senset/vnpy
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

[Add]增加海龟回测中的手续费和滑点计算

Browse Source
This commit is contained in:
vn.py 2018-11-11 14:57:51 +08:00
parent 7071af22c2
commit e5c0850956
4 changed files with 63 additions and 247 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

107
examples/TurtleStrategy/.ipynb_checkpoints/run-checkpoint.ipynb
View File

@ -6,13 +6,11 @@
"metadata": {},
"outputs": [],
"source": [
"import sys\n",
"reload(sys)\n",
"\n",
"\n",
"%matplotlib inline\n",
"\n",
"from datetime import datetime\n",
"\n",
"import numpy as np\n",
"import matplotlib.pyplot as plt\n",
"\n",
"from turtleEngine import BacktestingEngine"
@ -22,28 +20,33 @@
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"outputs": [
{
"ename": "TypeError",
"evalue": "coercing to Unicode: need string or buffer, int found",
"output_type": "error",
"traceback": [
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[1;31mTypeError\u001b[0m Traceback (most recent call last)",
"\u001b[1;32m<ipython-input-2-a69b1c674549>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[0;32m 1\u001b[0m \u001b[0mengine\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mBacktestingEngine\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 2\u001b[0m \u001b[0mengine\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msetPeriod\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mdatetime\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m2015\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m1\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m1\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdatetime\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m2018\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m11\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m9\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 3\u001b[1;33m \u001b[0mengine\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0minitPortfolio\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m10000000\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m'setting.csv'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
"\u001b[1;32mC:\\Github\\vnpy\\examples\\TurtleStrategy\\turtleEngine.py\u001b[0m in \u001b[0;36minitPortfolio\u001b[1;34m(self, filename, portfolioValue)\u001b[0m\n\u001b[0;32m 60\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0minitPortfolio\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mfilename\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mportfolioValue\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m10000000\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 61\u001b[0m \u001b[1;34m\"\"\"\"\"\"\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 62\u001b[1;33m \u001b[1;32mwith\u001b[0m \u001b[0mopen\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mfilename\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0mf\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 63\u001b[0m \u001b[0mr\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mDictReader\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mf\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 64\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0md\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mr\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;31mTypeError\u001b[0m: coercing to Unicode: need string or buffer, int found"
]
}
],
"source": [
"l = ['IF99'] #, 'CU99', 'I99', 'TA99']\n",
"engine = BacktestingEngine()\n",
"engine.setPeriod(datetime(2015, 1, 1), datetime(2018, 11, 9))\n",
"engine.initPortfolio(l)"
"engine.initPortfolio('setting.csv')"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"11:39:12.298000:IF99数据加载完成，总数据量：940\n",
"11:39:12.299000:全部数据加载完成\n"
]
}
],
"execution_count": null,
"metadata": {
"scrolled": false
},
"outputs": [],
"source": [
"engine.loadData()\n",
"engine.runBacktesting()\n",
@ -52,34 +55,16 @@
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"2015-06-08 00:00:00\n"
]
"execution_count": null,
"metadata": {
"scrolled": false
},
{
"ename": "UnicodeDecodeError",
"evalue": "'ascii' codec can't decode byte 0xe5 in position 0: ordinal not in range(128)",
"output_type": "error",
"traceback": [
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[1;31mUnicodeDecodeError\u001b[0m Traceback (most recent call last)",
"\u001b[1;32m<ipython-input-4-74c05e0f545f>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[0;32m 2\u001b[0m \u001b[1;32mprint\u001b[0m \u001b[0mdt\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 3\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mtrade\u001b[0m \u001b[1;32min\u001b[0m \u001b[0ml\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 4\u001b[1;33m \u001b[1;32mprint\u001b[0m \u001b[0mtrade\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
"\u001b[1;32mC:\\Github\\vnpy\\examples\\TurtleStrategy\\turtleEngine.py\u001b[0m in \u001b[0;36m__str__\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m 134\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0moffset\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mencode\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'UTF-8'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 135\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mvolume\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 136\u001b[1;33m self.price)\n\u001b[0m\u001b[0;32m 137\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 138\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;31mUnicodeDecodeError\u001b[0m: 'ascii' codec can't decode byte 0xe5 in position 0: ordinal not in range(128)"
]
}
],
"outputs": [],
"source": [
"for dt, l in engine.tradeDict.items():\n",
" print dt\n",
" for trade in l:\n",
" print trade"
" print trade.vtSymbol, trade.direction, trade.offset, trade.price, trade.volume"
]
},
{
@ -91,29 +76,16 @@
"outputs": [],
"source": [
"for result in engine.resultList:\n",
" if result.totalPnl:\n",
" print result.date, result.totalPnl"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
"metadata": {
"scrolled": true
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import numpy as np"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"l = [result.totalPnl for result in engine.resultList]\n",
@ -121,25 +93,6 @@
"plt.plot(equity)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"for data in engine.dataDict.values():\n",
" print data"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"print trade."
]
},
{
"cell_type": "code",
"execution_count": null,

182
examples/TurtleStrategy/run.ipynb
View File

@ -6,13 +6,11 @@
"metadata": {},
"outputs": [],
"source": [
"import sys\n",
"reload(sys)\n",
"\n",
"\n",
"%matplotlib inline\n",
"\n",
"from datetime import datetime\n",
"\n",
"import numpy as np\n",
"import matplotlib.pyplot as plt\n",
"\n",
"from turtleEngine import BacktestingEngine"
@ -20,30 +18,22 @@
},
{
"cell_type": "code",
"execution_count": 2,
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"l = ['IF99'] #, 'CU99', 'I99', 'TA99']\n",
"engine = BacktestingEngine()\n",
"engine.setPeriod(datetime(2015, 1, 1), datetime(2018, 11, 9))\n",
"engine.initPortfolio(l)"
"engine.initPortfolio('setting.csv', 10000000)"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"11:39:12.298000:IF99数据加载完成，总数据量：940\n",
"11:39:12.299000:全部数据加载完成\n"
]
}
],
"execution_count": null,
"metadata": {
"scrolled": false
},
"outputs": [],
"source": [
"engine.loadData()\n",
"engine.runBacktesting()\n",
@ -52,122 +42,11 @@
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"2015-06-08 00:00:00\n",
"IF99 多 开仓 5370.6182 1\n",
"IF99 多 开仓 5370.6182 1\n",
"2015-06-17 00:00:00\n",
"IF99 空 平仓 4994.5359289007665 1\n",
"IF99 空 平仓 4994.5359289007665 1\n",
"2015-10-12 00:00:00\n",
"IF99 多 开仓 3341.0982 1\n",
"2015-10-26 00:00:00\n",
"IF99 多 开仓 3424.5987371468213 1\n",
"2015-11-04 00:00:00\n",
"IF99 多 开仓 3508.099274293643 1\n",
"2015-11-05 00:00:00\n",
"IF99 多 开仓 3591.5998114404642 1\n",
"2015-11-23 00:00:00\n",
"IF99 空 平仓 3603.8898 4\n",
"2015-12-21 00:00:00\n",
"IF99 多 开仓 3786.5235 1\n",
"2015-12-23 00:00:00\n",
"IF99 多 开仓 3834.280588057014 1\n",
"2015-12-28 00:00:00\n",
"IF99 空 平仓 3643.2522358289566 2\n",
"2016-03-07 00:00:00\n",
"IF99 多 开仓 3027.3054 1\n",
"IF99 多 开仓 3074.3983619185256 1\n",
"2016-03-18 00:00:00\n",
"IF99 多 开仓 3121.4913238370505 1\n",
"2016-03-21 00:00:00\n",
"IF99 多 开仓 3168.584285755576 1\n",
"2016-04-20 00:00:00\n",
"IF99 空 平仓 3105.8006 4\n",
"2016-07-07 00:00:00\n",
"IF99 多 开仓 3166.5061 1\n",
"2016-07-11 00:00:00\n",
"IF99 多 开仓 3194.9341606344988 1\n",
"IF99 多 开仓 3192.2685 1\n",
"2016-07-12 00:00:00\n",
"IF99 多 开仓 3223.3622212689975 1\n",
"2016-07-27 00:00:00\n",
"IF99 空 平仓 3173.5677 4\n",
"2016-08-11 00:00:00\n",
"IF99 多 开仓 3245.6871 1\n",
"2016-08-12 00:00:00\n",
"IF99 多 开仓 3268.4782362989677 1\n",
"IF99 多 开仓 3274.5309 1\n",
"2016-08-15 00:00:00\n",
"IF99 多 开仓 3291.269372597935 1\n",
"2016-08-25 00:00:00\n",
"IF99 空 平仓 3251.8034639734847 4\n",
"2016-10-19 00:00:00\n",
"IF99 多 开仓 3294.1809 1\n",
"2016-10-24 00:00:00\n",
"IF99 多 开仓 3313.0011487826814 1\n",
"IF99 多 开仓 3331.821397565363 1\n",
"IF99 多 开仓 3350.6416463480446 1\n",
"2016-12-07 00:00:00\n",
"IF99 空 平仓 3432.9777 4\n",
"2017-03-24 00:00:00\n",
"IF99 多 开仓 3468.6291 1\n",
"2017-03-30 00:00:00\n",
"IF99 空 平仓 3406.5561141656326 1\n",
"2017-04-05 00:00:00\n",
"IF99 多 开仓 3474.3432 1\n",
"IF99 多 开仓 3491.1258202647214 1\n",
"IF99 多 开仓 3474.3432 1\n",
"IF99 多 开仓 3491.1258202647214 1\n",
"2017-04-17 00:00:00\n",
"IF99 空 平仓 3440.7779594705567 3\n",
"IF99 空 平仓 3440.7779594705567 1\n",
"2017-05-25 00:00:00\n",
"IF99 多 开仓 3433.5201 1\n",
"IF99 多 开仓 3449.826458335901 1\n",
"IF99 多 开仓 3466.1328166718017 1\n",
"2017-05-26 00:00:00\n",
"IF99 多 开仓 3482.4391750077025 1\n",
"2017-06-15 00:00:00\n",
"IF99 空 平仓 3498.115614786368 4\n",
"2017-06-22 00:00:00\n",
"IF99 多 开仓 3579.0624 1\n",
"2017-06-26 00:00:00\n",
"IF99 多 开仓 3597.53568462007 1\n",
"IF99 多 开仓 3616.0089692401393 1\n",
"IF99 多 开仓 3634.4822538602093 1\n",
"2017-08-11 00:00:00\n",
"IF99 空 平仓 3656.9743 4\n",
"2018-01-02 00:00:00\n",
"IF99 多 开仓 4105.3543 1\n",
"2018-01-03 00:00:00\n",
"IF99 多 开仓 4132.444330290369 1\n",
"2018-01-08 00:00:00\n",
"IF99 多 开仓 4159.534360580738 1\n",
"2018-01-09 00:00:00\n",
"IF99 多 开仓 4186.624390871108 1\n",
"2018-02-01 00:00:00\n",
"IF99 空 平仓 4253.1416 4\n",
"2018-07-24 00:00:00\n",
"IF99 多 开仓 3507.8183 1\n",
"IF99 多 开仓 3547.101357149508 1\n",
"2018-08-02 00:00:00\n",
"IF99 空 平仓 3389.9691285514746 2\n",
"2018-09-21 00:00:00\n",
"IF99 多 开仓 3407.2856 1\n",
"2018-09-26 00:00:00\n",
"IF99 多 开仓 3438.7157642602238 1\n",
"2018-10-08 00:00:00\n",
"IF99 空 平仓 3312.9951072193303 2\n"
]
}
],
"execution_count": null,
"metadata": {
"scrolled": false
},
"outputs": [],
"source": [
"for dt, l in engine.tradeDict.items():\n",
" print dt\n",
@ -184,29 +63,16 @@
"outputs": [],
"source": [
"for result in engine.resultList:\n",
" if result.totalPnl:\n",
" print result.date, result.totalPnl"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
"metadata": {
"scrolled": true
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import numpy as np"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"l = [result.totalPnl for result in engine.resultList]\n",
@ -219,19 +85,7 @@
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"for data in engine.dataDict.values():\n",
" print data"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"print trade."
]
"source": []
},
{
"cell_type": "code",

10
examples/TurtleStrategy/turtleEngine.py
View File

@ -203,12 +203,22 @@ class DailyResult(object):
close = self.closeDict[vtSymbol]
size = SIZE_DICT[vtSymbol]
slippage = SLIPPAGE_DICT[vtSymbol]
variableCommission = VARIABLE_COMMISSION_DICT[vtSymbol]
fixedCommission = FIXED_COMMISSION_DICT[vtSymbol]
for trade in l:
if trade.direction == DIRECTION_LONG:
side = 1
else:
side = -1
commissionCost = (trade.volume * fixedCommission +
trade.volume * trade.price * variableCommission)
slippageCost = trade.volume * slippage
pnl = (close - trade.price) * trade.volume * side * size
pnl -= (commissionCost + slippageCost)
self.tradingPnl += pnl
#----------------------------------------------------------------------

1
examples/TurtleStrategy/turtleStrategy.py
View File

@ -255,7 +255,6 @@ class TurtleSignal(object):
return tradePrice
########################################################################
class TurtlePortfolio(object):
"""海龟组合"""