diff --git a/docs/hyperopt.md b/docs/hyperopt.md
index 06b90cff9..c4dd76009 100644
--- a/docs/hyperopt.md
+++ b/docs/hyperopt.md
@@ -98,12 +98,13 @@ So let's write the buy strategy using these values:
                 conditions.append(dataframe['rsi'] < params['rsi-value'])
 
             # TRIGGERS
-            if params['trigger'] == 'bb_lower':
-                conditions.append(dataframe['close'] < dataframe['bb_lowerband'])
-            if params['trigger'] == 'macd_cross_signal':
-                conditions.append(qtpylib.crossed_above(
-                    dataframe['macd'], dataframe['macdsignal']
-                ))
+            if 'trigger' in params:
+                if params['trigger'] == 'bb_lower':
+                    conditions.append(dataframe['close'] < dataframe['bb_lowerband'])
+                if params['trigger'] == 'macd_cross_signal':
+                    conditions.append(qtpylib.crossed_above(
+                        dataframe['macd'], dataframe['macdsignal']
+                    ))
 
             dataframe.loc[
                 reduce(lambda x, y: x & y, conditions),
diff --git a/freqtrade/optimize/default_hyperopt.py b/freqtrade/optimize/default_hyperopt.py
index 1c2d92950..315a1e8a5 100644
--- a/freqtrade/optimize/default_hyperopt.py
+++ b/freqtrade/optimize/default_hyperopt.py
@@ -57,16 +57,17 @@ class DefaultHyperOpts(IHyperOpt):
                 conditions.append(dataframe['rsi'] < params['rsi-value'])
 
             # TRIGGERS
-            if params['trigger'] == 'bb_lower':
-                conditions.append(dataframe['close'] < dataframe['bb_lowerband'])
-            if params['trigger'] == 'macd_cross_signal':
-                conditions.append(qtpylib.crossed_above(
-                    dataframe['macd'], dataframe['macdsignal']
-                ))
-            if params['trigger'] == 'sar_reversal':
-                conditions.append(qtpylib.crossed_above(
-                    dataframe['close'], dataframe['sar']
-                ))
+            if 'trigger' in params:
+                if params['trigger'] == 'bb_lower':
+                    conditions.append(dataframe['close'] < dataframe['bb_lowerband'])
+                if params['trigger'] == 'macd_cross_signal':
+                    conditions.append(qtpylib.crossed_above(
+                        dataframe['macd'], dataframe['macdsignal']
+                    ))
+                if params['trigger'] == 'sar_reversal':
+                    conditions.append(qtpylib.crossed_above(
+                        dataframe['close'], dataframe['sar']
+                    ))
 
             dataframe.loc[
                 reduce(lambda x, y: x & y, conditions),
diff --git a/user_data/hyperopts/sample_hyperopt.py b/user_data/hyperopts/sample_hyperopt.py
index ee4e4dca7..1700af932 100644
--- a/user_data/hyperopts/sample_hyperopt.py
+++ b/user_data/hyperopts/sample_hyperopt.py
@@ -66,16 +66,17 @@ class SampleHyperOpts(IHyperOpt):
                 conditions.append(dataframe['rsi'] < params['rsi-value'])
 
             # TRIGGERS
-            if params['trigger'] == 'bb_lower':
-                conditions.append(dataframe['close'] < dataframe['bb_lowerband'])
-            if params['trigger'] == 'macd_cross_signal':
-                conditions.append(qtpylib.crossed_above(
-                    dataframe['macd'], dataframe['macdsignal']
-                ))
-            if params['trigger'] == 'sar_reversal':
-                conditions.append(qtpylib.crossed_above(
-                    dataframe['close'], dataframe['sar']
-                ))
+            if 'trigger' in params:
+                if params['trigger'] == 'bb_lower':
+                    conditions.append(dataframe['close'] < dataframe['bb_lowerband'])
+                if params['trigger'] == 'macd_cross_signal':
+                    conditions.append(qtpylib.crossed_above(
+                        dataframe['macd'], dataframe['macdsignal']
+                    ))
+                if params['trigger'] == 'sar_reversal':
+                    conditions.append(qtpylib.crossed_above(
+                        dataframe['close'], dataframe['sar']
+                    ))
 
             dataframe.loc[
                 reduce(lambda x, y: x & y, conditions),