diff --git a/freqtrade/analyze.py b/freqtrade/analyze.py index 5c734b24e..3143abc1f 100644 --- a/freqtrade/analyze.py +++ b/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 diff --git a/freqtrade/tests/test_hyperopt.py b/freqtrade/tests/test_hyperopt.py index 50f3b94f4..bece2edae 100644 --- a/freqtrade/tests/test_hyperopt.py +++ b/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) - profit_loss = exp(-total_profit**3 / 10**11) + trade_loss = 1 - 0.4 * exp(-(trade_count - TARGET_TRADES) ** 2 / 10 ** 5.2) + 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)} - ]), - 'cci': hp.choice('cci', [ - {'enabled': False}, - {'enabled': True, 'value': hp.uniform('cci-value', -150, -100)} + {'enabled': True, 'value': hp.quniform('adx-value', 15, 50, 1)} ]), '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'))