diff --git a/freqtrade/optimize/hyperopt.py b/freqtrade/optimize/hyperopt.py
index 16bb30fd4..60778f993 100644
--- a/freqtrade/optimize/hyperopt.py
+++ b/freqtrade/optimize/hyperopt.py
@@ -225,6 +225,16 @@ def calculate_loss(total_profit: float, trade_count: int, trade_duration: float)
     return trade_loss + profit_loss + duration_loss
 
 
+def generate_roi_table(params):
+    roi_table = {}
+    roi_table["0"] = params['roi_p1'] + params['roi_p2'] + params['roi_p3']
+    roi_table[str(params['roi_t3'])] = params['roi_p1'] + params['roi_p2']
+    roi_table[str(params['roi_t3'] + params['roi_t2'])] = params['roi_p1']
+    roi_table[str(params['roi_t3'] + params['roi_t2'] + params['roi_t1'])] = 0
+
+    return roi_table
+
+
 def roi_space() -> List[Dict]:
     return {
         'roi_t1': hp.quniform('roi_t1', 10, 220, 10),
@@ -236,6 +246,12 @@ def roi_space() -> List[Dict]:
     }
 
 
+def stoploss_space() -> Dict:
+    return {
+        'stoploss': hp.uniform('stoploss', -0.5, -0.02),
+    }
+
+
 def indicator_space() -> List[Dict]:
     """
     Define your Hyperopt space for searching strategy parameters
@@ -293,12 +309,11 @@ def indicator_space() -> List[Dict]:
             {'type': 'heiken_reversal_bull'},
             {'type': 'di_cross'},
         ]),
-        'stoploss': hp.uniform('stoploss', -0.5, -0.02),
     }
 
 
 def hyperopt_space() -> List[Dict]:
-    return {**indicator_space(), **roi_space()}
+    return {**indicator_space(), **roi_space(), **stoploss_space()}
 
 
 def buy_strategy_generator(params) -> None:
@@ -378,6 +393,10 @@ def buy_strategy_generator(params) -> None:
 def optimizer(params):
     global _CURRENT_TRIES
 
+    if 'roi_t1' in params:
+        strategy = Strategy()
+        strategy.minimal_roi = generate_roi_table(params)
+
     backtesting.populate_buy_trend = buy_strategy_generator(params)
 
     results = backtest({'stake_amount': OPTIMIZE_CONFIG['stake_amount'],
@@ -498,6 +517,8 @@ def start(args):
         )
 
     logger.info('Best parameters:\n%s', json.dumps(best_parameters, indent=4))
+    if 'roi_t1' in best_parameters:
+        logger.info('ROI table:\n%s', generate_roi_table(best_parameters))
     logger.info('Best Result:\n%s', best_result)
 
     # Store trials result to file to resume next time
diff --git a/freqtrade/tests/optimize/test_hyperopt.py b/freqtrade/tests/optimize/test_hyperopt.py
index 9e5517df6..13c45ac94 100644
--- a/freqtrade/tests/optimize/test_hyperopt.py
+++ b/freqtrade/tests/optimize/test_hyperopt.py
@@ -1,6 +1,6 @@
 # pragma pylint: disable=missing-docstring,W0212,C0103
 from freqtrade.optimize.hyperopt import calculate_loss, TARGET_TRADES, EXPECTED_MAX_PROFIT, start, \
-    log_results, save_trials, read_trials
+    log_results, save_trials, read_trials, generate_roi_table
 
 
 def test_loss_calculation_prefer_correct_trade_count():
@@ -234,3 +234,15 @@ def test_read_trials_returns_trials_file(mocker):
     assert read_trials() == trials
     mock_open.assert_called_once()
     mock_load.assert_called_once()
+
+
+def test_roi_table_generation():
+    params = {
+        'roi_t1': 5,
+        'roi_t2': 10,
+        'roi_t3': 15,
+        'roi_p1': 1,
+        'roi_p2': 2,
+        'roi_p3': 3,
+    }
+    assert generate_roi_table(params) == {'0': 6, '15': 3, '25': 1, '30': 0}