def init_detection_process_for_automated_trade_update(
self, mean: int, sma_number: int):
self.config.detection_process = PDP.UPDATE_TRADE_DATA
self.config.pattern_type_list = FT.get_long_trade_able_types()
self.exchange_config.trade_strategy_dict = {
BT.BREAKOUT: [
TSTR.LIMIT, TSTR.LIMIT_FIX, TSTR.TRAILING_STOP,
TSTR.TRAILING_STEPPED_STOP
]
}
self.exchange_config.default_trade_strategy_dict = {
BT.BREAKOUT: TSTR.LIMIT
}
self.config.detection_process = PDP.UPDATE_TRADE_DATA
self.config.plot_data = False
self.config.with_trading = True
self.config.trading_last_price_mean_aggregation = mean
self.config.simple_moving_average_number = sma_number # default = 8
self.config.save_pattern_data = False
self.config.save_trade_data = True
self.config.replace_existing_trade_data_on_db = False # default = False
self.config.plot_only_pattern_with_fibonacci_waves = False
self.config.plot_min_max = True
self.config.plot_volume = False
self.config.length_for_local_min_max = 2
self.config.length_for_local_min_max_fibonacci = 1
self.config.bound_upper_value = CN.CLOSE
self.config.bound_lower_value = CN.CLOSE
self.config.fibonacci_tolerance_pct = 0.1 # default is 0.20
self.sound_machine.is_active = False
def __adjust_sys_config__(self):
print('TradeTest.__adjust_sys_config__')
self.sys_config.runtime_config.actual_trade_process = self.trade_process
self.sys_config.config.plot_data = False
if self.trade_process == TP.BACK_TESTING:
self.sys_config.config.pattern_type_list = FT.get_long_trade_able_types()
self.sys_config.config.save_pattern_data = False
self.sys_config.config.save_trade_data = False
def __get_optimal_pattern_type_dict_for_long_trading__(self):
opt_dict = {}
for pattern_type in FT.get_long_trade_able_types():
if self._pattern_type_pos_neg_result_dict[
pattern_type] >= self.expected_relation_pos_neg:
opt_dict[
pattern_type] = self._pattern_type_pos_neg_result_dict[
pattern_type]
return opt_dict
def update_trade_records(self,
mean: int,
sma_number: int,
trade_strategies: dict = None,
pattern_end_date=str):
if pattern_end_date == '':
pattern_end_date = str(MyDate.adjust_by_days(
None, -90)) # only the ones which are 3 month back
self.sys_config.init_detection_process_for_automated_trade_update(
mean, sma_number)
if trade_strategies is None:
trade_strategies = {
BT.BREAKOUT: [
TSTR.LIMIT, TSTR.LIMIT_FIX, TSTR.TRAILING_STOP,
TSTR.TRAILING_STEPPED_STOP
]
}
for pattern_type in FT.get_long_trade_able_types():
where_clause = "pattern_type = '{}' and period = 'DAILY' and trade_type in ('', 'long')".format(
pattern_type)
if pattern_end_date != '':
where_clause += " AND {} > '{}'".format(
DC.PATTERN_END_DT, pattern_end_date)
df_pattern_for_pattern_type = self.db_stock.get_pattern_records_as_dataframe(
where_clause)
pattern_id_dict = {
row[DC.ID]: row[DC.TRADE_TYPE]
for index, row in df_pattern_for_pattern_type.iterrows()
}
# pattern_id_list = ['20_1_1_LTCUSD_20_2016-11-02_00:00_2016-12-04_00:00']
counter = 0
for pattern_id, trade_type in pattern_id_dict.items():
counter += 1
run_detail = '{} ({:03d} of {:03d}): {}'.format(
pattern_type, counter, len(pattern_id_dict), pattern_id)
result_dict = self.db_stock.get_missing_trade_strategies_for_pattern_id(
pattern_id, trade_strategies, mean, sma_number)
for buy_trigger, trade_strategy_list in result_dict.items():
if len(trade_strategy_list) == 0:
print('{}: OK'.format(run_detail))
else:
print('{}: processing...'.format(run_detail))
self.sys_config.config.pattern_ids_to_find = [
pattern_id
]
self.sys_config.exchange_config.trade_strategy_dict = {
buy_trigger: trade_strategy_list
}
pattern_controller = PatternDetectionController(
self.sys_config)
pattern_controller.run_pattern_detector()
if trade_type == '':
self.db_stock.update_trade_type_for_pattern(
pattern_id, TRT.LONG)
def get_pattern_records_for_replay_as_dataframe(self) -> pd.DataFrame:
query = self._pattern_table.get_query_select_for_records(
"Period = 'DAILY'")
db_df = DatabaseDataFrame(self, query)
return db_df.df[db_df.df[DC.PATTERN_TYPE].isin(
FT.get_long_trade_able_types())]
def __perform_task__(self):
self._db_updater.update_trade_policy_metric_for_today(
FT.get_long_trade_able_types())
"""
Description: This module contains the global system configuration classes for stock pattern detection
Author: Josef Sertl
Copyright: SERTL Analytics, https://sertl-analytics.com
Date: 2018-05-14
"""
from sertl_analytics.constants.pattern_constants import FT, BT, TSTR, TTC, TP, INDICES
from sertl_analytics.datafetcher.web_data_fetcher import IndicesComponentFetcher
from pattern_test.trade_test import TradeTest, TradeTestApi
api = TradeTestApi()
api.test_process = TP.BACK_TESTING
back_testing = TradeTest(api)
back_testing.sys_config.config.pattern_type_list = FT.get_long_trade_able_types(
)
# back_testing.sys_config.config.pattern_type_list = [FT.TRIANGLE_DOWN]
back_testing.sys_config.config.save_trade_data = True
back_testing.sys_config.config.simple_moving_average_number = 20
back_testing.sys_config.config.trading_last_price_mean_aggregation = 8
# ******** START setup **********
api.buy_trigger = BT.BREAKOUT
api.trade_strategy = TSTR.TRAILING_STOP
# ******** END setup **********
ticker_dic = IndicesComponentFetcher.get_ticker_name_dic(INDICES.DOW_JONES)
# ticker_dic = IndicesComponentFetcher.get_ticker_name_dic(INDICES.CRYPTO_CCY)
# ticker_dic = {'CVX': 'a'}
api.and_clause = "Date BETWEEN '2018-06-07' AND '2019-09-04'"