def testIGE_BrokerWithCommission(self):
commision = 0.5
initialCash = 42.09 + commision
# This testcase is based on an example from Ernie Chan's book:
# 'Quantitative Trading: How to Build Your Own Algorithmic Trading Business'
barFeed = yahoofeed.Feed()
barFeed.addBarsFromCSV(
"ige", common.get_data_file_path("sharpe-ratio-test-ige.csv"))
strat = strategy_test.TestStrategy(barFeed, initialCash)
strat.getBroker().setCommission(backtesting.FixedPerTrade(commision))
strat.getBroker().setUseAdjustedValues(True)
strat.setBrokerOrdersGTC(True)
stratAnalyzer = sharpe.SharpeRatio()
strat.attachAnalyzer(stratAnalyzer)
# Manually place the order to get it filled on the first bar.
order = strat.getBroker().createMarketOrder(broker.Order.Action.BUY,
"ige", 1,
True) # Adj. Close: 42.09
order.setGoodTillCanceled(True)
strat.getBroker().placeOrder(order)
strat.addOrder(strategy_test.datetime_from_date(2007, 11, 13),
strat.getBroker().createMarketOrder,
broker.Order.Action.SELL, "ige", 1,
True) # Adj. Close: 127.64
strat.run()
self.assertTrue(
round(strat.getBroker().getCash(), 2) == initialCash +
(127.64 - 42.09 - commision * 2))
self.assertTrue(strat.getOrderUpdatedEvents() == 4)
# The results are slightly different only because I'm taking into account the first bar as well,
# and I'm also adding commissions.
self.assertEqual(round(stratAnalyzer.getSharpeRatio(0.04, True), 6),
0.776443)
def testTwoBarReturns_CloseClose(self):
initialCash = 15.90
barFeed = yahoofeed.Feed()
barFeed.setBarFilter(
csvfeed.DateRangeFilter(datetime.datetime(2001, 12, 06),
datetime.datetime(2001, 12, 07)))
barFeed.addBarsFromCSV(
AnalyzerTestCase.TestInstrument,
common.get_data_file_path("orcl-2001-yahoofinance.csv"))
strat = strategy_test.TestStrategy(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,
True) # Close: 15.90
strat.getBroker().submitOrder(order)
strat.addOrder(datetime.datetime(2001, 12, 06),
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 - 15.90))
# First day returns: 0
self.assertTrue(stratAnalyzer.getReturns()[0] == 0)
# Second day returns: Open vs Prev. day's close
self.assertTrue(stratAnalyzer.getReturns()[1] == (15.91 - 15.90) /
15.90)
def main():
# Load the orders file.
ordersFile = OrdersFile("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") == 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, 252))
def turtle_test(dataString='pyalg'):
"""
:param dataString:
:return:
"""
feed = yahoofeed.Feed()
feed.addBarsFromCSV("orcl", "../../api/stock/csv/orcl-2000.csv") #注意查看该csv的格式，Open为大写
myStrategy = pdr.turtle(feed, "orcl", 20, 10)
# Attach a returns analyzers to the trategy.
returnsAnalyzer = returns.Returns()
myStrategy.attachAnalyzer(returnsAnalyzer)
# Attach the plotter to the strategy.
plt = plotter.StrategyPlotter(myStrategy)
# Plot the simple returns on each bar.
plt.getOrCreateSubplot("returns").addDataSeries("Simple returns", returnsAnalyzer.getReturns())
if dataString == 'pyalg_util':
ds = pyalg_utils.dataSet(myStrategy) # 抽取交易数据集语句，若使用系统自带画图功能则不需要该项
myStrategy.run()
myStrategy.info("Final portfolio value: $%.2f" % myStrategy.getResult())
if dataString == 'pyalg_util':
rs = ds.getDefault() # 获取默认的交易信息，dic格式
plot(rs["cumulativeReturns"][:, 0], rs["cumulativeReturns"][:, 1]) # 简单作图示例
plt.plot()
def build_feed(instruments,
fromYear,
toYear,
storage,
frequency=bar.Frequency.DAY,
timezone=None,
skipErrors=False):
logger = pyalgotrade.logger.getLogger("yahoofinance")
ret = yahoofeed.Feed(frequency, timezone)
if not os.path.exists(storage):
logger.info("Creating %s directory" % (storage))
os.mkdir(storage)
for year in range(fromYear, toYear + 1):
for instrument in instruments:
fileName = os.path.join(
storage, "%s-%d-yahoofinance.csv" % (instrument, year))
if not os.path.exists(fileName):
logger.info("Downloading %s %d to %s" %
(instrument, year, fileName))
try:
if frequency == bar.Frequency.DAY:
download_daily_bars(instrument, year, fileName)
elif frequency == bar.Frequency.WEEK:
download_weekly_bars(instrument, year, fileName)
else:
raise Exception("Invalid frequency")
except Exception, e:
if skipErrors:
logger.error(str(e))
continue
else:
raise e
ret.addBarsFromCSV(instrument, fileName)
def __testIGE_BrokerImpl(self, quantity):
initialCash = 42.09 * quantity
# This testcase is based on an example from Ernie Chan's book:
# 'Quantitative Trading: How to Build Your Own Algorithmic Trading Business'
barFeed = yahoofeed.Feed()
barFeed.addBarsFromCSV(
"ige", common.get_data_file_path("sharpe-ratio-test-ige.csv"))
strat = strategy_test.TestStrategy(barFeed, initialCash)
strat.setUseAdjustedValues(True)
strat.setBrokerOrdersGTC(True)
stratAnalyzer = sharpe.SharpeRatio()
strat.attachAnalyzer(stratAnalyzer)
# Disable volume checks to match book results.
strat.getBroker().getFillStrategy().setVolumeLimit(None)
# Manually place the order to get it filled on the first bar.
order = strat.getBroker().createMarketOrder(broker.Order.Action.BUY,
"ige", quantity,
True) # Adj. Close: 42.09
order.setGoodTillCanceled(True)
strat.getBroker().submitOrder(order)
strat.addOrder(datetime.datetime(2007, 11, 13),
strat.getBroker().createMarketOrder,
broker.Order.Action.SELL, "ige", quantity,
True) # Adj. Close: 127.64
strat.run()
self.assertEqual(round(strat.getBroker().getCash(), 2),
initialCash + (127.64 - 42.09) * quantity)
self.assertEqual(strat.orderUpdatedCalls, 6)
# The results are slightly different only because I'm taking into account the first bar as well.
self.assertEqual(round(stratAnalyzer.getSharpeRatio(0.04, True), 4),
0.7889)
self.assertEqual(round(stratAnalyzer.getSharpeRatio(0.04, False), 4),
0.0497)
def __testIGE_BrokerImpl(self, quantity):
initialCash = 42.09*quantity
# This testcase is based on an example from Ernie Chan's book:
# 'Quantitative Trading: How to Build Your Own Algorithmic Trading Business'
barFeed = yahoofeed.Feed()
barFeed.addBarsFromCSV("ige", common.get_data_file_path("sharpe-ratio-test-ige.csv"))
strat = strategy_test.TestStrategy(barFeed, initialCash)
strat.setUseAdjustedValues(True)
strat.setBrokerOrdersGTC(True)
stratAnalyzer = drawdown.DrawDown()
strat.attachAnalyzer(stratAnalyzer)
# Disable volume checks to match book results.
strat.getBroker().getFillStrategy().setVolumeLimit(None)
# Manually place the order to get it filled on the first bar.
order = strat.getBroker().createMarketOrder(broker.Order.Action.BUY, "ige", quantity, True) # Adj. Close: 42.09
order.setGoodTillCanceled(True)
strat.getBroker().submitOrder(order)
strat.addOrder(datetime.datetime(2007, 11, 13), strat.getBroker().createMarketOrder, broker.Order.Action.SELL, "ige", quantity, True) # Adj. Close: 127.64
strat.run()
self.assertTrue(round(strat.getBroker().getCash(), 2) == initialCash + (127.64 - 42.09) * quantity)
self.assertEqual(strat.orderUpdatedCalls, 6)
self.assertTrue(round(stratAnalyzer.getMaxDrawDown(), 5) == 0.31178)
self.assertTrue(stratAnalyzer.getLongestDrawDownDuration() == datetime.timedelta(days=623))
def __test(self, strategyClass, finalValue):
feed = yahoofeed.Feed()
feed.addBarsFromCSV("orcl", common.get_data_file_path("orcl-2001-yahoofinance.csv"))
myStrategy = strategyClass(feed, 10, 25)
myStrategy.run()
myStrategy.printDebug("Final result:", round(myStrategy.getFinalValue(), 2))
self.assertTrue(round(myStrategy.getFinalValue(), 2) == finalValue)
def testBaseBarFeed(self):
barFeed = yahoofeed.Feed()
barFeed.sanitizeBars(True)
barFeed.addBarsFromCSV(
FeedTestCase.TestInstrument,
common.get_data_file_path("orcl-2000-yahoofinance.csv"))
barfeed_test.check_base_barfeed(self, barFeed, True)
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.TestStrategy(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 __getFeed(self):
# Load the feed and process all bars.
barFeed = yahoofeed.Feed()
barFeed.addBarsFromCSV(
INSTRUMENT,
common.get_data_file_path("orcl-2001-yahoofinance.csv"))
return barFeed
def main(plot):
cod = "002739"
#万达院线
cname = 'wanda'
fss = "dat\\" + cod + ".csv"
df = pd.read_csv(fss, encoding='gbk')
#df2=zwBox.zw_df2yhaoo(df);
df2 = zwx.df2yhaoo(df)
cfn = "dat\\" + cod + "_yh.csv"
print(fss)
df2.to_csv(cfn, encoding='utf-8')
#
#instrument = "aapl" #使用新变量名cname替代
vwapWindowSize = 5
threshold = 0.01
# Download the bars.
#feed = yahoofinance.build_feed([cname], 2011, 2012, ".")
feed = yahoofeed.Feed()
feed.addBarsFromCSV(cname, cfn)
strat = VWAPMomentum(feed, cname, vwapWindowSize, threshold)
sharpeRatioAnalyzer = sharpe.SharpeRatio()
strat.attachAnalyzer(sharpeRatioAnalyzer)
if plot:
plt = plotter.StrategyPlotter(strat, True, False, True)
plt.getInstrumentSubplot(cname).addDataSeries("vwap", strat.getVWAP())
strat.run()
print "夏普指数 Sharpe ratio: %.2f" % sharpeRatioAnalyzer.getSharpeRatio(0.05)
if plot:
plt.plot()
def testBounded(self):
tmpFeed = TemporarySQLiteFeed(SQLiteFeedTestCase.dbName,
bar.Frequency.DAY,
maxLen=2)
with tmpFeed:
# Load bars using a Yahoo! feed.
yahooFeed = yahoofeed.Feed(maxLen=1)
yahooFeed.addBarsFromCSV(
"orcl",
common.get_data_file_path("orcl-2000-yahoofinance.csv"),
marketsession.USEquities.timezone)
yahooFeed.addBarsFromCSV(
"orcl",
common.get_data_file_path("orcl-2001-yahoofinance.csv"),
marketsession.USEquities.timezone)
# Fill the database using the bars from the Yahoo! feed.
sqliteFeed = tmpFeed.getFeed()
sqliteFeed.getDatabase().addBarsFromFeed(yahooFeed)
# Load the SQLite feed and process all bars.
sqliteFeed.loadBars("orcl")
for bars in sqliteFeed:
pass
barDS = sqliteFeed["orcl"]
self.assertEqual(len(barDS), 2)
self.assertEqual(len(barDS.getDateTimes()), 2)
self.assertEqual(len(barDS.getCloseDataSeries()), 2)
self.assertEqual(len(barDS.getCloseDataSeries().getDateTimes()), 2)
self.assertEqual(len(barDS.getOpenDataSeries()), 2)
self.assertEqual(len(barDS.getHighDataSeries()), 2)
self.assertEqual(len(barDS.getLowDataSeries()), 2)
self.assertEqual(len(barDS.getAdjCloseDataSeries()), 2)
def testLoadDailyBars(self):
tmpFeed = TemporarySQLiteFeed(SQLiteFeedTestCase.dbName, barfeed.Frequency.DAY)
with tmpFeed:
# Load bars using a Yahoo! feed.
yahooFeed = yahoofeed.Feed()
yahooFeed.addBarsFromCSV("orcl", common.get_data_file_path("orcl-2000-yahoofinance.csv"), marketsession.USEquities.timezone)
yahooFeed.addBarsFromCSV("orcl", common.get_data_file_path("orcl-2001-yahoofinance.csv"), marketsession.USEquities.timezone)
# Fill the database using the bars from the Yahoo! feed.
sqliteFeed = tmpFeed.getFeed()
sqliteFeed.getDatabase().addBarsFromFeed(yahooFeed)
# Load the SQLite feed and process all bars.
sqliteFeed.loadBars("orcl")
for bars in sqliteFeed:
pass
# Check that both dataseries have the same bars.
yahooDS = yahooFeed["orcl"]
sqliteDS = sqliteFeed["orcl"]
self.assertEqual(len(yahooDS), len(sqliteDS))
for i in xrange(len(yahooDS)):
self.assertEqual(yahooDS[i].getDateTime(), sqliteDS[i].getDateTime())
self.assertEqual(yahooDS[i].getOpen(), sqliteDS[i].getOpen())
self.assertEqual(yahooDS[i].getHigh(), sqliteDS[i].getHigh())
self.assertEqual(yahooDS[i].getLow(), sqliteDS[i].getLow())
self.assertEqual(yahooDS[i].getClose(), sqliteDS[i].getClose())
self.assertEqual(yahooDS[i].getAdjClose(), sqliteDS[i].getAdjClose())
self.assertEqual(yahooDS[i].getBarsTillSessionClose(), sqliteDS[i].getBarsTillSessionClose())
self.assertEqual(yahooDS[i].getSessionClose(), sqliteDS[i].getSessionClose())
def main(plot):
instrument = "yhoo"
bBandsPeriod = 40
# Download the bars.
# feed = yahoofinance.build_feed([instrument], 2011, 2012, ".")
feed = yahoofeed.Feed()
feed.addBarsFromCSV(instrument, "dat\\yhoo-201x.csv")
strat = BBands(feed, instrument, bBandsPeriod)
sharpeRatioAnalyzer = sharpe.SharpeRatio()
strat.attachAnalyzer(sharpeRatioAnalyzer)
if plot:
mpl.style.use('seaborn-whitegrid')
plt = plotter.StrategyPlotter(strat, True, True, True)
plt.getInstrumentSubplot(instrument).addDataSeries(
"upper",
strat.getBollingerBands().getUpperBand())
plt.getInstrumentSubplot(instrument).addDataSeries(
"middle",
strat.getBollingerBands().getMiddleBand())
plt.getInstrumentSubplot(instrument).addDataSeries(
"lower",
strat.getBollingerBands().getLowerBand())
strat.run()
print("Sharpe ratio: %.2f" % sharpeRatioAnalyzer.getSharpeRatio(0.05))
if plot:
plt.plot()
def write_intermediate_csv(instrument, csvFiles, csvToUpload):
csvToUpload.write("key,instrument,barType,dateTime,open_,close_,high,low,volume,adjClose\n")
instrument = instrument.upper()
barType = 1
feed = yahoofeed.Feed()
for csvFile in csvFiles:
print "Loading bars from %s" % csvFile
feed.addBarsFromCSV(instrument, csvFile)
print "Writing intermediate csv into %s" % csvToUpload.name
for dateTime, bars in feed:
bar = bars[instrument]
csvToUpload.write("%s,%s,%d,%s,%s,%s,%s,%s,%s,%s\n" % (
gen_bar_key(instrument, barType, bar),
instrument,
barType,
datetimeToCSV(bar.getDateTime()),
bar.getOpen(),
bar.getClose(),
bar.getHigh(),
bar.getLow(),
bar.getVolume(),
bar.getAdjClose()
))
csvToUpload.flush()
def __getFeed(self):
# Load the feed and process all bars.
barFeed = yahoofeed.Feed()
barFeed.addBarsFromCSV(
VWAPTestCase.Instrument,
common.get_data_file_path("orcl-2001-yahoofinance.csv"))
return barFeed
def __init__(self, start=None, end=None):
''' load all the ashare feed'''
project_root_dir = os.path.dirname(
os.path.dirname(os.path.abspath(__file__)))
data_root_dir = os.path.join(project_root_dir, "data", "history")
feed = yahoofeed.Feed()
for _, _, filenames in os.walk(data_root_dir):
for filename in filenames:
if os.path.splitext(filename)[1] == '.csv':
stock_code = os.path.splitext(filename)[0]
csvfile = os.path.join(data_root_dir, filename)
feed.addBarsFromCSV(stock_code, csvfile)
strategy.BacktestingStrategy.__init__(self, feed)
self.setUseAdjustedValues(True)
self._feed = self.getFeed()
self._universe = []
self._start_date = None
self._end_date = None
if start is not None:
self._start_date = datetime.datetime.strptime(start, '%Y-%m-%d')
if end is not None:
self._end_date = datetime.datetime.strptime(end, '%Y-%m-%d')
self.__instruments = self._feed.getRegisteredInstruments()
self.__sma = {}
self.__prices = {}
self.__position = {}
'add the techical indectitor to the feed'
for instrument in self.__instruments:
self.__sma[instrument] = ma.SMA(
self._feed[instrument].getCloseDataSeries(), 15)
self.__prices[instrument] = self._feed[
instrument].getPriceDataSeries()
self.__position[instrument] = None
def testResampledBarFeed(self):
barFeed = yahoofeed.Feed()
barFeed.addBarsFromCSV(
"spy", common.get_data_file_path("spy-2010-yahoofinance.csv"))
barFeed.addBarsFromCSV(
"nikkei",
common.get_data_file_path("nikkei-2010-yahoofinance.csv"))
resampledBarFeed = resampled_bf.ResampledBarFeed(
barFeed, bar.Frequency.MONTH)
disp = dispatcher.Dispatcher()
disp.addSubject(barFeed)
disp.addSubject(resampledBarFeed)
disp.run()
weeklySpyBarDS = resampledBarFeed["spy"]
weeklyNikkeiBarDS = resampledBarFeed["nikkei"]
# Check first bar
self.assertEqual(weeklySpyBarDS[0].getDateTime().date(),
datetime.date(2010, 1, 1))
self.assertEqual(weeklyNikkeiBarDS[0].getDateTime().date(),
datetime.date(2010, 1, 1))
# Check last bar
self.assertEqual(weeklySpyBarDS[-1].getDateTime().date(),
datetime.date(2010, 11, 1))
self.assertEqual(weeklyNikkeiBarDS[-1].getDateTime().date(),
datetime.date(2010, 11, 1))
def main(plot):
instruments = ["gld/USD", "gdx/USD"]
priceCurrency = "USD"
initialBalance = {priceCurrency: 1000000}
windowSize = 50
# Load the bars. These files were manually downloaded from Yahoo Finance.
feed = yahoofeed.Feed()
for year in range(2006, 2012 + 1):
for instrument in instruments:
symbol = instrument.split("/")[0]
fileName = "%s-%d-yahoofinance.csv" % (symbol, year)
print("Loading bars from %s" % fileName)
feed.addBarsFromCSV(instrument, fileName)
strat = StatArb(feed, instruments[0], instruments[1], initialBalance,
windowSize)
sharpeRatioAnalyzer = sharpe.SharpeRatio(priceCurrency)
strat.attachAnalyzer(sharpeRatioAnalyzer)
if plot:
from pyalgotrade import plotter
plt = plotter.StrategyPlotter(strat, False, False, True)
plt.getOrCreateSubplot("hedge").addDataSeries("Hedge Ratio",
strat.getHedgeRatioDS())
plt.getOrCreateSubplot("spread").addDataSeries("Spread",
strat.getSpreadDS())
strat.run()
print("Sharpe ratio: %.2f" % sharpeRatioAnalyzer.getSharpeRatio(0.05))
if plot:
plt.plot()
def runStrategy():
# 下载数据
jdf = ts.get_k_data("000725")
# 新建Adj Close字段
jdf["Adj Close"] = jdf.close
# 将tushare下的数据的字段保存为pyalgotrade所要求的数据格式
jdf.columns = [
"Date", "Open", "Close", "High", "Low", "Volume", "code", "Adj Close"
]
# 将数据保存成本地csv文件
jdf.to_csv("jdf.csv", index=False)
feed = yahoofeed.Feed()
feed.addBarsFromCSV("jdf", "jdf.csv")
myStrategy = MyStrategy(feed, "jdf")
returnsAnalyzer = returns.Returns()
myStrategy.attachAnalyzer(returnsAnalyzer)
plt = plotter.StrategyPlotter(myStrategy)
plt.getInstrumentSubplot("jdf")
plt.getOrCreateSubplot("returns").addDataSeries(
"Simple returns", returnsAnalyzer.getReturns())
myStrategy.run()
print("Final portfolio value: $%.2f" % myStrategy.getResult())
plt.plot()
def testLocal(self):
barFeed = yahoofeed.Feed()
instrument = "orcl"
barFeed.addBarsFromCSV(instrument, common.get_data_file_path("orcl-2000-yahoofinance.csv"))
res = local.run(sma_crossover.SMACrossOver, barFeed, parameters_generator(instrument, 5, 100))
self.assertEquals(round(res.getResult(), 2), 1295462.6)
self.assertEquals(res.getParameters()[1], 20)
def run_strategy(index, startYear, endYear, smaShort, smaLong):
# Load the yahoo feed from the CSV file
feed = yahoofeed.Feed()
feed.sanitizeBars(True)
for year in range(startYear, endYear):
feed.addBarsFromCSV(index,
"./data/" + index + "-" + str(year) + ".csv")
myStrategy = MyStrategy(feed, index, smaShort, smaLong)
myStrategy.run()
# Important! Otherwise the Benchmark won't run (nor fail)
feed.reset()
myBenchmark = MyBenchmark(feed, index, smaShort, smaLong)
myBenchmark.run()
retStrategy = myStrategy.getBroker().getEquity()
retBenchmark = myBenchmark.getBroker().getEquity()
return [
str(startYear) + "-" + str(endYear), retStrategy, retBenchmark,
(retStrategy - retBenchmark)
]
def main(plot):
#--------数据格式转换，常用国内A股数据，转换为yahoo财经格式
cod = "002739"
#万达院线
cname = 'wanda'
fss = "dat\\" + cod + ".csv"
df = pd.read_csv(fss, encoding='gbk')
df2 = zwx.df2yhaoo(df)
cfn = "dat\\" + cod + "_yh.csv"
print(fss)
df2.to_csv(cfn, encoding='utf-8')
#------------
#instrument = "aapl",使用新变量名cname替代
#smaPeriod = 163
smaPeriod = 20
# Download the bars.
#feed = yahoofinance.build_feed([instrument], 2011, 2012, ".")
feed = yahoofeed.Feed()
feed.addBarsFromCSV(cname, cfn)
strat = sma_crossover.SMACrossOver(feed, cname, smaPeriod)
sharpeRatioAnalyzer = sharpe.SharpeRatio()
strat.attachAnalyzer(sharpeRatioAnalyzer)
if plot:
plt = plotter.StrategyPlotter(strat, True, False, True)
plt.getInstrumentSubplot(cname).addDataSeries("sma", strat.getSMA())
strat.run()
print("夏普指数 Sharpe ratio: %.2f" % sharpeRatioAnalyzer.getSharpeRatio(0.05))
if plot:
plt.plot()
def testOneBarReturn(self):
initialCash = 1000
barFeed = yahoofeed.Feed()
barFeed.setBarFilter(
csvfeed.DateRangeFilter(datetime.datetime(2001, 12, 07),
datetime.datetime(2001, 12, 07)))
barFeed.addBarsFromCSV(
AnalyzerTestCase.TestInstrument,
common.get_data_file_path("orcl-2001-yahoofinance.csv"))
strat = strategy_test.TestStrategy(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(plot):
instrument = "DIA"
entrySMA = 200
exitSMA = 5
rsiPeriod = 2
overBoughtThreshold = 90
overSoldThreshold = 10
# Download the bars.
#feed = yahoofinance.build_feed([instrument], 2009, 2012, ".")
feed = yahoofeed.Feed()
feed.addBarsFromCSV(instrument, "dat\\dia-201x.csv")
strat = rsi2.RSI2(feed, instrument, entrySMA, exitSMA, rsiPeriod,
overBoughtThreshold, overSoldThreshold)
sharpeRatioAnalyzer = sharpe.SharpeRatio()
strat.attachAnalyzer(sharpeRatioAnalyzer)
if plot:
plt = plotter.StrategyPlotter(strat, True, False, True)
plt.getInstrumentSubplot(instrument).addDataSeries(
"Entry SMA", strat.getEntrySMA())
plt.getInstrumentSubplot(instrument).addDataSeries(
"Exit SMA", strat.getExitSMA())
plt.getOrCreateSubplot("rsi").addDataSeries("RSI", strat.getRSI())
plt.getOrCreateSubplot("rsi").addLine("Overbought",
overBoughtThreshold)
plt.getOrCreateSubplot("rsi").addLine("Oversold", overSoldThreshold)
strat.run()
print "Sharpe ratio: %.2f" % sharpeRatioAnalyzer.getSharpeRatio(0.05)
if plot:
plt.plot()
def testFirstBar(self):
initialCash = 1000
barFeed = yahoofeed.Feed()
barFeed.addBarsFromCSV(
AnalyzerTestCase.TestInstrument,
common.get_data_file_path("orcl-2001-yahoofinance.csv"))
strat = strategy_test.TestStrategy(barFeed, initialCash)
strat.addOrder(datetime.datetime(2001, 01, 02),
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 vwap(plot):
"""
组合管理示例
:param plot:
:return:
"""
instrument = ["lenovo", "mi"]
vwapWindowSize = 5
threshold = 0.01
# Download the bars.
feed = yahoofeed.Feed()
feed.addBarsFromCSV("lenovo", "../../api/stock/csv/600847.csv")
feed.addBarsFromCSV("mi", "../../api/stock/csv/600848.csv")
strat = pdr.VWAPMomentum(feed, instrument, vwapWindowSize, threshold)
sharpeRatioAnalyzer = sharpe.SharpeRatio()
strat.attachAnalyzer(sharpeRatioAnalyzer)
if plot:
plt = plotter.StrategyPlotter(strat, True, True, True)
# plt.getPortfolioSubplot().addDataSeries("vwap", strat.getVWAP()[instrument[-1]])
ds = pyalg_utils.dataSet(strat) # 抽取交易数据集语句，若使用系统自带画图功能则不需要该项
strat.run()
print("Sharpe ratio: %.2f" % sharpeRatioAnalyzer.getSharpeRatio(0.05))
if plot:
plt.plot()
rs = ds.getReturns() # 获取默认的交易信息，dic格式,可忽略
def run_strategy(smaPeriod):
feed = yahoofeed.Feed()
feed.addBarsFromCSV("fb", "fb.csv")
myStrategy = MyStrategy(feed, "fb", smaPeriod)
myStrategy.run()
print "Final portfolio value: $%.2f" % myStrategy.getBroker().getEquity()
def testSetSharesWithNoStartingCash(self):
barFeed = yahoofeed.Feed()
barFeed.addBarsFromCSV(
AnalyzerTestCase.TestInstrument,
common.get_data_file_path("orcl-2001-yahoofinance.csv"))
strat = test_strategy.BacktestingStrategy(barFeed, 0)
initialShares = 2
initialPrice = 16.25
strat.getBroker().setShares(AnalyzerTestCase.TestInstrument,
initialShares, initialPrice)
# Close initial position
closingPrice = 32.50
strat.scheduleCall(
datetime.datetime(2001, 1, 4), lambda: strat.marketOrder(
AnalyzerTestCase.TestInstrument, -initialShares))
stratAnalyzer = returns.Returns()
strat.attachAnalyzer(stratAnalyzer)
strat.run()
self.assertEqual(
strat.getBroker().getShares(AnalyzerTestCase.TestInstrument), 0)
self.assertEqual(strat.getBroker().getCash(),
closingPrice * initialShares)
# Check period returns.
expectedPeriodReturns = [
(26.37 - initialPrice) / initialPrice,
(32.00 - 26.37) / 26.37,
(32.56 - 32.00) / 32.00,
(32.50 - 32.56) / 32.56,
0,
# Nothing should change moving forward
0,
0,
]
for i, expectedReturn in enumerate(expectedPeriodReturns):
self.assertEqual(stratAnalyzer.getReturns()[i], expectedReturn)
self.assertEqual(stratAnalyzer.getReturns()[-1],
expectedPeriodReturns[-1])
# Check cumulative returns.
expectedCumulativeReturns = [
(26.37 - initialPrice) / initialPrice,
(32.00 - initialPrice) / initialPrice,
(32.56 - initialPrice) / initialPrice,
(32.50 - initialPrice) / initialPrice,
# Nothing should change moving forward
(32.50 - initialPrice) / initialPrice,
(32.50 - initialPrice) / initialPrice,
]
for i, expectedReturn in enumerate(expectedCumulativeReturns):
self.assertEqual(round(stratAnalyzer.getCumulativeReturns()[i], 4),
round(expectedReturn, 4))
self.assertEqual(round(stratAnalyzer.getCumulativeReturns()[-1], 4),
round(expectedCumulativeReturns[-1], 4))
