diff --git a/docs/strategy-customization.md b/docs/strategy-customization.md
index adcdf0208..ca76071af 100644
--- a/docs/strategy-customization.md
+++ b/docs/strategy-customization.md
@@ -138,15 +138,19 @@ def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
     """
     dataframe.loc[
         (
-            (dataframe['adx'] > 30) &
-            (dataframe['tema'] <= dataframe['bb_middleband']) &
-            (dataframe['tema'] > dataframe['tema'].shift(1))
+            (qtpylib.crossed_above(dataframe['rsi'], 30)) &  # Signal: RSI crosses above 30
+            (dataframe['tema'] <= dataframe['bb_middleband']) &  # Guard
+            (dataframe['tema'] > dataframe['tema'].shift(1)) &  # Guard
+            (dataframe['volume'] > 0)  # Make sure Volume is not 0
         ),
         'buy'] = 1
 
     return dataframe
 ```
 
+!!! Note
+    Buying requires sellers to buy from - therefore volume needs to be > 0 (`dataframe['volume'] > 0`) to make sure that the bot does not buy/sell in no-activity periods.
+
 ### Sell signal rules
 
 Edit the method `populate_sell_trend()` into your strategy file to update your sell strategy.
@@ -168,9 +172,10 @@ def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame
     """
     dataframe.loc[
         (
-            (dataframe['adx'] > 70) &
-            (dataframe['tema'] > dataframe['bb_middleband']) &
-            (dataframe['tema'] < dataframe['tema'].shift(1))
+            (qtpylib.crossed_above(dataframe['rsi'], 70)) &  # Signal: RSI crosses above 70
+            (dataframe['tema'] > dataframe['bb_middleband']) &  # Guard
+            (dataframe['tema'] < dataframe['tema'].shift(1)) &  # Guard
+            (dataframe['volume'] > 0)  # Make sure Volume is not 0
         ),
         'sell'] = 1
     return dataframe
diff --git a/tests/strategy/test_strategy.py b/tests/strategy/test_strategy.py
index 88e29b40e..52216e0ef 100644
--- a/tests/strategy/test_strategy.py
+++ b/tests/strategy/test_strategy.py
@@ -39,7 +39,7 @@ def test_search_strategy():
 def test_load_strategy(default_conf, result):
     default_conf.update({'strategy': 'SampleStrategy'})
     resolver = StrategyResolver(default_conf)
-    assert 'adx' in resolver.strategy.advise_indicators(result, {'pair': 'ETH/BTC'})
+    assert 'rsi' in resolver.strategy.advise_indicators(result, {'pair': 'ETH/BTC'})
 
 
 def test_load_strategy_base64(result, caplog, default_conf):
@@ -48,7 +48,7 @@ def test_load_strategy_base64(result, caplog, default_conf):
     default_conf.update({'strategy': 'SampleStrategy:{}'.format(encoded_string)})
 
     resolver = StrategyResolver(default_conf)
-    assert 'adx' in resolver.strategy.advise_indicators(result, {'pair': 'ETH/BTC'})
+    assert 'rsi' in resolver.strategy.advise_indicators(result, {'pair': 'ETH/BTC'})
     # Make sure strategy was loaded from base64 (using temp directory)!!
     assert log_has_re(r"Using resolved strategy SampleStrategy from '"
                       + tempfile.gettempdir() + r"/.*/SampleStrategy\.py'\.\.\.", caplog)
diff --git a/user_data/strategies/sample_strategy.py b/user_data/strategies/sample_strategy.py
index 623addb1e..35ddbdf68 100644
--- a/user_data/strategies/sample_strategy.py
+++ b/user_data/strategies/sample_strategy.py
@@ -34,9 +34,8 @@ class SampleStrategy(IStrategy):
     # Minimal ROI designed for the strategy.
     # This attribute will be overridden if the config file contains "minimal_roi".
     minimal_roi = {
-        "40": 0.0,
-        "30": 0.01,
-        "20": 0.02,
+        "60": 0.01,
+        "30": 0.02,
         "0": 0.04
     }
 
@@ -99,13 +98,16 @@ class SampleStrategy(IStrategy):
         :return: a Dataframe with all mandatory indicators for the strategies
         """
 
-        # Momentum Indicator
+        # Momentum Indicators
         # ------------------------------------
 
-        # ADX
-        dataframe['adx'] = ta.ADX(dataframe)
+        # RSI
+        dataframe['rsi'] = ta.RSI(dataframe)
 
         """
+        # ADX
+        # dataframe['adx'] = ta.ADX(dataframe)
+
         # Awesome oscillator
         dataframe['ao'] = qtpylib.awesome_oscillator(dataframe)
 
@@ -133,9 +135,6 @@ class SampleStrategy(IStrategy):
         # ROC
         dataframe['roc'] = ta.ROC(dataframe)
 
-        # RSI
-        dataframe['rsi'] = ta.RSI(dataframe)
-
         # Inverse Fisher transform on RSI, values [-1.0, 1.0] (https://goo.gl/2JGGoy)
         rsi = 0.1 * (dataframe['rsi'] - 50)
         dataframe['fisher_rsi'] = (numpy.exp(2 * rsi) - 1) / (numpy.exp(2 * rsi) + 1)
@@ -255,7 +254,7 @@ class SampleStrategy(IStrategy):
         dataframe['ha_low'] = heikinashi['low']
         """
 
-        # Retrieve best bid and best ask
+        # Retrieve best bid and best ask from the orderbook
         # ------------------------------------
         """
         # first check if dataprovider is available
@@ -277,9 +276,9 @@ class SampleStrategy(IStrategy):
         """
         dataframe.loc[
             (
-                (dataframe['adx'] > 30) &
-                (dataframe['tema'] <= dataframe['bb_middleband']) &
-                (dataframe['tema'] > dataframe['tema'].shift(1)) &
+                (qtpylib.crossed_above(dataframe['rsi'], 30)) &  # Signal: RSI crosses above 30
+                (dataframe['tema'] <= dataframe['bb_middleband']) &  # Guard: tema below BB middle
+                (dataframe['tema'] > dataframe['tema'].shift(1)) &  # Guard: tema is raising
                 (dataframe['volume'] > 0)  # Make sure Volume is not 0
             ),
             'buy'] = 1
@@ -295,9 +294,9 @@ class SampleStrategy(IStrategy):
         """
         dataframe.loc[
             (
-                (dataframe['adx'] > 70) &
-                (dataframe['tema'] > dataframe['bb_middleband']) &
-                (dataframe['tema'] < dataframe['tema'].shift(1)) &
+                (qtpylib.crossed_above(dataframe['rsi'], 70)) &  # Signal: RSI crosses above 70
+                (dataframe['tema'] > dataframe['bb_middleband']) &  # Guard: tema above BB middle
+                (dataframe['tema'] < dataframe['tema'].shift(1)) &  # Guard: tema is falling
                 (dataframe['volume'] > 0)  # Make sure Volume is not 0
             ),
             'sell'] = 1