diff --git a/fincal/core.py b/fincal/core.py
index 0064814..f762c7f 100644
--- a/fincal/core.py
+++ b/fincal/core.py
@@ -124,11 +124,11 @@ class TimeSeriesCore:
         data = _preprocess_timeseries(data, date_format=date_format)
 
         self.time_series = dict(data)
-        self.dates = set(list(self.time_series))
-        if len(self.dates) != len(data):
+        self.dates = list(self.time_series)
+        if len(self.time_series) != len(data):
             print("Warning: The input data contains duplicate dates which have been ignored.")
-        self.start_date = list(self.time_series)[0]
-        self.end_date = list(self.time_series)[-1]
+        self.start_date = self.dates[0]
+        self.end_date = self.dates[-1]
         self.frequency = getattr(AllFrequencies, frequency)
 
     def __repr__(self):
diff --git a/fincal/fincal.py b/fincal/fincal.py
index b11b0cf..f313b0e 100644
--- a/fincal/fincal.py
+++ b/fincal/fincal.py
@@ -177,10 +177,14 @@ class TimeSeries(TimeSeriesCore):
     ) -> List[tuple]:
         """Calculates the rolling return"""
 
-        all_dates = create_date_series(from_date, to_date, getattr(AllFrequencies, frequency))
-        dates = set(all_dates)
+        try:
+            frequency = getattr(AllFrequencies, frequency)
+        except AttributeError:
+            raise ValueError(f"Invalid argument for frequency {frequency}")
+
+        dates = create_date_series(from_date, to_date, frequency)
         if frequency == AllFrequencies.D:
-            dates = all_dates.intersection(self.dates)
+            dates = [i for i in dates if i in self.time_series]
 
         rolling_returns = []
         for i in dates:
@@ -193,8 +197,8 @@ class TimeSeries(TimeSeriesCore):
                 closest=closest,
             )
             rolling_returns.append((i, returns))
-        self.rolling_returns = rolling_returns
-        return self.rolling_returns
+        rolling_returns.sort()
+        return rolling_returns
 
 
 if __name__ == "__main__":