交易执行机制怎样才符合实际环境 – backtrader中文教程

通常我们这样认为：

• 使用每日柱线但使用开盘价引入订单

比如：#105 带有当天数据的订单执行逻辑和 #101 动态赌注计算

backtrader尽量保持现实，并且在使用每日柱线时适用以下前提：

• 当评估每日柱时，柱已经结束

这是有道理的，因为所有价格（开盘价/最高价/最低价/收盘价）组件都是已知的。 当收盘价已知时，允许对开盘价采取行动实际上似乎不合逻辑。

显而易见的方法是使用日内数据并在已知开盘价时输入。但似乎盘中数据并不那么普遍。

这就是向数据馈送添加过滤器可以提供帮助的地方。一个过滤器：

• 将每日数据转换为日内数据

起泡藤壶！！！好奇的读者会立即指出， 例如对 to进行上采样是合乎逻辑且有效的，但 无法对to进行下采样。MinutesDays DaysMinutes

这是 100% 正确的。下面介绍的过滤器不会尝试这样做，而是一个非常谦虚和简单的目标：

• 将每日酒吧分成两部分
  1. 只有开盘价没有成交量的柱
  2. 2 ^nd bar 是常规每日 bar 的副本

这仍然可以作为一种合乎逻辑的方法：

• 看到开盘价，交易者可以行动
• 订单在当天剩余时间匹配（实际上可能匹配也可能不匹配，具体取决于执行类型和价格限制）

完整的代码如下所示。让我们看一个带有众所周知的255 每日柱线数据的示例运行：

$ ./daysteps.py --data ../../datas/2006-day-001.txt

输出：

Calls,Len Strat,Len Data,Datetime,Open,High,Low,Close,Volume,OpenInterest
0001,0001,0001,2006-01-02T23:59:59,3578.73,3578.73,3578.73,3578.73,0.00,0.00
- I could issue a buy order during the Opening
0002,0001,0001,2006-01-02T23:59:59,3578.73,3605.95,3578.73,3604.33,0.00,0.00
0003,0002,0002,2006-01-03T23:59:59,3604.08,3604.08,3604.08,3604.08,0.00,0.00
- I could issue a buy order during the Opening
0004,0002,0002,2006-01-03T23:59:59,3604.08,3638.42,3601.84,3614.34,0.00,0.00
0005,0003,0003,2006-01-04T23:59:59,3615.23,3615.23,3615.23,3615.23,0.00,0.00
- I could issue a buy order during the Opening
0006,0003,0003,2006-01-04T23:59:59,3615.23,3652.46,3615.23,3652.46,0.00,0.00
...
...
0505,0253,0253,2006-12-27T23:59:59,4079.70,4079.70,4079.70,4079.70,0.00,0.00
- I could issue a buy order during the Opening
0506,0253,0253,2006-12-27T23:59:59,4079.70,4134.86,4079.70,4134.86,0.00,0.00
0507,0254,0254,2006-12-28T23:59:59,4137.44,4137.44,4137.44,4137.44,0.00,0.00
- I could issue a buy order during the Opening
0508,0254,0254,2006-12-28T23:59:59,4137.44,4142.06,4125.14,4130.66,0.00,0.00
0509,0255,0255,2006-12-29T23:59:59,4130.12,4130.12,4130.12,4130.12,0.00,0.00
- I could issue a buy order during the Opening
0510,0255,0255,2006-12-29T23:59:59,4130.12,4142.01,4119.94,4119.94,0.00,0.00

会发生以下情况：

• next被称为：510 times这是255 x 2
• 策略和数据的总和达到 len，这是预期的：数据只有那么多条255
• 数据len的每增加一次，这4个价格分量都有相同的值，即价格open

  此处打印出一条备注，表明在此开盘阶段可以采取行动，例如购买。

有效：

• 每日数据馈送每天以 2 个步骤重播open，提供在其他价格组成部分之间采取行动的选项

该过滤器将在下一个版本中添加到backtrader的默认分发中。

包含过滤器的示例代码。

from __future__ import (absolute_import, division, print_function,
                        unicode_literals)

import argparse
from datetime import datetime, time

import backtrader as bt


class DayStepsFilter(object):
    def __init__(self, data):
        self.pendingbar = None

    def __call__(self, data):
        # Make a copy of the new bar and remove it from stream
        newbar = [data.lines[i][0] for i in range(data.size())]
        data.backwards()  # remove the copied bar from stream

        openbar = newbar[:]  # Make an open only bar
        o = newbar[data.Open]
        for field_idx in [data.High, data.Low, data.Close]:
            openbar[field_idx] = o

        # Nullify Volume/OpenInteres at the open
        openbar[data.Volume] = 0.0
        openbar[data.OpenInterest] = 0.0

        # Overwrite the new data bar with our pending data - except start point
        if self.pendingbar is not None:
            data._updatebar(self.pendingbar)

        self.pendingbar = newbar  # update the pending bar to the new bar
        data._add2stack(openbar)  # Add the openbar to the stack for processing

        return False  # the length of the stream was not changed

    def last(self, data):
        '''Called when the data is no longer producing bars
        Can be called multiple times. It has the chance to (for example)
        produce extra bars'''
        if self.pendingbar is not None:
            data.backwards()  # remove delivered open bar
            data._add2stack(self.pendingbar)  # add remaining
            self.pendingbar = None  # No further action
            return True  # something delivered

        return False  # nothing delivered here


class St(bt.Strategy):
    params = ()

    def __init__(self):
        pass

    def start(self):
        self.callcounter = 0
        txtfields = list()
        txtfields.append('Calls')
        txtfields.append('Len Strat')
        txtfields.append('Len Data')
        txtfields.append('Datetime')
        txtfields.append('Open')
        txtfields.append('High')
        txtfields.append('Low')
        txtfields.append('Close')
        txtfields.append('Volume')
        txtfields.append('OpenInterest')
        print(','.join(txtfields))

        self.lcontrol = 0

    def next(self):
        self.callcounter += 1

        txtfields = list()
        txtfields.append('%04d' % self.callcounter)
        txtfields.append('%04d' % len(self))
        txtfields.append('%04d' % len(self.data0))
        txtfields.append(self.data.datetime.datetime(0).isoformat())
        txtfields.append('%.2f' % self.data0.open[0])
        txtfields.append('%.2f' % self.data0.high[0])
        txtfields.append('%.2f' % self.data0.low[0])
        txtfields.append('%.2f' % self.data0.close[0])
        txtfields.append('%.2f' % self.data0.volume[0])
        txtfields.append('%.2f' % self.data0.openinterest[0])
        print(','.join(txtfields))

        if len(self.data) > self.lcontrol:
            print('- I could issue a buy order during the Opening')

        self.lcontrol = len(self.data)


def runstrat():
    args = parse_args()

    cerebro = bt.Cerebro()
    data = bt.feeds.BacktraderCSVData(dataname=args.data)

    data.addfilter(DayStepsFilter)
    cerebro.adddata(data)

    cerebro.addstrategy(St)

    cerebro.run(stdstats=False, runonce=False, preload=False)
    if args.plot:
        cerebro.plot(style='bar')


def parse_args():
    parser = argparse.ArgumentParser(
        formatter_class=argparse.ArgumentDefaultsHelpFormatter,
        description='Sample for pivot point and cross plotting')

    parser.add_argument('--data', required=False,
                        default='../../datas/2005-2006-day-001.txt',
                        help='Data to be read in')

    parser.add_argument('--plot', required=False, action='store_true',
                        help=('Plot the result'))

    return parser.parse_args()


if __name__ == '__main__':
    runstrat()