似乎在世界某个地方有一种权益(Interest)可以总结如下：
- 使用每日柱线引入订单，但使用开盘价
这来自工单#105订单执行逻辑与当前数据和#101动态投注计算中的对话
backtrader 尝试尽可能保持现实，并且在处理每日柱线时适用以下前提：
- 当每日柱被评估时，柱线已经结束
这是有道理的，因为所有价格（open/high/low/close）元件都是已知的。实际上，当价格已知时，允许对open 价格采取行动似乎是不合逻辑的 close 。
明显的方法是使用日内数据并输入开盘价何时已知。但日内数据似乎并不那么普遍。
这就是将筛选器添加到 data feed 可以提供说明的地方。具有以下特性的过滤器：
- 将每日数据转换为类似日内的数据
起泡的藤壶!!!好奇的读者会立即指出，例如Minutes 向上采样是 Days 合乎逻辑的并且有效，但是向下采样 Days 到 Minutes 是无法完成的。
这是100%正确的。下面介绍的筛检程式不会尝试这一点，而是一个谦卑而简单的目标：
-
将每日酒吧分成两部分
-
只有开盘价而没有 volume
-
第 2个 柱，它是常规每日柱的副本
-
这仍然可以作为一种合乎逻辑的方法：
-
看到开盘价后，交易者可以采取行动
-
订单在当天的其余时间内匹配（实际上可能会匹配也可能不匹配，具体取决于执行类型和价格约束）
完整代码如下所示。让我们看一个示例运行，其中包含每日柱的255 已知数据：
$ ./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
将发生以下情况：
-
next称为：510 times即255 x 2 -
len策略和数据的总数255达到 ，这是预期的：数据只有那么多柱 -
每当
len数据增加时，4个价格成分具有相同的值，open即价格这里列印出一个注释，以表明在这个开放阶段可以采取行动，例如购买。
有效：
- 每日 data feed 每天重播2个步骤，可以选择在价格组成部分和其他价格组成部分之间
open采取行动
该筛选器将添加到下一版本中的预设 backtrader 分发版中。
包含筛选器的范例代码。
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()