diff --git a/freqtrade/tests/optimize/test_backtest_detail.py b/freqtrade/tests/optimize/test_backtest_detail.py
index 6430f6c1e..f2b97c744 100644
--- a/freqtrade/tests/optimize/test_backtest_detail.py
+++ b/freqtrade/tests/optimize/test_backtest_detail.py
@@ -1,11 +1,11 @@
 # pragma pylint: disable=missing-docstring, W0212, line-too-long, C0103, unused-argument
 import logging
 from unittest.mock import MagicMock
-from typing import NamedTuple
+from typing import NamedTuple, List
 
 from pandas import DataFrame
 import pytest
-from arrow import get as getdate
+import arrow
 
 
 from freqtrade.optimize.backtesting import Backtesting
@@ -13,11 +13,15 @@ from freqtrade.strategy.interface import SellType
 from freqtrade.tests.conftest import patch_exchange, log_has
 
 
+ticker_start_time = arrow.get(2018, 10, 3)
+ticker_interval_in_minute = 60
+
+
 class BTContainer(NamedTuple):
     """
     NamedTuple Defining BacktestResults inputs.
     """
-    data: DataFrame
+    data: List[float]
     stop_loss: float
     roi: float
     trades: int
@@ -25,19 +29,24 @@ class BTContainer(NamedTuple):
     sell_r: SellType
 
 
-columns = ['date', 'open', 'high', 'low', 'close', 'volume', 'buy', 'sell']
-data_profit = DataFrame([
-    [getdate('2018-07-08 18:00:00').datetime, 0.0009910,
-     0.001011, 0.00098618, 0.001000, 12345, 1, 0],
-    [getdate('2018-07-08 19:00:00').datetime, 0.001000,
-     0.001010, 0.0009900, 0.0009900, 12345, 0, 0],
-    [getdate('2018-07-08 20:00:00').datetime, 0.0009900,
-     0.001011, 0.00091618, 0.0009900, 12345, 0, 0],
-    [getdate('2018-07-08 21:00:00').datetime, 0.001000,
-     0.001011, 0.00098618, 0.001100, 12345, 0, 1],
-    [getdate('2018-07-08 22:00:00').datetime, 0.001000,
-     0.001011, 0.00098618, 0.0009900, 12345, 0, 0]
-], columns=columns)
+def _build_dataframe(ticker_with_signals):
+    columns = ['date', 'open', 'high', 'low', 'close', 'volume', 'buy', 'sell']
+
+    frame = DataFrame.from_records(ticker_with_signals, columns=columns)
+    frame['date'] = frame['date'].apply(lambda x: ticker_start_time.shift(
+                    minutes=(x * ticker_interval_in_minute)).datetime)
+    # Ensure floats are in place
+    for column in ['open', 'high', 'low', 'close', 'volume']:
+        frame[column] = frame[column].astype('float64')
+    return frame
+
+
+data_profit = [
+    [0, 0.0009910, 0.001011, 0.00098618, 0.001000, 12345, 1, 0],
+    [1, 0.001000, 0.001010, 0.0009900, 0.0009900, 12345, 0, 0],
+    [2, 0.0009900, 0.001011, 0.00091618, 0.0009900, 12345, 0, 0],
+    [3, 0.001000, 0.001011, 0.00098618, 0.001100, 12345, 0, 1],
+    [4, 0.001000, 0.001011, 0.00098618, 0.0009900, 12345, 0, 0]]
 
 tc_profit1 = BTContainer(data=data_profit, stop_loss=-0.01, roi=1, trades=1,
                          profit_perc=0.10557, sell_r=SellType.STOP_LOSS)  # should be stoploss - drops 8%
@@ -45,18 +54,12 @@ tc_profit2 = BTContainer(data=data_profit, stop_loss=-0.10, roi=1,
                          trades=1, profit_perc=0.10557, sell_r=SellType.STOP_LOSS)
 
 
-tc_loss0 = BTContainer(data=DataFrame([
-    [getdate('2018-07-08 18:00:00').datetime, 0.0009910,
-     0.001011, 0.00098618, 0.001000, 12345, 1, 0],
-    [getdate('2018-07-08 19:00:00').datetime, 0.001000,
-     0.001010, 0.0009900, 0.001000, 12345, 0, 0],
-    [getdate('2018-07-08 20:00:00').datetime, 0.001000,
-     0.001011, 0.0010618, 0.00091618, 12345, 0, 0],
-    [getdate('2018-07-08 21:00:00').datetime, 0.001000,
-     0.001011, 0.00098618, 0.00091618, 12345, 0, 0],
-    [getdate('2018-07-08 22:00:00').datetime, 0.001000,
-     0.001011, 0.00098618, 0.00091618, 12345, 0, 0]
-], columns=columns),
+tc_loss0 = BTContainer(data=[
+    [0, 0.0009910, 0.001011, 0.00098618, 0.001000, 12345, 1, 0],
+    [1, 0.001000, 0.001010, 0.0009900, 0.001000, 12345, 0, 0],
+    [2, 0.001000, 0.001011, 0.0010618, 0.00091618, 12345, 0, 0],
+    [3, 0.001000, 0.001011, 0.00098618, 0.00091618, 12345, 0, 0],
+    [4, 0.001000, 0.001011, 0.00098618, 0.00091618, 12345, 0, 0]],
     stop_loss=-0.05, roi=1, trades=1, profit_perc=-0.08839, sell_r=SellType.STOP_LOSS)
 
 
@@ -64,30 +67,27 @@ tc_loss0 = BTContainer(data=DataFrame([
 # Candle Data for test 1 – close at -8% (9200)
 # Test with Stop-loss at 1%
 # TC1: Stop-Loss Triggered 1% loss
-tc1 = BTContainer(data=DataFrame([
-    [getdate('2018-06-10 07:00:00').datetime, 10000, 10050, 9950, 9975, 12345, 1, 0],
-    [getdate('2018-06-10 08:00:00').datetime, 10000, 10050, 9950, 9975, 12345, 0, 0],
-    [getdate('2018-06-10 09:00:00').datetime, 9975, 10025, 9200, 9200, 12345, 0, 0],
-    [getdate('2018-06-10 10:00:00').datetime, 9950, 10000, 9960, 9955, 12345, 0, 0],
-    [getdate('2018-06-10 11:00:00').datetime, 9955, 9975, 9955, 9990, 12345, 0, 0],
-    [getdate('2018-06-10 12:00:00').datetime, 9990, 9990, 9990, 9900, 12345, 0, 0]
-], columns=columns),
-    stop_loss=-0.01, roi=1, trades=1, profit_perc=-0.01, sell_r=SellType.STOP_LOSS)  # should be
-    # stop_loss=-0.01, roi=1, trades=1, profit_perc=-0.003, sell_r=SellType.FORCE_SELL)  #
+tc1 = BTContainer(data=[
+    [0, 10000.0, 10050, 9950, 9975, 12345, 1, 0],
+    [1, 10000, 10050, 9950, 9975, 12345, 0, 0],
+    [2, 9975, 10025, 9200, 9200, 12345, 0, 0],
+    [3, 9950, 10000, 9960, 9955, 12345, 0, 0],
+    [4, 9955, 9975, 9955, 9990, 12345, 0, 0],
+    [5, 9990, 9990, 9990, 9900, 12345, 0, 0]],
+    stop_loss=-0.01, roi=1, trades=1, profit_perc=-0.01, sell_r=SellType.STOP_LOSS)
 
 
 # Test 2 Minus 4% Low, minus 1% close
 # Candle Data for test 2
 # Test with Stop-Loss at 3%
 # TC2: Stop-Loss Triggered 3% Loss
-tc2 = BTContainer(data=DataFrame([
-    [getdate('2018-06-10 07:00:00').datetime, 10000, 10050, 9950, 9975, 12345, 1, 0],
-    [getdate('2018-06-10 08:00:00').datetime, 10000, 10050, 9950, 9975, 12345, 0, 0],
-    [getdate('2018-06-10 09:00:00').datetime, 9975, 10025, 9925, 9950, 12345, 0, 0],
-    [getdate('2018-06-10 10:00:00').datetime, 9950, 10000, 9600, 9925, 12345, 0, 0],
-    [getdate('2018-06-10 11:00:00').datetime, 9925, 9975, 9875, 9900, 12345, 0, 0],
-    [getdate('2018-06-10 12:00:00').datetime, 9900, 9950, 9850, 9900, 12345, 0, 0]
-], columns=columns),
+tc2 = BTContainer(data=[
+    [0, 10000, 10050, 9950, 9975, 12345, 1, 0],
+    [1, 10000, 10050, 9950, 9975, 12345, 0, 0],
+    [2, 9975, 10025, 9925, 9950, 12345, 0, 0],
+    [3, 9950, 10000, 9600, 9925, 12345, 0, 0],
+    [4, 9925, 9975, 9875, 9900, 12345, 0, 0],
+    [5, 9900, 9950, 9850, 9900, 12345, 0, 0]],
     stop_loss=-0.03, roi=1, trades=1, profit_perc=-0.03, sell_r=SellType.STOP_LOSS)  #should be
     # stop_loss=-0.03, roi=1, trades=1, profit_perc=-0.007, sell_r=SellType.FORCE_SELL)  #
 
@@ -99,15 +99,14 @@ tc2 = BTContainer(data=DataFrame([
 # Test with Stop-Loss at 2%
 # TC3: Trade-A: Stop-Loss Triggered 2% Loss
 #          Trade-B: Stop-Loss Triggered 2% Loss
-tc3 = BTContainer(data=DataFrame([
-    [getdate('2018-06-10 07:00:00').datetime, 10000, 10050, 9950, 9975, 12345, 1, 0],
-    [getdate('2018-06-10 08:00:00').datetime, 10000, 10050, 9950, 9975, 12345, 0, 0],
-    [getdate('2018-06-10 09:00:00').datetime, 9975, 10025, 9600, 9950, 12345, 0, 0],
-    [getdate('2018-06-10 10:00:00').datetime, 9950, 10000, 9900, 9925, 12345, 1, 0],
-    [getdate('2018-06-10 11:00:00').datetime, 9950, 10000, 9900, 9925, 12345, 0, 0],
-    [getdate('2018-06-10 12:00:00').datetime, 9925, 9975, 8000, 8000, 12345, 0, 0],
-    [getdate('2018-06-10 13:00:00').datetime, 9900, 9950, 9950, 9900, 12345, 0, 0]
-], columns=columns),
+tc3 = BTContainer(data=[
+    [0, 10000, 10050, 9950, 9975, 12345, 1, 0],
+    [1, 10000, 10050, 9950, 9975, 12345, 0, 0],
+    [2, 9975, 10025, 9600, 9950, 12345, 0, 0],
+    [3, 9950, 10000, 9900, 9925, 12345, 1, 0],
+    [4, 9950, 10000, 9900, 9925, 12345, 0, 0],
+    [5, 9925, 9975, 8000, 8000, 12345, 0, 0],
+    [6, 9900, 9950, 9950, 9900, 12345, 0, 0]],
     stop_loss=-0.02, roi=1, trades=2, profit_perc=-0.04, sell_r=SellType.STOP_LOSS)  #should be
     # stop_loss=-0.02, roi=1, trades=1, profit_perc=-0.02, sell_r=SellType.STOP_LOSS)  #should be
     # stop_loss=-0.02, roi=1, trades=1, profit_perc=-0.012, sell_r=SellType.FORCE_SELL)  #
@@ -117,14 +116,13 @@ tc3 = BTContainer(data=DataFrame([
 # Candle Data for test 4 – Candle drops 3% Closed 15% up
 # Test with Stop-loss at 2% ROI 6%
 # TC4: Stop-Loss Triggered 2% Loss
-tc4 = BTContainer(data=DataFrame([
-    [getdate('2018-06-10 07:00:00').datetime, 10000, 10050, 9950, 9975, 12345, 1, 0],
-    [getdate('2018-06-10 08:00:00').datetime, 10000, 10050, 9950, 9975, 12345, 0, 0],
-    [getdate('2018-06-10 09:00:00').datetime, 9975, 11500, 9700, 11500, 12345, 0, 0],
-    [getdate('2018-06-10 10:00:00').datetime, 9950, 10000, 9900, 9925, 12345, 0, 0],
-    [getdate('2018-06-10 11:00:00').datetime, 9925, 9975, 9875, 9900, 12345, 0, 0],
-    [getdate('2018-06-10 12:00:00').datetime, 9900, 9950, 9850, 9900, 12345, 0, 0]
-], columns=columns),
+tc4 = BTContainer(data=[
+    [0, 10000, 10050, 9950, 9975, 12345, 1, 0],
+    [1, 10000, 10050, 9950, 9975, 12345, 0, 0],
+    [2, 9975, 11500, 9700, 11500, 12345, 0, 0],
+    [3, 9950, 10000, 9900, 9925, 12345, 0, 0],
+    [4, 9925, 9975, 9875, 9900, 12345, 0, 0],
+    [5, 9900, 9950, 9850, 9900, 12345, 0, 0]],
     stop_loss=-0.02, roi=0.06, trades=1, profit_perc=-0.02, sell_r=SellType.STOP_LOSS)  #should be
     # stop_loss=-0.02, roi=0.06, trades=1, profit_perc=-0.012, sell_r=SellType.FORCE_SELL)
 
@@ -132,14 +130,13 @@ tc4 = BTContainer(data=DataFrame([
 # Candle Data for test 5
 # Set stop-loss at 1% ROI 3%
 # TC5: ROI triggers 3% Gain
-tc5 = BTContainer(data=DataFrame([
-    [getdate('2018-06-10 07:00:00').datetime, 10000, 10050, 9960, 9975, 12345, 1, 0],
-    [getdate('2018-06-10 08:00:00').datetime, 10000, 10050, 9960, 9975, 12345, 0, 0],
-    [getdate('2018-06-10 09:00:00').datetime, 9975, 10050, 9950, 9975, 12345, 0, 0],
-    [getdate('2018-06-10 10:00:00').datetime, 9950, 12000, 9950, 12000, 12345, 0, 0],
-    [getdate('2018-06-10 11:00:00').datetime, 9925, 9975, 9945, 9900, 12345, 0, 0],
-    [getdate('2018-06-10 12:00:00').datetime, 9900, 9950, 9850, 9900, 12345, 0, 0]
-], columns=columns),
+tc5 = BTContainer(data=[
+    [0, 10000, 10050, 9960, 9975, 12345, 1, 0],
+    [1, 10000, 10050, 9960, 9975, 12345, 0, 0],
+    [2, 9975, 10050, 9950, 9975, 12345, 0, 0],
+    [3, 9950, 12000, 9950, 12000, 12345, 0, 0],
+    [4, 9925, 9975, 9945, 9900, 12345, 0, 0],
+    [5, 9900, 9950, 9850, 9900, 12345, 0, 0]],
     stop_loss=-0.01, roi=0.03, trades=1, profit_perc=0.03, sell_r=SellType.ROI)  #should be
     # stop_loss=-0.01, roi=0.03, trades=1, profit_perc=-0.012, sell_r=SellType.FORCE_SELL)
 
@@ -147,14 +144,13 @@ tc5 = BTContainer(data=DataFrame([
 # Candle Data for test 6
 # Set stop-loss at 2% ROI at 5%
 # TC6: Stop-Loss triggers 2% Loss
-tc6 = BTContainer(data=DataFrame([
-    [getdate('2018-06-10 07:00:00').datetime, 10000, 10050, 9950, 9975, 12345, 1, 0],
-    [getdate('2018-06-10 08:00:00').datetime, 10000, 10050, 9950, 9975, 12345, 0, 0],
-    [getdate('2018-06-10 09:00:00').datetime, 9975, 10600, 9700, 10100, 12345, 0, 0],
-    [getdate('2018-06-10 10:00:00').datetime, 9950, 10000, 9900, 9925, 12345, 0, 0],
-    [getdate('2018-06-10 11:00:00').datetime, 9925, 9975, 9945, 9900, 12345, 0, 0],
-    [getdate('2018-06-10 12:00:00').datetime, 9900, 9950, 9850, 9900, 12345, 0, 0]
-], columns=columns),
+tc6 = BTContainer(data=[
+    [0, 10000, 10050, 9950, 9975, 12345, 1, 0],
+    [1, 10000, 10050, 9950, 9975, 12345, 0, 0],
+    [2, 9975, 10600, 9700, 10100, 12345, 0, 0],
+    [3, 9950, 10000, 9900, 9925, 12345, 0, 0],
+    [4, 9925, 9975, 9945, 9900, 12345, 0, 0],
+    [5, 9900, 9950, 9850, 9900, 12345, 0, 0]],
     stop_loss=-0.02, roi=0.05, trades=1, profit_perc=-0.02, sell_r=SellType.STOP_LOSS)  #should be
     # stop_loss=-0.02, roi=0.05, trades=1, profit_perc=-0.012, sell_r=SellType.FORCE_SELL)  #
 
@@ -162,14 +158,13 @@ tc6 = BTContainer(data=DataFrame([
 # Candle Data for test 7
 # Set stop-loss at 2% ROI at 3%
 # TC7: ROI Triggers 3% Gain
-tc7 = BTContainer(data=DataFrame([
-    [getdate('2018-06-10 07:00:00').datetime, 10000, 10050, 9950, 9975, 12345, 1, 0],
-    [getdate('2018-06-10 08:00:00').datetime, 10000, 10050, 9950, 9975, 12345, 0, 0],
-    [getdate('2018-06-10 09:00:00').datetime, 9975, 10600, 9900, 10100, 12345, 0, 0],
-    [getdate('2018-06-10 10:00:00').datetime, 9950, 10000, 9900, 9925, 12345, 0, 0],
-    [getdate('2018-06-10 11:00:00').datetime, 9925, 9975, 9945, 9900, 12345, 0, 0],
-    [getdate('2018-06-10 12:00:00').datetime, 9900, 9950, 9850, 9900, 12345, 0, 0]
-], columns=columns),
+tc7 = BTContainer(data=[
+    [0, 10000, 10050, 9950, 9975, 12345, 1, 0],
+    [1, 10000, 10050, 9950, 9975, 12345, 0, 0],
+    [2, 9975, 10600, 9900, 10100, 12345, 0, 0],
+    [3, 9950, 10000, 9900, 9925, 12345, 0, 0],
+    [4, 9925, 9975, 9945, 9900, 12345, 0, 0],
+    [5, 9900, 9950, 9850, 9900, 12345, 0, 0]],
     stop_loss=-0.02, roi=0.03, trades=1, profit_perc=0.03, sell_r=SellType.ROI)  #should be
     # stop_loss=-0.02, roi=0.03, trades=1, profit_perc=-0.012, sell_r=SellType.FORCE_SELL)  #
 
@@ -198,10 +193,10 @@ def test_backtest_results(default_conf, fee, mocker, caplog, data) -> None:
     # TODO: don't Mock fee to for now
     mocker.patch('freqtrade.exchange.Exchange.get_fee', MagicMock(return_value=0.0))
     patch_exchange(mocker)
-
+    frame = _build_dataframe(data.data)
     backtesting = Backtesting(default_conf)
-    backtesting.advise_buy = lambda a, m: data.data
-    backtesting.advise_sell = lambda a, m: data.data
+    backtesting.advise_buy = lambda a, m: frame
+    backtesting.advise_sell = lambda a, m: frame
     caplog.set_level(logging.DEBUG)
 
     pair = 'UNITTEST/BTC'