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[Mod]修改CTA自带策略使用ArrayManager，技术指标函数支持返回数组

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This commit is contained in:
vn.py 2017-10-07 22:36:23 +08:00
parent b901e579ae
commit ce65a32159
9 changed files with 178 additions and 471 deletions
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124
examples/CtaBacktesting/.ipynb_checkpoints/backtesting_IF-checkpoint.ipynb
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108
examples/CtaBacktesting/.ipynb_checkpoints/backtesting_rb-checkpoint.ipynb
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160
examples/CtaBacktesting/backtesting_IF.ipynb
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28
examples/CtaBacktesting/backtesting_rb.ipynb
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@ -2,7 +2,7 @@
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"execution_count": null,
"metadata": {
"collapsed": false
},
@ -16,7 +16,7 @@
},
{
"cell_type": "code",
"execution_count": 2,
"execution_count": null,
"metadata": {
"collapsed": false
},
@ -28,7 +28,7 @@
},
{
"cell_type": "code",
"execution_count": 3,
"execution_count": null,
"metadata": {
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},
@ -42,7 +42,7 @@
},
{
"cell_type": "code",
"execution_count": 4,
"execution_count": null,
"metadata": {
"collapsed": true
},
@ -58,7 +58,7 @@
},
{
"cell_type": "code",
"execution_count": 5,
"execution_count": null,
"metadata": {
"collapsed": true
},
@ -71,25 +71,11 @@
},
{
"cell_type": "code",
"execution_count": 6,
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"2017-10-07 18:16:51.192000\t开始载入数据\n",
"2017-10-07 18:16:51.306000\t载入完成，数据量：332899\n",
"2017-10-07 18:16:51.306000\t开始回测\n",
"2017-10-07 18:16:51.306000\t策略初始化完成\n",
"2017-10-07 18:16:51.306000\t策略启动完成\n",
"2017-10-07 18:16:51.306000\t开始回放数据\n",
"2017-10-07 18:17:04.696000\t数据回放结束\n"
]
}
],
"outputs": [],
"source": [
"# 运行回测\n",
"engine.runBacktesting()"

69
vnpy/trader/app/ctaStrategy/ctaTemplate.py
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@ -486,20 +486,50 @@ class ArrayManager(object):
return self.volumeArray
#----------------------------------------------------------------------
def sma(self, n, shift=0):
"""均线"""
return talib.SMA(self.close, n)[-1-shift]
def sma(self, n, array=False):
"""简单均线"""
result = talib.SMA(self.close, n)
if array:
return result
return result[-1]
#----------------------------------------------------------------------
def std(self, n, shift=0):
def std(self, n, array=False):
"""标准差"""
return talib.STDDEV(self.close, n)[-1-shift]
result = talib.STDDEV(self.close, n)
if array:
return result
return result[-1]
#----------------------------------------------------------------------
def boll(self, n, dev, shift=0):
def cci(self, n, array=False):
"""CCI指标"""
result = talib.CCI(self.high, self.low, self.close, n)
if array:
return result
return result[-1]
#----------------------------------------------------------------------
def atr(self, n, array=False):
"""ATR指标"""
result = talib.ATR(self.high, self.low, self.close, n)
if array:
return result
return result[-1]
#----------------------------------------------------------------------
def rsi(self, n, array=False):
"""RSI指标"""
result = talib.RSI(self.close, n)
if array:
return result
return result[-1]
#----------------------------------------------------------------------
def boll(self, n, dev, array=False):
"""布林通道"""
mid = self.sma(n, shift)
std = self.std(n, shift)
mid = self.sma(n, array)
std = self.std(n, array)
up = mid + std * dev
down = mid - std * dev
@ -507,13 +537,22 @@ class ArrayManager(object):
return up, down
#----------------------------------------------------------------------
def cci(self, n, shift=0):
"""CCI指标"""
return talib.CCI(self.high, self.low, self.close, n)[-1-shift]
def keltner(self, n, dev, array=False):
"""肯特纳通道"""
mid = self.sma(n, array)
atr = self.atr(n, array)
up = mid + atr * dev
down = mid - atr * dev
return up, down
#----------------------------------------------------------------------
def atr(self, n, shift=0):
"""ATR指标"""
return talib.ATR(self.high, self.low, self.close, n)[-1-shift]
def donchian(self, n, array=False):
"""唐奇安通道"""
up = talib.MAX(self.high, n)
down = talib.MIN(self.low, n)
if array:
return up, down
return up[-1], down[-1]

48
vnpy/trader/app/ctaStrategy/strategy/strategyAtrRsi.py
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@ -10,12 +10,11 @@
"""
import talib
import numpy as np
from vnpy.trader.vtObject import VtBarData
from vnpy.trader.vtConstant import EMPTY_STRING
from vnpy.trader.app.ctaStrategy.ctaTemplate import CtaTemplate, BarManager
from vnpy.trader.app.ctaStrategy.ctaTemplate import (CtaTemplate,
BarManager,
ArrayManager)
########################################################################
@ -34,17 +33,8 @@ class AtrRsiStrategy(CtaTemplate):
fixedSize = 1 # 每次交易的数量
# 策略变量
bufferSize = 100 # 需要缓存的数据的大小
bufferCount = 0 # 目前已经缓存了的数据的计数
highArray = np.zeros(bufferSize) # K线最高价的数组
lowArray = np.zeros(bufferSize) # K线最低价的数组
closeArray = np.zeros(bufferSize) # K线收盘价的数组
atrCount = 0 # 目前已经缓存了的ATR的计数
atrArray = np.zeros(bufferSize) # ATR指标的数组
atrValue = 0 # 最新的ATR指标数值
atrMa = 0 # ATR移动平均的数值
rsiValue = 0 # RSI指标的数值
rsiBuy = 0 # RSI买开阈值
rsiSell = 0 # RSI卖开阈值
@ -81,6 +71,7 @@ class AtrRsiStrategy(CtaTemplate):
# 创建K线合成器对象
self.bm = BarManager(self.onBar)
self.am = ArrayManager()
# 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，
# 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，
@ -129,34 +120,17 @@ class AtrRsiStrategy(CtaTemplate):
self.orderList = []
# 保存K线数据
self.closeArray[0:self.bufferSize-1] = self.closeArray[1:self.bufferSize]
self.highArray[0:self.bufferSize-1] = self.highArray[1:self.bufferSize]
self.lowArray[0:self.bufferSize-1] = self.lowArray[1:self.bufferSize]
self.closeArray[-1] = bar.close
self.highArray[-1] = bar.high
self.lowArray[-1] = bar.low
self.bufferCount += 1
if self.bufferCount < self.bufferSize:
am = self.am
am.updateBar(bar)
if not am.inited:
return
# 计算指标数值
self.atrValue = talib.ATR(self.highArray,
self.lowArray,
self.closeArray,
self.atrLength)[-1]
self.atrArray[0:self.bufferSize-1] = self.atrArray[1:self.bufferSize]
self.atrArray[-1] = self.atrValue
atrArray = am.atr(self.atrLength, array=True)
self.atrValue = atrArray[-1]
self.atrMa = atrArray[-self.atrMaLength:].mean()
self.atrCount += 1
if self.atrCount < self.bufferSize:
return
self.atrMa = talib.MA(self.atrArray,
self.atrMaLength)[-1]
self.rsiValue = talib.RSI(self.closeArray,
self.rsiLength)[-1]
self.rsiValue = am.rsi(self.rsiLength)
# 判断是否要进行交易

3
vnpy/trader/app/ctaStrategy/strategy/strategyBollChannel.py
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@ -18,9 +18,6 @@
from __future__ import division
import talib
import numpy as np
from vnpy.trader.vtObject import VtBarData
from vnpy.trader.vtConstant import EMPTY_STRING
from vnpy.trader.app.ctaStrategy.ctaTemplate import (CtaTemplate,

54
vnpy/trader/app/ctaStrategy/strategy/strategyEmaDemo.py → vnpy/trader/app/ctaStrategy/strategy/strategyDoubleMa.py
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@ -1,7 +1,7 @@
# encoding: UTF-8
"""
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：
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：
1. 委托价格超出涨跌停价导致的委托失败
2. 委托未成交，需要撤单后重新委托
3. 断网后恢复交易状态
@ -13,28 +13,28 @@
from __future__ import division
from vnpy.trader.vtObject import VtBarData
#from vnpy.trader.vtObject import VtBarData
from vnpy.trader.vtConstant import EMPTY_STRING, EMPTY_FLOAT
from vnpy.trader.app.ctaStrategy.ctaTemplate import CtaTemplate, BarManager
from vnpy.trader.app.ctaStrategy.ctaTemplate import (CtaTemplate,
BarManager,
ArrayManager)
########################################################################
class EmaDemoStrategy(CtaTemplate):
class DoubleMaStrategy(CtaTemplate):
"""双指数均线策略Demo"""
className = 'EmaDemoStrategy'
className = 'DoubleMaStrategy'
author = u'用Python的交易员'
# 策略参数
fastK = 0.9 # 快速EMA参数
slowK = 0.1 # 慢速EMA参数
fastWindow = 10 # 快速均线参数
slowWindow = 60 # 慢速均线参数
initDays = 10 # 初始化数据所用的天数
# 策略变量
fastMa = [] # 快速EMA均线数组
fastMa0 = EMPTY_FLOAT # 当前最新的快速EMA
fastMa1 = EMPTY_FLOAT # 上一根的快速EMA
slowMa = [] # 与上面相同
slowMa0 = EMPTY_FLOAT
slowMa1 = EMPTY_FLOAT
@ -43,8 +43,8 @@ class EmaDemoStrategy(CtaTemplate):
'className',
'author',
'vtSymbol',
'fastK',
'slowK']
'fastWindow',
'slowWindow']
# 变量列表，保存了变量的名称
varList = ['inited',
@ -58,16 +58,15 @@ class EmaDemoStrategy(CtaTemplate):
#----------------------------------------------------------------------
def __init__(self, ctaEngine, setting):
"""Constructor"""
super(EmaDemoStrategy, self).__init__(ctaEngine, setting)
super(DoubleMaStrategy, self).__init__(ctaEngine, setting)
self.bm = BarManager(self.onBar)
self.am = ArrayManager()
# 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，
# 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，
# 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
# 策略时方便（更多是个编程习惯的选择）
self.fastMa = []
self.slowMa = []
#----------------------------------------------------------------------
def onInit(self):
@ -100,22 +99,19 @@ class EmaDemoStrategy(CtaTemplate):
#----------------------------------------------------------------------
def onBar(self, bar):
"""收到Bar推送（必须由用户继承实现）"""
# 计算快慢均线
if not self.fastMa0:
self.fastMa0 = bar.close
self.fastMa.append(self.fastMa0)
else:
self.fastMa1 = self.fastMa0
self.fastMa0 = bar.close * self.fastK + self.fastMa0 * (1 - self.fastK)
self.fastMa.append(self.fastMa0)
am = self.am
am.updateBar(bar)
if not am.inited:
return
if not self.slowMa0:
self.slowMa0 = bar.close
self.slowMa.append(self.slowMa0)
else:
self.slowMa1 = self.slowMa0
self.slowMa0 = bar.close * self.slowK + self.slowMa0 * (1 - self.slowK)
self.slowMa.append(self.slowMa0)
# 计算快慢均线
fastMa = am.sma(self.fastWindow, array=True)
self.fastMa0 = fastMa[-1]
self.fastMa1 = fastMa[-2]
slowMa = am.sma(self.slowWindow, array=True)
self.slowMa0 = slowMa[-1]
self.slowMa1 = slowMa[-2]
# 判断买卖
crossOver = self.fastMa0>self.slowMa0 and self.fastMa1<self.slowMa1 # 金叉上穿

39
vnpy/trader/app/ctaStrategy/strategy/strategyKingKeltner.py
View File

@ -12,12 +12,11 @@
from __future__ import division
import talib
import numpy as np
from vnpy.trader.vtObject import VtBarData
from vnpy.trader.vtConstant import EMPTY_STRING
from vnpy.trader.app.ctaStrategy.ctaTemplate import CtaTemplate, BarManager
from vnpy.trader.app.ctaStrategy.ctaTemplate import (CtaTemplate,
BarManager,
ArrayManager)
########################################################################
@ -34,14 +33,6 @@ class KkStrategy(CtaTemplate):
fixedSize = 1 # 每次交易的数量
# 策略变量
bufferSize = 100 # 需要缓存的数据的大小
bufferCount = 0 # 目前已经缓存了的数据的计数
highArray = np.zeros(bufferSize) # K线最高价的数组
lowArray = np.zeros(bufferSize) # K线最低价的数组
closeArray = np.zeros(bufferSize) # K线收盘价的数组
atrValue = 0 # 最新的ATR指标数值
kkMid = 0 # KK通道中轨
kkUp = 0 # KK通道上轨
kkDown = 0 # KK通道下轨
intraTradeHigh = 0 # 持仓期内的最高点
@ -63,8 +54,6 @@ class KkStrategy(CtaTemplate):
varList = ['inited',
'trading',
'pos',
'atrValue',
'kkMid',
'kkUp',
'kkDown']
@ -74,6 +63,7 @@ class KkStrategy(CtaTemplate):
super(KkStrategy, self).__init__(ctaEngine, setting)
self.bm = BarManager(self.onBar, 5, self.onFiveBar) # 创建K线合成器对象
self.am = ArrayManager()
#----------------------------------------------------------------------
def onInit(self):
@ -118,26 +108,13 @@ class KkStrategy(CtaTemplate):
self.orderList = []
# 保存K线数据
self.closeArray[0:self.bufferSize-1] = self.closeArray[1:self.bufferSize]
self.highArray[0:self.bufferSize-1] = self.highArray[1:self.bufferSize]
self.lowArray[0:self.bufferSize-1] = self.lowArray[1:self.bufferSize]
self.closeArray[-1] = bar.close
self.highArray[-1] = bar.high
self.lowArray[-1] = bar.low
self.bufferCount += 1
if self.bufferCount < self.bufferSize:
am = self.am
am.updateBar(bar)
if not am.inited:
return
# 计算指标数值
self.atrValue = talib.ATR(self.highArray,
self.lowArray,
self.closeArray,
self.kkLength)[-1]
self.kkMid = talib.MA(self.closeArray, self.kkLength)[-1]
self.kkUp = self.kkMid + self.atrValue * self.kkDev
self.kkDown = self.kkMid - self.atrValue * self.kkDev
self.kkUp, self.kkDown = am.keltner(self.kkLength, self.kkDev)
# 判断是否要进行交易