diff --git a/pandas_ta/momentum/rsx.py b/pandas_ta/momentum/rsx.py
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+++ b/pandas_ta/momentum/rsx.py
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+# -*- coding: utf-8 -*-
+from numpy import NaN as npNaN
+from pandas import DataFrame, Series, concat
+from pandas_ta.utils import get_drift, get_offset, verify_series, signals
+  
+def rsx(close, length=None, drift=None, offset=None, **kwargs):
+    """Indicator: Relative Strength Xtra (inspired by Jurik RSX)"""
+    # Validate arguments
+    close = verify_series(close)
+    length = int(length) if length and length > 0 else 14
+    drift = get_drift(drift)
+    offset = get_offset(offset)
+    
+    # variables
+    f0 = 0
+    f8 = 0
+    f10 = 0
+    f18 = 0
+    f20 = 0
+    f28 = 0
+    f30 = 0
+    f38 = 0
+    f40 = 0
+    f48 = 0
+    f50 = 0
+    f58 = 0
+    f60 = 0
+    f68 = 0
+    f70 = 0
+    f78 = 0
+    f80 = 0
+    f88 = 0
+    f90 = 0
+
+    v4 = 0
+    v8 = 0
+    v10 = 0
+    v14 = 0
+    v18 = 0
+    v20 = 0
+
+    vC = 0
+    v1C = 0
+    
+    # Calculate Result
+    m = close.size
+    result = [npNaN for _ in range(0, length - 1)] + [0]
+    for i in range(length, m):
+        if f90 == 0:
+            f90 = 1.0
+            f0 = 0.0
+            if length - 1.0 >= 5:
+                f88 = length - 1.0
+            else:
+                f88 = 5.0
+            f8 = 100.0 * close[i]
+            f18 = 3.0 / (length + 2.0)
+            f20 = 1.0 - f18
+        else:
+            if f88 <= f90:
+                f90 = f88 + 1
+            else:
+                f90 = f90 + 1
+            f10 = f8
+            f8 = 100 * close[i]
+            v8 = f8 - f10
+            f28 = f20 * f28 + f18 * v8
+            f30 = f18 * f28 + f20 * f30
+            vC = f28 * 1.5 - f30 * 0.5
+            f38 = f20 * f38 + f18 * vC
+            f40 = f18 * f38 + f20 * f40
+            v10 = f38 * 1.5 - f40 * 0.5
+            f48 = f20 * f48 + f18 * v10
+            f50 = f18 * f48 + f20 * f50
+            v14 = f48 * 1.5 - f50 * 0.5
+            f58 = f20 * f58 + f18 * abs(v8)
+            f60 = f18 * f58 + f20 * f60
+            v18 = f58 * 1.5 - f60 * 0.5
+            f68 = f20 * f68 + f18 * v18
+            f70 = f18 * f68 + f20 * f70
+            v1C = f68 * 1.5 - f70 * 0.5
+            f78 = f20 * f78 + f18 * v1C
+            f80 = f18 * f78 + f20 * f80
+            v20 = f78 * 1.5 - f80 * 0.5
+            if f88 >= f90 and f8 != f10:
+                f0 = 1.0
+            if f88 == f90 and f0 == 0.0:
+                f90 = 0.0
+        if f88 < f90 and v20 > 0.0000000001:
+            v4 = (v14 / v20 + 1.0) * 50.0
+            if v4 > 100.0:
+                v4 = 100.0
+            if v4 < 0.0:
+                v4 = 0.0
+        else:
+            v4 = 50.0
+        result.append(v4)
+        # print('v4', v4)
+    rsx = Series(result, index=close.index)
+
+    # Offset
+    if offset != 0:
+        rsx = rsx.shift(offset)
+
+    # Handle fills
+    if "fillna" in kwargs:
+        rsx.fillna(kwargs["fillna"], inplace=True)
+    if "fill_method" in kwargs:
+        rsx.fillna(method=kwargs["fill_method"], inplace=True)
+
+    # Name and Categorize it
+    # print(rsx)
+    # print(length)
+    rsx.name = f"RSX_{length}"
+    rsx.category = "momentum"
+
+    signal_indicators = kwargs.pop("signal_indicators", False)
+    if signal_indicators:
+        signalsdf = concat(
+            [
+                DataFrame({rsx.name: rsx}),
+                signals(
+                    indicator=rsx,
+                    xa=kwargs.pop("xa", 80),
+                    xb=kwargs.pop("xb", 20),
+                    xserie=kwargs.pop("xserie", None),
+                    xserie_a=kwargs.pop("xserie_a", None),
+                    xserie_b=kwargs.pop("xserie_b", None),
+                    cross_values=kwargs.pop("cross_values", False),
+                    cross_series=kwargs.pop("cross_series", True),
+                    offset=offset,
+                ),
+            ],
+            axis=1
+        )
+
+        return signalsdf
+    else:
+        return rsx
+
+
+rsx.__doc__ = \
+"""Relative Strength Xtra (rsx)
+
+The Relative Strength Xtra is based on the popular RSI indicator and inspired by the work Jurik Research.
+The code implemented is based on published code found at 'prorealcode.com'. This enhanced version of the rsi
+reduces noise and provides a clearer, only slightly delayed insight on momentum and velocity of price movements.
+
+Sources:
+    http://www.jurikres.com/catalog1/ms_rsx.htm
+    https://www.prorealcode.com/prorealtime-indicators/jurik-rsx/
+
+Calculation:
+    Refer to the sources above for information as well as code example.
+  
+Args:
+    close (pd.Series): Series of 'close's
+    length (int): It's period.  Default: 14    
+    drift (int): The difference period.  Default: 1
+    offset (int): How many periods to offset the result.  Default: 0
+
+Kwargs:
+    fillna (value, optional): pd.DataFrame.fillna(value)
+    fill_method (value, optional): Type of fill method
+
+Returns:
+    pd.Series: New feature generated.
+"""
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