156 lines
5.9 KiB
Python
156 lines
5.9 KiB
Python
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# encoding: UTF-8
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"""
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这里的Demo是一个最简单的双均线策略实现，并未考虑太多实盘中的交易细节，如：
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1. 委托价格超出涨跌停价导致的委托失败
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2. 委托未成交，需要撤单后重新委托
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3. 断网后恢复交易状态
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4. 等等
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这些点是作者选择特意忽略不去实现，因此想实盘的朋友请自己多多研究CTA交易的一些细节，
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做到了然于胸后再去交易，对自己的money和时间负责。
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也希望社区能做出一个解决了以上潜在风险的Demo出来。
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"""
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from __future__ import division
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from vnpy.trader.vtConstant import EMPTY_STRING, EMPTY_FLOAT
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from vnpy.trader.app.ctaStrategy.ctaTemplate import (CtaTemplate,
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BarManager,
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ArrayManager)
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########################################################################
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class DoubleMaStrategy(CtaTemplate):
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"""双指数均线策略Demo"""
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className = 'DoubleMaStrategy'
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author = u'用Python的交易员'
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# 策略参数
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fastWindow = 10 # 快速均线参数
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slowWindow = 60 # 慢速均线参数
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initDays = 10 # 初始化数据所用的天数
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# 策略变量
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fastMa0 = EMPTY_FLOAT # 当前最新的快速EMA
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fastMa1 = EMPTY_FLOAT # 上一根的快速EMA
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slowMa0 = EMPTY_FLOAT
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slowMa1 = EMPTY_FLOAT
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# 参数列表，保存了参数的名称
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paramList = ['name',
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'className',
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'author',
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'vtSymbol',
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'fastWindow',
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'slowWindow']
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# 变量列表，保存了变量的名称
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varList = ['inited',
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'trading',
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'pos',
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'fastMa0',
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'fastMa1',
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'slowMa0',
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'slowMa1']
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#----------------------------------------------------------------------
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def __init__(self, ctaEngine, setting):
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"""Constructor"""
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super(DoubleMaStrategy, self).__init__(ctaEngine, setting)
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self.bm = BarManager(self.onBar)
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self.am = ArrayManager()
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# 注意策略类中的可变对象属性（通常是list和dict等），在策略初始化时需要重新创建，
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# 否则会出现多个策略实例之间数据共享的情况，有可能导致潜在的策略逻辑错误风险，
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# 策略类中的这些可变对象属性可以选择不写，全都放在__init__下面，写主要是为了阅读
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# 策略时方便（更多是个编程习惯的选择）
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#----------------------------------------------------------------------
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def onInit(self):
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"""初始化策略（必须由用户继承实现）"""
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self.writeCtaLog(u'双EMA演示策略初始化')
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initData = self.loadBar(self.initDays)
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for bar in initData:
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self.onBar(bar)
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self.putEvent()
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#----------------------------------------------------------------------
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def onStart(self):
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"""启动策略（必须由用户继承实现）"""
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self.writeCtaLog(u'双EMA演示策略启动')
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self.putEvent()
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#----------------------------------------------------------------------
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def onStop(self):
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"""停止策略（必须由用户继承实现）"""
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self.writeCtaLog(u'双EMA演示策略停止')
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self.putEvent()
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#----------------------------------------------------------------------
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def onTick(self, tick):
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"""收到行情TICK推送（必须由用户继承实现）"""
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self.bm.updateTick(tick)
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#----------------------------------------------------------------------
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def onBar(self, bar):
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"""收到Bar推送（必须由用户继承实现）"""
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am = self.am
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am.updateBar(bar)
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if not am.inited:
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return
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# 计算快慢均线
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fastMa = am.sma(self.fastWindow, array=True)
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self.fastMa0 = fastMa[-1]
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self.fastMa1 = fastMa[-2]
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slowMa = am.sma(self.slowWindow, array=True)
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self.slowMa0 = slowMa[-1]
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self.slowMa1 = slowMa[-2]
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# 判断买卖
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crossOver = self.fastMa0>self.slowMa0 and self.fastMa1<self.slowMa1 # 金叉上穿
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crossBelow = self.fastMa0<self.slowMa0 and self.fastMa1>self.slowMa1 # 死叉下穿
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# 金叉和死叉的条件是互斥
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# 所有的委托均以K线收盘价委托（这里有一个实盘中无法成交的风险，考虑添加对模拟市价单类型的支持）
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if crossOver:
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# 如果金叉时手头没有持仓，则直接做多
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if self.pos == 0:
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self.buy(bar.close, 1)
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# 如果有空头持仓，则先平空，再做多
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elif self.pos < 0:
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self.cover(bar.close, 1)
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self.buy(bar.close, 1)
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# 死叉和金叉相反
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elif crossBelow:
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if self.pos == 0:
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self.short(bar.close, 1)
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elif self.pos > 0:
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self.sell(bar.close, 1)
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self.short(bar.close, 1)
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# 发出状态更新事件
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self.putEvent()
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#----------------------------------------------------------------------
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def onOrder(self, order):
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"""收到委托变化推送（必须由用户继承实现）"""
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# 对于无需做细粒度委托控制的策略，可以忽略onOrder
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pass
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#----------------------------------------------------------------------
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def onTrade(self, trade):
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"""收到成交推送（必须由用户继承实现）"""
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# 对于无需做细粒度委托控制的策略，可以忽略onOrder
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pass
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#----------------------------------------------------------------------
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def onStopOrder(self, so):
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"""停止单推送"""
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pass
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