似乎在世界某個地方有一種权益(Interest)可以總結如下：
- 使用每日柱線引入訂單，但使用開盤價
這來自工單#105订单执行逻辑与当前数据和#101动态投注计算中的對話
backtrader 嘗試盡可能保持現實，並且在處理每日柱線時適用以下前提：
- 當每日柱被評估時，柱線已經結束
這是有道理的，因為所有價格（open/high/low/close）元件都是已知的。實際上，當價格已知時，允許對open 價格採取行動似乎是不合邏輯的 close 。
明顯的方法是使用日內數據並輸入開盤價何時已知。但日內數據似乎並不那麼普遍。
這就是將篩選器添加到 data feed 可以提供説明的地方。具有以下特性的過濾器：
- 將每日數據轉換為類似日內的數據
起泡的藤壺!!!好奇的讀者會立即指出，例如Minutes 向上採樣是 Days 合乎邏輯的並且有效，但是向下採樣 Days 到 Minutes 是無法完成的。
這是100%正確的。下面介紹的篩檢程式不會嘗試這一點，而是一個謙卑而簡單的目標：
-
將每日酒吧分成兩部分
-
只有開盤價而沒有 volume
-
第 2個 柱，它是常規每日柱的副本
-
這仍然可以作為一種合乎邏輯的方法：
-
看到開盤價后，交易者可以採取行動
-
訂單在當天的其餘時間內匹配（實際上可能會匹配也可能不匹配，具體取決於執行類型和價格約束）
完整代碼如下所示。讓我們看一個示例運行，其中包含每日柱的255 已知數據：
$ ./daysteps.py --data ../../datas/2006-day-001.txt
輸出：
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
將發生以下情況：
-
next稱為：510 times即255 x 2 -
len策略和數據的總數255達到 ，這是預期的：數據只有那麼多柱 -
每當
len數據增加時，4個價格成分具有相同的值，open即價格這裡列印出一個註釋，以表明在這個開放階段可以採取行動，例如購買。
有效：
- 每日 data feed 每天重播2個步驟，可以選擇在價格組成部分和其他價格組成部分之間
open採取行動
該篩選器將添加到下一版本中的預設 backtrader 分發版中。
包含篩選器的範例代碼。
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()