Merge pull request #232 from gcarq/tweak-hyperopt

Tweak Hyperopt

freqtrade/optimize/backtesting.py

@@ -64,7 +64,7 @@ def generate_text_table(
     return tabulate(tabular_data, headers=headers)
 
 
-def backtest(config: Dict, processed: Dict[str, DataFrame],
+def backtest(stake_amount: float, processed: Dict[str, DataFrame],
              max_open_trades: int = 0, realistic: bool = True) -> DataFrame:
     """
     Implements backtesting functionality
@@ -98,8 +98,8 @@ def backtest(config: Dict, processed: Dict[str, DataFrame],
             trade = Trade(
                 open_rate=row.close,
                 open_date=row.date,
-                stake_amount=config['stake_amount'],
-                amount=config['stake_amount'] / row.open,
+                stake_amount=stake_amount,
+                amount=stake_amount / row.open,
                 fee=exchange.get_fee()
             )
 
@@ -170,7 +170,7 @@ def start(args):
 
     # Execute backtest and print results
     results = backtest(
-        config, preprocess(data), max_open_trades, args.realistic_simulation
+        config['stake_amount'], preprocess(data), max_open_trades, args.realistic_simulation
     )
     logger.info(
         '\n====================== BACKTESTING REPORT ======================================\n%s',

freqtrade/optimize/hyperopt.py

@@ -32,9 +32,13 @@ TARGET_TRADES = 1100
 TOTAL_TRIES = None
 _CURRENT_TRIES = 0
 
-TOTAL_PROFIT_TO_BEAT = 3
-AVG_PROFIT_TO_BEAT = 0.2
-AVG_DURATION_TO_BEAT = 50
+TOTAL_PROFIT_TO_BEAT = 0
+AVG_PROFIT_TO_BEAT = 0
+AVG_DURATION_TO_BEAT = 100
+
+# this is expexted avg profit * expected trade count
+# for example 3.5%, 1100 trades, EXPECTED_MAX_PROFIT = 3.85
+EXPECTED_MAX_PROFIT = 3.85
 
 # Configuration and data used by hyperopt
 PROCESSED = optimize.preprocess(optimize.load_data())
@@ -101,12 +105,10 @@ def log_results(results):
     current_try = results['current_tries']
     total_tries = results['total_tries']
     result = results['result']
-    profit = results['total_profit'] / 1000
-
-    outcome = '{:5d}/{}: {}'.format(current_try, total_tries, result)
+    profit = results['total_profit']
 
     if profit >= TOTAL_PROFIT_TO_BEAT:
-        logger.info(outcome)
+        logger.info('\n{:5d}/{}: {}'.format(current_try, total_tries, result))
     else:
         print('.', end='')
         sys.stdout.flush()
@@ -118,15 +120,15 @@ def optimizer(params):
     from freqtrade.optimize import backtesting
     backtesting.populate_buy_trend = buy_strategy_generator(params)
 
-    results = backtest(OPTIMIZE_CONFIG, PROCESSED)
+    results = backtest(OPTIMIZE_CONFIG['stake_amount'], PROCESSED)
 
     result = format_results(results)
 
-    total_profit = results.profit_percent.sum() * 1000
+    total_profit = results.profit_percent.sum()
     trade_count = len(results.index)
 
     trade_loss = 1 - 0.35 * exp(-(trade_count - TARGET_TRADES) ** 2 / 10 ** 5.2)
-    profit_loss = max(0, 1 - total_profit / 10000)  # max profit 10000
+    profit_loss = max(0, 1 - total_profit / EXPECTED_MAX_PROFIT)
 
     _CURRENT_TRIES += 1
 
@@ -142,8 +144,6 @@ def optimizer(params):
         'result': result,
         'results': results
     }
-
-    # logger.info('{:5d}/{}: {}'.format(_CURRENT_TRIES, TOTAL_TRIES, result))
     log_results(result_data)
 
     return {
@@ -157,7 +157,7 @@ def optimizer(params):
 
 def format_results(results: DataFrame):
     return ('Made {:6d} buys. Average profit {: 5.2f}%. '
-            'Total profit was {: 7.3f}. Average duration {:5.1f} mins.').format(
+            'Total profit was {: 11.8f} BTC. Average duration {:5.1f} mins.').format(
                 len(results.index),
                 results.profit_percent.mean() * 100.0,
                 results.profit_BTC.sum(),

freqtrade/tests/test_optimize_backtesting.py

@@ -12,7 +12,7 @@ def test_backtest(default_conf, mocker):
     exchange._API = Bittrex({'key': '', 'secret': ''})
 
     data = optimize.load_data(ticker_interval=5, pairs=['BTC_ETH'])
-    results = backtest(default_conf, optimize.preprocess(data), 10, True)
+    results = backtest(default_conf['stake_amount'], optimize.preprocess(data), 10, True)
     num_results = len(results)
     assert num_results > 0
 
@@ -23,7 +23,7 @@ def test_1min_ticker_interval(default_conf, mocker):
 
     # Run a backtesting for an exiting 5min ticker_interval
     data = optimize.load_data(ticker_interval=1, pairs=['BTC_UNITEST'])
-    results = backtest(default_conf, optimize.preprocess(data), 1, True)
+    results = backtest(default_conf['stake_amount'], optimize.preprocess(data), 1, True)
     assert len(results) > 0