184 lines
6.7 KiB
Python
184 lines
6.7 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 ctaBase import *
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from ctaTemplate import CtaTemplate
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########################################################################
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class DoubleEmaDemo(CtaTemplate):
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"""双指数均线策略Demo"""
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className = 'DoubleEmaDemo'
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author = u'用Python的交易员'
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# 策略参数
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fastK = 0.9 # 快速EMA参数
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slowK = 0.1 # 慢速EMA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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bar = None
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barMinute = EMPTY_STRING
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fastMa = [] # 快速EMA均线数组
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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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slowMa = [] # 与上面相同
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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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'fastK',
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'slowK']
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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(DoubleEmaDemo, self).__init__(ctaEngine, setting)
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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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# 计算K线
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tickMinute = tick.datetime.minute
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if tickMinute != self.barMinute:
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if self.bar:
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self.onBar(self.bar)
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bar = CtaBarData()
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bar.vtSymbol = tick.vtSymbol
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bar.symbol = tick.symbol
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bar.exchange = tick.exchange
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bar.open = tick.lastPrice
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bar.high = tick.lastPrice
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bar.low = tick.lastPrice
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bar.close = tick.lastPrice
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bar.date = tick.date
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bar.time = tick.time
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bar.datetime = tick.datetime # K线的时间设为第一个Tick的时间
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# 实盘中用不到的数据可以选择不算,从而加快速度
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#bar.volume = tick.volume
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#bar.openInterest = tick.openInterest
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self.bar = bar # 这种写法为了减少一层访问,加快速度
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self.barMinute = tickMinute # 更新当前的分钟
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else: # 否则继续累加新的K线
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bar = self.bar # 写法同样为了加快速度
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bar.high = max(bar.high, tick.lastPrice)
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bar.low = min(bar.low, tick.lastPrice)
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bar.close = tick.lastPrice
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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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# 计算快慢均线
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if not self.fastMa0:
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self.fastMa0 = bar.close
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self.fastMa.append(self.fastMa0)
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else:
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self.fastMa1 = self.fastMa0
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self.fastMa0 = bar.close * self.fastK + self.fastMa0 * (1 - self.fastK)
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self.fastMa.append(self.fastMa0)
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if not self.slowMa0:
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self.slowMa0 = bar.close
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self.slowMa.append(self.slowMa0)
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else:
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self.slowMa1 = self.slowMa0
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self.slowMa0 = bar.close * self.slowK + self.slowMa0 * (1 - self.slowK)
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self.slowMa.append(self.slowMa0)
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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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