def pause(self, today):
today_volume = self.kl_pd.volume[int(today.key)]
upper, middle, lower = calc_boll(self.kl_pd.close, self.time_period, self.nb_dev)
if pd.isnull(middle[int(today.key)]):
return None
dif = today.pre_close - today.close
ma_volume = calc_ma(self.kl_pd.volume, 20)
if pd.isnull(ma_volume[int(today.key)]):
return
if today_volume / ma_volume[int(today.key)] > 2.5 and dif < 0 and dif / today.pre_close < -0.1:
self.lock = True
self.status = 0
if today_volume / ma_volume[int(today.key)] > 2.5 and dif / today.pre_close > -0.05:
self.status = 1
if self.status == 1 and today.close >= upper[int(today.key)] * 1.05:
self.lock = False
self.status = 0
if today.close >= upper[int(today.key)]:
self.lock = False
self.status = 0
def fit_day(self, today):
if self.lock:
# 如果封锁策略进行交易的情况下，策略不进行择时
return None
long_kl = self.past_today_kl(today, self.past_factor * self.xd)
tl_long = AbuTLine(long_kl.close, 'long')
# 判断长周期是否属于上涨趋势
# if not tl_long.is_up_trend(up_deg_threshold=self.up_deg_threshold, show=False):
# return None
upper, middle, lower = calc_boll(self.kl_pd.close, self.time_period,
self.nb_dev)
if pd.isnull(middle[int(today.key) - 1]):
return None
if today.pre_close <= middle[int(today.key) -
1] and today.close >= middle[int(
today.key)]:
print(u"穿过布林带中间线， 买入", "pre_close=", str(today.pre_close),
"middle=", str(middle[int(today.key) - 1]), "close=",
str(today.close), "middle=", str(middle[int(today.key)]),
'date=', str(today.date))
return self.buy_tomorrow()
def fit_day(self, today, orders):
"""
寻找向下突破作为策略卖出驱动event
:param today: 当前驱动的交易日金融时间序列数据
:param orders: 买入择时策略中生成的订单序列
"""
upper, middle, lower = calc_boll(self.kl_pd.close, self.time_period,
self.nb_dev)
dif, dea, bar = calc_macd(self.kl_pd.close)
if pd.isnull(upper[int(today.key)]):
return None
# if self.is_wave_period(today):
# if today.close < middle[int(today.key)]:
# print(u"震荡卖出")
# print("close=", str(today.close), "upper=", str(lower[int(today.key)]), 'date=', str(today.date))
# for order in orders:
# self.sell_tomorrow(order)
'''快速上涨macd策略卖出'''
if self._is_fast_up_period(today) and int(today.key) != 0:
pre_i = int(today.key) - 1
now_i = int(today.key)
if dif[pre_i] > dea[pre_i] and dif[now_i] <= dea[now_i]:
# print(u"快速上涨macd卖出", "close=", str(today.close), "middle=", str(middle[int(today.key)]), 'date=', str(today.date))
for order in orders:
self.sell_tomorrow(order)
'''原本是达到布林线上端时卖出，但回测结果并不好'''
'''跌破布林线下端卖出'''
if today.close < lower[int(today.key)]:
# print(u"跌穿布林带底线卖出", "close=", str(today.close), "lower=", str(lower[int(today.key)]), 'date=', str(today.date))
for order in orders:
self.sell_tomorrow(order)
def fit_day(self, today):
# logging.info("enter fit_day, %s %d %f" % (self.kl_pd.name, today.date, today.close))
if self.lock:
# 如果封锁策略进行交易的情况下，策略不进行择时
return None
short_kl = self.past_today_kl(today, 21)
sl_short = AbuTLine(short_kl.close, 'short')
# 判断长周期是否属于上涨趋势
# if not tl_long.is_up_trend(up_deg_threshold=self.up_deg_threshold, show=False):
# return None
upper, middle, lower = calc_boll(self.kl_pd.close, self.time_period,
self.nb_dev)
dif, dea, bar = calc_macd(self.kl_pd.close)
# if pd.isnull(middle[int(today.key) - 1]):
if pd.isnull(middle[int(today.key)]):
return None
# long_kl = self.past_today_kl(today, 21)
# long_line = AbuTLine(long_kl.close, 'long')
# if long_line.is_down_trend(down_deg_threshold=-3, show=False):
# return None
'''处于快速上涨区, 跌到布林带中间线买入效果不好'''
# if tl_short.is_up_trend(6, show=False):
# if middle[int(today.key) - 1] < today.pre_close < middle[int(today.key) - 1] * 1.05 and today.close >= today.pre_close:
# print(u"快速上涨区，跌到布林带中间线，未跌穿， 买入", "pre_close=", str(today.pre_close), "middle=", str(middle[int(today.key) - 1]),
# "close=", str(today.close), "middle=", str(middle[int(today.key)]), 'date=', str(today.date))
# return self.buy_tomorrow()
if int(today.key) != 0:
pre_i = int(today.key) - 1
now_i = int(today.key)
'''0值之上不操作买入, 增加这个逻辑后整体收益不好，去掉'''
# if not sl_short.is_up_trend(up_deg_threshold=2, show=False):
# return None
if dif[pre_i] < dea[pre_i] and dif[now_i] >= dea[now_i]:
# print(u"macd金叉， 买入", "pre_close=", str(today.pre_close), "middle=", str(middle[int(today.key) - 1]),
# "close=", str(today.close), "middle=", str(middle[int(today.key)]), 'date=', str(today.date))
# order =
# if order is not None:
# today_record = FuTodayCanBuyRecord()
# today_record.record_today_can_buy_stock(today, self.kl_pd.name, 1)
return self.buy_today()
if today.pre_close <= middle[int(today.key) -
1] and today.close >= middle[int(
today.key)]:
# print(u"穿过布林带中间线， 买入", "pre_close=", str(today.pre_close), "middle=", str(middle[int(today.key) - 1]),
# "close=", str(today.close), "middle=", str(middle[int(today.key)]), 'date=', str(today.date))
# order = self.buy_today()
return self.buy_today()
def fit_day(self, today):
# logging.info("enter fit_day, %s %d %f" % (self.kl_pd.name, today.date, today.close))
self.pause(today)
if self.lock:
# 如果封锁策略进行交易的情况下，策略不进行择时
return None
upper, middle, lower = calc_boll(self.kl_pd.close, self.time_period, self.nb_dev)
if pd.isnull(middle[int(today.key)]):
return None
if today.close <= lower[int(today.key)]:
return self.buy_today()
def fit_day(self, today, orders):
"""
寻找向下突破作为策略卖出驱动event
:param today: 当前驱动的交易日金融时间序列数据
:param orders: 买入择时策略中生成的订单序列
"""
upper, middle, lower = calc_boll(self.kl_pd.close, self.time_period,
self.nb_dev)
if pd.isnull(upper[int(today.key)]):
return None
'''达到布林线上端时卖出'''
if today.close >= upper[int(today.key)]:
# print(u"跌穿布林带底线卖出", "close=", str(today.close), "lower=", str(lower[int(today.key)]), 'date=', str(today.date))
for order in orders:
if order.buy_price < today.close:
self.sell_today(order)
def sample_13():
kl_pd = ABuSymbolPd.make_kl_df(
'601398',
data_mode=ABuEnv.EMarketDataSplitMode.E_DATA_SPLIT_UNDO,
start='2012-04-20',
end='2018-04-20',
parallel=False)
print(kl_pd)
# kl_pd.to_csv("/Users/juchen/abu/601398.csv")
upper, middle, lower = calc_boll(kl_pd.close, 20, 2)
print(middle)
print(lower)
rsi = calc_rsi(kl_pd.close)
print(rsi)
abupy.nd.boll.plot_boll_from_klpd(kl_pd)
abupy.nd.rsi.plot_rsi_from_klpd(kl_pd)
def fit_pick(self, kl_pd, target_symbol):
upper, middle, lower = calc_boll(kl_pd.close, 20, 2)
ma_volume = calc_ma(kl_pd.volume, 20)
status = 0
lock = False
if len(kl_pd) < self.back_count:
return False
for index in np.arange(len(kl_pd) - self.back_count, len(kl_pd)):
today_volume = kl_pd.volume[index]
if pd.isnull(middle[index]):
continue
dif = kl_pd.close[index] - kl_pd.close[index - 1]
if pd.isnull(ma_volume[index]):
return
if today_volume / ma_volume[
index] > 2 and dif < 0 and dif / kl_pd.close[index -
1] < -0.1:
lock = True
status = 0
'放量且不是大跌的情况，预解除锁定'
if today_volume / ma_volume[index] > 2.5 and dif / kl_pd.close[
index - 1] > -0.05:
status = 1
'放量后涨到boll带顶端，解除锁定'
if status == 1 and kl_pd.close[index] >= upper[index] * 1.05:
lock = False
status = 0
# if kl_pd.close[index] >= upper[index]:
# self.lock = False
# self.status = 0
if ~lock:
# return True
if kl_pd.close[len(kl_pd.volume) -
1] < lower[len(kl_pd.volume) - 1] * 1.05:
return True
return False
def fit_day(self, today):
upper, middle, lower = calc_boll(self.kl_pd.close)
if pd.isnull(middle[int(today.key) - 1]):
return None
'''判断是否处于快速上涨区'''
long_kl = self.past_today_kl(today, 120)
tl_long = AbuTLine(long_kl.close, 'long')
# 判断长周期是否属于上涨趋势
if tl_long.is_up_trend(up_deg_threshold=self.up_deg_threshold,
show=False):
if today.close == self.xd_kl.close.min() and \
AbuTLine(self.xd_kl.close, 'short').is_down_trend(
down_deg_threshold=-self.down_deg_threshold, show=False):
# if middle[int(today.key) - 1] < today.pre_close < middle[int(today.key) - 1] * 1.1 \
# and today.close >= today.pre_close:
# print(u"补仓，快速上涨区，跌到布林带中间线，未跌穿， 买入", "pre_close=", str(today.pre_close), "middle=",
# str(middle[int(today.key) - 1]),
# "close=", str(today.close), "middle=", str(middle[int(today.key)]), 'date=', str(today.date))
# print("补仓")
return self.buy_today()
def fit_pick(self, kl_pd, target_symbol):
upper, middle, lower = calc_boll(kl_pd.close, 20, 3)
ma_volume = calc_ma(kl_pd.volume, 20)
status = 0
for i in np.arange(1, 20):
index = len(kl_pd.volume) - i
today_volume = kl_pd.volume[index]
if pd.isnull(middle[index]):
return False
if index - 1 < 0:
return False
dif = kl_pd.close[index] - kl_pd.close[index - 1]
if pd.isnull(ma_volume[index]):
return
if today_volume / ma_volume[
index] > 2.5 and dif < 0 and dif / kl_pd.close[index -
1] < -0.1:
return False
# if status == 1 and today_volume / ma_volume[index] > 2.5 and kl_pd.close[index - 1] > -0.05:
if status == 1 and today_volume / ma_volume[
index] > 2.5 and kl_pd.close[index - 1] > -0.05:
status = 2
break
if kl_pd.close[index] >= upper[index] * 0.95:
status = 1
if status == 2:
# return True
if kl_pd.close[len(kl_pd.volume) -
1] < lower[len(kl_pd.volume) - 1] * 1.05:
return True
return False
def parse_one_stock(his_df, symbol, symbol_complete):
profit_sum, profit_cgs = parse_actions(symbol_complete)
if profit_sum <= 0:
logging.info('profit_sum < 0, symbol={}, profit_cgs={}'.format(
symbol_complete, profit_cgs))
return
global can_buy_df
all_close = his_df.close.copy()
# stock_now = now_df[now_df.code == int(symbol)]
# if stock_now is None:
# return
# now_price_s = stock_now.trade.astype(float)
# all_close.add(now_price_s)
# if len(stock_now["trade"].values) == 0:
# logging.error("today price null, {}".format(symbol))
# return
#
# now_price = stock_now["trade"].values.tolist()[0]
now_price = all_close[len(all_close) - 1]
upper, middle, lower = calc_boll(all_close, 20, 2)
dif, dea, bar = calc_macd(all_close)
# print(now_price)
if his_df.close[len(his_df.close) - 1] < middle[len(middle) - 2] \
and now_price > middle[len(middle) - 1]:
df_temp = pd.DataFrame(
[[str(symbol), now_price, 'boll', profit_sum, profit_cgs]],
columns=['symbol', 'price', 'type', 'profit_sum', 'profit_cgs'])
can_buy_df = can_buy_df.append(df_temp)
if dif[len(dif) - 2] < dea[len(dea) - 2] \
and dif[len(dif) - 1] >= dea[len(dea) - 1]:
df_temp = pd.DataFrame(
[[str(symbol), now_price, 'macd', profit_sum, profit_cgs]],
columns=['symbol', 'price', 'type', 'profit_sum', 'profit_cgs'])
can_buy_df = can_buy_df.append(df_temp)