def main(plot):
initialCash = 10000
instrumentsByClass = {
"US Stocks": ["VTI"],
"Foreign Stocks": ["VEU"],
"US 10 Year Government Bonds": ["IEF"],
"Real Estate": ["VNQ"],
"Commodities": ["DBC"],
}
# Download the bars.
instruments = ["SPY"]
for assetClass in instrumentsByClass:
instruments.extend(instrumentsByClass[assetClass])
feed = yahoofinance.build_feed(instruments, 2007, 2013, "data", skipErrors=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()
def main(plot):
initialCash = 10000
instrumentsByClassMain = {
"Atlantic American Corporation": ["AAOI"],
"Applied Optoelectronics, Inc.": ["AAON"],
"AAON, Inc.": ["AAPC"],
"Atlantic Alliance Partnership Corp. Ordinary Sh": ["AAPL"],
"Apple Inc.": ["AAWW"],
"Atlas Air Worldwide Holdings": ["AAXJ"],
"iShares MSCI All Country Asia ex Japan Index ": ["ABAC"],
"Aoxin Tianli Group, Inc. Common Sh": ["ABAX"],
"ABAXIS, Inc.": ["ABCB"],
"Ameris Bancorp": ["ABCD"],
"Cambium Learning Group, Inc.": ["ABCO"],
"The Advisory Board Company": ["ABDC"],
"Alcentra Capital Corp.": ["ABEO"],
}
# Download the bars.
instruments = ["SPY"]
for assetClass in instrumentsByClass:
instruments.extend(instrumentsByClass[assetClass])
feed = yahoofinance.build_feed(instruments, 2010, 2016, "data", skipErrors=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)
print "Returns All: %.2f %%" % (returnsAnalyzer.getReturns()[-1] * 100)
# returnsAnalyzer.getCumulativeReturns()[-1] * 100
if plot:
plt.plot()
def testCumRet(self):
values = dataseries.SequenceDataSeries()
rets = cumret.CumulativeReturn(values)
for value in [1, 2, 3, 4, 4, 3, 1, 1.2]:
values.append(value)
self.assertEqual(rets[0], None)
self.assertEqual(rets[1], 1)
self.assertEqual(rets[2], 2)
self.assertEqual(rets[3], 3)
self.assertEqual(rets[4], 3)
self.assertEqual(rets[5], 2)
self.assertEqual(rets[6], 0)
self.assertEqual(round(rets[7], 1), 0.2)
def main(plot):
priceCurrency = "USD"
instrumentsByClass = {
"US Stocks": ["VTI/USD"],
"Foreign Stocks": ["VEU/USD"],
"US 10 Year Government Bonds": ["IEF/USD"],
"Real Estate": ["VNQ/USD"],
"Commodities": ["DBC/USD"],
}
# Load the bars. These files were manually downloaded from Yahoo Finance.
feed = yahoofeed.Feed()
instruments = ["SPY/USD"] + sum(instrumentsByClass.values(), [])
for year in range(2007, 2013 + 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)
broker = backtesting.Broker({priceCurrency: 10000}, feed)
# Build the strategy and attach some metrics.
strat = MarketTiming(feed, broker, instrumentsByClass, priceCurrency)
sharpeRatioAnalyzer = sharpe.SharpeRatio(priceCurrency)
strat.attachAnalyzer(sharpeRatioAnalyzer)
returnsAnalyzer = returns.Returns(priceCurrency)
strat.attachAnalyzer(returnsAnalyzer)
if plot:
from pyalgotrade import plotter
plt = plotter.StrategyPlotter(strat, False, False, True)
plt.getOrCreateSubplot("cash").addCallback(
"Cash", lambda x: strat.getBroker().getBalance("USD"))
# 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 = {
"US Stocks": ["VTI"],
"Foreign Stocks": ["VEU"],
"US 10 Year Government Bonds": ["IEF"],
"Real Estate": ["VNQ"],
"Commodities": ["DBC"],
}
# Load the bars. These files were manually downloaded from Yahoo Finance.
feed = yahoofeed.Feed()
instruments = ["SPY"]
for assetClass in instrumentsByClass:
instruments.extend(instrumentsByClass[assetClass])
for year in range(2007, 2013 + 1):
for instrument in instruments:
fileName = "%s-%d-yahoofinance.csv" % (instrument, year)
print("Loading bars from %s" % fileName)
feed.addBarsFromCSV(instrument, fileName)
# Build the strategy and attach some metrics.
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()
def main(plot, sz50, HQ, HQ_hs300):
initialCash = 10000000
sz50_code = sz50['code']
feed = dataFramefeed.Feed()
feed.addBarsFromDataFrame("hs300", HQ_hs300)
instrumentsByClass = {}
for i in range(0, len(sz50_code)):
l = []
l.append(sz50_code[i])
instrumentsByClass[sz50_code[i]] = l
feed.addBarsFromDataFrame(sz50_code[i], HQ[sz50_code[i]])
HQ['600000']
'''
instrumentsByClass = {
"002768": ["002768"],
"002493": ["002493"]
}
# 这里instruments暂时没用 instrumentsByClass是portfolio
instruments = ['hs300']
for assetClass in instrumentsByClass:
instruments.extend(instrumentsByClass[assetClass])
##feed 是dataFramefeed模块Feed类的一个实例，Feed继承DataFrameBarfeed.BarFeed，BarFeed继承membf.BarFeed
feed = dataFramefeed.Feed()
dat=ts.get_hist_data("hs300",start='2017-01-01',end='2017-12-27')
dat['Adj Close']=dat['close']
feed.addBarsFromDataFrame("hs300", dat.ix[:,(0,1,2,3,4,13)])
dat=ts.get_hist_data("002768",start='2017-01-01',end='2017-12-27')
dat['Adj Close']=dat['close']
feed.addBarsFromDataFrame("002768", dat.ix[:,(0,1,2,3,4,14)])
dat=ts.get_hist_data('002493',start='2017-01-01',end='2017-12-27')
dat['Adj Close']=dat['close']
feed.addBarsFromDataFrame("002493", dat.ix[:,(0,1,2,3,4,14)])
'''
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())
#plt.getOrCreateSubplot("cash").addCallback("Cash", strat.getBroker().getCash())
# Plot strategy vs. benchmark HS300 cumulative returns.
plt.getOrCreateSubplot("returns").addDataSeries(
"hs300",
cumret.CumulativeReturn(feed["hs300"].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()