def generate_3mindata(self, am:ArrayManager, bar:BarData):
offset = -self.offset
offset_m = int(offset / 2)
calc_nums = np.array(self.ma_tag[-offset:-1])
# var_val = np.var(calc_nums)
std_val = np.std(calc_nums)
std_val2 = np.std(np.array(self.ma_tag[-10:-1]))
std_val3 = np.std(np.array(am.range[-30:-10]))
ma = self.ma_tag[-1]
mean_val = np.mean(calc_nums)
mean_val2 = np.mean(np.array(self.ma_tag[-5:-1]))
mean_val3 = np.mean(np.array(self.ma_tag[-20:-1]))
mean_val4 = np.mean(np.array(self.ma_tag[-30:-5]))
kdj_val = am.kdj()
deg1 = calc_regress_deg(am.close[offset : offset_m], False)
deg2 = calc_regress_deg(am.close[offset_m :], False)
deg3 = calc_regress_deg(am.close[-10 :], False)
deg_full = calc_regress_deg(am.close[offset :], False)
wave = self.wave(am.close[-30:])
wave_r_sum = np.sum(wave["range"])
macd=am.macd(20,40, 16)
calc_data = (dict(
kdj=[round(kdj_val["k"][-1],2),round(kdj_val["d"][-1],2),round(kdj_val["j"][-1],2)],
cci_20=am.cci(20),rsi=am.rsi(20),adx=am.adx(20),boll=am.boll(20, 3.4),
macd=[round(macd[0],2),round(macd[1],2),round(macd[2],2)],
deg40_20=round(deg1,2), deg20_0=round(deg2,2), deg20_10=round(calc_regress_deg(am.close[-20:-10], False),2), deg10_0=round(deg3,2),
deg30_15=round(calc_regress_deg(am.close[-30:-15], False),2), deg15_0=round(calc_regress_deg(am.close[-15:], False),2),deg_f=round(deg_full,2),
atr=round(am.atr(10, length=15), 3), tr=round(am.atr(1, length=2), 3),atr_40=round(am.atr(40, length=42), 3),
time=bar.datetime, price=bar.close_price, ma=round(ma, 2),
std_40=round(std_val, 2),mean40=round(mean_val,2), mean_std=np.mean(self.std_range.data[-5:]),
std_10=round(std_val2,2), mean30_10=round(mean_val4,2), mean10=round(mean_val2,2),
vol=am.volume[-1], std_range=self.std_range.data[-1:-5:-1], range=am.range[-1:-5:-1].tolist(),
range_sum=np.sum(am.range[-5:]),
pattern=list(map(lambda x: KLINE_PATTERN_CHINESE[x], self.pattern_record.keys())),
ma120t=self.ma120_track,
ma120t_list=self.ma120_track_list[-1:-10:-1],
ma120t_sort=sorted(self.ma120_track_list[-20:-1], key=abs),
ma120t_sum=np.sum(self.ma120_track_list[-20:-1] + [self.ma120_track]),
ma120t_mean=np.mean(self.ma120_track_list[-20:-1] + [self.ma120_track]),
ma120t_std=np.std(self.ma120_track_list[-20:-1] + [self.ma120_track]),
ma_info=list(map(lambda x:x["std"], self.ma_info[-1:])),
wave_cnt=len(wave), wave_r_sum=wave_r_sum, atr_mean=np.mean(am.atr(20, array=True,length=240)[-200:])
))
return calc_data
class CciSignal(CtaSignal):
""""""
def __init__(self, cci_window: int, cci_level: float):
""""""
super(CciSignal, self).__init__()
self.cci_window = cci_window
self.cci_level = cci_level
self.cci_long = self.cci_level
self.cci_short = -self.cci_level
self.bg = BarGenerator(self.on_bar)
self.am = ArrayManager()
def on_tick(self, tick: TickData):
"""
Callback of new tick data update.
"""
self.bg.update_tick(tick)
def on_bar(self, bar: BarData):
"""
Callback of new bar data update.
"""
self.am.update_bar(bar)
if not self.am.inited:
self.set_signal_pos(0)
cci_value = self.am.cci(self.cci_window)
if cci_value >= self.cci_long:
self.set_signal_pos(1)
elif cci_value <= self.cci_short:
self.set_signal_pos(-1)
else:
self.set_signal_pos(0)
class CciSignal(CtaSignal):
""""""
def __init__(self, cci_window: int, cci_level: float):
""""""
super(CciSignal, self).__init__()
self.cci_window = cci_window
self.cci_level = cci_level
self.cci_long = self.cci_level
self.cci_short = -self.cci_level
self.bg = BarGenerator(self.on_bar)
self.am = ArrayManager()
def on_tick(self, tick: TickData):
"""
Callback of new tick data update.
"""
self.bg.update_tick(tick)
def on_bar(self, bar: BarData):
"""
Callback of new bar data update.
"""
self.am.update_bar(bar)
if not self.am.inited:
self.set_signal_pos(0)
cci_value = self.am.cci(self.cci_window)
if cci_value >= self.cci_long:
self.set_signal_pos(1)
elif cci_value <= self.cci_short:
self.set_signal_pos(-1)
else:
self.set_signal_pos(0)
def generate_data(self, am: ArrayManager, bar: BarData):
offset = -self.offset
offset_m = int(offset / 2)
std_val3 = np.std(np.array(am.range[-30:-10]))
kdj_val = am.kdj()
has_kdj_recore = False
k = kdj_val["k"]
d = kdj_val["d"]
j = kdj_val["j"]
if (k[-1] > 75 and d[-1] > 75 and j[-1] > 75) or \
(k[-1] < 25 and d[-1] < 25 and j[-1] < 75):
if (j[-2] < k[-2] or j[-2] < d[-2]) and (j[-1] > k[-1] and j[-1] > d[-1]) \
or \
(j[-2] > k[-2] or j[-2] > d[-2]) and (j[-1] < k[-1] and j[-1] < d[-1]):
has_kdj_recore = True
t = bar.datetime
self.kdj_record.append(
(t.strftime("%H:%M:%S"), round(k[-1], 3), round(d[-1], 3),
round(j[-1], 3)))
deg1 = calc_regress_deg(am.close[offset:offset_m], False)
deg2 = calc_regress_deg(am.close[offset_m:], False)
deg3 = calc_regress_deg(am.close[-10:], False)
deg_full = calc_regress_deg(am.close[offset:], False)
macd = am.macd(20, 40, 16)
calc_data = (dict(
kdj=[
round(kdj_val["k"][-1], 2),
round(kdj_val["d"][-1], 2),
round(kdj_val["j"][-1], 2)
],
cci_20=am.cci(20),
rsi=am.rsi(20),
adx=am.adx(20),
boll=am.boll(20, 3.4),
macd=[round(macd[0], 2),
round(macd[1], 2),
round(macd[2], 2)],
deg40_20=round(deg1, 2),
deg20_0=round(deg2, 2),
deg20_10=round(calc_regress_deg(am.close[-20:-10], False), 2),
deg30_15=round(calc_regress_deg(am.close[-30:-15], False), 2),
deg15_0=round(calc_regress_deg(am.close[-15:], False), 2),
deg_f=round(deg_full, 2),
deg30_10=round(calc_regress_deg(am.close[-30:-10], False), 2),
deg10_0=round(deg3, 2),
atr=round(am.atr(10, length=15), 3),
tr=round(am.atr(1, length=2), 3),
atr_40=round(am.atr(40, length=42), 3),
time=bar.datetime,
price=bar.close_price,
mean_std=np.mean(self.std_range.data[-5:]),
vol=am.volume[-1],
std_range=self.std_range.data[-1:-5:-1],
range=am.range[-1:-5:-1].tolist(),
range_sum=np.sum(am.range[-5:]),
pattern=list(
map(lambda x: KLINE_PATTERN_CHINESE[x],
self.pattern_record.keys())),
atr_mean=np.mean(am.atr(20, array=True, length=240)[-200:]),
))
if self.ma_info.info.index.size >= 31:
ma5 = self.ma_info.info[5][-31:]
x = AnalyseWave(ma5)
calc_data["ma5_info"] = x.optimize
ma10 = self.ma_info.info[10][-31:]
x = AnalyseWave(ma10)
calc_data["ma10_info"] = x.optimize
return calc_data
class DudlThrustEmaPositionStrategy(CtaTemplate):
""""""
author = "yunyu"
open_window = 5
xminute_window = 30
rolling_period = 70
upper_open = 0.45
lower_open = 0.45
cci_length = 5
ema_length = 60
position_atr_length = 6
risk_level = 1000
# fixed_size = 1
trading_size = 0
atr_value = 0
up = 0
down = 0
current_ema = 0
last_ema = 0
ema_mid = 0
ema_new_value = 0
ema_length_new = 0
cci_value = 0
exit_long_nex = 0
exit_long_last = 0
exit_short_nex = 0
exit_short_last = 0
current_close = 0
last_close = 0
front_close = 0
exit_long = 0
exit_short = 0
ask = 0
bid = 0
parameters = [
"open_window", "xminute_window", "rolling_period", "upper_open",
"lower_open", "cci_length", "ema_length", "position_atr_length",
"risk_level"
]
variables = [
"trading_size",
"up",
"down",
"current_ema",
"last_ema",
"ema_mid",
"ema_new_value",
"ema_length_new",
"cci_value",
"exit_long_nex",
"exit_long_last",
"exit_short_nex",
"exit_short_last",
"current_close",
"last_close",
"front_close",
"exit_long",
"exit_short",
]
def __init__(self, cta_engine, strategy_name, vt_symbol, setting):
""""""
super().__init__(cta_engine, strategy_name, vt_symbol, setting)
self.bg_open = BarGenerator(on_bar=self.on_bar,
window=self.open_window,
on_window_bar=self.on_open_bar)
self.am_open = ArrayManager()
self.bg = NewBarGenerator(on_bar=self.on_bar,
window=self.xminute_window,
on_window_bar=self.on_xmin_bar)
self.am = ArrayManager(self.rolling_period + 50)
def on_init(self):
"""
Callback when strategy is inited.
"""
self.write_log("策略初始化")
self.load_bar(10)
def on_start(self):
"""
Callback when strategy is started.
"""
self.write_log("策略启动")
def on_stop(self):
"""
Callback when strategy is stopped.
"""
self.write_log("策略停止")
def on_tick(self, tick: TickData):
"""
Callback of new tick data update.
"""
self.bg.update_tick(tick)
self.ask = tick.ask_price_1 # 卖一价
self.bid = tick.bid_price_1 # 买一价
def on_bar(self, bar: BarData):
"""
Callback of new bar data update.
"""
self.bg.update_bar(bar)
self.bg_open.update_bar(bar)
def on_open_bar(self, bar: BarData):
"""
Callback of new bar data update.
"""
self.cancel_all()
self.am_open.update_bar(bar)
if not self.am.inited or not self.am_open.inited:
return
if self.pos == 0:
self.cci_value = self.am.cci(self.cci_length)
# 判断数据是否正常，如果atr 计算结果正常，才计算仓位，避免下单时下出不正常的数量
self.atr_value = self.am.atr(self.position_atr_length)
if self.atr_value == 0:
return
self.trading_size = max(int(self.risk_level / self.atr_value), 1)
if self.cci_value > 0:
self.buy(self.up, self.trading_size, True)
elif self.cci_value < 0:
self.short(self.down, self.trading_size, True)
elif self.pos > 0:
con1 = bar.close_price < self.current_ema
con2 = bar.close_price >= self.last_ema
if con1 and con2:
self.exit_long_nex = bar.close_price # 保存当前收盘价
if self.exit_long_last == 0 or self.exit_long_nex > self.exit_long_last:
self.exit_long_last = self.exit_long_nex
self.ema_length_new = self.ema_length
self.exit_long = self.ema_mid
else:
if bar.close_price > (
(self.ema_mid + self.current_ema) / 2):
self.exit_long = bar.close_price
elif bar.close_price < self.ema_mid:
self.exit_long = bar.close_price
else:
self.exit_long = self.ema_mid
else:
self.exit_long = self.ema_mid
self.sell(self.exit_long, abs(self.pos), True)
elif self.pos < 0:
con1 = bar.close_price > self.current_ema
con2 = bar.close_price <= self.last_ema
if con1 and con2:
self.exit_short_nex = bar.close_price
if self.exit_short_last == 0 or self.exit_short_nex < self.exit_short_last:
self.exit_short_last = self.exit_short_nex
self.ema_length_new = self.ema_length
self.exit_short = self.ema_mid
else:
if bar.close_price < (self.ema_mid + self.current_ema / 2):
self.exit_short = bar.close_price
elif bar.close_price < self.ema_mid:
self.exit_short = bar.close_price
else:
self.exit_short = self.ema_mid
else:
self.exit_short = self.ema_mid
self.cover(self.exit_short, abs(self.pos), True)
self.put_event()
self.sync_data()
def on_xmin_bar(self, bar: BarData):
"""
Callback of new bar data update.
"""
self.am.update_bar(bar)
if not self.am.inited:
return
# 计算海龟 上轨，下轨
high_max = self.am.high[-self.rolling_period:].max()
close_min = self.am.close[-self.rolling_period:].min()
close_max = self.am.close[-self.rolling_period:].max()
low_min = self.am.low[-self.rolling_period:].min()
hc = high_max - close_min
cl = close_max - low_min
dual = max(hc, cl)
self.up = self.am.open[-2] + dual * self.upper_open
self.down = self.am.open[-2] - dual * self.upper_open
# print(f"up:{self.up},{self.down}")
self.current_close = self.am.close[-1]
self.last_close = self.am.close[-2]
self.front_close = self.am.close[-3]
if self.pos == 0:
self.exit_long_nex = 0
self.exit_long_last = 0
self.exit_short_nex = 0
self.exit_short_last = 0
self.ema_length_new = self.ema_length
elif self.pos > 0:
close_long = self.current_close > self.last_close > self.front_close
if close_long:
self.ema_length_new -= 1
self.ema_length_new = max(self.ema_length_new, 5)
elif self.pos < 0:
close_short = self.current_close < self.last_close < self.front_close
if close_short:
self.ema_length_new -= 1
self.ema_length_new = max(self.ema_length_new, 5)
self.ema_mid = self.am.ema(self.ema_length)
ema_mid_new = self.am.ema(self.ema_length_new, True)
self.current_ema = ema_mid_new[-1]
self.last_ema = ema_mid_new[-2]
def on_order(self, order: OrderData):
"""
Callback of new order data update.
"""
pass
def on_trade(self, trade: TradeData):
"""
Callback of new trade data update.
"""
pass
def on_stop_order(self, stop_order: StopOrder):
"""
Callback of stop order update.
"""
pass
# self.put_event()
def market_order(self):
""""""
pass
# self.buy(self.last_tick.limit_up, 1)
# self.write_log("执行市价单测试")
def limit_order(self):
""""""
pass
# self.buy(self.last_tick.limit_down, 1)
# self.write_log("执行限价单测试")
def stop_order(self):
""""""
pass
class CciSignal(CtaSignal):
"""
"""
cci_up_array = 0
cci_dow_array = 0
cci_value = 0
cci_up = 0
cci_down = 0
cci_ma = 0
last_cci_value = 0
current_cci_value = 0
last_cci_up = 0
current_cci_up = 0
last_cci_down = 0
current_cci_down = 0
last_cci_ma = 0
current_cci_ma = 0
def __init__(self, open_window: int, cci_window: int, cci_level: float):
""""""
super().__init__()
self.open_window = open_window
self.cci_window = cci_window
self.cci_level = cci_level
self.cci_long = self.cci_level
self.cci_short = -self.cci_level
self.bg = BarGenerator(self.on_bar, self.open_window, self.on_x_bar)
self.am = ArrayManager()
def on_tick(self, tick: TickData):
"""
Callback of new tick data update.
"""
self.bg.update_tick(tick)
def on_bar(self, bar: BarData):
"""
:param bar:
:return:
"""
self.bg.update_bar(bar)
def on_x_bar(self, bar: BarData):
"""
Callback of new bar data update.
"""
self.am.update_bar(bar)
if not self.am.inited:
self.set_signal_pos(0)
# 计算 前一根K线的 cci
cci_array = talib.CCI(self.am.high[:-1], self.am.low[:-1],
self.am.close[:-1], self.cci_window)
cci_ema = talib.EMA(cci_array, self.cci_window)
dev_array = abs(
cci_array[-self.cci_window:] -
cci_ema[-self.cci_window:]) / cci_ema[-self.cci_window:]
dev = np.max(dev_array[-self.cci_window:])
self.cci_up_array = cci_ema[
-self.cci_window:] + cci_array[-self.cci_window:] * dev
self.cci_dow_array = cci_ema[
-self.cci_window:] - cci_array[-self.cci_window:] * dev
self.cci_value = self.am.cci(self.cci_window, True)
self.last_cci_value = self.cci_value[-2]
self.current_cci_value = self.cci_value[-1]
self.last_cci_up = self.cci_up_array[-2]
self.current_cci_up = self.cci_up_array[-1]
self.last_cci_down = self.cci_dow_array[-2]
self.current_cci_down = self.cci_dow_array[-1]
self.last_cci_ma = cci_ema[-2]
self.current_cci_ma = cci_ema[-1]
if self.last_cci_value <= self.last_cci_up and self.current_cci_value > self.current_cci_up:
self.set_signal_pos(1)
elif self.last_cci_value >= self.last_cci_up and self.current_cci_value < self.current_cci_up:
self.set_signal_pos(-1)
cci_sell = self.last_cci_value >= self.last_cci_ma and self.current_cci_value < self.current_cci_ma
cci_court = self.last_cci_value <= self.last_cci_ma and self.current_cci_value > self.current_cci_ma
if cci_sell and cci_court:
self.set_signal_pos(0)
class DudlThrustKkStrategy(CtaTemplate):
""""""
author = "yunyu"
xminute_window = 1
rolling_period = 70
upper_open = 0.2
lower_open = 0.2
cci_window = 30
keltner_window = 24
keltner_dev = 1
fixed_size = 1
cci_value = 0
exit_kk_up = 0
exit_kk_down = 0
dualthrust_up = 0
dualthrust_down = 0
ask = 0
bid = 0
parameters = [
"xminute_window",
"rolling_period",
"upper_open",
"lower_open",
"cci_window",
"keltner_window",
"keltner_dev",
"fixed_size",
]
variables = [
"dualthrust_up",
"dualthrust_down",
"cci_value",
"exit_kk_up",
"exit_kk_down",
]
def __init__(self, cta_engine, strategy_name, vt_symbol, setting):
""""""
super().__init__(cta_engine, strategy_name, vt_symbol, setting)
self.bg = NewBarGenerator(on_bar=self.on_bar,
window=self.xminute_window,
on_window_bar=self.on_min_bar,
interval=Interval.MINUTE)
self.am = ArrayManager()
def on_init(self):
"""
Callback when strategy is inited.
"""
self.write_log("策略初始化")
self.load_bar(10)
def on_start(self):
"""
Callback when strategy is started.
"""
self.write_log("策略启动")
def on_stop(self):
"""
Callback when strategy is stopped.
"""
self.write_log("策略停止")
def on_tick(self, tick: TickData):
"""
Callback of new tick data update.
"""
self.bg.update_tick(tick)
self.ask = tick.ask_price_1 # 卖一价
self.bid = tick.bid_price_1 # 买一价
def on_bar(self, bar: BarData):
"""
Callback of new bar data update.
"""
self.bg.update_bar(bar)
def on_min_bar(self, bar: BarData):
"""
Callback of new bar data update.
"""
self.am.update_bar(bar)
self.cancel_all()
if not self.am.inited:
return
self.dualthrust_up, self.dualthrust_down = self.dualthrust(
self.am.high, self.am.low, self.am.close, self.am.open,
self.rolling_period, self.upper_open, self.lower_open)
self.cci_value = self.am.cci(self.cci_window)
print(self.cci_value)
self.keltner_up, self.keltner_down = self.am.keltner(
self.keltner_window, self.keltner_dev)
if self.pos == 0:
if self.cci_value > 0:
self.buy(self.dualthrust_up, self.fixed_size, True)
elif self.cci_value < 0:
self.short(self.dualthrust_down, self.fixed_size, True)
elif self.pos > 0:
self.sell(self.exit_kk_down, self.fixed_size, True)
elif self.pos < 0:
self.cover(self.exit_kk_up, self.fixed_size, True)
self.put_event()
self.sync_data()
self.put_event()
def on_order(self, order: OrderData):
"""
Callback of new order data update.
"""
pass
def on_trade(self, trade: TradeData):
"""
Callback of new trade data update.
"""
self.put_event()
def on_stop_order(self, stop_order: StopOrder):
"""
Callback of stop order update.
"""
pass
# self.put_event()
def market_order(self):
""""""
pass
# self.buy(self.last_tick.limit_up, 1)
# self.write_log("执行市价单测试")
def limit_order(self):
""""""
pass
# self.buy(self.last_tick.limit_down, 1)
# self.write_log("执行限价单测试")
def stop_order(self):
""""""
pass
# self.buy(self.last_tick.ask_price_1, 1, True)
# self.write_log("执行停止单测试")
def dualthrust(self, high, low, close, open, n, k1, k2):
"""
:param high:
:param low:
:param close:
:return:
"""
#计算N日最高价的最高价，收盘价的最高价、最低价，最低价的最低价
hh = high[-n:].max()
lc = close[-n:].min()
hc = close[-n:].max()
ll = low[-n:].min()
#计算range,上下轨的距离前一根K线开盘价的距离
range = max(hh - lc, hc - ll)
up = open[-2] + k1 * range
down = open[-2] - k2 * range
return up, down
class MaLevelTrackStrategy(CtaTemplate):
author = "用Python的交易员"
ma_level = [5, 10, 20, 30, 120]
ma_tag = []
bd = []
fast_ma0 = 0.0
fast_ma1 = 0.0
slow_ma0 = 0.0
slow_ma1 = 0.0
request_order = []
bar_identify = []
parameters = ["ma_level"]
variables = ["fast_ma0", "fast_ma1", "slow_ma0", "slow_ma1"]
def __init__(self, cta_engine, strategy_name, vt_symbol, setting):
""""""
super(MaLevelTrackStrategy, self).__init__(cta_engine, strategy_name,
vt_symbol, setting)
self.bg = BarGenerator(self.on_bar, 15, self.on_1min_bar)
self.am = ArrayManager(400)
self.am3 = ArrayManager(150)
self.bg3 = BarGenerator(self.on_bar, 3, self.on_3min_bar)
self.am5 = ArrayManager(120)
self.bg5 = BarGenerator(self.on_bar, 5, self.on_5min_bar)
self.order_data = None
self.positions = Position(self)
self.std_range = IntervalGen(np.std, 5)
self.std_range3 = IntervalGen(np.std, 5)
self.std_range5 = IntervalGen(np.std, 5)
self.pattern_record = PatternRecord()
# self.pattern_record.set_expiry([KlinePattern.CDLEVENINGSTAR], 3)
self.pattern_record.set_expiry(list(KlinePattern), 1)
five_min_open_5 = partial(self.reverse_shape_strategy,
setting={
"atr": 10,
"atr_valve": 0.8,
"deg1": (10, 5),
"deg2": 5
})
self.open_strategy = {
"1": [self.reverse_shape_strategy],
"5": [five_min_open_5],
}
self.offset = 40
self.ma120_track = None
self.ma120_track_list = []
def on_init(self):
"""
Callback when strategy is inited.
"""
self.write_log("策略初始化")
self.load_bar(10)
def on_start(self):
"""
Callback when strategy is started.
"""
self.write_log("策略启动")
self.put_event()
def on_stop(self):
"""
Callback when strategy is stopped.
"""
self.write_log("策略停止")
self.put_event()
def on_tick(self, tick: TickData):
"""
Callback of new tick data update.
"""
self.bg.update_tick(tick)
self.bg3.update_tick(tick)
self.bg5.update_tick(tick)
def on_3min_bar(self, bar: BarData):
self.am3.update_bar(bar)
self.std_range3.update(self.am3.range[-1])
if not self.am.inited or not self.trading:
return
pattern = self.am3.pattern(
[KlinePattern.CDLEVENINGSTAR, KlinePattern.CDL2CROWS])
if len(pattern) > 0:
print(pattern)
self.pattern_record.add_pattern(pattern)
# deg = calc_regress_deg(self.am3.close[-20:])
def wave(self, data, window=0.0002):
if len(data) <= 0:
return
# r = array[::-1]
result = {"value": [], "range": [], "pos": [], "length": []}
r = data
l = len(data) - 1
now = r[0]
# v_list.append(now)
# p_list.append(0)
pos = 1
vol = 0
u_tag = None
d_tag = None
end_tag = None
start_pos = 0
while pos < l:
if math.isnan(now):
now = r[pos]
pos += 1
continue
else:
start_pos = pos - 1
break
while pos < l:
if now < r[pos]:
u_tag = pos
if d_tag:
diff = r[start_pos] - r[d_tag]
if abs(diff /
r[start_pos]) > window and d_tag - start_pos > 1:
end_tag = d_tag
elif now > r[pos]:
d_tag = pos
if u_tag:
diff = r[start_pos] - r[u_tag]
if abs(diff /
r[start_pos]) > window and d_tag - start_pos > 1:
end_tag = u_tag
if end_tag is not None:
result["range"].append(r[end_tag] / r[start_pos] - 1)
result["length"].append(end_tag - start_pos)
start_pos = end_tag
result["value"].append(r[end_tag])
result["pos"].append(end_tag)
end_tag = None
vol += r[pos] - now
now = r[pos]
pos += 1
return pd.DataFrame(result)
def mode_identify(self, bar: BarData):
self.bar_identify = []
hl_scale = round(bar.high_price / bar.low_price - 1, 4)
if hl_scale > 0.001:
diff = bar.high_price - bar.low_price
diff_up = bar.low_price + diff / 2 * 1.20
diff_down = bar.low_price + diff / 2 * 0.80
close = bar.close_price
if bar.open_price < diff_up and bar.open_price > diff_down and \
bar.close_price < diff_up and bar.close_price > diff_down:
if bar.close_price > bar.open_price:
print("绿十字星", bar.datetime, bar.high_price, bar.low_price,
diff, diff_up, diff_down, bar.open_price,
bar.close_price)
else:
print("红十字星", bar.datetime, bar.high_price, bar.low_price,
diff, diff_up, diff_down, bar.open_price,
bar.close_price)
def on_5min_bar(self, bar: BarData):
self.std_range5.update(self.am5.range[-1])
self.am5.update_bar(bar)
if not self.am.inited or not self.trading:
return
self.on_strategy(self.am5, bar, self.open_strategy["5"])
# pattern_list = [KlinePattern.CDLEVENINGSTAR, KlinePattern.CDL2CROWS, KlinePattern.CDLCONCEALBABYSWALL, KlinePattern.CDLEVENINGDOJISTAR]
# pattern = self.am5.pattern(list(KlinePattern))
# if len(pattern) > 0:
# print(list(map(lambda x: (KLINE_PATTERN_CHINESE[x[0]],x[1]), pattern)))
# self.pattern_record.add_pattern(pattern)
# deg_full = calc_regress_deg(self.am.close[-40 :], False)
# print("deg:",deg_full)
# self.pattern_record.update()
def open_v3(self, am: ArrayManager, bar: BarData):
std_val2 = np.std(np.array(self.ma_tag[-10:-1]))
mean_val2 = np.mean(np.array(self.ma_tag[-10:-1]))
mean = np.mean(np.array(self.ma_tag[-30:-10]))
if std_val2 < 0.2:
if mean_val2 > 3:
if mean_val2 >= (mean + 1):
return self.buy(bar.close_price, 1, type=OrderType.MARKET)
elif mean_val2 < 2:
if mean_val2 <= (mean - 1):
return self.short(bar.close_price,
1,
type=OrderType.MARKET)
def open_v1(self, am: ArrayManager, bar: BarData):
offset = -40
offset_m = int(offset / 2)
calc_nums = np.array(self.ma_tag[-offset:-1])
mean_val = np.mean(calc_nums)
# var_val = np.var(calc_nums)
std_val = np.std(calc_nums)
if std_val < 1 and mean_val < 2 and self.ma_tag[-1] >= (mean_val + 2):
return self.buy(bar.close_price, 1, type=OrderType.MARKET)
elif std_val < 1 and mean_val > 3 and self.ma_tag[-1] <= (mean_val -
2):
return self.short(bar.close_price, 1, type=OrderType.MARKET)
def open_v2(self, am: ArrayManager, bar: BarData):
std_val2 = np.std(np.array(self.ma_tag[-10:-1]))
mean_val2 = np.mean(np.array(self.ma_tag[-10:-1]))
mean = np.mean(np.array(self.ma_tag[-30:-10]))
if std_val2 < 0.2:
if mean_val2 > 2.5:
if mean_val2 >= (mean + 1):
return self.buy(bar.close_price, 1, type=OrderType.MARKET)
elif mean_val2 < 2.5:
if mean_val2 <= (mean - 1):
return self.short(bar.close_price,
1,
type=OrderType.MARKET)
def open2(self, am: ArrayManager, bar: BarData, calc_data):
deg = calc_data["deg20"]
ma = self.ma_tag[-1]
if deg > 0.5 and ma > 3 and self.am5.range[-1] > -0.002:
return self.buy(bar.close_price, 1, type=OrderType.MARKET)
elif deg < -0.5 and ma < 2 and self.am5.range[-1] < 0.002:
return self.short(bar.close_price, 1, type=OrderType.MARKET)
def open1(self, am: ArrayManager, bar: BarData, calc_data):
mean = calc_data["mean30_10"]
mean_val2 = calc_data["mean10"]
# if std_val2 < 0.2:
if mean_val2 > 3.5 and mean_val2 >= (mean + 2):
return self.buy(bar.close_price, 1, type=OrderType.MARKET)
elif mean_val2 < 1.5 and mean_val2 <= (mean - 2):
return self.short(bar.close_price, 1, type=OrderType.MARKET)
# v形反转捕获
def reverse_shape_strategy(self,
am: ArrayManager,
bar: BarData,
calc_data,
setting={
"atr": 40,
"atr_valve": 0.8,
"deg1": (40, 20),
"deg2": (20, 0),
}):
deg1 = calc_data["deg40_20"]
deg2 = calc_data["deg20_0"]
kdj = calc_data["kdj"]
atr = self.am.atr(40)
if atr < 0.08:
return
if deg1 > 0 and deg2 > 0 or \
deg1 < 0 and deg2 < 0:
return
if not (abs(deg1) > 0.15 and abs(deg2) > 0.1 and
(abs(deg1) + abs(deg2)) > 0.3):
return
close = am.close[-40:]
min_val = np.min(close)
max_val = np.max(close)
mid_val = max_val if deg1 > 0 else min_val
mid_pos = np.where(close == mid_val)[0][0]
if mid_pos < 10 or mid_pos > 30:
return
start_val = np.min(close[:mid_pos]) if deg1 > 0 else np.max(
close[:mid_pos])
start_pos = np.where(close == start_val)[0][0]
l = mid_pos - start_pos
# pos2 = np.where(close == min_val)[0][0]
x_fit = reg_util.regress_y_polynomial(close[:mid_pos], zoom=True)
deg1_remake = calc_regress_deg(x_fit[:abs(mid_pos)], False)
y_fit = reg_util.regress_y_polynomial(close[mid_pos:], zoom=True)
deg2_remake = calc_regress_deg(y_fit[:abs(mid_pos)], False)
print(start_pos, mid_pos, deg1, deg2, deg1_remake, deg2_remake, l,
start_val, mid_val)
if deg2 < 0:
if kdj[0] < 20 and kdj[1] < 10 and kdj[2] < 10:
# if kdj[2] < 10:
return self.short(bar.close_price, 1, type=OrderType.MARKET)
else:
if kdj[0] > 80 and kdj[1] > 90 and kdj[2] > 90:
# if kdj[2] > 90:
return self.buy(bar.close_price, 1, type=OrderType.MARKET)
# print("找到大v形:", deg1, deg2 )
def open5(self, am: ArrayManager, bar: BarData, calc_data):
ma = self.ma_tag[-1]
mean = calc_data["mean30_10"]
atr = self.am.atr(10, array=True, length=20)
tr = self.am.atr(1, array=True, length=11)
# self.ma120_track
ma120 = self.am.sma(120)
# if std_val2 < 0.2:
mean_std = calc_data["mean_std"]
if mean_std < 0.8 and tr[-1] > 0.1 and tr[-1] / tr[-10] > 3 and tr[
-1] / atr[-1] >= 1.7 and tr[-10] / atr[-10] < 1:
if np.sum(self.am.range[-10:]) > 0 and self.ma120_track > 0:
return self.buy(bar.close_price, 1, type=OrderType.MARKET)
elif self.ma120_track < 0:
return self.short(bar.close_price, 1, type=OrderType.MARKET)
def open_kline1(self, am: ArrayManager, bar: BarData, calc_data):
if KlinePattern.CDLEVENINGSTAR not in self.pattern_record:
return
# if std_val2 < 0.2:
deg = calc_regress_deg(self.am.close[-5:], False)
print("kline_strategy", deg)
if deg < -0.1:
return self.short(bar.close_price, 1, type=OrderType.MARKET)
def generate_data(self, bar: BarData):
offset = -self.offset
offset_m = int(offset / 2)
calc_nums = np.array(self.ma_tag[-offset:-1])
# var_val = np.var(calc_nums)
std_val = np.std(calc_nums)
std_val2 = np.std(np.array(self.ma_tag[-10:-1]))
std_val3 = np.std(np.array(self.am.range[-30:-10]))
ma = self.ma_tag[-1]
mean_val = np.mean(calc_nums)
mean_val2 = np.mean(np.array(self.ma_tag[-5:-1]))
mean_val3 = np.mean(np.array(self.ma_tag[-20:-1]))
mean_val4 = np.mean(np.array(self.ma_tag[-30:-5]))
kdj_val = self.am.kdj()
deg1 = calc_regress_deg(self.am.close[offset:offset_m], False)
deg2 = calc_regress_deg(self.am.close[offset_m:], False)
deg3 = calc_regress_deg(self.am.close[-10:], False)
deg_full = calc_regress_deg(self.am.close[offset:], False)
wave = self.wave(self.am.close[-30:])
wave_r_sum = np.sum(wave["range"])
macd = self.am.macd(20, 40, 16)
calc_data = (dict(
kdj=[
round(kdj_val["k"][-1], 2),
round(kdj_val["d"][-1], 2),
round(kdj_val["j"][-1], 2)
],
cci_20=self.am.cci(20),
rsi=self.am.rsi(20),
adx=self.am.adx(20),
boll=self.am.boll(20, 3.4),
macd=[round(macd[0], 2),
round(macd[1], 2),
round(macd[2], 2)],
deg40_20=round(deg1, 2),
deg20_0=round(deg2, 2),
deg20_10=round(calc_regress_deg(self.am.close[-20:-10], False), 2),
deg10_0=round(deg3, 2),
deg30_15=round(calc_regress_deg(self.am.close[-30:-15], False), 2),
deg15_0=round(calc_regress_deg(self.am.close[-15:], False), 2),
deg_f=round(deg_full, 2),
atr=round(self.am.atr(10, length=15), 3),
tr=round(self.am.atr(1, length=2), 3),
atr_40=round(self.am.atr(40, length=42), 3),
time=bar.datetime,
price=bar.close_price,
ma=round(ma, 2),
std_40=round(std_val, 2),
mean40=round(mean_val, 2),
mean_std=np.mean(self.std_range.data[-5:]),
std_10=round(std_val2, 2),
mean30_10=round(mean_val4, 2),
mean10=round(mean_val2, 2),
vol=self.am.volume[-1],
std_range=self.std_range.data[-1:-5:-1],
range=self.am.range[-1:-5:-1].tolist(),
range_sum=np.sum(self.am.range[-5:]),
pattern=list(
map(lambda x: KLINE_PATTERN_CHINESE[x],
self.pattern_record.keys())),
ma120t=self.ma120_track,
ma120t_list=self.ma120_track_list[-1:-10:-1],
ma120t_sort=sorted(self.ma120_track_list[-20:-1], key=abs),
ma120t_sum=np.sum(self.ma120_track_list[-20:-1] +
[self.ma120_track]),
ma120t_mean=np.mean(self.ma120_track_list[-20:-1] +
[self.ma120_track]),
ma120t_std=np.std(self.ma120_track_list[-20:-1] +
[self.ma120_track]),
wave_cnt=len(wave),
wave_r_sum=wave_r_sum,
atr_mean=np.mean(self.am.atr(20, array=True, length=240)[-200:])))
return calc_data
def on_strategy(self, am: ArrayManager, bar: BarData, strategy_list):
calc_data = self.generate_data(bar)
order_id = None
if self.pos == 0:
for open_strategy in strategy_list:
if order_id is not None:
break
order_id = open_strategy(am, bar, calc_data)
else:
order_id = self.positions.on_strategy(bar, calc_data)
if order_id is not None:
offset = -self.offset
offset_m = int(offset / 2)
self.tracker["trade_info"].append(
(self.am.time_array[offset], self.am.time_array[offset_m],
bar.datetime, calc_data["deg40_20"], calc_data["deg20_0"]))
self.request_order.extend(order_id)
if self.tracker is not None:
self.tracker["ma_tag_ls"].append(calc_data)
def on_1min_bar(self, bar: BarData):
self.am.update_bar(bar)
am = self.am
max_len = self.ma_level[-1] + 20
data = self.am.close[-max_len:-1]
ma_lvl = []
for i in self.ma_level:
ma = self.am.sma(i, True)[-1]
ma_lvl.append(ma)
l = len(ma_lvl)
ma_lvl_tag = []
now = bar.close_price
direction = 1 if now > ma_lvl[0] else 0
ma_lvl_tag.append(direction)
for i in range(l - 1):
val = 1 if ma_lvl[i] > ma_lvl[i + 1] else 0
ma_lvl_tag.append(val)
bincount_val = np.bincount(np.array(ma_lvl_tag))
tag_val = 0
if len(bincount_val) == 2:
tag_val = bincount_val[1]
if len(self.ma_tag) < 200:
self.ma_tag.append(tag_val)
else:
self.ma_tag[:-1] = self.ma_tag[1:]
self.ma_tag[-1] = tag_val
if self.tracker is not None:
self.tracker["bar_data"].append(bar)
self.std_range.update(self.am.range[-1])
ma120 = self.am.sma(120)
if bar.close_price >= ma120:
if self.ma120_track is None:
self.ma120_track = 1
elif self.ma120_track > 0:
self.ma120_track += 1
else:
self.ma120_track_list.append(self.ma120_track)
self.ma120_track = 1
elif bar.close_price < ma120:
if self.ma120_track is None:
self.ma120_track = -1
elif self.ma120_track < 0:
self.ma120_track -= 1
else:
self.ma120_track_list.append(self.ma120_track)
self.ma120_track = -1
if not am.inited or not self.trading:
return
self.on_strategy(am, bar, self.open_strategy["1"])
# median_val = np.median(calc_nums)
self.put_event()
def on_bar(self, bar: BarData):
"""
Callback of new bar data update.
"""
self.bg3.update_bar(bar)
self.bg5.update_bar(bar)
self.bg.update_bar(bar)
# def init_order_data(self):
# self.order_data = np.array([])
def on_order(self, order: OrderData):
"""
Callback of new order data update.
"""
print("{}产生了{},价格为{},笔数为{},交易{},pos={}".format(
order.datetime.strftime("%m/%d %H:%M:%S"),
order.offset.value + order.direction.value, order.price,
order.volume, order.status.value, self.pos))
if order.vt_orderid in self.request_order:
self.positions.on_order(order)
if order.status == Status.ALLTRADED or order.status == Status.CANCELLED or order.status == Status.REJECTED:
self.request_order.remove(order.vt_orderid)
# if order.status == Status.ALLTRADED or order.status == Status.PARTTRADED:
# if order.direction == Direction.LONG:
# if self.positions.volumn == 0:
# self.positions.close_price = round(order.price * 0.995)
# self.positions.volumn += order.volume
# elif order.direction == Direction.SHORT:
# self.positions.volumn -= order.volume
# elif order.direction == Direction.NET:
# self.positions.volumn = order.volume
def on_trade(self, trade: TradeData):
"""
Callback of new trade data update.
"""
self.put_event()
def on_stop_order(self, stop_order: StopOrder):
"""
Callback of stop order update.
"""
pass
class DudlThrust_NewStrategy(CtaTemplate):
""""""
author = "yunyu"
window_min = 15
rolling_period = 70
upper_open = 0.5
lower_open = 0.6
stop_multiplier = 1.8
dc_length = 30
cci_length = 10
cci_stop = 20
trailing_tax = 1.8
fixed_size = 1
up = 0
down = 0
exit_shour = 0
exit_long = 0
intra_trade_high = 0
intra_trade_low = 0
long_stop = 0
short_stop = 0
long_entry = 0
short_entry = 0
long_out = 0
short_out = 0
cci_value = 0
ask = 0
bid = 0
parameters = [
"window_min",
"rolling_period",
"upper_open",
"lower_open",
"stop_multiplier",
"dc_length",
"cci_length",
"cci_stop",
"trailing_tax",
"fixed_size",
]
variables = [
"up", "down", "exit_shour", "exit_long", "intra_trade_high",
"intra_trade_low", "long_stop", "short_stop", "long_entry",
"short_entry", "long_out", "short_out", "cci_value"
]
def __init__(self, cta_engine, strategy_name, vt_symbol, setting):
""""""
super().__init__(cta_engine, strategy_name, vt_symbol, setting)
self.bg = BarGenerator(on_bar=self.on_bar)
self.am = ArrayManager(
(max(self.dc_length, self.rolling_period) + 10) * 60)
self.bg_xmin = BarGenerator(on_bar=self.on_bar,
window=self.window_min,
on_window_bar=self.on_xmin_bar)
self.am_xmin = ArrayManager(
max(self.dc_length, self.rolling_period) + 10)
def on_init(self):
"""
Callback when strategy is inited.
"""
self.write_log("策略初始化")
self.load_bar(10)
def on_start(self):
"""
Callback when strategy is started.
"""
self.write_log("策略启动")
def on_stop(self):
"""
Callback when strategy is stopped.
"""
self.write_log("策略停止")
def on_tick(self, tick: TickData):
"""
Callback of new tick data update.
"""
self.bg.update_tick(tick)
self.ask = tick.ask_price_1 # 卖一价
self.bid = tick.bid_price_1 # 买一价
self.put_event()
def on_bar(self, bar: BarData):
"""
Callback of new bar data update.
"""
self.bg_xmin.update_bar(bar)
self.cancel_all()
self.exit_shour, self.exit_long = self.am.donchian(self.dc_length * 60)
if self.pos == 0:
self.intra_trade_high = bar.high_price
self.intra_trade_low = bar.low_price
if self.cci_value > self.cci_stop:
self.buy(self.up, self.fixed_size, True)
elif self.cci_value < -self.cci_stop:
self.short(self.down, self.fixed_size, True)
elif self.pos > 0:
self.intra_trade_high = max(self.intra_trade_high, bar.high_price)
self.intra_trade_low = bar.low_price
self.long_out = self.intra_trade_high * (1 -
self.trailing_tax / 100)
self.long_stop = max(self.long_entry, self.long_out,
self.exit_long)
self.sell(self.long_stop, abs(self.pos), True)
elif self.pos < 0:
self.intra_trade_high = bar.high_price
self.intra_trade_low = min(self.intra_trade_low, bar.low_price)
self.short_out = self.intra_trade_low * (1 +
self.trailing_tax / 100)
self.short_stop = min(self.short_entry, self.short_out,
self.exit_shour)
self.cover(self.short_stop, abs(self.pos), True)
self.put_event()
def on_xmin_bar(self, bar: BarData):
"""
Callback of new bar data update.
"""
self.am_xmin.update_bar(bar)
if not self.am_xmin.inited:
return
self.up, self.down = self.dualthrust(self.am_xmin.high,
self.am_xmin.low,
self.am_xmin.close,
self.am_xmin.open,
self.rolling_period,
self.upper_open, self.lower_open)
self.cci_value = self.am_xmin.cci(self.cci_length)
self.atr_value = self.am.atr(16)
self.put_event()
def on_order(self, order: OrderData):
"""
Callback of new order data update.
"""
pass
def on_trade(self, trade: TradeData):
"""
Callback of new trade data update.
"""
if trade.direction == Direction.LONG:
long_price = trade.price
self.long_entry = long_price - self.stop_multiplier * self.atr_value
else:
short_price = trade.price
self.short_entry = short_price + self.stop_multiplier * self.atr_value
self.put_event()
def on_stop_order(self, stop_order: StopOrder):
"""
Callback of stop order update.
"""
pass
# self.put_event()
def market_order(self):
""""""
pass
# self.buy(self.last_tick.limit_up, 1)
# self.write_log("执行市价单测试")
def limit_order(self):
""""""
pass
# self.buy(self.last_tick.limit_down, 1)
# self.write_log("执行限价单测试")
def stop_order(self):
""""""
pass
# self.buy(self.last_tick.ask_price_1, 1, True)
# self.write_log("执行停止单测试")
def dualthrust(self, high, low, close, open, n, k1, k2):
"""
:param high:
:param low:
:param close:
:return:
"""
#计算N日最高价的最高价，收盘价的最高价、最低价，最低价的最低价
hh = high[-n:-1].max()
lc = close[-n:-1].min()
hc = close[-n:-1].max()
ll = low[-n:-1].max()
#计算range,上下轨的距离前一根K线开盘价的距离
range = max(hh - lc, hc - ll)
up = open[-2] + k1 * range
down = open[-2] - k2 * range
return up, down
def generate_data(self, am:ArrayManager, bar:BarData):
offset = -self.offset
offset_m = int(offset / 2)
calc_nums = np.array(self.ma_tag[-offset:-1])
# var_val = np.var(calc_nums)
std_val = np.std(calc_nums)
std_val2 = np.std(np.array(self.ma_tag[-10:-1]))
std_val3 = np.std(np.array(am.range[-30:-10]))
ma = self.ma_tag[-1]
mean_val = np.mean(calc_nums)
mean_val2 = np.mean(np.array(self.ma_tag[-5:-1]))
mean_val3 = np.mean(np.array(self.ma_tag[-20:-1]))
mean_val4 = np.mean(np.array(self.ma_tag[-30:-5]))
kdj_val = am.kdj()
has_kdj_recore = False
k = kdj_val["k"]
d = kdj_val["d"]
j = kdj_val["j"]
if (k[-1] > 75 and d[-1] > 75 and j[-1] > 75) or \
(k[-1] < 25 and d[-1] < 25 and j[-1] < 75):
if (j[-2] < k[-2] or j[-2] < d[-2]) and (j[-1] > k[-1] and j[-1] > d[-1]) \
or \
(j[-2] > k[-2] or j[-2] > d[-2]) and (j[-1] < k[-1] and j[-1] < d[-1]):
has_kdj_recore = True
t = local_to_eastern(bar.datetime.timestamp())
self.kdj_record.append((t.strftime("%H:%M:%S"), round(k[-1], 3), round(d[-1], 3), round(j[-1], 3)))
deg1 = calc_regress_deg(am.close[offset : offset_m], False)
deg2 = calc_regress_deg(am.close[offset_m :], False)
deg3 = calc_regress_deg(am.close[-10 :], False)
deg_full = calc_regress_deg(am.close[offset :], False)
wave = self.wave(am.close[-30:])
wave_r_sum = np.sum(wave["range"])
macd=am.macd(20,40, 16)
calc_data = (dict(
ma_info=self.ma_info[-1:],
kdj=[round(kdj_val["k"][-1],2),round(kdj_val["d"][-1],2),round(kdj_val["j"][-1],2)],
cci_20=am.cci(20),rsi=am.rsi(20),adx=am.adx(20),boll=am.boll(20, 3.4),
macd=[round(macd[0],2),round(macd[1],2),round(macd[2],2)],
deg40_20=round(deg1,2), deg20_0=round(deg2,2), deg20_10=round(calc_regress_deg(am.close[-20:-10], False),2),
deg30_10=round(calc_regress_deg(am.close[-30:-10], False),2),deg10_0=round(deg3,2),
deg30_15=round(calc_regress_deg(am.close[-30:-15], False),2), deg15_0=round(calc_regress_deg(am.close[-15:], False),2),deg_f=round(deg_full,2),
atr=round(am.atr(10, length=15), 3), tr=round(am.atr(1, length=2), 3),atr_40=round(am.atr(40, length=42), 3),
time=bar.datetime, price=bar.close_price, ma=round(ma, 2),
std_40=round(std_val, 2),mean40=round(mean_val,2), mean_std=np.mean(self.std_range.data[-5:]),
std_10=round(std_val2,2), mean30_10=round(mean_val4,2), mean10=round(mean_val2,2),
vol=am.volume[-1], std_range=self.std_range.data[-1:-5:-1], range=am.range[-1:-5:-1].tolist(),
range_sum=np.sum(am.range[-5:]),
pattern=list(map(lambda x: KLINE_PATTERN_CHINESE[x], self.pattern_record.keys())),
ma120t=self.ma120_track,
ma120t_list=self.ma120_track_list[-1:-10:-1],
ma120t_sort=sorted(self.ma120_track_list[-20:-1], key=abs),
ma120t_sum=np.sum(self.ma120_track_list[-20:-1] + [self.ma120_track]),
ma120t_mean=np.mean(self.ma120_track_list[-20:-1] + [self.ma120_track]),
ma120t_std=np.std(self.ma120_track_list[-20:-1] + [self.ma120_track]),
wave_cnt=len(wave), wave_r_sum=wave_r_sum, atr_mean=np.mean(am.atr(20, array=True,length=240)[-200:]),
kdj_record=self.kdj_record[-10:],
))
if self.ma_info[-1]["ma5"] <= 0.16:
calc_data["kdj_key"] = True
return calc_data
def reverse2_strategy(self, am:ArrayManager, bar:BarData, calc_data, setting={"len":40, "atr":40, "atr_valve":0.09, "mid_sign":(10,30)}):
length = 30
offset1 = -30
offset2 = int(-10)
close = am.close
deg1 = calc_regress_deg(close[-30:-8], False)
deg2 = calc_regress_deg(close[-8:], False)
if deg1 > 0 and deg2 > 0 or \
deg1 < 0 and deg2 < 0:
return
if not (abs(deg1) > 0.15 and abs(deg2) > 0.15 and (abs(deg1) + abs(deg2)) > 0.35) :
return
close = am.close[-length:]
min_val = np.min(close)
max_val = np.max(close)
mid_val = max_val if deg1 > 0 else min_val
mid_pos = np.where(close == mid_val)[0][0]
if mid_pos < setting["mid_sign"][0] or mid_pos > setting["mid_sign"][1]:
return
start_val = np.min(close[:mid_pos]) if deg1 > 0 else np.max(close[:mid_pos])
start_pos = np.where(close == start_val)[0][0]
l = mid_pos - start_pos
# pos2 = np.where(close == min_val)[0][0]
kdj = am.kdj()
k = kdj["k"][-1]
d = kdj["d"][-1]
j = kdj["j"][-1]
x_fit = reg_util.regress_y_polynomial(close[:mid_pos], zoom=True)
deg1_remake = calc_regress_deg(x_fit[:abs(mid_pos)], False)
y_fit = reg_util.regress_y_polynomial(close[mid_pos:], zoom=True)
deg2_remake = calc_regress_deg(y_fit[:abs(mid_pos)], False)
# print(start_pos, mid_pos, deg1, deg2, deg1_remake, deg2_remake, l, start_val, mid_val)
cci = am.cci(20)
ma60 = am.sma(60)
if deg2 < 0:
# if k < 20 and d < 10 and j < 10:
# if kdj[2] < 10:
if cci < -100 and bar.close_price < ma60:
if self.pos == 0:
calc_data["trade_open"] = "开空,deg={},cci={}".format(deg2, cci)
return self.short(bar.close_price, 1, type=OrderType.MARKET)
elif self.pos > 0:
calc_data["trade_close"] = "平多后做空仓,deg={},cci={}".format(deg2, cci)
order_id_cover = self.sell(bar.close_price, abs(self.volumn), type=OrderType.MARKET)
order_id_buy = self.short(bar.close_price, 1, type=OrderType.MARKET)
return order_id_cover.extend(order_id_buy)
else:
# if k > 80 and d > 90 and j > 90:
# if kdj[2] > 90:
if cci > 100 and bar.close_price > ma60:
if self.pos == 0:
calc_data["trade_open"] = "开多,deg={},cci={}".format(deg2, cci)
return self.buy(bar.close_price, 1, type=OrderType.MARKET)
elif self.pos < 0:
calc_data["trade_close"] = "平空后多仓,deg={},cci={}".format(deg2, cci)
order_id_cover = self.cover(bar.close_price, abs(self.volumn), type=OrderType.MARKET)
order_id_buy = self.buy(bar.close_price, 1, type=OrderType.MARKET)
return order_id_cover.extend(order_id_buy)
class MinuteSuperTurtleStrategy(CtaTemplate):
"""
唐安奇通道策略
"""
author = "yuya"
open_window = 15
entry_window = 28
exit_window = 7
atr_window = 4
cci_window = 10
risk_level = 0.2
trading_size = 0
entry_up = 0
entry_down = 0
exit_up = 0
exit_down = 0
atr_value = 0
cci_value = 0
long_entry = 0
short_entry = 0
long_stop = 0
short_stop = 0
parameters = [
"open_window", "entry_window", "exit_window", "atr_window",
"risk_level", "cci_window"
]
variables = [
"entry_up", "entry_down", "exit_up", "exit_down", "trading_size",
"atr_value", "cci_value"
]
def __init__(self, cta_engine, strategy_name, vt_symbol, setting):
""""""
super().__init__(cta_engine, strategy_name, vt_symbol, setting)
self.bg = BarGenerator(self.on_bar, self.open_window, self.on_hour_bar)
self.am = ArrayManager()
def on_init(self):
"""
Callback when strategy is inited.
"""
self.write_log("策略初始化")
self.load_bar(20)
def on_start(self):
"""
Callback when strategy is started.
"""
self.write_log("策略启动")
def on_stop(self):
"""
Callback when strategy is stopped.
"""
self.write_log("策略停止")
def on_tick(self, tick: TickData):
"""
Callback of new tick data update.
"""
self.bg.update_tick(tick)
def on_bar(self, bar: BarData):
"""
Callback of new bar data update.
"""
self.bg.update_bar(bar)
def on_hour_bar(self, bar: BarData):
""""""
self.cancel_all()
self.am.update_bar(bar)
if not self.am.inited:
return
self.entry_up, self.entry_down = self.am.donchian(self.entry_window)
self.exit_up, self.exit_down = self.am.donchian(self.exit_window)
self.cci_value = self.am.cci(self.cci_window)
if not self.pos:
self.atr_value = self.am.atr(self.atr_window)
if self.atr_value == 0:
return
# 反向合约的计算方法，
atr_risk = talib.ATR(1 / self.am.high, 1 / self.am.low,
1 / self.am.close, self.atr_window)[-1]
self.trading_size = max(int(self.risk_level / atr_risk), 1)
self.long_entry = 0
self.short_entry = 0
self.long_stop = 0
self.short_stop = 0
if self.cci_value > 0:
self.buy(self.entry_up, self.trading_size, True)
elif self.cci_value < 0:
self.short(self.entry_down, self.trading_size, True)
elif self.pos > 0:
sell_price = max(self.long_stop, self.exit_down)
self.sell(sell_price, abs(self.pos), True)
elif self.pos < 0:
cover_price = min(self.short_stop, self.exit_up)
self.cover(cover_price, abs(self.pos), True)
self.put_event()
def on_trade(self, trade: TradeData):
"""
Callback of new trade data update.
"""
if trade.direction == Direction.LONG:
self.long_entry = trade.price # 成交最高价
self.long_stop = self.long_entry - 2 * self.atr_value
else:
self.short_entry = trade.price
self.short_stop = self.short_entry + 2 * self.atr_value
self.sync_data()
def on_order(self, order: OrderData):
"""
Callback of new order data update.
"""
pass
def on_stop_order(self, stop_order: StopOrder):
"""
Callback of stop order update.
"""
pass
class TurtleCCIStrategy(CtaTemplate):
"""基于布林通道的交易策略"""
className = 'TurtleCCIStrategy'
author = u'ForwardCapital'
# 策略参数
turtleWindow = 20 # 通道窗口数
trailingPrcnt = 0.4 # 移动止损百分比
CCIWindow = 14 # 过滤用均线窗口
ma1Window = 10 # 过滤用均线窗口
ma2Window = 20 # 过滤用均线窗口
initDays = 10 # 初始化数据所用的天数
fixedSize = 1 # 每次交易的数量
# 策略变量
periodHigh = 0 # 布林带中轨
periodLow = 0 # 布林带宽度
entryUp = 0 # 开仓上轨
exitUp = 0 # 平仓上轨
CCIFilter = 0 # 均线过滤
CCIFilter1 = 0 # 上一期均线
intraTradeHigh = 0 # 持仓期内的最高点
intraTradeLow = 0 # 持仓期内的最低点
longEntry = 0 # 多头开仓
longExit = 0 # 多头平仓
orderList = [] # 保存委托代码的列表
buyOrderID = None
sellOrderID = None
shortOrderID = None
coverOrderID = None
# 参数列表，保存了参数的名称
paramList = []
# 变量列表，保存了变量的名称
varList = []
# 同步列表
syncList = ['pos', 'intraTradeHigh', 'intraTradeLow']
#----------------------------------------------------------------------
def __init__(self, ctaEngine, setting):
"""Constructor"""
super(TurtleCCIStrategy, self).__init__(ctaEngine, setting)
self.bm = BarGenerator(self.on_bar, 15, self.onFiveBar)
self.am = ArrayManager()
#----------------------------------------------------------------------
def on_init(self):
"""初始化策略（必须由用户继承实现）"""
self.write_log(u'策略初始化')
# 载入历史数据，并采用回放计算的方式初始化策略数值
self.load_bar(self.initDays)
self.put_event()
#----------------------------------------------------------------------
def on_start(self):
"""启动策略（必须由用户继承实现）"""
self.write_log(u'策略启动')
self.put_event()
#----------------------------------------------------------------------
def on_stop(self):
"""停止策略（必须由用户继承实现）"""
self.write_log(u'策略停止')
self.put_event()
#----------------------------------------------------------------------
def on_tick(self, tick):
"""收到行情TICK推送（必须由用户继承实现）"""
self.bm.update_tick(tick)
#----------------------------------------------------------------------
def on_bar(self, bar):
"""收到Bar推送（必须由用户继承实现）"""
self.bm.update_bar(bar)
#----------------------------------------------------------------------
def orderIDConvert(self, orderList):
if not orderList:
return []
else:
return orderList[0]
#----------------------------------------------------------------------
def onFiveBar(self, bar, lastTick):
"""收到5分钟K线"""
# 保存K线数据
self.am.update_bar(bar)
if not self.am.inited or not self.trading:
return
# 撤销之前发出的尚未成交的委托（包括限价单和停止单）
print(u'onFiveBar↓↓↓↓↓↓↓↓↓↓↓↓↓↓↓↓↓↓↓↓↓↓,datetime:%s' % bar.datetime)
# 计算指标数值
self.entryUp = max(self.am.high[-self.turtleWindow:])
self.entryDown = min(self.am.low[-self.turtleWindow:])
self.entryUp = self.bollMid + self.bollStd * self.entryDev
self.exitUp = self.bollMid + self.bollStd * self.exitDev
ma1 = self.am.sma(self.ma1Window, False)
ma2 = self.am.sma(self.ma2Window, False)
cci = self.am.cci(self.CCIWindow, True)
# 判断是否要进行交易
if not self.buyOrderID or not self.shortOrderID:
if self.pos == 0:
# 下开仓单
if ma1 > ma2:
self.buyOrderID = self.buy(self.entryUp, self.fixedSize,
True)
self.buyOrderID = self.orderIDConvert(self.buyOrderID)
print('None order!!!buyOrderID is : %s ' % self.buyOrderID)
if self.buyOrderID:
self.orderList.append(self.buyOrderID)
else:
self.shortOrderID = self.short(self.entryDown,
self.fixedSize, True)
self.shortOrderID = self.orderIDConvert(self.shortOrderID)
print('None order!!!shortOrderID is : %s ' %
self.shortOrderID)
if self.shortOrderID:
self.orderList.append(self.shortOrderID)
elif self.pos > 0:
# 下平仓单
if cci[-1] < 100 and cci[-2] > 100:
# ######此处实盘需要修改发单价格
self.sellOrderID = self.sell(bar.low * 0.9, self.fixedSize)
self.sellOrderID = self.orderIDConvert(self.sellOrderID)
print('order None!!!sellOrderID is : %s ' %
self.sellOrderID)
if self.sellOrderID:
self.orderList.append(self.sellOrderID)
elif self.pos < 0:
# 下平仓单
if cci[-1] > -100 and cci[-2] < -100:
# ######此处实盘需要修改发单价格
self.coverOrderID = self.cover(bar.high * 0.9,
self.fixedSize)
self.coverOrderID = self.orderIDConvert(self.coverOrderID)
print('order None!!!coverOrderID is : %s ' %
self.coverOrderID)
if self.coverOrderID:
self.orderList.append(self.coverOrderID)
else:
if self.buyOrderID in self.orderList or self.shortOrderID in self.orderList:
self.cancel_all()
# 下开仓单
if ma1 > ma2:
self.buyOrderID = self.buy(self.entryUp, self.fixedSize,
True)
self.buyOrderID = self.orderIDConvert(self.buyOrderID)
print('buyOrderID is : %s ' % self.buyOrderID)
if self.buyOrderID:
self.orderList.append(self.buyOrderID)
else:
self.shortOrderID = self.short(self.entryDown,
self.fixedSize, True)
self.shortOrderID = self.orderIDConvert(self.shortOrderID)
print('shortOrderID is : %s ' % self.shortOrderID)
if self.shortOrderID:
self.orderList.append(self.shortOrderID)
else:
if self.pos > 0:
# 下平仓单
if cci[-1] < 100 and cci[-2] > 100:
# ######此处实盘需要修改发单价格
self.sellOrderID = self.sell(bar.low * 0.9,
self.fixedSize)
self.sellOrderID = self.orderIDConvert(
self.sellOrderID)
print('order None!!!sellOrderID is : %s ' %
self.sellOrderID)
if self.sellOrderID:
self.orderList.append(self.sellOrderID)
elif self.pos < 0:
# 下平仓单
if cci[-1] > -100 and cci[-2] < -100:
# ######此处实盘需要修改发单价格
self.coverOrderID = self.cover(bar.high * 0.9,
self.fixedSize)
self.coverOrderID = self.orderIDConvert(
self.coverOrderID)
print('order None!!!coverOrderID is : %s ' %
self.coverOrderID)
if self.coverOrderID:
self.orderList.append(self.coverOrderID)
elif self.pos == 0:
# 下开仓单
if ma1 > ma2:
self.buyOrderID = self.buy(self.entryUp,
self.fixedSize, True)
self.buyOrderID = self.orderIDConvert(self.buyOrderID)
print('buyOrderID is : %s ' % self.buyOrderID)
if self.buyOrderID:
self.orderList.append(self.buyOrderID)
else:
self.shortOrderID = self.short(self.entryDown,
self.fixedSize, True)
self.shortOrderID = self.orderIDConvert(
self.shortOrderID)
print('shortOrderID is : %s ' % self.shortOrderID)
if self.shortOrderID:
self.orderList.append(self.shortOrderID)
# 发出状态更新事件
# self.putEvent()
#----------------------------------------------------------------------
def on_order(self, order):
"""收到委托变化推送（必须由用户继承实现）"""
pass
#----------------------------------------------------------------------
def on_trade(self, trade):
"""收到成交推送（必须由用户继承实现）"""
print(u'成交推送：%s' % trade)
self.orderList.remove(trade.tradeID)
# 发出状态更新事件
# self.putEvent()
#----------------------------------------------------------------------
def on_stop_order(self, so):
"""停止单推送"""
print(u'StopOrder回报,stopOrderID:%s, status:%s' %
(so.stopOrderID, so.status))
if so.status == StopOrderStatus.CANCELLED or so.status == StopOrderStatus.TRIGGERED:
self.orderList.remove(so.stopOrderID)
pass
class Boll_kk_vix_simple_Strategy(CtaTemplate):
"""
本策略为反向策略，币本位 Reverse 反向
"""
author = "yunya"
open_window = 5
xminute_window = 15
com_length = 450
exit_dc_length = 10
fast_sma_length = 45
slow_sma_length = 110
cci_length = 30
cci_exit = 26
sl_multiplier = 8.0
fixed_size = 1
bollkk_ema = 0
bollkk_up = 0
bollkk_down = 0
bollkk_width = 0
cci_vlue = 0
long_stop = 0
short_stop = 0
exit_up = 0
exit_down = 0
atr_value = 0
long_entry = 0
short_entry = 0
ma_trend = 0
exit_dc_long = 0
exit_dc_short = 0
intra_trade_high = 0
intra_trade_low = 0
parameters = [
"open_window",
"xminute_window",
"com_length",
"fast_sma_length",
"slow_sma_length",
"cci_length",
"cci_exit",
"exit_dc_length",
"sl_multiplier",
"fixed_size",
]
variables = [
"bollkk_ema",
"bollkk_up",
"bollkk_down",
"bollkk_width",
"cci_vlue",
"long_stop",
"short_stop",
"exit_up",
"exit_down",
"atr_value",
"long_entry",
"short_entry",
"ma_trend",
]
def __init__(self, cta_engine, strategy_name, vt_symbol, setting):
""""""
super().__init__(cta_engine, strategy_name, vt_symbol, setting)
self.bg_xminute = BarGenerator(on_bar=self.on_bar,
window=self.xminute_window,
on_window_bar=self.on_xminute_bar,
interval=Interval.MINUTE)
self.am_xminute = ArrayManager(self.com_length + 10)
self.bg = BarGenerator(self.on_bar, self.open_window, self.on_open_bar)
self.am = ArrayManager()
def on_init(self):
"""
Callback when strategy is inited.
"""
self.write_log("策略初始化")
self.load_bar(10)
def on_start(self):
"""
Callback when strategy is started.
"""
self.write_log("策略启动")
def on_stop(self):
"""
Callback when strategy is stopped.
"""
self.write_log("策略停止")
def on_tick(self, tick: TickData):
"""
Callback of new tick data update.
"""
self.bg_xminute.update_tick(tick)
def on_bar(self, bar: BarData):
"""
Callback of new bar data update.
"""
self.bg.update_bar(bar)
self.bg_xminute.update_bar(bar)
def on_open_bar(self, bar: BarData):
"""
:param bar:
:return:
"""
# 先使用挂单全撤的粗化订单管理
self.cancel_all()
self.am.update_bar(bar)
if not self.am_xminute.inited or not self.am.inited:
return
if self.pos == 0:
# 根据布林带宽度动态调整仓位大小
# self.trading_size = max(int(self.risk_level / self.xminute_com_width), 1)
self.intra_trade_high = bar.high_price
self.intra_trade_low = bar.low_price
if self.cci_value > self.cci_exit and self.ma_trend > 0:
self.buy(self.bollkk_up, self.fixed_size, True)
elif self.cci_value < -self.cci_exit and self.ma_trend < 0:
self.short(self.bollkk_down, self.fixed_size, True)
elif self.pos > 0:
self.intra_trade_high = max(self.intra_trade_high, bar.high_price)
self.intra_trade_low = bar.low_price
exit_long_stop = self.intra_trade_high - self.bollkk_width * self.sl_multiplier
exit_long_dc = max(exit_long_stop, self.exit_dc_long)
self.exit_up = max(exit_long_dc, self.long_stop)
self.sell(self.exit_up, abs(self.pos), True)
elif self.pos < 0:
self.intra_trade_high = bar.high_price
self.intra_trade_low = min(self.intra_trade_low, bar.low_price)
exit_short_stop = self.intra_trade_low + self.bollkk_width * self.sl_multiplier
exit_shout_dc = min(exit_short_stop, self.exit_dc_short)
self.exit_down = min(exit_shout_dc, self.short_stop)
self.cover(self.exit_down, abs(self.pos), True)
self.put_event()
self.sync_data()
def on_xminute_bar(self, bar: BarData):
"""
:param bar:
:return:
"""
# x分钟 多策略合合成的通道线
self.am_xminute.update_bar(bar)
if not self.am_xminute.inited:
return
bollkk_ema_value, self.bollkk_up, self.bollkk_down, = self.boll_kk_combination(
high=self.am_xminute.high[:-1],
close=self.am_xminute.close[:-1],
low=self.am_xminute.low[:-1],
com_length=self.com_length)
# 计算开平信号
self.current_close = self.am_xminute.close[-1]
self.last_close = self.am_xminute.close[-2]
self.bollkk_ema = bollkk_ema_value[-1]
self.bollkk_width = abs(self.bollkk_up - self.bollkk_down)
self.cci_value = self.am_xminute.cci(self.cci_length)
self.fast_ma = self.am_xminute.sma(self.fast_sma_length)
self.slow_ma = self.am_xminute.sma(self.slow_sma_length)
if self.fast_ma > self.slow_ma:
self.ma_trend = 1
else:
self.ma_trend = -1
self.atr_value = self.am_xminute.atr(30)
self.exit_dc_short, self.exit_dc_long = self.am_xminute.donchian(
self.exit_dc_length)
self.sync_data()
self.put_event()
def on_order(self, order: OrderData):
"""
Callback of new order data update.
"""
pass
def on_trade(self, trade: TradeData):
"""
Callback of new trade data update.
"""
if trade.direction == Direction.LONG:
self.long_entry = trade.price # 成交最高价
self.long_stop = self.long_entry - 2 * self.atr_value
else:
self.short_entry = trade.price
self.short_stop = self.short_entry + 2 * self.atr_value
self.sync_data()
def on_stop_order(self, stop_order: StopOrder):
"""
Callback of stop order update.
"""
pass
def boll_kk_combination(self, high, close, low, com_length):
"""
通过计算收盘价与收盘价均线之间的倍数，来自动调整boll 、kk 的通过宽度
"""
# 计算组合均线
bollkk_ema = talib.EMA(close, com_length)
# 计算自适布林带
boll_std = talib.STDDEV(close, com_length)
boll_dev = abs(close - bollkk_ema) / boll_std
boll_up = bollkk_ema + boll_dev * boll_std
boll_down = bollkk_ema - boll_dev * boll_std
# 计算自适肯特通道
kk_atr = talib.ATR(high, low, close, com_length)
kk_dev = abs(close - bollkk_ema) / kk_atr
kk_up = bollkk_ema + kk_atr * kk_dev
kk_down = bollkk_ema - kk_atr * kk_dev
bollkk_up = max(boll_up[-1], kk_up[-1])
bollkk_down = min(boll_down[-1], kk_down[-1])
return bollkk_ema, bollkk_up, bollkk_down,
