def calculate_adaptive_channel(am: ArrayManager, n: int, dev: float):
""""""
ma = am.sma(n)
std = am.std(n)
boll_up = ma + std * dev
boll_down = ma - std * dev
kk_up = ma + atr * dev
kk_down = ma - atr * dev
donchian_up = am.high[-n:].max()
donchian_down = am.low[-n:].min()
channel_up = max(boll_up, kk_up, donchian_up)
channel_down = min(boll_down, kk_down, donchian_down)
return channel_up, channel_down
class MaSignal(CtaSignal):
""""""
def __init__(self, fast_window: int, slow_window: int):
""""""
super(MaSignal, self).__init__()
self.fast_window = fast_window
self.slow_window = slow_window
self.bg = BarGenerator(self.on_bar, 5, self.on_5min_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.bg.update_bar(bar)
def on_5min_bar(self, bar: BarData):
""""""
self.am.update_bar(bar)
if not self.am.inited:
self.set_signal_pos(0)
fast_ma = self.am.sma("c", self.fast_window)
slow_ma = self.am.sma("c", self.slow_window)
if fast_ma > slow_ma:
self.set_signal_pos(1)
elif fast_ma < slow_ma:
self.set_signal_pos(-1)
else:
self.set_signal_pos(0)
class StatisticalArbitrageStrategy(SpreadStrategyTemplate):
""""""
author = "用Python的交易员"
boll_window = 20
boll_dev = 2
max_pos = 10
payup = 10
interval = 5
spread_pos = 0.0
boll_up = 0.0
boll_down = 0.0
boll_mid = 0.0
parameters = ["boll_window", "boll_dev", "max_pos", "payup", "interval"]
variables = ["spread_pos", "boll_up", "boll_down", "boll_mid"]
def __init__(self, strategy_engine, strategy_name: str, spread: SpreadData,
setting: dict):
""""""
super().__init__(strategy_engine, strategy_name, spread, setting)
self.bg = BarGenerator(self.on_spread_bar)
self.am = ArrayManager()
def on_init(self):
"""
Callback when strategy is inited.
"""
self.write_log("策略初始化")
self.load_bar(1)
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")
self.put_event()
def on_spread_data(self):
"""
Callback when spread price is updated.
"""
tick = self.get_spread_tick()
self.on_spread_tick(tick)
def on_spread_tick(self, tick: TickData):
"""
Callback when new spread tick data is generated.
"""
self.bg.update_tick(tick)
def on_spread_bar(self, bar: BarData):
"""
Callback when spread bar data is generated.
"""
self.stop_all_algos()
self.am.update_bar(bar)
if not self.am.inited:
return
self.boll_mid = self.am.sma(self.boll_window)
self.boll_up, self.boll_down = self.am.boll(self.boll_window,
self.boll_dev)
if not self.spread_pos:
if bar.close_price >= self.boll_up:
self.start_short_algo(bar.close_price - 10,
self.max_pos,
payup=self.payup,
interval=self.interval)
elif bar.close_price <= self.boll_down:
self.start_long_algo(bar.close_price + 10,
self.max_pos,
payup=self.payup,
interval=self.interval)
elif self.spread_pos < 0:
if bar.close_price <= self.boll_mid:
self.start_long_algo(bar.close_price + 10,
abs(self.spread_pos),
payup=self.payup,
interval=self.interval)
else:
if bar.close_price >= self.boll_mid:
self.start_short_algo(bar.close_price - 10,
abs(self.spread_pos),
payup=self.payup,
interval=self.interval)
self.put_event()
def on_spread_pos(self):
"""
Callback when spread position is updated.
"""
self.spread_pos = self.get_spread_pos()
self.put_event()
def on_spread_algo(self, algo: SpreadAlgoTemplate):
"""
Callback when algo status is updated.
"""
pass
def on_order(self, order: OrderData):
"""
Callback when order status is updated.
"""
pass
def on_trade(self, trade: TradeData):
"""
Callback when new trade data is received.
"""
pass
def stop_open_algos(self):
""""""
if self.buy_algoid:
self.stop_algo(self.buy_algoid)
if self.short_algoid:
self.stop_algo(self.short_algoid)
def stop_close_algos(self):
""""""
if self.sell_algoid:
self.stop_algo(self.sell_algoid)
if self.cover_algoid:
self.stop_algo(self.cover_algoid)
class StatisticalArbitrageGridStrategy(SpreadStrategyTemplate):
"""
算法逻辑是在统计算法基础上增加加仓位逻辑
"""
author = "yunya"
boll_window = 60
boll_dev = 4.0
fixed_pos = 10
max_pos = 4
price_proportion = 2.0
pay_up = 5
increase_price = 0.0 # 超价
interval = 5
spread_pos = 0
boll_up = 0
boll_down = 0
boll_mid = 0
grid_count = 0
buy_grid_count = 0
short_grid_count = 0
long_price = 0
short_price = 0
parameters = [
"boll_window", "boll_dev", "fixed_pos", "max_pos", "price_proportion",
"pay_up", "interval", "increase_price"
]
variables = [
"spread_pos",
"boll_up",
"boll_down",
"boll_mid",
"grid_count",
"buy_grid_count",
"short_grid_count",
"long_price",
"short_price",
]
def __init__(self, strategy_engine, strategy_name: str, spread: SpreadData,
setting: dict):
""""""
super().__init__(strategy_engine, strategy_name, spread, setting)
self.bg = BarGenerator(self.on_spread_bar)
self.am = ArrayManager()
def on_init(self):
"""
Callback when strategy is inited.
"""
self.write_log("策略初始化")
self.load_bar(5)
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")
self.put_event()
def on_spread_data(self):
"""
Callback when spread price is updated.
收到差价推送后，合成价差TICK数据
"""
#这里的价差tick
tick = self.get_spread_tick()
self.on_spread_tick(tick)
def on_spread_tick(self, tick: TickData):
"""
Callback when new spread tick data is generated.
"""
self.bg.update_tick(tick)
def on_spread_bar(self, bar: BarData):
"""
Callback when spread bar data is generated.
"""
# 把老算法先停止，
self.stop_all_algos()
self.am.update_bar(bar)
if not self.am.inited:
return
self.boll_mid = self.am.sma(self.boll_window)
self.boll_up, self.boll_down = self.am.boll(self.boll_window,
self.boll_dev)
if not self.spread_pos:
if bar.close_price >= self.boll_up:
self.start_short_algo(bar.close_price - self.increase_price,
self.fixed_pos,
payup=self.pay_up,
interval=self.interval)
elif bar.close_price <= self.boll_down:
self.start_long_algo(bar.close_price + self.increase_price,
self.fixed_pos,
payup=self.pay_up,
interval=self.interval)
elif self.spread_pos < 0:
if bar.close_price <= self.boll_mid:
self.start_long_algo(bar.close_price + self.increase_price,
abs(self.spread_pos),
payup=self.pay_up,
interval=self.interval)
self.buy_grid_count = 0
else:
# 加仓
grid_count = self.buy_grid_count < self.max_pos
bar_change = bar.close_price > self.long_price * (
1 + self.price_proportion / 1000)
if grid_count and bar_change:
if bar.close_price >= self.boll_up:
self.start_short_algo(bar.close_price -
self.increase_price,
self.fixed_pos,
payup=self.pay_up,
interval=self.interval)
else:
if bar.close_price >= self.boll_mid:
self.start_short_algo(bar.close_price - self.increase_price,
abs(self.spread_pos),
payup=self.pay_up,
interval=self.interval)
self.short_grid_count = 0
else:
# 加仓
grid_count = self.short_grid_count < self.max_pos
bar_change = bar.close_price < self.short_price * (
1 - self.price_proportion / 1000)
if grid_count and bar_change:
if bar.close_price <= self.boll_down:
self.start_long_algo(bar.close_price +
self.increase_price,
self.fixed_pos,
payup=self.pay_up,
interval=self.interval)
def on_spread_pos(self):
"""
Callback when spread position is updated.
"""
self.spread_pos = self.get_spread_pos()
self.put_event()
def on_spread_algo(self, algo: SpreadAlgoTemplate):
"""
Callback when algo status is updated.
"""
pass
def on_order(self, order: OrderData):
"""
Callback when order status is updated.
"""
if order.status == Status.ALLTRADED:
if order.direction == Direction.LONG:
self.buy_grid_count += 1
else:
self.short_grid_count += 1
def on_trade(self, trade: TradeData):
"""
Callback when new trade data is received.
"""
if trade.direction == Direction.LONG:
self.long_price = trade.price
else:
self.short_price = trade.price
class StatisticalArbitrageStrategy(SpreadStrategyTemplate):
""""""
author = "用Python的交易员"
open_window = 1
boll_window = 40
boll_dev = 4.9
fixed_pos = 10
payup = 10.0
increase_price = 0.0 # 超价
interval = 5
spread_pos = 0.0
boll_up = 0.0
boll_down = 0.0
boll_mid = 0.0
parameters = [
"boll_window", "boll_dev", "fixed_pos", "payup", "interval",
"increase_price"
]
variables = ["spread_pos", "boll_up", "boll_down", "boll_mid"]
def __init__(self, strategy_engine, strategy_name: str, spread: SpreadData,
setting: dict):
""""""
super().__init__(strategy_engine, strategy_name, spread, setting)
self.bg = BarGenerator(self.on_open_spread_bar, self.open_window,
self.on_open_spread_bar)
self.am = ArrayManager()
self.spread_pos = 0.0
self.boll_up = 0.0
self.boll_down = 0.0
self.boll_mid = 0.0
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")
self.put_event()
def on_spread_data(self):
"""
Callback when spread price is updated.
收到差价推送后，合成价差TICK数据
"""
#这里的价差tick
tick = self.get_spread_tick()
self.on_spread_tick(tick)
def on_spread_tick(self, tick: TickData):
"""
Callback when new spread tick data is generated.
"""
self.bg.update_tick(tick)
def on_spread_bar(self, bar: BarData):
"""
Callback when new spread bar data is generated.
"""
self.bg.update_bar(bar)
def on_open_spread_bar(self, bar: BarData):
"""
Callback when spread bar data is generated.
目前的策略逻辑：
1、当价差价格大于布林上轨，以当前收盘加低10的价格下单（以市价下单保证成交），当价格跌破中轨时平仓 （做空）
2、当价差价格小于布林下轨，以当前收盘价加10的价格下单，当价格高于中轨时平仓 （做多）
策略优化方向：
1、把目前在分钟价差K线逻辑移到 tick逻辑中实盘，增加细腻度
2、仓位分为四次加减仓，第一次上穿时，开一份，第二次上穿的价格要高于第一次一定比较时，开第二份，一直到满四份。
（这两个参数，一个是份数，一个是跨度（格距）），目的解决如果出现单边短时趋势抗单时爆仓（最后都会回归中轨）
3、回到中轨全部平仓位
"""
# 把老算法先停止，
self.stop_all_algos()
self.am.update_bar(bar)
if not self.am.inited:
return
self.boll_mid = self.am.sma(self.boll_window)
self.boll_up, self.boll_down = self.am.boll(self.boll_window,
self.boll_dev)
if not self.spread_pos:
if bar.close_price >= self.boll_up:
self.start_short_algo(bar.close_price - self.increase_price,
self.fixed_pos,
payup=self.payup,
interval=self.interval)
elif bar.close_price <= self.boll_down:
self.start_long_algo(bar.close_price + self.increase_price,
self.fixed_pos,
payup=self.payup,
interval=self.interval)
elif self.spread_pos < 0:
if bar.close_price <= self.boll_mid:
self.start_long_algo(bar.close_price + self.increase_price,
abs(self.spread_pos),
payup=self.payup,
interval=self.interval)
else:
if bar.close_price >= self.boll_mid:
self.start_short_algo(bar.close_price - self.increase_price,
abs(self.spread_pos),
payup=self.payup,
interval=self.interval)
self.put_event()
def on_spread_pos(self):
"""
Callback when spread position is updated.
"""
self.spread_pos = self.get_spread_pos()
self.put_event()
def on_spread_algo(self, algo: SpreadAlgoTemplate):
"""
Callback when algo status is updated.
"""
pass
def on_order(self, order: OrderData):
"""
Callback when order status is updated.
"""
pass
def on_trade(self, trade: TradeData):
"""
Callback when new trade data is received.
"""
pass
class MultiTimeframeStrategy(CtaTemplate):
""""""
author = "中科云集"
rsi_signal = 20
rsi_window = 14
fast_window = 5
slow_window = 20
fixed_size = 1
rsi_value = 0
rsi_long = 0
rsi_short = 0
fast_ma = 0
slow_ma = 0
ma_trend = 0
parameters = [
"rsi_signal", "rsi_window", "fast_window", "slow_window", "fixed_size"
]
variables = [
"rsi_value", "rsi_long", "rsi_short", "fast_ma", "slow_ma", "ma_trend"
]
def __init__(self, cta_engine, strategy_name, vt_symbol, setting):
""""""
super(MultiTimeframeStrategy, self).__init__(cta_engine, strategy_name,
vt_symbol, setting)
self.rsi_long = 50 + self.rsi_signal
self.rsi_short = 50 - self.rsi_signal
self.bg5 = BarGenerator(self.on_bar, 5, self.on_5min_bar)
self.am5 = ArrayManager()
self.bg15 = BarGenerator(self.on_bar, 15, self.on_15min_bar)
self.am15 = 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.bg5.update_tick(tick)
def on_bar(self, bar: BarData):
"""
Callback of new bar data update.
"""
self.bg5.update_bar(bar)
self.bg15.update_bar(bar)
def on_5min_bar(self, bar: BarData):
""""""
self.cancel_all()
self.am5.update_bar(bar)
if not self.am5.inited:
return
if not self.ma_trend:
return
self.rsi_value = self.am5.rsi(self.rsi_window)
if self.pos == 0:
if self.ma_trend > 0 and self.rsi_value >= self.rsi_long:
self.buy(bar.close_price + 5, self.fixed_size)
elif self.ma_trend < 0 and self.rsi_value <= self.rsi_short:
self.short(bar.close_price - 5, self.fixed_size)
elif self.pos > 0:
if self.ma_trend < 0 or self.rsi_value < 50:
self.sell(bar.close_price - 5, abs(self.pos))
elif self.pos < 0:
if self.ma_trend > 0 or self.rsi_value > 50:
self.cover(bar.close_price + 5, abs(self.pos))
self.put_event()
def on_15min_bar(self, bar: BarData):
""""""
self.am15.update_bar(bar)
if not self.am15.inited:
return
self.fast_ma = self.am15.sma("c", self.fast_window)
self.slow_ma = self.am15.sma("c", self.slow_window)
if self.fast_ma > self.slow_ma:
self.ma_trend = 1
else:
self.ma_trend = -1
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