diff --git a/pyFTS/common/Transformations.py b/pyFTS/common/Transformations.py
index aa18b71..ad78545 100644
--- a/pyFTS/common/Transformations.py
+++ b/pyFTS/common/Transformations.py
@@ -15,6 +15,8 @@ class Transformation(object):
 
     def __init__(self, **kwargs):
         self.is_invertible = True
+        self.is_multivariate = False
+        """detemine if this transformation can be applied to multivariate data"""
         self.minimal_length = 1
         self.name = ''
 
diff --git a/pyFTS/common/transformations/som.py b/pyFTS/common/transformations/som.py
index a5aee39..a965ae6 100644
--- a/pyFTS/common/transformations/som.py
+++ b/pyFTS/common/transformations/som.py
@@ -18,6 +18,7 @@ class SOMTransformation(Transformation):
         self.data: pd.DataFrame = None
         self.grid_dimension: Tuple = grid_dimension
         self.pbc = kwargs.get('PBC', True)
+        self.is_multivariate = True
 
         # debug attributes
         self.name = 'Kohonen Self Organizing Maps FTS'
@@ -25,8 +26,6 @@ class SOMTransformation(Transformation):
 
     def apply(self,
               data: pd.DataFrame,
-              endogen_variable=None,
-              names: Tuple[str] = ('x', 'y'),
               param=None,
               **kwargs):
         """
@@ -45,6 +44,9 @@ class SOMTransformation(Transformation):
 
         """
 
+        endogen_variable = kwargs.get('endogen_variable', None)
+        names = kwargs.get('names', ('x', 'y'))
+
         if endogen_variable not in data.columns:
             endogen_variable = None
         cols = data.columns[:-1] if endogen_variable is None else [col for col in data.columns if
diff --git a/pyFTS/models/multivariate/mvfts.py b/pyFTS/models/multivariate/mvfts.py
index 632b5db..aba3afb 100644
--- a/pyFTS/models/multivariate/mvfts.py
+++ b/pyFTS/models/multivariate/mvfts.py
@@ -35,6 +35,12 @@ class MVFTS(fts.FTS):
         self.name = "Multivariate FTS"
         self.uod_clip = False
 
+    def append_transformation(self, transformation, **kwargs):
+        if not transformation.is_multivariate:
+            raise Exception('The transformation is not multivariate')
+        self.transformations.append(transformation)
+        self.transformations_param.append(kwargs)
+
     def append_variable(self, var):
         """
         Append a new endogenous variable to the model
@@ -53,6 +59,9 @@ class MVFTS(fts.FTS):
 
     def apply_transformations(self, data, params=None, updateUoD=False, **kwargs):
         ndata = data.copy(deep=True)
+        for ct, transformation in enumerate(self.transformations):
+            ndata = transformation.apply(ndata, **self.transformations_param[ct])
+
         for var in self.explanatory_variables:
             try:
                 values = ndata[var.data_label].values #if isinstance(ndata, pd.DataFrame) else ndata[var.data_label]