diff --git a/docs/hyperopt.md b/docs/hyperopt.md
index 6c1505e75..15ef26c99 100644
--- a/docs/hyperopt.md
+++ b/docs/hyperopt.md
@@ -381,12 +381,6 @@ Best result:
 
     44/100:    135 trades. Avg profit  0.57%. Total profit  0.03871918 BTC (0.7722Σ%). Avg duration 180.4 mins. Objective: 1.94367
 
-Buy hyperspace params:
-{   'adx-value': 44,
-    'rsi-value': 29,
-    'adx-enabled': False,
-    'rsi-enabled': True,
-    'trigger': 'bb_lower'}
 ROI table:
 {   0: 0.10674,
     21: 0.09158,
@@ -410,7 +404,7 @@ As stated in the comment, you can also use it as the value of the `minimal_roi`
 
 #### Default ROI Search Space
 
-If you are optimizing ROI, Freqtrade creates the 'roi' optimization hyperspace for you -- it's the hyperspace of components for the ROI tables. By default, each ROI table generated by the Freqtrade consists of 4 rows (steps). Hyperopt implements adaptive ranges for ROI tables with ranges for values in the ROI steps that depend on the ticker_interval used. By default the values can vary in the following ranges (for some of the most used ticker intervals, values are rounded to 5 digits after the decimal point):
+If you are optimizing ROI, Freqtrade creates the 'roi' optimization hyperspace for you -- it's the hyperspace of components for the ROI tables. By default, each ROI table generated by the Freqtrade consists of 4 rows (steps). Hyperopt implements adaptive ranges for ROI tables with ranges for values in the ROI steps that depend on the ticker_interval used. By default the values vary in the following ranges (for some of the most used ticker intervals, values are rounded to 5 digits after the decimal point):
 
 | # step | 1m |  | 5m |  | 1h |  | 1d |  |
 |---|---|---|---|---|---|---|---|---|
@@ -454,12 +448,46 @@ As stated in the comment, you can also use it as the value of the `stoploss` set
 
 #### Default Stoploss Search Space
 
-If you are optimizing stoploss values, Freqtrade creates the 'stoploss' optimization hyperspace for you. By default, the stoploss values in that hyperspace can vary in the range -0.35...-0.02, which is sufficient in most cases.
+If you are optimizing stoploss values, Freqtrade creates the 'stoploss' optimization hyperspace for you. By default, the stoploss values in that hyperspace vary in the range -0.35...-0.02, which is sufficient in most cases.
 
 If you have the `stoploss_space()` method in your custom hyperopt file, remove it in order to utilize Stoploss hyperoptimization space generated by Freqtrade by default.
 
 Override the `stoploss_space()` method and define the desired range in it if you need stoploss values to vary in other range during hyperoptimization. A sample for this method can be found in [user_data/hyperopts/sample_hyperopt_advanced.py](https://github.com/freqtrade/freqtrade/blob/develop/user_data/hyperopts/sample_hyperopt_advanced.py).
 
+### Understand Hyperopt Trailing Stop results
+
+If you are optimizing trailing stop values (i.e. if optimization search-space contains 'all' or 'trailing'), your result will look as follows and include trailing stop parameters:
+
+```
+Best result:
+
+    45/100:    606 trades. Avg profit  1.04%. Total profit  0.31555614 BTC ( 630.48Σ%). Avg duration 150.3 mins. Objective: -1.10161
+
+Trailing stop:
+{   'trailing_only_offset_is_reached': True,
+    'trailing_stop': True,
+    'trailing_stop_positive': -0.02005,
+    'trailing_stop_positive_offset': 0.05726}
+```
+
+In order to use these best trailing stop parameters found by Hyperopt in backtesting and for live trades/dry-run, copy-paste them as the values of the corresponding attributes of your custom strategy:
+
+```
+    # Trailing stop
+    # These attributes will be overridden if the config file contains corresponding values.
+    trailing_stop = True
+    trailing_stop_positive = -0.02005
+    trailing_stop_positive_offset = 0.05726
+    trailing_only_offset_is_reached = True
+```
+As stated in the comment, you can also use it as the values of the corresponding settings in the configuration file.
+
+#### Default Trailing Stop Search Space
+
+If you are optimizing trailing stop values, Freqtrade creates the 'trailing' optimization hyperspace for you. By default, the `trailing_stop` parameter is always set to True in that hyperspace, the value of the `trailing_only_offset_is_reached` vary between True and False, the values of the `trailing_stop_positive` and `trailing_stop_positive_offset` parameters vary in the ranges -0.35...-0.02 and 0.01...0.1 correspondingly, which is sufficient in most cases.
+
+Override the `trailing_space()` method and define the desired range in it if you need values of the trailing stop parameters to vary in other ranges during hyperoptimization. A sample for this method can be found in [user_data/hyperopts/sample_hyperopt_advanced.py](https://github.com/freqtrade/freqtrade/blob/develop/user_data/hyperopts/sample_hyperopt_advanced.py).
+
 ### Validate backtesting results
 
 Once the optimized strategy has been implemented into your strategy, you should backtest this strategy to make sure everything is working as expected.