diff --git a/pandas_ta/statistics/stdev.py b/pandas_ta/statistics/stdev.py
index 1f92b3f..74d2fc1 100644
--- a/pandas_ta/statistics/stdev.py
+++ b/pandas_ta/statistics/stdev.py
@@ -3,15 +3,16 @@ from numpy import sqrt as npsqrt
 from .variance import variance
 from ..utils import get_offset, verify_series
 
-def stdev(close, length=None, offset=None, **kwargs):
+def stdev(close, length=None, ddof=1, offset=None, **kwargs):
     """Indicator: Standard Deviation"""
     # Validate Arguments
     close = verify_series(close)
     length = int(length) if length and length > 0 else 30
+    ddof = int(ddof) if ddof >= 0 and ddof < length else 1
     offset = get_offset(offset)
 
     # Calculate Result
-    stdev = variance(close=close, length=length).apply(npsqrt)
+    stdev = variance(close=close, length=length, ddof=ddof).apply(npsqrt)
 
     # Offset
     if offset != 0:
@@ -39,6 +40,9 @@ Calculation:
 Args:
     close (pd.Series): Series of 'close's
     length (int): It's period.  Default: 30
+    ddof (int): Delta Degrees of Freedom. 
+                The divisor used in calculations is N - ddof, 
+                where N represents the number of elements. Default: 1 
     offset (int): How many periods to offset the result.  Default: 0
 
 Kwargs:
@@ -47,4 +51,4 @@ Kwargs:
 
 Returns:
     pd.Series: New feature generated.
-"""
\ No newline at end of file
+"""
diff --git a/pandas_ta/statistics/variance.py b/pandas_ta/statistics/variance.py
index 7d5fd26..bb6e2cb 100644
--- a/pandas_ta/statistics/variance.py
+++ b/pandas_ta/statistics/variance.py
@@ -1,16 +1,18 @@
 # -*- coding: utf-8 -*-
 from ..utils import get_offset, verify_series
 
-def variance(close, length=None, offset=None, **kwargs):
+def variance(close, length=None, ddof=1, offset=None, **kwargs):
     """Indicator: Variance"""
     # Validate Arguments
     close = verify_series(close)
     length = int(length) if length and length > 1 else 30
+    ddof = int(ddof) if ddof >= 0 and ddof < length else 1
+
     min_periods = int(kwargs['min_periods']) if 'min_periods' in kwargs and kwargs['min_periods'] is not None else length
     offset = get_offset(offset)
 
     # Calculate Result
-    variance = close.rolling(length, min_periods=min_periods).var()
+    variance = close.rolling(length, min_periods=min_periods).var(ddof)
 
     # Offset
     if offset != 0:
@@ -37,6 +39,9 @@ Calculation:
 Args:
     close (pd.Series): Series of 'close's
     length (int): It's period.  Default: 30
+    ddof (int): Delta Degrees of Freedom. 
+                The divisor used in calculations is N - ddof, 
+                where N represents the number of elements. Default: 1 
     offset (int): How many periods to offset the result.  Default: 0
 
 Kwargs:
@@ -45,4 +50,4 @@ Kwargs:
 
 Returns:
     pd.Series: New feature generated.
-"""
\ No newline at end of file
+"""