發佈 backtrader 使用示例使我對缺失的東西有了深刻的瞭解。對於初學者：
-
多核優化
-
傭金：股票與期貨
後者向我展示了：
-
經紀人在計算損益方面做了正確的事情，併為調用策略提供了正確的訂單通知
-
該策略無法訪問
operations（又名trades），這是訂單開倉和平倉的結果（後者顯示損益數位） -
繪製的
Operation損益數位是由收集Observer的，並且無法訪問實際commission scheme值，因此為futures-like操作和stocks-like操作呈現相同的損益
顯然，需要進行少量的內部返工才能實現：
-
Operation策略通知 -
Operations顯示正確的損益數據
broker已經擁有所有需要的信息，並且已經將大部分資訊塞進了order正在通知創建它的人的資訊中strategy。唯一要做出的決定是，是否將broker額外的資訊位放入訂單中，或者它可以計算自身operations。
由於策略已經獲得orders 並且將保留在 operations 清單中似乎是很自然的 broker ，因此當訂單部分/全部平倉時，只需添加實際的損益，將計算的責任留給 strategy.
反過來，這簡化了實際作用，Operations Observer 即觀察新關閉 Operation 並記錄它。它應該一直扮演的角色。
下面的代碼已經過重新設計，不再計算損益數位，而只是關注那些通知的人notify_operation。
圖表現在反映了現實的損益數位（cash 和 value 是現實的）
期貨的舊 logging ：
2006-03-09, BUY CREATE, 3757.59 2006-03-10, BUY EXECUTED, Price: 3754.13, Cost: 2000.00, Comm 2.00 2006-04-11, SELL CREATE, 3788.81 2006-04-12, SELL EXECUTED, Price: 3786.93, Cost: 2000.00, Comm 2.00 2006-04-12, OPERATION PROFIT, GROSS 328.00, NET 324.00 2006-04-20, BUY CREATE, 3860.00 2006-04-21, BUY EXECUTED, Price: 3863.57, Cost: 2000.00, Comm 2.00 2006-04-28, SELL CREATE, 3839.90 2006-05-02, SELL EXECUTED, Price: 3839.24, Cost: 2000.00, Comm 2.00 2006-05-02, OPERATION PROFIT, GROSS -243.30, NET -247.30
期貨新 logging ：
2006-03-09, BUY CREATE, 3757.59 2006-03-10, BUY EXECUTED, Price: 3754.13, Cost: 2000.00, Comm 2.00 2006-04-11, SELL CREATE, 3788.81 2006-04-12, SELL EXECUTED, Price: 3786.93, Cost: 2000.00, Comm 2.00 2006-04-12, OPERATION PROFIT, GROSS 328.00, NET 324.00 2006-04-20, BUY CREATE, 3860.00 2006-04-21, BUY EXECUTED, Price: 3863.57, Cost: 2000.00, Comm 2.00 2006-04-28, SELL CREATE, 3839.90 2006-05-02, SELL EXECUTED, Price: 3839.24, Cost: 2000.00, Comm 2.00 2006-05-02, OPERATION PROFIT, GROSS -243.30, NET -247.30 2006-05-02, BUY CREATE, 3862.24
股票的舊 logging ：
2006-03-09, BUY CREATE, 3757.59 2006-03-10, BUY EXECUTED, Price: 3754.13, Cost: 3754.13, Comm 18.77 2006-04-11, SELL CREATE, 3788.81 2006-04-12, SELL EXECUTED, Price: 3786.93, Cost: 3786.93, Comm 18.93 2006-04-12, OPERATION PROFIT, GROSS 32.80, NET -4.91 2006-04-20, BUY CREATE, 3860.00 2006-04-21, BUY EXECUTED, Price: 3863.57, Cost: 3863.57, Comm 19.32 2006-04-28, SELL CREATE, 3839.90 2006-05-02, SELL EXECUTED, Price: 3839.24, Cost: 3839.24, Comm 19.20 2006-05-02, OPERATION PROFIT, GROSS -24.33, NET -62.84
股票的新 logging ：
2006-03-09, BUY CREATE, 3757.59 2006-03-10, BUY EXECUTED, Price: 3754.13, Cost: 3754.13, Comm 18.77 2006-04-11, SELL CREATE, 3788.81 2006-04-12, SELL EXECUTED, Price: 3786.93, Cost: 3786.93, Comm 18.93 2006-04-12, OPERATION PROFIT, GROSS 32.80, NET -4.91 2006-04-20, BUY CREATE, 3860.00 2006-04-21, BUY EXECUTED, Price: 3863.57, Cost: 3863.57, Comm 19.32 2006-04-28, SELL CREATE, 3839.90 2006-05-02, SELL EXECUTED, Price: 3839.24, Cost: 3839.24, Comm 19.20 2006-05-02, OPERATION PROFIT, GROSS -24.33, NET -62.84 2006-05-02, BUY CREATE, 3862.24
和圖表（只有新的）。操作和操作之間的區別futures-like現在可以清楚地看到，而不僅僅是在 和value的cash演變stock-like中。
期貨傭金
股票傭金
代碼
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import backtrader as bt
import backtrader.feeds as btfeeds
import backtrader.indicators as btind
futures_like = True
if futures_like:
commission, margin, mult = 2.0, 2000.0, 10.0
else:
commission, margin, mult = 0.005, None, 1
class SMACrossOver(bt.Strategy):
def log(self, txt, dt=None):
''' Logging function fot this strategy'''
dt = dt or self.datas[0].datetime.date(0)
print('%s, %s' % (dt.isoformat(), txt))
def notify(self, order):
if order.status in [order.Submitted, order.Accepted]:
# Buy/Sell order submitted/accepted to/by broker - Nothing to do
return
# Check if an order has been completed
# Attention: broker could reject order if not enougth cash
if order.status in [order.Completed, order.Canceled, order.Margin]:
if order.isbuy():
self.log(
'BUY EXECUTED, Price: %.2f, Cost: %.2f, Comm %.2f' %
(order.executed.price,
order.executed.value,
order.executed.comm))
else: # Sell
self.log('SELL EXECUTED, Price: %.2f, Cost: %.2f, Comm %.2f' %
(order.executed.price,
order.executed.value,
order.executed.comm))
def notify_trade(self, trade):
if trade.isclosed:
self.log('TRADE PROFIT, GROSS %.2f, NET %.2f' %
(trade.pnl, trade.pnlcomm))
def __init__(self):
sma = btind.SMA(self.data)
# > 0 crossing up / < 0 crossing down
self.buysell_sig = btind.CrossOver(self.data, sma)
def next(self):
if self.buysell_sig > 0:
self.log('BUY CREATE, %.2f' % self.data.close[0])
self.buy() # keep order ref to avoid 2nd orders
elif self.position and self.buysell_sig < 0:
self.log('SELL CREATE, %.2f' % self.data.close[0])
self.sell()
if __name__ == '__main__':
# Create a cerebro entity
cerebro = bt.Cerebro()
# Add a strategy
cerebro.addstrategy(SMACrossOver)
# Create a Data Feed
datapath = ('../../datas/2006-day-001.txt')
data = bt.feeds.BacktraderCSVData(dataname=datapath)
# Add the Data Feed to Cerebro
cerebro.adddata(data)
# set commission scheme -- CHANGE HERE TO PLAY
cerebro.broker.setcommission(
commission=commission, margin=margin, mult=mult)
# Run over everything
cerebro.run()
# Plot the result
cerebro.plot()