各位前辈好,如果要实现程序在多个周期同时运行,不是老大课程上讲的先在15分钟判断方向,然后在5分钟上交易的那种,
是那种比如说在5分钟和30分钟各自独立的跑双均线策略,问题如下:
1:各个周期的订单会不会打架?我按照老大课程上的方法改了一个,但是单独跑5分钟回测和单独30分钟回测,两个分别的订单数量之和与以下程序实现的不相等
2:如果以下的程序用在实盘中,不考虑双均线是否盈利,只考虑程序照顾的全面程度还有什么需要改进和注意的地方?
以下是我修改的一个程序同时独立跑两个周期的代码,请各位指正,谢谢
from vnpy.app.cta_strategy import (
CtaTemplate,
StopOrder,
TickData,
BarData,
TradeData,
OrderData,
BarGenerator,
ArrayManager,
)
from vnpy.trader.constant import Interval
class 双周期(CtaTemplate):
""""""
# 策略作者
author = "Smart Trader"
# 定义参数
fast_window = 10
slow_window = 20
# 定义变量
fast_ma0 = 0.0
fast_ma1 = 0.0
slow_ma0 = 0.0
slow_ma1 = 0.0
# 添加参数和变量名到对应的列表
parameters = ["fast_window", "slow_window" ]
variables = ["fast_ma0", "fast_ma1", "slow_ma0", "slow_ma1"]
def __init__(self, cta_engine, strategy_name, vt_symbol, setting):
super().__init__(cta_engine, strategy_name, vt_symbol, setting)
self.bg5 = BarGenerator(
self.on_bar,
window=5,
on_window_bar=self.on_5min_bar,
interval=Interval.MINUTE
)
self.am5 = ArrayManager()
self.bg30 = BarGenerator(
self.on_bar,
window=30,
on_window_bar=self.on_30min_bar,
interval=Interval.MINUTE
)
self.am30 = 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)
self.bg30.update_tick(tick)
def on_bar(self, bar: BarData):
"""
Callback of new bar data update.
"""
self.bg5.update_bar(bar)
self.bg30.update_bar(bar)
def on_5min_bar(self,bar:BarData):
am5 = self.am5
# 更新K线到时间序列容器中
am5.update_bar(bar)
# 若缓存的K线数量尚不够计算技术指标,则直接返回
if not am5.inited:
return
# 计算快速均线
fast_ma = am5.sma(self.fast_window, array=True)
self.fast_ma0 = fast_ma[-1] # T时刻数值
self.fast_ma1 = fast_ma[-2] # T-1时刻数值
# 计算慢速均线
slow_ma = am5.sma(self.slow_window, array=True)
self.slow_ma0 = slow_ma[-1]
self.slow_ma1 = slow_ma[-2]
# 判断是否金叉
cross_over = (self.fast_ma0 > self.slow_ma0 and
self.fast_ma1 < self.slow_ma1)
# 判断是否死叉
cross_below = (self.fast_ma0 < self.slow_ma0 and
self.fast_ma1 > self.slow_ma1)
# 如果发生了金叉
if cross_over:
# 为了保证成交,在K线收盘价上加5发出限价单
price = bar.close_price + 5
# 当前无仓位,则直接开多
if self.pos == 0:
self.buy(price, 1)
# 当前持有空头仓位,则先平空,再开多
elif self.pos < 0:
self.cover(price, 1)
self.buy(price, 1)
# 如果发生了死叉
elif cross_below:
price = bar.close_price - 5
# 当前无仓位,则直接开空
if self.pos == 0:
self.short(price, 1)
# 当前持有空头仓位,则先平多,再开空
elif self.pos > 0:
self.sell(price, 1)
self.short(price, 1)
self.put_event()
def on_30min_bar(self,bar:BarData):
am30 = self.am30
# 更新K线到时间序列容器中
am30.update_bar(bar)
# 若缓存的K线数量尚不够计算技术指标,则直接返回
if not am30.inited:
return
# 计算快速均线
fast_ma = am30.sma(self.fast_window, array=True)
self.fast_ma0 = fast_ma[-1] # T时刻数值
self.fast_ma1 = fast_ma[-2] # T-1时刻数值
# 计算慢速均线
slow_ma = am30.sma(self.slow_window, array=True)
self.slow_ma0 = slow_ma[-1]
self.slow_ma1 = slow_ma[-2]
# 判断是否金叉
cross_over = (self.fast_ma0 > self.slow_ma0 and
self.fast_ma1 < self.slow_ma1)
# 判断是否死叉
cross_below = (self.fast_ma0 < self.slow_ma0 and
self.fast_ma1 > self.slow_ma1)
# 如果发生了金叉
if cross_over:
# 为了保证成交,在K线收盘价上加5发出限价单
price = bar.close_price + 5
# 当前无仓位,则直接开多
if self.pos == 0:
self.buy(price, 1)
# 当前持有空头仓位,则先平空,再开多
elif self.pos < 0:
self.cover(price, 1)
self.buy(price, 1)
# 如果发生了死叉
elif cross_below:
price = bar.close_price - 5
# 当前无仓位,则直接开空
if self.pos == 0:
self.short(price, 1)
# 当前持有空头仓位,则先平多,再开空
elif self.pos > 0:
self.sell(price, 1)
self.short(price, 1)
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