diff --git a/freqtrade/optimize/backtesting.py b/freqtrade/optimize/backtesting.py
index 47be60802..6f7f14b8c 100644
--- a/freqtrade/optimize/backtesting.py
+++ b/freqtrade/optimize/backtesting.py
@@ -5,7 +5,7 @@ import logging
 from typing import Tuple, Dict
 
 import arrow
-from pandas import DataFrame
+from pandas import DataFrame, Series
 from tabulate import tabulate
 
 from freqtrade import exchange
@@ -19,20 +19,17 @@ from freqtrade.persistence import Trade
 logger = logging.getLogger(__name__)
 
 
-def get_timeframe(data: Dict[str, Dict]) -> Tuple[arrow.Arrow, arrow.Arrow]:
+def get_timeframe(data: Dict[str, DataFrame]) -> Tuple[arrow.Arrow, arrow.Arrow]:
     """
     Get the maximum timeframe for the given backtest data
-    :param data: dictionary with backtesting data
+    :param data: dictionary with preprocessed backtesting data
     :return: tuple containing min_date, max_date
     """
-    min_date, max_date = None, None
-    for values in data.values():
-        sorted_values = sorted(values, key=lambda d: arrow.get(d['T']))
-        if not min_date or sorted_values[0]['T'] < min_date:
-            min_date = sorted_values[0]['T']
-        if not max_date or sorted_values[-1]['T'] > max_date:
-            max_date = sorted_values[-1]['T']
-    return arrow.get(min_date), arrow.get(max_date)
+    all_dates = Series([])
+    for pair, pair_data in data.items():
+        all_dates = all_dates.append(pair_data['date'])
+    all_dates.sort_values(inplace=True)
+    return arrow.get(all_dates.iloc[0]), arrow.get(all_dates.iloc[-1])
 
 
 def generate_text_table(
@@ -84,7 +81,8 @@ def backtest(stake_amount: float, processed: Dict[str, DataFrame],
         ticker = populate_sell_trend(populate_buy_trend(pair_data))
         # for each buy point
         lock_pair_until = None
-        for row in ticker[ticker.buy == 1].itertuples(index=True):
+        buy_subset = ticker[ticker.buy == 1][['buy', 'open', 'close', 'date', 'sell']]
+        for row in buy_subset.itertuples(index=True):
             if realistic:
                 if lock_pair_until is not None and row.Index <= lock_pair_until:
                     continue
@@ -106,7 +104,8 @@ def backtest(stake_amount: float, processed: Dict[str, DataFrame],
             )
 
             # calculate win/lose forwards from buy point
-            for row2 in ticker[row.Index + 1:].itertuples(index=True):
+            sell_subset = ticker[row.Index + 1:][['close', 'date', 'sell']]
+            for row2 in sell_subset.itertuples(index=True):
                 if max_open_trades > 0:
                     # Increase trade_count_lock for every iteration
                     trade_count_lock[row2.date] = trade_count_lock.get(row2.date, 0) + 1
@@ -157,10 +156,6 @@ def start(args):
         logger.info('Using stake_currency: %s ...', config['stake_currency'])
         logger.info('Using stake_amount: %s ...', config['stake_amount'])
 
-    # Print timeframe
-    min_date, max_date = get_timeframe(data)
-    logger.info('Measuring data from %s up to %s ...', min_date.isoformat(), max_date.isoformat())
-
     max_open_trades = 0
     if args.realistic_simulation:
         logger.info('Using max_open_trades: %s ...', config['max_open_trades'])
@@ -170,9 +165,14 @@ def start(args):
     from freqtrade import main
     main._CONF = config
 
+    preprocessed = preprocess(data)
+    # Print timeframe
+    min_date, max_date = get_timeframe(preprocessed)
+    logger.info('Measuring data from %s up to %s ...', min_date.isoformat(), max_date.isoformat())
+
     # Execute backtest and print results
     results = backtest(
-        config['stake_amount'], preprocess(data), max_open_trades, args.realistic_simulation
+        config['stake_amount'], preprocessed, max_open_trades, args.realistic_simulation
     )
     logger.info(
         '\n====================== BACKTESTING REPORT ================================\n%s',
diff --git a/freqtrade/tests/optimize/test_backtesting.py b/freqtrade/tests/optimize/test_backtesting.py
index e3e34de1d..8b416e64e 100644
--- a/freqtrade/tests/optimize/test_backtesting.py
+++ b/freqtrade/tests/optimize/test_backtesting.py
@@ -5,6 +5,7 @@ import pandas as pd
 # from unittest.mock import MagicMock
 from freqtrade import exchange, optimize
 from freqtrade.exchange import Bittrex
+from freqtrade.optimize import preprocess
 from freqtrade.optimize.backtesting import backtest, generate_text_table, get_timeframe
 # import freqtrade.optimize.backtesting as backtesting
 
@@ -27,7 +28,7 @@ def test_generate_text_table():
 
 
 def test_get_timeframe():
-    data = optimize.load_data(ticker_interval=1, pairs=['BTC_UNITEST'])
+    data = preprocess(optimize.load_data(ticker_interval=1, pairs=['BTC_UNITEST']))
     min_date, max_date = get_timeframe(data)
     assert min_date.isoformat() == '2017-11-04T23:02:00+00:00'
     assert max_date.isoformat() == '2017-11-14T22:59:00+00:00'