pyalgotrade教程4--broker设置：交易费用，滑点模型

# coding=utf-8
from pyalgotrade import plotter
from pyalgotrade.stratanalyzer import returns, sharpe, drawdown, trades
from pyalgotrade import strategy
from pyalgotrade.bar import Frequency
from pyalgotrade.barfeed.csvfeed import GenericBarFeed
from pyalgotrade.technical import ma
from pyalgotrade import broker
# 1.构建一个策略
class MyStrategy(strategy.BacktestingStrategy):
    def __init__(self, feed, instrument, brk):
        super(MyStrategy, self).__init__(feed, brk)
        self.__position = None
        self.__sma = ma.SMA(feed[instrument].getCloseDataSeries(), 150)
        self.__instrument = instrument
        self.getBroker()
    def onEnterOk(self, position):
        execInfo = position.getEntryOrder().getExecutionInfo()
        self.info("BUY at %.2f" % (execInfo.getPrice()))

    def onEnterCanceled(self, position):
        self.__position = None

    def onExitOk(self, position):
        execInfo = position.getExitOrder().getExecutionInfo()
        self.info("SELL at $%.2f" % (execInfo.getPrice()))
        self.__position = None

    def onExitCanceled(self, position):
        # If the exit was canceled, re-submit it.
        self.__position.exitMarket()

    def getSMA(self):
        return self.__sma

    def onBars(self, bars):# 每一个数据都会抵达这里，就像becktest中的next

        # Wait for enough bars to be available to calculate a SMA.
        if self.__sma[-1] is None:
            return
        #bar.getTyoicalPrice = (bar.getHigh() + bar.getLow() + bar.getClose())/ 3.0

        bar = bars[self.__instrument]
        # If a position was not opened, check if we should enter a long position.
        if self.__position is None:
            if bar.getPrice() > self.__sma[-1]:
                # 开多头.
                self.__position = self.enterLong(self.__instrument, 10, True)
        # 平掉多头头寸.
        elif bar.getPrice() < self.__sma[-1] and not self.__position.exitActive():
            self.__position.exitMarket()

# 2.获得回测数据，官网来源于yahoo，由于墙的关系，我们用本地数据
feed = GenericBarFeed(Frequency.DAY, None, None)
feed.addBarsFromCSV("fd", "fd.csv")
# 3.broker setting
# 3.1 commission类设置
broker_commission = broker.backtesting.TradePercentage(0.0001)
# 3.2 fill strategy设置
fill_stra = broker.fillstrategy.DefaultStrategy(volumeLimit=0.1)
sli_stra = broker.slippage.NoSlippage()
fill_stra.setSlippageModel(sli_stra)
# 3.3完善broker类
brk = broker.backtesting.Broker(1000000, feed, broker_commission)
brk.setFillStrategy(fill_stra)
# 4.把策略跑起来

myStrategy = MyStrategy(feed, "fd", brk)

# Attach a returns analyzers to the strategy.
trade_situation = trades.Trades()
myStrategy.attachAnalyzer(trade_situation)
# Attach the plotter to the strategy.
plt = plotter.StrategyPlotter(myStrategy)

# Run the strategy.
myStrategy.run()
myStrategy.info("Final portfolio value: $%.2f" % myStrategy.getResult())
print "total number of trades", trade_situation.getCount()
print "commissions for each trade",trade_situation.getCommissionsForAllTrades()
# Plot the strategy.
plt.plot()