def main():
import coloredlogs
coloredlogs.install(level='DEBUG',
fmt='[%(asctime)s] %(levelname)s %(message)s')
# Load the yahoo feed from CSV files.
feed = yahoofeed.Feed()
feed.addBarsFromCSV("aeti", "./tests/data/aeti-2011-yahoofinance.csv")
feed.addBarsFromCSV("egan", "./tests/data/egan-2011-yahoofinance.csv")
feed.addBarsFromCSV("glng", "./tests/data/glng-2011-yahoofinance.csv")
feed.addBarsFromCSV("simo", "./tests/data/simo-2011-yahoofinance.csv")
# Evaluate the strategy with the feed's bars.
myStrategy = MyStrategy(feed)
# 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))
print("Std. dev. daily return: %.4f" %
(stats.stddev(retAnalyzer.getReturns())))
print("Sharpe ratio: %.2f" % (sharpeRatioAnalyzer.getSharpeRatio(0)))
def main():
strat = thrSMA
instrument = '600288'
paras = [2, 20, 60, 10]
feeds = tushare.build_feed([instrument], 2016, 2017, "histdata/tushare")
strat = strat(feeds, instrument, *paras)
retAnalyzer = returns.Returns()
strat.attachAnalyzer(retAnalyzer)
sharpeRatioAnalyzer = sharpe.SharpeRatio()
strat.attachAnalyzer(sharpeRatioAnalyzer)
drawDownAnalyzer = drawdown.DrawDown()
strat.attachAnalyzer(drawDownAnalyzer)
tradesAnalyzer = trades.Trades()
strat.attachAnalyzer(tradesAnalyzer)
plter = plotter.StrategyPlotter(strat, True, True, True)
strat.run()
plter.plot()
# 夏普率
sharp = sharpeRatioAnalyzer.getSharpeRatio(0.05)
# 最大回撤
maxdd = drawDownAnalyzer.getMaxDrawDown()
# 收益率
return_ = retAnalyzer.getCumulativeReturns()[-1]
# 收益曲线
return_list = []
for item in retAnalyzer.getCumulativeReturns():
return_list.append(item)
def testCumulativeReturn(self):
initialCash = 33.06
barFeed = yahoofeed.Feed()
barFeed.addBarsFromCSV(
AnalyzerTestCase.TestInstrument,
common.get_data_file_path("orcl-2001-yahoofinance.csv"))
strat = position_test.MyTestStrategy(barFeed,
AnalyzerTestCase.TestInstrument,
initialCash)
strat.addPosEntry(datetime.datetime(2001, 1, 12), strat.enterLong,
AnalyzerTestCase.TestInstrument, 1) # 33.06
strat.addPosExitMarket(datetime.datetime(2001, 11, 27)) # 14.32
stratAnalyzer = returns.Returns(maxLen=10)
strat.attachAnalyzer(stratAnalyzer)
strat.run()
self.assertTrue(
round(strat.getBroker().getCash(), 2) == round(
initialCash + (14.32 - 33.06), 2))
self.assertTrue(
round(33.06 *
(1 + stratAnalyzer.getCumulativeReturns()[-1]), 2) == 14.32)
self.assertEqual(len(stratAnalyzer.getCumulativeReturns()), 10)
self.assertEqual(len(stratAnalyzer.getReturns()), 10)
def testFirstBar(self):
initialCash = 1000
barFeed = yahoofeed.Feed()
barFeed.addBarsFromCSV(
AnalyzerTestCase.TestInstrument,
common.get_data_file_path("orcl-2001-yahoofinance.csv"))
strat = strategy_test.MyTestStrategy(barFeed, initialCash)
strat.addOrder(datetime.datetime(2001, 1, 2),
strat.getBroker().createMarketOrder,
broker.Order.Action.BUY,
AnalyzerTestCase.TestInstrument, 1,
False) # 2001-01-03 Open: 25.25 Close: 32.00
stratAnalyzer = returns.Returns()
strat.attachAnalyzer(stratAnalyzer)
strat.run()
self.assertEqual(stratAnalyzer.getReturns()[0], 0)
self.assertEqual(stratAnalyzer.getReturns()[1], (32.00 - 25.25) / 1000)
# Check date times.
datetimes = barFeed[AnalyzerTestCase.TestInstrument].getDateTimes()
for i in [0, -1]:
self.assertEqual(stratAnalyzer.getReturns().getDateTimes()[i],
datetimes[i])
self.assertEqual(
stratAnalyzer.getCumulativeReturns().getDateTimes()[i],
datetimes[i])
def testOneBarReturn(self):
initialCash = 1000
barFeed = yahoofeed.Feed()
barFeed.setBarFilter(
csvfeed.DateRangeFilter(datetime.datetime(2001, 12, 7),
datetime.datetime(2001, 12, 7)))
barFeed.addBarsFromCSV(
AnalyzerTestCase.TestInstrument,
common.get_data_file_path("orcl-2001-yahoofinance.csv"))
strat = strategy_test.MyTestStrategy(barFeed, initialCash)
# 2001-12-07,15.74,15.95,15.55,15.91,42463200,15.56
# Manually place the orders to get them filled on the first (and only) bar.
order = strat.getBroker().createMarketOrder(
broker.Order.Action.BUY, AnalyzerTestCase.TestInstrument, 1,
False) # Open: 15.74
strat.getBroker().submitOrder(order)
order = strat.getBroker().createMarketOrder(
broker.Order.Action.SELL, AnalyzerTestCase.TestInstrument, 1,
True) # Close: 15.91
strat.getBroker().submitOrder(order)
stratAnalyzer = returns.Returns()
strat.attachAnalyzer(stratAnalyzer)
strat.run()
self.assertTrue(strat.getBroker().getCash() == initialCash +
(15.91 - 15.74))
finalValue = 1000 - 15.74 + 15.91
rets = (finalValue - initialCash) / float(initialCash)
self.assertEqual(stratAnalyzer.getReturns()[-1], rets)
def main():
# 2.读取csv文件.
feed = GenericBarFeed(Frequency.DAY, None, None)
feed.addBarsFromCSV("a", "a.csv")
feed.addBarsFromCSV("b", "b.csv")
feed.addBarsFromCSV("c", "c.csv")
feed.addBarsFromCSV("d", "d.csv")
strat = MyStrategy(feed)
# 3.加入分析器
retAnalyzer = returns.Returns()
strat.attachAnalyzer(retAnalyzer)
sharpeRatioAnalyzer = sharpe.SharpeRatio()
strat.attachAnalyzer(sharpeRatioAnalyzer)
# 4.运行策略
strat.run()
# 5.输出结果
# 最终的投资组合价值
print("Final portfolio value: $%.2f" % strat.getResult())
# 年化平均收益率
print("Anual return: %.2f %%" % (retAnalyzer.getCumulativeReturns()[-1] * 100))
# 平均日收益
print("Average daily return: %.2f %%" % (stats.mean(retAnalyzer.getReturns()) * 100))
# 每日收益标准开发
print("Std. dev. daily return: %.4f" % (stats.stddev(retAnalyzer.getReturns())))
# 夏普比率
print("Sharpe ratio: %.2f" % (sharpeRatioAnalyzer.getSharpeRatio(0)))
def testStrategy():
instrument = '600288'
frequency = bar.Frequency.TRADE
fromDate = '20160815'
toDate = '20160820'
strat = OrderBook
paras = [5, 20]
plot = True
from mooquant.tools import tushare
feeds = tushare.build_feed([instrument], 2016, 2017, "histdata/tushare")
strat = strat(feeds, instrument, *paras)
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(0.05)
# 最大回撤
maxdd = drawDownAnalyzer.getMaxDrawDown()
# 收益率
return_ = retAnalyzer.getCumulativeReturns()[-1]
# 收益曲线
return_list = []
for item in retAnalyzer.getCumulativeReturns():
return_list.append(item)
def main():
# Load the orders file.
ordersFile = OrdersFile("./tests/data/orders.csv")
print("First date", ordersFile.getFirstDate())
print("Last date", ordersFile.getLastDate())
print("Symbols", ordersFile.getInstruments())
# Load the data from QSTK storage. QS environment variable has to be defined.
if os.getenv("QS") is None:
raise Exception("QS environment variable not defined")
feed = yahoofeed.Feed()
feed.setBarFilter(
csvfeed.DateRangeFilter(ordersFile.getFirstDate(),
ordersFile.getLastDate()))
feed.setDailyBarTime(
datetime.time(0, 0, 0)
) # This is to match the dates loaded with the ones in the orders file.
for symbol in ordersFile.getInstruments():
feed.addBarsFromCSV(
symbol,
os.path.join(os.getenv("QS"), "QSData", "Yahoo", symbol + ".csv"))
# Run the strategy.
cash = 1000000
useAdjustedClose = True
myStrategy = MyStrategy(feed, cash, ordersFile, useAdjustedClose)
# Attach returns and sharpe ratio analyzers.
retAnalyzer = returns.Returns()
myStrategy.attachAnalyzer(retAnalyzer)
sharpeRatioAnalyzer = sharpe.SharpeRatio()
myStrategy.attachAnalyzer(sharpeRatioAnalyzer)
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))
print("Std. dev. daily return: %.4f" %
(stats.stddev(retAnalyzer.getReturns())))
print("Sharpe ratio: %.2f" % (sharpeRatioAnalyzer.getSharpeRatio(0)))
def testMultipleInstrumentsInterleaved(self):
barFeed = yahoofeed.Feed()
barFeed.addBarsFromCSV(
"spy", common.get_data_file_path("spy-2010-yahoofinance.csv"),
marketsession.NYSE.getTimezone())
barFeed.addBarsFromCSV(
"nikkei",
common.get_data_file_path("nikkei-2010-yahoofinance.csv"),
marketsession.TSE.getTimezone())
strat = strategy_test.MyTestStrategy(barFeed, 1000)
stratAnalyzer = returns.Returns()
strat.attachAnalyzer(stratAnalyzer)
strat.marketOrder("spy", 1)
strat.run()
# The cumulative return should be the same if we load nikkei or not.
self.assertEqual(round(stratAnalyzer.getCumulativeReturns()[-1], 5),
0.01338)
def testGoogle2011(self):
initialValue = 1000000
barFeed = yahoofeed.Feed()
barFeed.addBarsFromCSV(
AnalyzerTestCase.TestInstrument,
common.get_data_file_path("goog-2011-yahoofinance.csv"))
strat = strategy_test.MyTestStrategy(barFeed, initialValue)
order = strat.getBroker().createMarketOrder(
broker.Order.Action.BUY, AnalyzerTestCase.TestInstrument, 1654,
True) # 2011-01-03 close: 604.35
strat.getBroker().submitOrder(order)
stratAnalyzer = returns.Returns()
strat.attachAnalyzer(stratAnalyzer)
strat.run()
finalValue = strat.getBroker().getEquity()
self.assertEqual(
round(stratAnalyzer.getCumulativeReturns()[-1], 4),
round((finalValue - initialValue) / float(initialValue), 4))
def run_strategy():
# Load the yahoo feed from the CSV file
feed = GenericBarFeed(Frequency.DAY, None, None)
feed.addBarsFromCSV("orcl", "2000.csv")
# commission
broker_commission = broker.backtesting.TradePercentage(0.002)
broker_brk = floatBroker(500000, feed, broker_commission)
# Evaluate the strategy with the feed.
myStrategy = MyStrategy(feed, "orcl", broker_brk)
returnsAnalyzer = returns.Returns()
myStrategy.attachAnalyzer(returnsAnalyzer)
# Attach the plotter to the strategy.
plt = plotter.StrategyPlotter(myStrategy)
# Include the SMA in the instrument's subplot to get it displayed along
# with the closing prices.
plt.getInstrumentSubplot("orcl").addDataSeries("SMA60",
myStrategy.getSMA(60))
plt.getInstrumentSubplot("orcl").addDataSeries("SMA10",
myStrategy.getSMA(10))
plt.getInstrumentSubplot("orcl").addDataSeries("SMA30",
myStrategy.getSMA(30))
# Plot the simple returns on each bar.
plt.getOrCreateSubplot("returns").addDataSeries(
"Simple returns", returnsAnalyzer.getReturns())
myStrategy.run()
print(
"Final portfolio value: $%.2f %.2f %.2f" %
(myStrategy.getBroker().getEquity(), myStrategy.getBroker().getCash(),
myStrategy.getBroker().getShares('orcl')))
myStrategy.totalEnd()
# myStrategy.info("Final portfolio value: $%.2f" % myStrategy.getResult())
# Plot the strategy.
plt.plot()
print(myStrategy.getJSL())
def testStrategy():
strat = thrSMA
instrument = '600288'
market = 'SH'
fromDate = '20150101'
toDate = '20150601'
frequency = bar.Frequency.MINUTE
plot = True
paras = [2, 20, 60, 10]
feeds = tushare.build_feed([instrument], 2016, 2017, "histdata/tushare")
strat = strat(feeds, instrument, *paras)
retAnalyzer = returns.Returns()
strat.attachAnalyzer(retAnalyzer)
sharpeRatioAnalyzer = sharpe.SharpeRatio()
strat.attachAnalyzer(sharpeRatioAnalyzer)
drawDownAnalyzer = drawdown.DrawDown()
strat.attachAnalyzer(drawDownAnalyzer)
tradesAnalyzer = trades.Trades()
strat.attachAnalyzer(tradesAnalyzer)
strat.run()
# 夏普率
sharp = sharpeRatioAnalyzer.getSharpeRatio(0.05)
# 最大回撤
maxdd = drawDownAnalyzer.getMaxDrawDown()
# 收益率
return_ = retAnalyzer.getCumulativeReturns()[-1]
# 收益曲线
return_list = []
for item in retAnalyzer.getCumulativeReturns():
return_list.append(item)
def testTwoBarReturns_OpenClose(self):
initialCash = 15.61
barFeed = yahoofeed.Feed()
barFeed.setBarFilter(
csvfeed.DateRangeFilter(datetime.datetime(2001, 12, 6),
datetime.datetime(2001, 12, 7)))
barFeed.addBarsFromCSV(
AnalyzerTestCase.TestInstrument,
common.get_data_file_path("orcl-2001-yahoofinance.csv"))
strat = strategy_test.MyTestStrategy(barFeed, initialCash)
# 2001-12-06,15.61,16.03,15.50,15.90,66944900,15.55
# 2001-12-07,15.74,15.95,15.55,15.91,42463200,15.56
# Manually place the entry order, to get it filled on the first bar.
order = strat.getBroker().createMarketOrder(
broker.Order.Action.BUY, AnalyzerTestCase.TestInstrument, 1,
False) # Open: 15.61
strat.getBroker().submitOrder(order)
strat.addOrder(datetime.datetime(2001, 12, 6),
strat.getBroker().createMarketOrder,
broker.Order.Action.SELL,
AnalyzerTestCase.TestInstrument, 1,
True) # Close: 15.91
stratAnalyzer = returns.Returns()
strat.attachAnalyzer(stratAnalyzer)
strat.run()
self.assertTrue(strat.getBroker().getCash() == initialCash +
(15.91 - 15.61))
# First day returns: Open vs Close
self.assertTrue(stratAnalyzer.getReturns()[0] == (15.90 - 15.61) /
15.61)
# Second day returns: Close vs Prev. day's close
self.assertTrue(stratAnalyzer.getReturns()[1] == (15.91 - 15.90) /
15.90)
from mooquant import plotter
from mooquant.analyzer import returns
from mooquant.tools import tushare
from samples import sma_crossover
if __name__ == '__main__':
instrument = '600016'
feeds = tushare.build_feed([instrument], 2016, 2018, './histdata/tushare')
strat = sma_crossover.SMACrossOver(feeds, instrument, 20)
# Attach a returns analyzers to the strategy.
returnsAnalyzer = returns.Returns()
strat.attachAnalyzer(returnsAnalyzer)
# Attach the plotter to the strategy.
plt = plotter.StrategyPlotter(strat)
# Include the SMA in the instrument's subplot to get it displayed along with the closing prices.
plt.getInstrumentSubplot("orcl").addDataSeries("SMA", strat.getSMA())
# Plot the simple returns on each bar.
plt.getOrCreateSubplot("returns").addDataSeries("Simple returns", returnsAnalyzer.getReturns())
# Run the strategy.
strat.run()
strat.info("Final portfolio value: $%.2f" % strat.getResult())
# Plot the strategy.
plt.plot()
def testStrategy():
from mooquant import bar
from mooquant import plotter
strat = fourSMA
instrument = '600288'
market = 'SH'
fromDate = '20150101'
toDate = '20150601'
frequency = bar.Frequency.MINUTE
paras = [2, 20, 60, 10]
plot = True
# path set ############################33
# if frequency == bar.Frequency.MINUTE:
# path = os.path.join('..', 'histdata', 'minute')
# elif frequency == bar.Frequency.DAY:
# path = os.path.join('..', 'histdata', 'day')
# filepath = os.path.join(path, instrument + market + ".csv")
# don't change ############################33
# barfeed = Feed(frequency)
# barfeed.setDateTimeFormat('%Y-%m-%d %H:%M:%S')
# barfeed.loadBars(instrument, market, fromDate, toDate, filepath)
# mooquant_id = instrument + '.' + market
# strat = strat(barfeed, mooquant_id, *paras)
from mooquant.tools import tushare
feeds = tushare.build_feed([instrument], 2016, 2017, "histdata/tushare")
strat = strat(feeds, instrument, *paras)
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(0.05)
# 最大回撤
maxdd = drawDownAnalyzer.getMaxDrawDown()
# 收益率
return_ = retAnalyzer.getCumulativeReturns()[-1]
# 收益曲线
return_list = []
for item in retAnalyzer.getCumulativeReturns():
return_list.append(item)
