\u5728\u524d\u9762\u7684\u4f8b\u5b50\u4e2d\u4f7f\u7528\u7b56\u7565\u7684\u65f6\u5019\uff0c\u6ca1\u6709\u4ec0\u4e48\u53c2\u6570\u53ef\u4ee5\u8c03\u8282\u6d4b\u8bd5\u3002\u6846\u67b6\u672c\u8eab\u662f\u652f\u6301\u53c2\u6570\u7684\uff0c\u4f7f\u7528\u8d77\u6765\u4e5f\u6bd4\u8f83\u7b80\u5355<\/p>\n\n\n\n
\u53c2\u6570\u7684\u5b9a\u4e49\u5f88\u7b80\u5355\uff0c\u5982\u4e0b\u6240\u793a\uff1a<\/p>\n\n\n\n
params = (('myparam', 27), ('exitbars', 5),)<\/code><\/pre>\n\n\n\n\u4f7f\u7528\u4e86python\u57fa\u672c\u7684\u6570\u636e\u7ed3\u6784\u5143\u7ec4\uff08tuple\uff09\u3002\u6bcf\u4e2a\u5143\u7ec4\u67092\u4e2a\u5143\u7d20\u3002\u5176\u4e2d\uff0c\u7b2c\u4e00\u4e2a\u5143\u7d20\u4e3a\u53c2\u6570\u7684\u540d\u79f0\uff0c\u7b2c\u4e8c\u4e2a\u5143\u4e3a\u53d8\u91cf\u5bf9\u5e94\u7684\u503c\u3002\u7528\u66f4\u76f4\u89c2\u7684\u683c\u5f0f\u5c55\u793a\u5982\u4e0b\uff1a<\/p>\n\n\n\n
params = (\n ('myparam', 27),\n ('exitbars', 5),\n)<\/code><\/pre>\n\n\n\n\u9664\u4e86\u5f00\u59cb\u8d4b\u503c\u9ed8\u8ba4\u503c\uff0c\u8fd8\u53ef\u4ee5\u5728\u6846\u67b6\uff0c\u589e\u52a0\u7b56\u7565\u7684\u65f6\u5019\u8fdb\u884c\u8d4b\u503c\uff0c\u8d4b\u503c\u4e0b\u65b9\u6cd5\u5982\u4e0b\uff1a<\/p>\n\n\n\n
# Add a strategy\ncerebro.addstrategy(TestStrategy, myparam=20, exitbars=7)<\/code><\/pre>\n\n\n\n\u4e0b\u9762\u5b9e\u73b0\u4e00\u4e2a\u901a\u8fc7\u8bbe\u7f6e\u53c2\u6570\uff0c\u6765\u5b9e\u73b0\u53c2\u6570\u6307\u5b9a\u591a\u4e2a\u5c11\u51e0\u4ea4\u6613\u65e5\u540e\u6e05\u4ed3\u7684\u6848\u4f8b\uff0c\u6301\u80a15\u5929\u5c31\u6e05\u4ed3\uff1a<\/p>\n\n\n\n
# -*- coding: utf-8 -*-\n\"\"\"\nbacktrader\u624b\u518c\u6837\u4f8b\u4ee3\u7801\n@author: \u4e00\u5757\u81ea\u7531\u7684\u7816\n\"\"\"\n#############################################################\n#import\n#############################################################\nfrom __future__ import (absolute_import, division, print_function,\n unicode_literals)\nimport os,sys\nimport pandas as pd\nimport backtrader as bt\n#############################################################\n#global const values\n#############################################################\n#############################################################\n#static function\n#############################################################\n#############################################################\n#class\n#############################################################\n# Create a Stratey\nclass TestStrategy(bt.Strategy):\n params = (\n ('exitbars', 5),\n )\n\n def log(self, txt, dt=None):\n ''' Logging function for this strategy\uff0c\u8fd9\u91cc\u5b9a\u4e49\u65e5\u5fd7\u7684\u663e\u793a\u683c\u5f0f'''\n dt = dt or self.datas[0].datetime.date(0)\n print('%s, %s' % (dt.isoformat(), txt))\n\n def __init__(self):\n # Keep a reference to the \"close\" line in the data[0] dataseries\uff08\u83b7\u53d6\u6536\u76d8\u4ef7\uff09\n self.dataclose = self.datas[0].close\n # To keep track of pending orders and buy price\/commission(\u4ef7\u683c\u3001\u4f63\u91d1)\n self.order = None\n self.buyprice = None\n self.buycomm = None\n \n def notify_order(self, order):\n if order.status in [order.Submitted, order.Accepted]:\n # Buy\/Sell order submitted\/accepted to\/by broker - Nothing to do\n return\n # Check if an order has been completed\n # Attention: broker could reject order if not enough cash\n if order.status in [order.Completed]:\n if order.isbuy():\n # \u5b9e\u9645\u53d1\u751f\u4e70\u5355\u7684\u4ef7\u683c\uff0c\u6210\u672c\uff0c\u4f63\u91d1\n self.log(\n 'BUY EXECUTED, Price: %.2f, Cost: %.2f, Comm %.2f' %\n (order.executed.price,\n order.executed.value,\n order.executed.comm))\n self.buyprice = order.executed.price\n self.buycomm = order.executed.comm\n elif order.issell():\n # \u5b9e\u9645\u53d1\u751f\u5356\u5355\u7684\u4ef7\u683c\uff0c\u6210\u672c\uff0c\u4f63\u91d1\n self.log('SELL EXECUTED, Price: %.2f, Cost: %.2f, Comm %.2f' %\n (order.executed.price,\n order.executed.value,\n order.executed.comm))\n # \u53d1\u751f\u4e70\u5355\u65f6\u7684\u4ea4\u6613\u65e5\u7684\u7d22\u5f15\n self.bar_executed = len(self)\n\n elif order.status in [order.Canceled, order.Margin, order.Rejected]:\n self.log('Order Canceled\/Margin\/Rejected')\n\n # Write down: no pending order\n self.order = None\n\n def notify_trade(self, trade):\n if not trade.isclosed:\n return\n # \u4e00\u6b21\u5356\u51fa\u540e\u4ea4\u6613\u5b8c\u6210\u540e\u7684\u6536\u76ca\u60c5\u51b5\uff1a gross \u6bdb\u5229 net \u51c0\/\u7eaf\u5229\n self.log('OPERATION PROFIT, GROSS %.2f, NET %.2f' %\n (trade.pnl, trade.pnlcomm))\n\n def next(self):\n # Simply log the closing price of the series from the reference\uff08\u8c03\u7528\u65e5\u5fd7\u65b9\u6cd5\uff0c\u663e\u793a\u6536\u76d8\u4ef7\uff09\n self.log('Close, %.2f' % self.dataclose[0])\n # Check if an order is pending ... if yes, we cannot send a 2nd one\n if self.order:\n return\n # Check if we are in the market\uff08\u68c0\u67e5\u662f\u5426\u6301\u80a1\uff09\n if not self.position:\n # \u5224\u5b9a\u5f53\u524d\u4ea4\u6613\u65e5\u7684\u6536\u76d8\u4ef7\u662f\u5426\u5c0f\u4e8e\u6628\u65e5\u7684\n if self.dataclose[0] < self.dataclose[-1]:\n # current close less than previous close\uff08\u5224\u5b9a\u6628\u65e5\u7684\u6536\u76d8\u4ef7\u662f\u5426\u5c0f\u4e8e\u524d\u65e5\u7684\uff09\n if self.dataclose[-1] < self.dataclose[-2]:\n # previous close less than the previous close\n # BUY, BUY, BUY!!! \u8d2d\u4e70\u52a8\u4f5c\uff0c\u521b\u5efa\u4e70\u5355\uff0c\u7ed9\u4e70\u5165\u4ef7\n self.log('BUY CREATE, %.2f' % self.dataclose[0])\n # Keep track of the created order to avoid a 2nd order\n self.order = self.buy()\n else:\n # Already in the market ... we might sell\uff0c\u6301\u80a1\u68c0\u67e5\u662f\u5426\u5df2\u7ecf\u5927\u4e8e5\u4e2a\u4ea4\u6613\u65e5\n if len(self) >= (self.bar_executed + self.params.exitbars):\n # SELL, SELL, SELL!!! (with all possible default parameters)\n self.log('SELL CREATE, %.2f' % self.dataclose[0])\n\n # Keep track of the created order to avoid a 2nd order\n self.order = self.sell()\n#############################################################\n#global values\n#############################################################\n#############################################################\n#global function\n#############################################################\n# \u901a\u8fc7\u8bfb\u53d6cvs\u6587\u4ef6\uff0c\u83b7\u53d6\u60f3\u8981\u7684\u6570\u636e\ndef get_dataframe():\n # Get a pandas dataframe\uff08\u8fd9\u91cc\u662f\u80a1\u7968\u6570\u636e\u6587\u4ef6\u653e\u7684\u76ee\u5f55\u8def\u5f84\uff09\n datapath = 'qtbt\\data\\stockinfo.csv'\n # \u6570\u636e\u8f6c\u6362\u7528\u4e34\u65f6\u6587\u4ef6\u8def\u5f84\u548c\u540d\u79f0\uff0c\u7528\u5b8c\u540e\u5220\u9664\n tmpdatapath = datapath + '.tmp'\n print('-----------------------read csv---------------------------')\n dataframe = pd.read_csv(datapath,\n skiprows=0,\n header=0,\n parse_dates=True,\n index_col=0)\n # \u5b9a\u4e49\u4ea4\u6613\u65e5\u671f\u683c\u5f0f\n dataframe.trade_date = pd.to_datetime(dataframe.trade_date, format=\"%Y%m%d\")\n # \u539f\u59cbcvs\u6570\u636e\u6709\u5f88\u591a\u5217\uff0c\u8fd9\u91cc\u7ec4\u7ec7\u9700\u8981\u4f7f\u7528\u7684\u6570\u636e\u5217\uff0c\u751f\u6210\u76ee\u6807\u6570\u636e\u7684tmp\u6570\u636e\u6587\u4ef6\u540e\uff0c\u8bfb\u53d6\u9700\u8981\u7684\u6570\u636e\n dataframe['openinterest'] = '0'\n feedsdf = dataframe[['trade_date', 'open', 'high', 'low', 'close', 'vol', 'openinterest']]\n feedsdf.columns =['datetime', 'open', 'high', 'low', 'close', 'volume', 'openinterest']\n # \u6309\u7167\u4ea4\u6613\u65e5\u671f\u5347\u5e8f\u6392\u5217\n feedsdf.set_index(keys='datetime', inplace =True)\n # \u751f\u6210\u4e34\u65f6\u6587\u4ef6\n feedsdf.iloc[::-1].to_csv(tmpdatapath)\n # \u83b7\u53d6\u9700\u8981\u4f7f\u7528\u7684\u6570\u636e\n feedsdf = pd.read_csv(tmpdatapath, skiprows=0, header=0, parse_dates=True, index_col=0)\n # \u5220\u9664tmp\u4e34\u65f6\u6587\u4ef6\n if os.path.isfile(tmpdatapath):\n os.remove(tmpdatapath)\n print(tmpdatapath+\" removed!\")\n # \u8fd4\u56de\u9700\u8981\u7684\u6570\u636e\n return feedsdf\n########################################################################\n#main\n########################################################################\nif __name__ == '__main__':\n # Create a cerebro entity(\u521b\u5efacerebro)\n cerebro = bt.Cerebro()\n # Add a strategy(\u52a0\u5165\u81ea\u5b9a\u4e49\u7b56\u7565,\u53ef\u4ee5\u8bbe\u7f6e\u81ea\u5b9a\u4e49\u53c2\u6570\uff0c\u65b9\u4fbf\u8c03\u8282)\n cerebro.addstrategy(TestStrategy)\n # Get a pandas dataframe(\u83b7\u53d6dataframe\u683c\u5f0f\u80a1\u7968\u6570\u636e)\n feedsdf = get_dataframe()\n # Pass it to the backtrader datafeed and add it to the cerebro(\u52a0\u5165\u6570\u636e)\n data = bt.feeds.PandasData(dataname=feedsdf)\n # \u52a0\u5165\u6570\u636e\u5230Cerebro\n cerebro.adddata(data)\n # Add a FixedSize sizer according to the stake(\u56fd\u51851\u624b\u662f100\u80a1\uff0c\u6700\u5c0f\u7684\u4ea4\u6613\u5355\u4f4d)\n cerebro.addsizer(bt.sizers.FixedSize, stake=100)\n # Set our desired cash start(\u7ed9\u7ecf\u7eaa\u4eba\uff0c\u53ef\u4ee5\u7406\u89e3\u4e3a\u4ea4\u6613\u6240\u80a1\u7968\u8d26\u6237\u5145\u94b1)\n cerebro.broker.setcash(100000.0)\n # Set the commission - 0.1% ... divide by 100 to remove the %\n cerebro.broker.setcommission(commission=0.001)\n # Print out the starting conditions(\u8f93\u51fa\u8d26\u6237\u91d1\u989d)\n print('Starting Portfolio Value: %.2f' % cerebro.broker.getvalue())\n # Run over everything(\u6267\u884c\u56de\u6d4b)\n cerebro.run()\n # Print out the final result(\u8f93\u51fa\u8d26\u6237\u91d1\u989d)\n print('Final Portfolio Value: %.2f' % cerebro.broker.getvalue())\n<\/code><\/pre>\n\n\n\n\u6267\u884c\u8f93\u51fa\uff1a<\/p>\n\n\n\n
2021-09-14, Close, 9.21
2021-09-14, BUY CREATE, 9.21
2021-09-15, BUY EXECUTED, Price: 9.21, Cost: 921.00, Comm 0.92
2021-09-15, Close, 9.19
2021-09-16, Close, 9.12
2021-09-17, Close, 9.11
2021-09-22, Close, 9.03
2021-09-23, Close, 9.03
2021-09-24, Close, 9.02
2021-09-24, SELL CREATE, 9.02
2021-09-27, SELL EXECUTED, Price: 9.02, Cost: 921.00, Comm 0.90
2021-09-27, OPERATION PROFIT, GROSS -19.00, NET -20.82
2021-09-27, Close, 9.02
2021-09-28, Close, 9.03
2021-09-29, Close, 9.02
2021-09-30, Close, 9.00
2021-09-30, BUY CREATE, 9.00
Final Portfolio Value: 99734.77<\/p>\n\n\n\n
2021-09-15\u4e70\u5165\uff0c 2021-09-24 \u5356\u51fa<\/p>\n","protected":false},"excerpt":{"rendered":"
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