Merge pull request #99 from gcarq/more_triggers2

Expanding hyperopt

freqtrade/analyze.py

@@ -39,9 +39,7 @@ def populate_indicators(dataframe: DataFrame) -> DataFrame:
     dataframe['sma'] = ta.SMA(dataframe, timeperiod=40)
     dataframe['tema'] = ta.TEMA(dataframe, timeperiod=9)
     dataframe['mfi'] = ta.MFI(dataframe)
-    dataframe['cci'] = ta.CCI(dataframe)
     dataframe['rsi'] = ta.RSI(dataframe)
-    dataframe['mom'] = ta.MOM(dataframe)
     dataframe['ema5'] = ta.EMA(dataframe, timeperiod=5)
     dataframe['ema10'] = ta.EMA(dataframe, timeperiod=10)
     dataframe['ema50'] = ta.EMA(dataframe, timeperiod=50)
@@ -51,6 +49,9 @@ def populate_indicators(dataframe: DataFrame) -> DataFrame:
     dataframe['macd'] = macd['macd']
     dataframe['macdsignal'] = macd['macdsignal']
     dataframe['macdhist'] = macd['macdhist']
+    hilbert = ta.HT_SINE(dataframe)
+    dataframe['htsine'] = hilbert['sine']
+    dataframe['htleadsine'] = hilbert['leadsine']
     return dataframe
 
 

freqtrade/tests/test_hyperopt.py

@@ -15,41 +15,44 @@ from freqtrade.vendor.qtpylib.indicators import crossed_above
 logging.disable(logging.DEBUG)  # disable debug logs that slow backtesting a lot
 
 # set TARGET_TRADES to suit your number concurrent trades so its realistic to 20days of data
-TARGET_TRADES = 1200
+TARGET_TRADES = 1300
-
+TOTAL_TRIES = 4
+current_tries = 0
 
 def buy_strategy_generator(params):
-    print(params)
-
     def populate_buy_trend(dataframe: DataFrame) -> DataFrame:
         conditions = []
         # GUARDS AND TRENDS
         if params['uptrend_long_ema']['enabled']:
             conditions.append(dataframe['ema50'] > dataframe['ema100'])
+        if params['uptrend_short_ema']['enabled']:
+            conditions.append(dataframe['ema5'] > dataframe['ema10'])
         if params['mfi']['enabled']:
             conditions.append(dataframe['mfi'] < params['mfi']['value'])
         if params['fastd']['enabled']:
             conditions.append(dataframe['fastd'] < params['fastd']['value'])
         if params['adx']['enabled']:
             conditions.append(dataframe['adx'] > params['adx']['value'])
-        if params['cci']['enabled']:
-            conditions.append(dataframe['cci'] < params['cci']['value'])
         if params['rsi']['enabled']:
             conditions.append(dataframe['rsi'] < params['rsi']['value'])
         if params['over_sar']['enabled']:
             conditions.append(dataframe['close'] > dataframe['sar'])
+        if params['green_candle']['enabled']:
+            conditions.append(dataframe['close'] > dataframe['open'])
         if params['uptrend_sma']['enabled']:
             prevsma = dataframe['sma'].shift(1)
             conditions.append(dataframe['sma'] > prevsma)
 
-        prev_fastd = dataframe['fastd'].shift(1)
         # TRIGGERS
         triggers = {
             'lower_bb': dataframe['tema'] <= dataframe['blower'],
-            'faststoch10': (dataframe['fastd'] >= 10) & (prev_fastd < 10),
+            'faststoch10': (crossed_above(dataframe['fastd'], 10.0)),
             'ao_cross_zero': (crossed_above(dataframe['ao'], 0.0)),
             'ema5_cross_ema10': (crossed_above(dataframe['ema5'], dataframe['ema10'])),
             'macd_cross_signal': (crossed_above(dataframe['macd'], dataframe['macdsignal'])),
+            'sar_reversal': (crossed_above(dataframe['close'], dataframe['sar'])),
+            'stochf_cross': (crossed_above(dataframe['fastk'], dataframe['fastd'])),
+            'ht_sine': (crossed_above(dataframe['htleadsine'], dataframe['htsine'])),
         }
         conditions.append(triggers.get(params['trigger']['type']))
 
@@ -72,13 +75,16 @@ def test_hyperopt(backtest_conf, backdata, mocker):
         results = backtest(backtest_conf, backdata, mocker)
 
         result = format_results(results)
-        print(result)
 
         total_profit = results.profit.sum() * 1000
         trade_count = len(results.index)
 
-        trade_loss = 1 - 0.8 * exp(-(trade_count - TARGET_TRADES) ** 2 / 10 ** 5)
+        trade_loss = 1 - 0.4 * exp(-(trade_count - TARGET_TRADES) ** 2 / 10 ** 5.2)
-        profit_loss = exp(-total_profit**3 / 10**11)
+        profit_loss = max(0, 1 - total_profit / 15000)  # max profit 15000
+
+        global current_tries
+        current_tries += 1
+        print('{}/{}: {}'.format(current_tries, TOTAL_TRIES, result))
 
         return {
             'loss': trade_loss + profit_loss,
@@ -89,32 +95,36 @@ def test_hyperopt(backtest_conf, backdata, mocker):
     space = {
         'mfi': hp.choice('mfi', [
             {'enabled': False},
-            {'enabled': True, 'value': hp.uniform('mfi-value', 5, 15)}
+            {'enabled': True, 'value': hp.quniform('mfi-value', 5, 25, 1)}
         ]),
         'fastd': hp.choice('fastd', [
             {'enabled': False},
-            {'enabled': True, 'value': hp.uniform('fastd-value', 5, 40)}
+            {'enabled': True, 'value': hp.quniform('fastd-value', 10, 50, 1)}
         ]),
         'adx': hp.choice('adx', [
             {'enabled': False},
-            {'enabled': True, 'value': hp.uniform('adx-value', 10, 30)}
+            {'enabled': True, 'value': hp.quniform('adx-value', 15, 50, 1)}
-        ]),
-        'cci': hp.choice('cci', [
-            {'enabled': False},
-            {'enabled': True, 'value': hp.uniform('cci-value', -150, -100)}
         ]),
         'rsi': hp.choice('rsi', [
             {'enabled': False},
-            {'enabled': True, 'value': hp.uniform('rsi-value', 20, 30)}
+            {'enabled': True, 'value': hp.quniform('rsi-value', 20, 40, 1)}
         ]),
         'uptrend_long_ema': hp.choice('uptrend_long_ema', [
             {'enabled': False},
             {'enabled': True}
         ]),
+        'uptrend_short_ema': hp.choice('uptrend_short_ema', [
+            {'enabled': False},
+            {'enabled': True}
+        ]),
         'over_sar': hp.choice('over_sar', [
             {'enabled': False},
             {'enabled': True}
         ]),
+        'green_candle': hp.choice('green_candle', [
+            {'enabled': False},
+            {'enabled': True}
+        ]),
         'uptrend_sma': hp.choice('uptrend_sma', [
             {'enabled': False},
             {'enabled': True}
@@ -125,10 +135,13 @@ def test_hyperopt(backtest_conf, backdata, mocker):
             {'type': 'ao_cross_zero'},
             {'type': 'ema5_cross_ema10'},
             {'type': 'macd_cross_signal'},
+            {'type': 'sar_reversal'},
+            {'type': 'stochf_cross'},
+            {'type': 'ht_sine'},
         ]),
     }
     trials = Trials()
-    best = fmin(fn=optimizer, space=space, algo=tpe.suggest, max_evals=4, trials=trials)
+    best = fmin(fn=optimizer, space=space, algo=tpe.suggest, max_evals=TOTAL_TRIES, trials=trials)
     print('\n\n\n\n==================== HYPEROPT BACKTESTING REPORT ==============================')
     print('Best parameters {}'.format(best))
     newlist = sorted(trials.results, key=itemgetter('loss'))