop = long_stop_.rolling(q).max()
 
-    short_stop_ = high.rolling(p).min() + x * atr_
+    short_stop_ = low.rolling(p).min() + x * atr_
     short_stop = short_stop_.rolling(q).min()
 
     # Offset
@@ -57,16 +62,22 @@ def cksp(high, low, close, p=None, x=None, q=None, offset=None, **kwargs):
 cksp.__doc__ = \
 """Chande Kroll Stop (CKSP)
 
-The Tushar Chande and Stanley Kroll in their book “The New Technical Trader”.
-It is a trend-following indicator, identifying your stop by calculating the
-average true range of the recent market volatility.
+The Tushar Chande and Stanley Kroll in their book
+“The New Technical Trader”. It is a trend-following indicator,
+identifying your stop by calculating the average true range of
+the recent market volatility. The indicator defaults to the implementation
+found on tradingview but it provides the original book implementation as well,
+which differs by the default periods and moving average mode. While the trading
+view implementation uses the Welles Wilder moving average, the book uses a
+simple moving average.
 
 Sources:
     https://www.multicharts.com/discussion/viewtopic.php?t=48914
+    "The New Technical Trader", Wikey 1st ed. ISBN 9780471597803, page 95
 
 Calculation:
     Default Inputs:
-        p=10, x=1, q=9
+        p=10, x=1, q=9, tvmode=True
     ATR = Average True Range
 
     LS0 = high.rolling(p).max() - x * ATR(length=p)
@@ -77,10 +88,11 @@ Calculation:
 
 Args:
     close (pd.Series): Series of 'close's
-    p (int): ATR and first stop period. Default: 10
-    x (float): ATR scalar. Default: 1
-    q (int): Second stop period. Default: 9
+    p (int): ATR and first stop period. Default: 10 in both modes
+    x (float): ATR scalar. Default: 1 in TV mode, 3 otherwise
+    q (int): Second stop period. Default: 9 in TV mode, 20 otherwise
     offset (int): How many periods to offset the result. Default: 0
+    tvmode (bool): Trading View or book implementation mode. Default: True
 
 Kwargs:
     fillna (value, optional): pd.DataFrame.fillna(value)

tests/test_ext_indicator_trend.py

@@ -40,6 +40,7 @@ class TestTrendExtension(TestCase):
 
     def test_cksp_ext(self):
         self.data.ta.cksp(append=True)
+        self.data.ta.cksp(tv=True)
         self.assertIsInstance(self.data, DataFrame)
         self.assertEqual(self.data.columns[-1], "CKSPs_10_1_9")