def testStrategy():
from pyalgotrade import bar
from pyalgotrade import plotter
strat = DoubleMA
frequency = bar.Frequency.MINUTE
paras = [5, 20]
plot = True
#############################################path set ############################33
feed = Feed(frequency)
feed.loadBars('bitmex_BCHZ18', test_back=True)
strat = strat(feed, "bitmex_BCHZ18", *paras)
from pyalgotrade.stratanalyzer import returns
from pyalgotrade.stratanalyzer import sharpe
from pyalgotrade.stratanalyzer import drawdown
from pyalgotrade.stratanalyzer import trades
retAnalyzer = returns.Returns()
strat.attachAnalyzer(retAnalyzer)
sharpeRatioAnalyzer = sharpe.SharpeRatio()
strat.attachAnalyzer(sharpeRatioAnalyzer)
drawDownAnalyzer = drawdown.DrawDown()
strat.attachAnalyzer(drawDownAnalyzer)
tradesAnalyzer = trades.Trades()
strat.attachAnalyzer(tradesAnalyzer)
if plot:
plt = plotter.StrategyPlotter(strat, True, True, True)
strat.run()
if plot:
plt.plot()
# 夏普率
sharp = sharpeRatioAnalyzer.getSharpeRatio(0.02)
print(sharp)
# 最大回撤
maxdd = drawDownAnalyzer.getMaxDrawDown()
print(maxdd)
# 收益率
return_ = retAnalyzer.getCumulativeReturns()[-1]
print(return_)
# 收益曲线
return_list = []
for item in retAnalyzer.getCumulativeReturns():
return_list.append(item)
print(return_list)
def main(plot):
instruments = ['bitmex_XBTUSD','okex_BTCUSDT']
feed = Feed(Frequency.SECOND)
feed.loadBars("bitmex_XBTUSD", test_back=True)
feed.loadBars("okex_BTCUSDT", test_back=True)
'''初始保证金'''
initCash = 1000000
'''手续费设置
目前不支持多标的设置不同的手续费类型
3种手续费类型：
NoCommission：None 默认
FixedPerTrade：固定金额
TradePercentage：按比例收费
'''
commission = TradePercentage(0.0003)
broker = Broker(initCash,feed,commission)
#设置为滑点模型，默认为 NoSlippage
#broker.getFillStrategy().setSlippageModel(VolumeShareSlippage)
#设置交易量限制
#每一个bar中的 volume * limit
#broker.getFillStrategy().setVolumeLimit(0.1)
strat = MultiSymbols(feed, instruments, broker)
sharpeRatioAnalyzer = sharpe.SharpeRatio()
strat.attachAnalyzer(sharpeRatioAnalyzer)
returnsAnalyzer = returns.Returns()
strat.attachAnalyzer(returnsAnalyzer)
if plot:
plt = plotter.StrategyPlotter(strat, False, False, True)
plt.getOrCreateSubplot("cash").addCallback("Cash", lambda x: strat.getBroker().getCash())
# Plot strategy vs. SPY cumulative returns.
# plt.getOrCreateSubplot("returns").addDataSeries("SPY", cumret.CumulativeReturn(feed["SPY"].getPriceDataSeries()))
plt.getOrCreateSubplot("returns").addDataSeries("Strategy", returnsAnalyzer.getCumulativeReturns())
strat.run()
print("Sharpe ratio: %.2f" % sharpeRatioAnalyzer.getSharpeRatio(0.05))
print("Returns: %.2f %%" % (returnsAnalyzer.getCumulativeReturns()[-1] * 100))
if plot:
plt.plot()
def main(plot):
initialCash = 10000
instrumentsByClass = {
# "bitmex_LTCZ18": ["bitmex_LTCZ18"],
"okex_LIGHTBTC": ["okex_LIGHTBTC"],
"binance_ADABTC": ["binance_ADABTC"],
}
# Download the bars.
instruments = []
for assetClass in instrumentsByClass:
instruments.extend(instrumentsByClass[assetClass])
# feed = yahoofinance.build_feed(instruments, 2007, 2013, "data", skipErrors=True)
instrument = "bitmex_LTCZ18"
feed = Feed(Frequency.MINUTE)
# feed.loadBars(instrument, test_back=True)
feed.loadBars('okex_LIGHTBTC', test_back=True)
feed.loadBars("binance_ADABTC", test_back=True)
strat = MarketTiming(feed, instrumentsByClass, initialCash)
sharpeRatioAnalyzer = sharpe.SharpeRatio()
strat.attachAnalyzer(sharpeRatioAnalyzer)
returnsAnalyzer = returns.Returns()
strat.attachAnalyzer(returnsAnalyzer)
if plot:
plt = plotter.StrategyPlotter(strat, False, False, True)
plt.getOrCreateSubplot("cash").addCallback(
"Cash", lambda x: strat.getBroker().getCash())
# Plot strategy vs. SPY cumulative returns.
# plt.getOrCreateSubplot("returns").addDataSeries("SPY", cumret.CumulativeReturn(feed["SPY"].getPriceDataSeries()))
plt.getOrCreateSubplot("returns").addDataSeries(
"Strategy", returnsAnalyzer.getCumulativeReturns())
strat.run()
print("Sharpe ratio: %.2f" % sharpeRatioAnalyzer.getSharpeRatio(0.05))
print("Returns: %.2f %%" %
(returnsAnalyzer.getCumulativeReturns()[-1] * 100))
if plot:
plt.plot()
from pyalgotrade.technical import rsi
# 构建一个策略
class MyStrategy(strategy.BacktestingStrategy):
def __init__(self, feed, instrument):
super(MyStrategy, self).__init__(feed)
self.__rsi = rsi.RSI(feed[instrument].getCloseDataSeries(), 14)
self.__sma_rsi = ma.SMA(self.__rsi, 15)
self.__sma = ma.SMA(feed[instrument].getCloseDataSeries(), 2)
# self.info("__sma: {}, {}.".format(self.__sma, self.__sma[-1]))
self.__instrument = instrument
def onBars(self, bars): # 每一个数据都会抵达这里
bar = bars[self.__instrument]
self.info("%s %s %s" % (bar.getClose(), self.__sma[-1],
self.__sma_rsi[-1])) # 我们打印输出收盘价与两分钟均线值
if __name__ == '__main__':
# 获得回测数据
feed = Feed(Frequency.SECOND)
feed.loadBars('bitmex_XBTUSD', test_back=True)
# feed.loadBarsFuture('okex_ltc', 'this_week_ticker', test_back=True)
# feed.loadBarsFutureIndex('okex_ltc', test_back=True, types='index')
# 把策略跑起来
myStrategy = MyStrategy(feed, "bitmex_XBTUSD")
myStrategy.run()
return
bar = bars[self.__instrument]
# # If a position was not opened, check if we should enter a long position.
if self.__position is None: # 如果手上没有头寸，那么
if bar.getPrice() > self.__sma[-1]:
# 开多，如果现价大于移动均线，且当前没有头寸.
self.__position = self.enterLong(self.__instrument, 100, True)
# 当前有多头头寸，平掉多头头寸.
elif bar.getPrice() < self.__sma[-1] and not self.__position.exitActive():
self.__position.exitMarket()
if __name__ == '__main__':
# 获得回测数据
feed = Feed(Frequency.SECOND)
feed.loadBars('bitmex_LTCZ18', test_back=True)
feed.loadBars('okex_LIGHTBTC', test_back=True)
myStrategy = MyStrategy(feed) # , ('bitmex_LTCZ18', "okex_LIGHTBTC")
retAnalyzer = returns.Returns()
myStrategy.attachAnalyzer(retAnalyzer)
sharpRatioAnalyzer = sharpe.SharpeRatio()
myStrategy.attachAnalyzer(sharpRatioAnalyzer)
myStrategy.run()
myStrategy.info("Final portfolio value: $%.10f" % myStrategy.getResult())
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))
# -*- coding:utf-8 -*-
from pyalgotrade import strategy
from pyalgotrade.bar import Frequency
from ccwt_client.ccwt_feed import Feed
# 构建一个策略
class MyStrategy(strategy.BacktestingStrategy):
def __init__(self, feed, instrument):
super(MyStrategy, self).__init__(feed)
self.__instrument = instrument
def onBars(self, bars): # 每一个数据都会抵达这里，就像becktest中的next
bar = bars[self.__instrument]
self.info(bar.getClose()) # 我们打印输出收盘价
if __name__ == '__main__':
# 获得回测数据
feed = Feed(Frequency.MINUTE)
#feed.loadBars('okex_LIGHTUSDT')
#feed.loadBars('binance_TRXBTC')
feed.loadBars('bitmex_XBTUSD')
# 把策略跑起来
#myStrategy = MyStrategy(feed, "okex_LIGHTUSDT")
#myStrategy = MyStrategy(feed, "binance_TRXBTC")
myStrategy = MyStrategy(feed, "bitmex_XBTUSD")
myStrategy.run()
# 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, 100, True)
# 平掉多头头寸.
elif bar.getPrice() < self.__sma[-1] and not self.__position.exitActive():
self.__position.exitMarket()
if __name__ == '__main__':
# 获得回测数据
feed = Feed(Frequency.MINUTE)
#feed.loadBars('okex_LIGHTUSDT')
feed.loadBars('bitmex_BCHZ18')
feed.loadBars('binance_TRXBTC')
# 4.设置指标和绘图
# 把策略跑起来
#myStrategy = MyStrategy(feed, "okex_LIGHTUSDT")
# myStrategy = MyStrategy(feed, "bitmex_BCHZ18")
myStrategy = MyStrategy(feed, "binance_TRXBTC")
#returnsAnalyzer = returns.Returns()
#myStrategy.attachAnalyzer(returnsAnalyzer)
sharpe_ratio = sharpe.SharpeRatio()
myStrategy.attachAnalyzer(sharpe_ratio)
from ccwt_client.ccwt_feed import Feed
# 构建一个策略
class MyStrategy(strategy.BacktestingStrategy):
def __init__(self, feed, instrument):
super(MyStrategy, self).__init__(feed)
self.__instrument = instrument
def onBars(self, bars): # 每一个数据都会抵达这里，就像becktest中的next
bar = bars[self.__instrument]
self.info(bar.getClose()) # 我们打印输出收盘价
if __name__ == '__main__':
# 获得回测数据
feed = Feed(Frequency.MINUTE)
#feed.loadBars('okex_LIGHTUSDT')
#feed.loadBars('binance_TRXBTC')
# feed.loadBars('bitmex_XBTUSD', test_back=True)
feed.loadBars('bitmex_XBTUSD',
test_back=False,
start_date='2018-12-10',
end_date='2018-12-12')
# 把策略跑起来
#myStrategy = MyStrategy(feed, "okex_LIGHTUSDT")
#myStrategy = MyStrategy(feed, "binance_TRXBTC")
myStrategy = MyStrategy(feed, "bitmex_XBTUSD")
myStrategy.run()
from pyalgotrade import strategy
from pyalgotrade.bar import Frequency
from ccwt_client.ccwt_feed import Feed
from pyalgotrade.technical import ma
from pyalgotrade.technical import rsi
# 构建一个策略
class MyStrategy(strategy.BacktestingStrategy):
def __init__(self, feed, instrument):
super(MyStrategy, self).__init__(feed)
self.__rsi = rsi.RSI(feed[instrument].getCloseDataSeries(), 14)
self.__sma_rsi = ma.SMA(self.__rsi, 15)
self.__sma = ma.SMA(feed[instrument].getCloseDataSeries(), 2)
self.__instrument = instrument
def onBars(self, bars): # 每一个数据都会抵达这里
bar = bars[self.__instrument]
self.info("%s %s %s" % (bar.getClose(), self.__sma[-1],
self.__sma_rsi[-1])) # 我们打印输出收盘价与两分钟均线值
if __name__ == '__main__':
# 获得回测数据
feed = Feed(Frequency.SECOND)
feed.loadBars('bitmex_BCHZ18')
# 把策略跑起来
myStrategy = MyStrategy(feed, "bitmex_BCHZ18")
myStrategy.run()
def onBars(self, bars): # 每一个数据都会抵达这里，
# SMA的计算存在窗口，所以前面的几个bar下是没有SMA的数据的.
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: # 如果手上没有头寸，那么
if bar.getPrice() > self.__sma[-1]:
# 开多，如果现价大于移动均线，且当前没有头寸.
self.__position = self.enterLong(self.__instrument, 100, True)
# 当前有多头头寸，平掉多头头寸.
elif bar.getPrice(
) < self.__sma[-1] and not self.__position.exitActive():
self.__position.exitMarket()
if __name__ == '__main__':
# 获得回测数据
feed = Feed(Frequency.SECOND)
feed.loadBars('okex_LIGHTUSDT', test_back=True)
# feed.loadBars('bitmex_LTCZ18', test_back=True)
# feed.loadBarsFuture('okex_ltc', 'quarter_ticker', test_back=True)
# 把策略跑起来
myStrategy = MyStrategy(feed, "okex_LIGHTUSDT")
# myStrategy = MyStrategy(feed, "okex_ltc")
myStrategy.run()
myStrategy.info("Final portfolio value: $%.10f" % myStrategy.getResult())