diff --git a/tests/optimize/conftest.py b/tests/optimize/conftest.py
index 690934b07..13d90b36f 100644
--- a/tests/optimize/conftest.py
+++ b/tests/optimize/conftest.py
@@ -39,17 +39,25 @@ def hyperopt(hyperopt_conf, mocker):
 def hyperopt_results():
     return pd.DataFrame(
         {
-            'pair': ['ETH/BTC', 'ETH/BTC', 'ETH/BTC', 'ETH/BTC'],
+            'pair': ['ETH/USDT', 'ETH/USDT', 'ETH/USDT', 'ETH/USDT'],
             'profit_ratio': [-0.1, 0.2, -0.1, 0.3],
             'profit_abs': [-0.2, 0.4, -0.2, 0.6],
             'trade_duration': [10, 30, 10, 10],
+            'amount': [0.1, 0.1, 0.1, 0.1],
             'sell_reason': [SellType.STOP_LOSS, SellType.ROI, SellType.STOP_LOSS, SellType.ROI],
+            'open_date':
+            [
+                datetime(2019, 1, 1, 9, 15, 0),
+                datetime(2019, 2, 1, 8, 55, 0),
+                datetime(2019, 3, 1, 9, 15, 0),
+                datetime(2019, 4, 1, 9, 15, 0),
+            ],
             'close_date':
             [
-                datetime(2019, 1, 1, 9, 26, 3, 478039),
-                datetime(2019, 2, 1, 9, 26, 3, 478039),
-                datetime(2019, 3, 1, 9, 26, 3, 478039),
-                datetime(2019, 4, 1, 9, 26, 3, 478039),
-            ]
+                datetime(2019, 1, 1, 9, 25, 0),
+                datetime(2019, 2, 1, 9, 25, 0),
+                datetime(2019, 3, 1, 9, 25, 0),
+                datetime(2019, 4, 1, 9, 25, 0),
+            ],
         }
     )
diff --git a/tests/strategy/test_strategy_helpers.py b/tests/strategy/test_strategy_helpers.py
index a01b55050..cb7cf97a1 100644
--- a/tests/strategy/test_strategy_helpers.py
+++ b/tests/strategy/test_strategy_helpers.py
@@ -9,13 +9,13 @@ from freqtrade.strategy import (merge_informative_pair, stoploss_from_absolute,
                                 timeframe_to_minutes)
 
 
-def generate_test_data(timeframe: str, size: int):
+def generate_test_data(timeframe: str, size: int, start: str = '2020-07-05'):
     np.random.seed(42)
     tf_mins = timeframe_to_minutes(timeframe)
 
     base = np.random.normal(20, 2, size=size)
 
-    date = pd.period_range('2020-07-05', periods=size, freq=f'{tf_mins}min').to_timestamp()
+    date = pd.date_range(start, periods=size, freq=f'{tf_mins}min', tz='UTC')
     df = pd.DataFrame({
         'date': date,
         'open': base,