def run_strategy(fastSma, slowSma, tp, stop):
# Load the bar feed from the CSV file
feed = csvfeed.GenericBarFeed(frequency=60 * 5)
feed.setDateTimeFormat("%Y-%m-%dT%H:%M:%S.%fZ")
feed.addBarsFromCSV("btc", "btc-5m-apr.csv")
# Create our broker defining the comission(0,01%) and the initial balance($15000)
commission = backtesting.TradePercentage(0.0001)
broker = backtesting.Broker(15000, feed, commission)
# Evaluate the strategy with the feed
myStrategy = MACrossoverStrategy(feed, "btc", broker, fastSma, slowSma, tp,
stop)
# Attach the plotter to the strategy
plt = plotter.StrategyPlotter(myStrategy)
# Include the MA in the instrument's subplot to get it displayed along with the closing prices
plt.getOrCreateSubplot("MA").addDataSeries("50 MA",
myStrategy.getFastSMA())
plt.getOrCreateSubplot("MA").addDataSeries("200 MA",
myStrategy.getSlowSMA())
# Run the strategy and show the final portfolio value
myStrategy.run()
myStrategy.info(f'Final portfolio value: ${myStrategy.getResult()}')
# Plot the strategy
plt.plot()
def __init__(self, feed, instrument):
super(MyStrategy, self).__init__(feed, 1000000)
self.__broker = self.getBroker()
self.__broker.setCommission(backtesting.TradePercentage(0.0005))
self.__instrument = instrument
self.__position = None
# self.setUseAdjustedValues(True)
self.__days = None
def __init__(self, barFeed, cash=1000000):
# The broker should subscribe to barFeed events before the strategy.
# This is to avoid executing orders placed in the current tick.
broker = backtesting.Broker(cash, barFeed,
backtesting.TradePercentage(0.002))
strategy.BaseStrategy.__init__(self, barFeed, broker)
self.__useAdjustedValues = False
self.setUseEventDateTimeInLogs(True)
def __init__(self, feed, instrument):
super(MyStrategy, self).__init__(feed, 1000000)
self.__broker = self.getBroker()
self.__broker.setCommission(backtesting.TradePercentage(0.0005))
self.__instrument = instrument
self.__position = None
# self.setUseAdjustedValues(True)
self.__prices = feed[instrument].getPriceDataSeries()
self.__sma10 = ma.SMA(self.__prices, 10)
self.__sma25 = ma.SMA(self.__prices, 25)
def __init__(self,
initialBalances,
barFeed,
fee=0.005,
instrumentTraits=livebroker.InstrumentTraits()):
super(BacktestingBroker,
self).__init__(initialBalances,
barFeed,
commission=backtesting.TradePercentage(fee),
instrumentTraits=instrumentTraits)
self._tradeValidatorPredicate = TradeValidatorPredicate(
instrumentTraits)
def __init__(self, feed, instruments, posMax, delay):
myBroker = broker.Broker(1000000, feed, broker.TradePercentage(0.002))
strategy.BacktestingStrategy.__init__(self, feed, myBroker)
self._delay = delay
self._liquidity = 0.05
self._positions = {}
self._posMax = posMax
self._instruments = instruments
self.setUseAdjustedValues(True)
self.getBroker().getFillStrategy().setVolumeLimit(None)
self.startDateTime = feed.peekDateTime()
self.endDateTime = None
def __init__(self,
feed,
instrument,
bBandsPeriod,
cash=10,
comission=0.002):
broker = backtesting.Broker(cash, feed,
backtesting.TradePercentage(comission))
strategy.BaseStrategy.__init__(self, feed, broker)
self.__instrument = instrument
self.__bbands = bollinger.BollingerBands(
feed[instrument].getCloseDataSeries(), bBandsPeriod, 2)
def __init__(self, feed, instrument):
# 起始金额100万刀
super(MyStrategy, self).__init__(feed, 1000000)
self.__broker = self.getBroker()
self.__broker.setCommission(backtesting.TradePercentage(0.0005))
self.__instrument = instrument
self.__position = None
# 如果想用修正后的收盘价，也就是股票数据csv文件中的Adj Close这一列的数据，那么需要使用这一行配置
# self.setUseAdjustedValues(True)
self.__k = 0.08
self.__bars = feed[self.__instrument]
self.__dual = Dual(self.__bars)
def __init__(self, feed, posMax, capital):
myBroker = broker.Broker(capital, feed, broker.TradePercentage(0.002))
myBroker.setAllowNegativeCash(True)
myBroker.getFillStrategy().setVolumeLimit(None)
super(MyBenchmark, self).__init__(feed, myBroker)
self._feed = feed
self._session = 0
self._liquidity = 0.05
self._posMax = posMax
self._positions = {}
self.startDateTime = None
self.endDateTime = None
self.setUseAdjustedValues(True)
def __init__(self, feed, delay):
myBroker = backtesting.Broker(1000000, feed, backtesting.TradePercentage(0.002))
myBroker.setAllowNegativeCash(True)
myBroker.getFillStrategy().setVolumeLimit(None)
super(MyBenchmark, self).__init__(feed, myBroker)
self._delay = delay
self._feed = feed
self._session = 0
self._liquidity = 0.05
self._posMax = len(feed.getRegisteredInstruments())
self._posLong = {}
self._posShort = {}
self.startDateTime = None
self.endDateTime = None
self.setUseAdjustedValues(True)
def __init__(self, feed, instrument, parametres, cash=10, comission=0.002):
broker = backtesting.Broker(cash, feed, backtesting.TradePercentage(comission))
strategy.BaseStrategy.__init__(self, feed, broker)
self.numOrder = 0
self.okOrder = 0
self.exitOrder = 0
self.s1 = self.s2 = self.s3 = 1
self.p1 = self.p2 = self.p3 = 1
self.windowTrust = parametres[3]
# SMA
self.__instrument = instrument
self.__position = None
self.__Close = feed[instrument].getCloseDataSeries()
self.__sma = ma.SMA(self.__Close, parametres[0])
# Bbands
self.__instrument = instrument
self.__bbands = bollinger.BollingerBands(feed[instrument].getCloseDataSeries(), parametres[1], 2)
# Vwap
self.__instrument = instrument
self.__vwap = vwap.VWAP(feed[instrument], parametres[2])
def testTradePercentage(self): comm = backtesting.TradePercentage(0.1) self.assertEqual(comm.calculate(None, 1, 1), 0.1) self.assertEqual(comm.calculate(None, 2, 2), 0.4)
def __init__(self, feed, instrument, vwapWindowSize, cash=10, comission=0.002):
broker = backtesting.Broker(cash, feed, backtesting.TradePercentage(comission))
strategy.BaseStrategy.__init__(self, feed, broker)
self.__instrument = instrument
self.__vwap = vwap.VWAP(feed[instrument], vwapWindowSize)
def __init__(self, cash, barFeed, commission = None): if commission is None: commission = backtesting.TradePercentage(0.006) backtesting.Broker.__init__(self, cash, barFeed, commission)
def __init__(self, cash, barFeed, fee=0.001):
commission = backtesting.TradePercentage(fee)
backtesting.Broker.__init__(self, cash, barFeed, commission)
def __init__(self, cash, barFeed, fee=0.005):
commission = backtesting.TradePercentage(fee)
backtesting.Broker.__init__(self, cash, barFeed, commission)
self.setAllowFractions(True)
def __init__(self, cash, barFeed, fee=common.DEFAULT_TAKER_FEE):
assert common.INSTRUMENT_TOKEN and common.CASH_TOKEN
commission = backtesting.TradePercentage(fee)
super(BacktestingBroker, self).__init__(cash, barFeed, commission)
# Load the yahoo feed from CSV files.
feed = yahoofeed.Feed()
feed.addBarsFromCSV("aeti", "aeti-2009-yahoofinance.csv")
feed.addBarsFromCSV("egan", "egan-2009-yahoofinance.csv")
feed.addBarsFromCSV("glng", "glng-2009-yahoofinance.csv")
feed.addBarsFromCSV("simo", "simo-2009-yahoofinance.csv")
# Evaluate the strategy with the feed's bars.
myStrategy = MyStrategy(feed)
# Set commission
# https://github.com/gbeced/pyalgotrade/blob/master/testcases/sharpe_analyzer_test.py
myStrategy.getBroker().setCommission(
backtesting.FixedPerTrade(10)) # $10 commission per trade
myStrategy.getBroker().setCommission(
backtesting.TradePercentage(.10)) # 10.% commission per trade
# Attach returns and sharpe ratio analyzers.
retAnalyzer = returns.Returns()
myStrategy.attachAnalyzer(retAnalyzer)
sharpeRatioAnalyzer = sharpe.SharpeRatio()
myStrategy.attachAnalyzer(sharpeRatioAnalyzer)
# Run the strategy
myStrategy.run()
# Print the results.
print "Final portfolio value: $%.2f" % myStrategy.getResult()
print "Anual return: %.2f %%" % (retAnalyzer.getCumulativeReturns()[-1] * 100)
print "Average daily return: %.2f %%" % (stats.mean(retAnalyzer.getReturns()) *
100)
def __init__(self, cash, barFeed, fee=0):
commission = backtesting.TradePercentage(fee)
super(BacktestingBroker, self).__init__(cash, barFeed, commission)
