diff --git a/freqtrade/tests/test_analyze.py b/freqtrade/tests/test_analyze.py
index e716eb3ad..d063de775 100644
--- a/freqtrade/tests/test_analyze.py
+++ b/freqtrade/tests/test_analyze.py
@@ -1,4 +1,5 @@
 # pragma pylint: disable=missing-docstring
+import json
 import pytest
 import arrow
 from pandas import DataFrame
@@ -6,31 +7,19 @@ from pandas import DataFrame
 from freqtrade.analyze import parse_ticker_dataframe, populate_buy_trend, populate_indicators, \
     get_buy_signal
 
-RESULT_BITTREX = {
-    'success': True,
-    'message': '',
-    'result': [
-        {'O': 0.00065311, 'H': 0.00065311, 'L': 0.00065311, 'C': 0.00065311, 'V': 22.17210568, 'T': '2017-08-30T10:40:00', 'BV': 0.01448082},
-        {'O': 0.00066194, 'H': 0.00066195, 'L': 0.00066194, 'C': 0.00066195, 'V': 33.4727437, 'T': '2017-08-30T10:34:00', 'BV': 0.02215696},
-        {'O': 0.00065311, 'H': 0.00065311, 'L': 0.00065311, 'C': 0.00065311, 'V': 53.85127609, 'T': '2017-08-30T10:37:00', 'BV': 0.0351708},
-        {'O': 0.00066194, 'H': 0.00066194, 'L': 0.00065311, 'C': 0.00065311, 'V': 46.29210665, 'T': '2017-08-30T10:42:00', 'BV': 0.03063118},
-    ]
-}
-
 @pytest.fixture
 def result():
-    return parse_ticker_dataframe(RESULT_BITTREX['result'], arrow.get('2017-08-30T10:00:00'))
+    with open('freqtrade/tests/testdata/btc-eth.json') as data_file:
+        data = json.load(data_file)
+
+    return parse_ticker_dataframe(data['result'], arrow.get('2017-08-30T10:00:00'))
 
 def test_dataframe_has_correct_columns(result):
     assert result.columns.tolist() == \
                         ['close', 'high', 'low', 'open', 'date', 'volume']
 
-def test_orders_by_date(result):
-    assert result['date'].tolist() == \
-                        ['2017-08-30T10:34:00',
-                        '2017-08-30T10:37:00',
-                        '2017-08-30T10:40:00',
-                        '2017-08-30T10:42:00']
+def test_dataframe_has_correct_length(result):
+    assert len(result.index) == 5751
 
 def test_populates_buy_trend(result):
     dataframe = populate_buy_trend(populate_indicators(result))