def three_black_crows(key, dataList, time_frame):
price_action = pd.DataFrame(dataList, columns=[id.time, id.open, id.close, id.high, id.low, id.volume])
if price_action.empty:
return
window_size = constants.strategy_params[id.window_size]
# crows=check if the last 3 candles are crows
crows = utils.__is_bear(price_action.iloc[-1][id.open], price_action.iloc[-1][id.close]) \
and utils.__is_bear(price_action.iloc[-2][id.open], price_action.iloc[-2][id.close]) \
and utils.__is_bear(price_action.iloc[-3][id.open], price_action.iloc[-3][id.close]) \
and __is_lower(price_action.iloc[-1][id.open], price_action.iloc[-1][id.close],
price_action.iloc[-2][id.open], price_action.iloc[-2][id.close], price_action.iloc[-2][id.low]) \
and __is_lower(price_action.iloc[-2][id.open], price_action.iloc[-2][id.close],
price_action.iloc[-3][id.open], price_action.iloc[-3][id.close], price_action.iloc[-3][id.low])
# check lower wick
lower_wick = __small_lower_wick(price_action.iloc[-1]) \
and __small_lower_wick(price_action.iloc[-2]) \
and __small_lower_wick(price_action.iloc[-3])
# find trend for candles from -17 to -3, extra window_size data for sma buffer
trend = utils.__uptrend(price_action.iloc[-2*window_size - 3:-3][id.close].values, window_size)
# check strategy
if trend and crows and lower_wick:
try:
#db.insert_strategy(key, time_frame, values.three_black_crow, price_action.iloc[-1][id.time])
return {
id.name: id.three_black_crow,
id.key: key,
id.price_action: dataList
}
except:
print('Unable to add to database')
return {}
def morning_star(key, dataList, time_frame):
price_action = pd.DataFrame(
dataList,
columns=[id.time, id.open, id.close, id.high, id.low, id.volume])
if price_action.empty:
return
window_size = constants.strategy_params[id.window_size]
downtrend = utils.__downtrend(
price_action.iloc[-window_size - 3:-3][id.close].values, window_size)
morning_star = utils.__is_bull(price_action.iloc[-1][id.open], price_action.iloc[-1][id.close]) \
and utils.__percentage_change(price_action.iloc[-1][id.open], price_action.iloc[-1][id.close]) > constants.strategy_params[id.body_percentage] \
and utils.__is_gap_up(price_action.iloc[-1][id.open], price_action.iloc[-2][id.open], price_action.iloc[-2][id.close]) \
and utils.__percentage_change(price_action.iloc[-2][id.open], price_action.iloc[-2][id.close]) < constants.strategy_params[id.small_body_percentage] \
and utils.__is_gap_up(price_action.iloc[-3][id.open], price_action.iloc[-2][id.open], price_action.iloc[-2][id.close]) \
and utils.__is_bear(price_action.iloc[-3][id.open], price_action.iloc[-3][id.close]) \
and utils.__percentage_change(price_action.iloc[-3][id.open], price_action.iloc[-3][id.close]) > constants.strategy_params[id.body_percentage] \
and utils.__threshold_down(price_action.iloc[-3][id.open], price_action.iloc[-3][id.close], price_action.iloc[-1][id.close])
if downtrend and morning_star:
try:
#db.insert_strategy(key, time_frame, values.morning_star, price_action.iloc[-1][id.time])
return {
id.name: id.morning_star,
id.key: key,
id.price_action: dataList
}
except:
print('Unable to add to database')
return {}
def bullish_abandoned_baby(key, dataList, time_frame):
price_action = pd.DataFrame(
dataList,
columns=[id.time, id.open, id.close, id.high, id.low, id.volume])
if price_action.empty:
return
window_size = constants.strategy_params[id.window_size]
downTrend = utils.__downtrend(
price_action.iloc[-2 * window_size - 3:-3][id.close].values,
window_size)
abandonedBaby = utils.__is_bull(price_action.iloc[-1][id.open], price_action.iloc[-1][id.close]) \
and utils.__percentage_change(price_action.iloc[-1][id.open], price_action.iloc[-1][id.close]) > constants.strategy_params[id.body_percentage] \
and price_action.iloc[-1][id.low] > price_action.iloc[-2][id.high] \
and utils.__is_doji(price_action.iloc[-2][id.open], price_action.iloc[-2][id.close]) \
and price_action.iloc[-3][id.high] > price_action.iloc[-2][id.low] \
and utils.__is_bear(price_action.iloc[-3][id.open], price_action.iloc[-3][id.close]) \
and utils.__percentage_change(price_action.iloc[-2][id.open], price_action.iloc[-2][id.close]) > constants.strategy_params[id.body_percentage]
if downTrend and abandonedBaby:
try:
#db.insert_strategy(key, time_frame, values.bullish_abandoned_baby, price_action.iloc[-1][id.time])
return {
id.name: id.bullish_abandoned_baby,
id.key: key,
id.price_action: price_action.to_dict()
}
except:
print('Unable to add to database')
return {}
def three_black_crows(key, price_action, time_frame):
window_size = constants.strategy_params[id.window_size]
# crows=check if the last 3 candles are crows
crows = utils.__is_bear(price_action.iloc[-1][id.open], price_action.iloc[-1][id.close]) \
and utils.__is_bear(price_action.iloc[-2][id.open], price_action.iloc[-2][id.close]) \
and utils.__is_bear(price_action.iloc[-3][id.open], price_action.iloc[-3][id.close]) \
and __is_lower(price_action.iloc[-1][id.open], price_action.iloc[-1][id.close],
price_action.iloc[-2][id.open], price_action.iloc[-2][id.close], price_action.iloc[-2][id.low]) \
and __is_lower(price_action.iloc[-2][id.open], price_action.iloc[-2][id.close],
price_action.iloc[-3][id.open], price_action.iloc[-3][id.close], price_action.iloc[-3][id.low])
# check lower wick
lower_wick = __small_lower_wick(price_action.iloc[-1]) \
and __small_lower_wick(price_action.iloc[-2]) \
and __small_lower_wick(price_action.iloc[-3])
# find trend for candles from -17 to -3, extra window_size data for sma buffer
trend = utils.__uptrend(
price_action.iloc[-2 * window_size - 3:-3][id.close].values,
window_size)
# check strategy
if trend and crows and lower_wick:
db.insert_strategy(key, time_frame, values.three_black_crow,
price_action.iloc[-1][id.time])
def bullish_abandoned_baby(key, price_action, time_frame):
window_size = constants.strategy_params[id.window_size]
downTrend = utils.__downtrend(
price_action.iloc[-2 * window_size - 3:-3][id.close].values,
window_size)
abandonedBaby = utils.__is_bull(price_action.iloc[-1][id.open], price_action.iloc[-1][id.close]) \
and utils.__percentage_change(price_action.iloc[-1][id.open], price_action.iloc[-1][id.close]) > constants.strategy_params[id.body_percentage] \
and price_action.iloc[-1][id.low] > price_action.iloc[-2][id.high] \
and utils.__is_doji(price_action.iloc[-2][id.open], price_action.iloc[-2][id.close]) \
and price_action.iloc[-3][id.high] > price_action.iloc[-2][id.low] \
and utils.__is_bear(price_action.iloc[-3][id.open], price_action.iloc[-3][id.close]) \
and utils.__percentage_change(price_action.iloc[-2][id.open], price_action.iloc[-2][id.close]) > constants.strategy_params[id.body_percentage]
if downTrend and abandonedBaby:
db.insert_strategy(key, time_frame, values.bullish_abandoned_baby,
price_action.iloc[-1][id.time])
def evening_star(data, w_start, window_size, ratio):
evening_star = utils.__is_bull(data['open'].values[w_start + window_size],
data['close'].values[w_start + window_size]) \
and utils.__is_gap_down(data['close'].values[w_start + window_size],
data['open'].values[w_start + window_size + 1],
data['close'].values[w_start + window_size + 1]) \
and utils.__body(data['open'].values[w_start + window_size + 1],
data['close'].values[w_start + window_size + 1]) < ratio * \
utils.__body(data['open'].values[w_start + window_size], data['close'].values[w_start + window_size]) \
and utils.__body(data['open'].values[w_start + window_size + 1],
data['close'].values[w_start + window_size + 1]) < ratio * \
utils.__body(data['open'].values[w_start + window_size + 2],
data['close'].values[w_start + window_size + 2]) \
and utils.__is_gap_down(data['open'].values[w_start + window_size + 2],
data['open'].values[w_start + window_size + 1],
data['close'].values[w_start + window_size + 1]) \
and utils.__is_bear(data['open'].values[w_start + window_size + 2],
data['close'].values[w_start + window_size + 2]) \
and utils.__threshold_up(data['open'].values[w_start + window_size],
data['close'].values[w_start + window_size],
data['close'].values[w_start + window_size + 2])
return evening_star