diff --git a/freqtrade/configuration/timerange.py b/freqtrade/configuration/timerange.py
index 156f0e1e2..a8be873df 100644
--- a/freqtrade/configuration/timerange.py
+++ b/freqtrade/configuration/timerange.py
@@ -39,12 +39,12 @@ class TimeRange:
         if self.startts:
             self.startts = self.startts - seconds
 
-    def adjust_start_if_necessary(self, ticker_interval_secs: int, startup_candles: int,
+    def adjust_start_if_necessary(self, timeframe_secs: int, startup_candles: int,
                                   min_date: arrow.Arrow) -> None:
         """
         Adjust startts by <startup_candles> candles.
         Applies only if no startup-candles have been available.
-        :param ticker_interval_secs: Ticker interval in seconds e.g. `timeframe_to_seconds('5m')`
+        :param timeframe_secs: Ticker timeframe in seconds e.g. `timeframe_to_seconds('5m')`
         :param startup_candles: Number of candles to move start-date forward
         :param min_date: Minimum data date loaded. Key kriterium to decide if start-time
                          has to be moved
@@ -55,7 +55,7 @@ class TimeRange:
             # If no startts was defined, or backtest-data starts at the defined backtest-date
             logger.warning("Moving start-date by %s candles to account for startup time.",
                            startup_candles)
-            self.startts = (min_date.timestamp + ticker_interval_secs * startup_candles)
+            self.startts = (min_date.timestamp + timeframe_secs * startup_candles)
             self.starttype = 'date'
 
     @staticmethod
diff --git a/freqtrade/optimize/hyperopt_interface.py b/freqtrade/optimize/hyperopt_interface.py
index 142f305df..ac41ba92f 100644
--- a/freqtrade/optimize/hyperopt_interface.py
+++ b/freqtrade/optimize/hyperopt_interface.py
@@ -106,10 +106,10 @@ class IHyperOpt(ABC):
         roi_t_alpha = 1.0
         roi_p_alpha = 1.0
 
-        ticker_interval_mins = timeframe_to_minutes(IHyperOpt.ticker_interval)
+        timeframe_mins = timeframe_to_minutes(IHyperOpt.ticker_interval)
 
         # We define here limits for the ROI space parameters automagically adapted to the
-        # ticker_interval used by the bot:
+        # timeframe used by the bot:
         #
         # * 'roi_t' (limits for the time intervals in the ROI tables) components
         #   are scaled linearly.
@@ -117,8 +117,8 @@ class IHyperOpt(ABC):
         #
         # The scaling is designed so that it maps exactly to the legacy Freqtrade roi_space()
         # method for the 5m ticker interval.
-        roi_t_scale = ticker_interval_mins / 5
-        roi_p_scale = math.log1p(ticker_interval_mins) / math.log1p(5)
+        roi_t_scale = timeframe_mins / 5
+        roi_p_scale = math.log1p(timeframe_mins) / math.log1p(5)
         roi_limits = {
             'roi_t1_min': int(10 * roi_t_scale * roi_t_alpha),
             'roi_t1_max': int(120 * roi_t_scale * roi_t_alpha),
diff --git a/tests/optimize/__init__.py b/tests/optimize/__init__.py
index fdbaaa54d..8756143a0 100644
--- a/tests/optimize/__init__.py
+++ b/tests/optimize/__init__.py
@@ -7,7 +7,7 @@ from freqtrade.exchange import timeframe_to_minutes
 from freqtrade.strategy.interface import SellType
 
 ticker_start_time = arrow.get(2018, 10, 3)
-tests_ticker_interval = '1h'
+tests_timeframe = '1h'
 
 
 class BTrade(NamedTuple):
@@ -36,7 +36,7 @@ class BTContainer(NamedTuple):
 
 
 def _get_frame_time_from_offset(offset):
-    return ticker_start_time.shift(minutes=(offset * timeframe_to_minutes(tests_ticker_interval))
+    return ticker_start_time.shift(minutes=(offset * timeframe_to_minutes(tests_timeframe))
                                    ).datetime
 
 
diff --git a/tests/optimize/test_backtest_detail.py b/tests/optimize/test_backtest_detail.py
index 54f4c8796..3f6cc8c9a 100644
--- a/tests/optimize/test_backtest_detail.py
+++ b/tests/optimize/test_backtest_detail.py
@@ -9,7 +9,7 @@ from freqtrade.optimize.backtesting import Backtesting
 from freqtrade.strategy.interface import SellType
 from tests.conftest import patch_exchange
 from tests.optimize import (BTContainer, BTrade, _build_backtest_dataframe,
-                            _get_frame_time_from_offset, tests_ticker_interval)
+                            _get_frame_time_from_offset, tests_timeframe)
 
 # Test 0: Sell with signal sell in candle 3
 # Test with Stop-loss at 1%
@@ -293,7 +293,7 @@ def test_backtest_results(default_conf, fee, mocker, caplog, data) -> None:
     """
     default_conf["stoploss"] = data.stop_loss
     default_conf["minimal_roi"] = data.roi
-    default_conf["ticker_interval"] = tests_ticker_interval
+    default_conf["ticker_interval"] = tests_timeframe
     default_conf["trailing_stop"] = data.trailing_stop
     default_conf["trailing_only_offset_is_reached"] = data.trailing_only_offset_is_reached
     # Only add this to configuration If it's necessary
diff --git a/tests/optimize/test_backtesting.py b/tests/optimize/test_backtesting.py
index a5ab6d84c..508c12e89 100644
--- a/tests/optimize/test_backtesting.py
+++ b/tests/optimize/test_backtesting.py
@@ -307,7 +307,7 @@ def test_backtesting_init(mocker, default_conf, order_types) -> None:
     get_fee = mocker.patch('freqtrade.exchange.Exchange.get_fee', MagicMock(return_value=0.5))
     backtesting = Backtesting(default_conf)
     assert backtesting.config == default_conf
-    assert backtesting.ticker_interval == '5m'
+    assert backtesting.timeframe == '5m'
     assert callable(backtesting.strategy.tickerdata_to_dataframe)
     assert callable(backtesting.strategy.advise_buy)
     assert callable(backtesting.strategy.advise_sell)