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Merge branch 'develop' into backtest-export

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This commit is contained in:
kryofly
2018-01-19 07:02:38 +01:00
parent d4008374f6 a4b8db38ca
commit 4a9e1cb345
28 changed files with 723 additions and 289 deletions
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51
freqtrade/optimize/hyperopt.py
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@@ -15,7 +15,7 @@ from hyperopt import STATUS_FAIL, STATUS_OK, Trials, fmin, hp, space_eval, tpe
from hyperopt.mongoexp import MongoTrials
from pandas import DataFrame
from freqtrade import main # noqa
from freqtrade import main, misc # noqa
from freqtrade import exchange, optimize
from freqtrade.exchange import Bittrex
from freqtrade.misc import load_config
@@ -30,18 +30,19 @@ logging.getLogger('hyperopt.tpe').setLevel(logging.WARNING)
logger = logging.getLogger(__name__)
# set TARGET_TRADES to suit your number concurrent trades so its realistic to 20days of data
TARGET_TRADES = 1100
TARGET_TRADES = 600
TOTAL_TRIES = 0
_CURRENT_TRIES = 0
CURRENT_BEST_LOSS = 100
# max average trade duration in minutes
# if eval ends with higher value, we consider it a failed eval
MAX_ACCEPTED_TRADE_DURATION = 240
MAX_ACCEPTED_TRADE_DURATION = 300
# this is expexted avg profit * expected trade count
# for example 3.5%, 1100 trades, EXPECTED_MAX_PROFIT = 3.85
EXPECTED_MAX_PROFIT = 3.85
# check that the reported Σ% values do not exceed this!
EXPECTED_MAX_PROFIT = 3.0
# Configuration and data used by hyperopt
PROCESSED = None # optimize.preprocess(optimize.load_data())
@@ -57,6 +58,10 @@ main._CONF = OPTIMIZE_CONFIG
SPACE = {
'macd_below_zero': hp.choice('macd_below_zero', [
{'enabled': False},
{'enabled': True}
]),
'mfi': hp.choice('mfi', [
{'enabled': False},
{'enabled': True, 'value': hp.quniform('mfi-value', 5, 25, 1)}
@@ -95,13 +100,15 @@ SPACE = {
]),
'trigger': hp.choice('trigger', [
{'type': 'lower_bb'},
{'type': 'lower_bb_tema'},
{'type': 'faststoch10'},
{'type': 'ao_cross_zero'},
{'type': 'ema5_cross_ema10'},
{'type': 'ema3_cross_ema10'},
{'type': 'macd_cross_signal'},
{'type': 'sar_reversal'},
{'type': 'stochf_cross'},
{'type': 'ht_sine'},
{'type': 'heiken_reversal_bull'},
{'type': 'di_cross'},
]),
'stoploss': hp.uniform('stoploss', -0.5, -0.02),
}
@@ -133,10 +140,11 @@ def log_results(results):
if results['loss'] < CURRENT_BEST_LOSS:
CURRENT_BEST_LOSS = results['loss']
logger.info('{:5d}/{}: {}'.format(
logger.info('{:5d}/{}: {}. Loss {:.5f}'.format(
results['current_tries'],
results['total_tries'],
results['result']))
results['result'],
results['loss']))
else:
print('.', end='')
sys.stdout.flush()
@@ -144,9 +152,9 @@ def log_results(results):
def calculate_loss(total_profit: float, trade_count: int, trade_duration: float):
""" objective function, returns smaller number for more optimal results """
trade_loss = 1 - 0.35 * exp(-(trade_count - TARGET_TRADES) ** 2 / 10 ** 5.2)
trade_loss = 1 - 0.25 * exp(-(trade_count - TARGET_TRADES) ** 2 / 10 ** 5.8)
profit_loss = max(0, 1 - total_profit / EXPECTED_MAX_PROFIT)
duration_loss = min(trade_duration / MAX_ACCEPTED_TRADE_DURATION, 1)
duration_loss = 0.7 + 0.3 * min(trade_duration / MAX_ACCEPTED_TRADE_DURATION, 1)
return trade_loss + profit_loss + duration_loss
@@ -192,12 +200,13 @@ def optimizer(params):
def format_results(results: DataFrame):
return ('{:6d} trades. Avg profit {: 5.2f}%. '
'Total profit {: 11.8f} BTC. Avg duration {:5.1f} mins.').format(
'Total profit {: 11.8f} BTC ({:.4f}Σ%). Avg duration {:5.1f} mins.').format(
len(results.index),
results.profit_percent.mean() * 100.0,
results.profit_BTC.sum(),
results.profit_percent.sum(),
results.duration.mean() * 5,
)
)
def buy_strategy_generator(params):
@@ -206,6 +215,8 @@ def buy_strategy_generator(params):
# GUARDS AND TRENDS
if params['uptrend_long_ema']['enabled']:
conditions.append(dataframe['ema50'] > dataframe['ema100'])
if params['macd_below_zero']['enabled']:
conditions.append(dataframe['macd'] < 0)
if params['uptrend_short_ema']['enabled']:
conditions.append(dataframe['ema5'] > dataframe['ema10'])
if params['mfi']['enabled']:
@@ -226,14 +237,17 @@ def buy_strategy_generator(params):
# TRIGGERS
triggers = {
'lower_bb': dataframe['tema'] <= dataframe['blower'],
'lower_bb': (dataframe['close'] < dataframe['bb_lowerband']),
'lower_bb_tema': (dataframe['tema'] < dataframe['bb_lowerband']),
'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'])),
'ema3_cross_ema10': (crossed_above(dataframe['ema3'], 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'])),
'heiken_reversal_bull': (crossed_above(dataframe['ha_close'], dataframe['ha_open'])) &
(dataframe['ha_low'] == dataframe['ha_open']),
'di_cross': (crossed_above(dataframe['plus_di'], dataframe['minus_di'])),
}
conditions.append(triggers.get(params['trigger']['type']))
@@ -261,8 +275,11 @@ def start(args):
logger.info('Using config: %s ...', args.config)
config = load_config(args.config)
pairs = config['exchange']['pair_whitelist']
PROCESSED = optimize.preprocess(optimize.load_data(
args.datadir, pairs=pairs, ticker_interval=args.ticker_interval))
timerange = misc.parse_timerange(args.timerange)
data = optimize.load_data(args.datadir, pairs=pairs,
ticker_interval=args.ticker_interval,
timerange=timerange)
PROCESSED = optimize.tickerdata_to_dataframe(data)
if args.mongodb:
logger.info('Using mongodb ...')