feat(Models): added StaticAverageModel for average ensembling & StaticNaiveModel (#64)

* feat(Models): added StaticAverageModel for average ensembling

* feat(Models): made sure we only pipe in predictions to StaticAverageModel, added StaticNaiveModel as potential baseline

* chore(Models): removed unnecessary commented out code

models/naive.py

@@ -0,0 +1,21 @@
+from models.base import Model
+import numpy as np
+
+class StaticNaiveModel(Model):
+    '''
+    Model that carries the last observation (from returns) to the next one, naively.
+    '''
+
+    # data_format = 'dataframe'
+    data_scaling = 'unscaled'
+    only_column = None
+
+    def fit(self, X, y):
+        # This is a static model, it can' learn anything
+        pass
+
+    def predict(self, X):
+        return np.array([X[-1][0]])
+
+    def clone(self):
+        return self