def __init__(self,
instruments,
initialCash,
fromYear,
toYear,
debugMode=True,
csvStorage="./googlefinance",
filterInvalidRows=True):
self.__logger = logger.getLogger(GoogleFinanceBacktest.LOGGER_NAME)
self.__finalPortfolioValue = 0
# Create Feed
self.__feed = googlefeed.Feed()
rowFilter = lambda row: row["Close"] == "-" or row["Open"] == "-" or row["High"] == "-" or row["Low"] == "-" or \
row["Volume"] == "-"
self.__feed = googlefinance.build_feed(
instruments,
fromYear,
toYear,
storage=csvStorage,
skipErrors=True,
rowFilter=rowFilter if filterInvalidRows else None)
# Create Broker
comissionModel = backtesting.FixedPerTrade(10)
self.__broker = backtesting.Broker(initialCash,
self.__feed,
commission=comissionModel)
self.__strategy = TradingSystem(self.__feed,
self.__broker,
debugMode=debugMode)
# Create Analyzers
returnsAnalyzer = returns.Returns()
self.__strategy.attachAnalyzer(returnsAnalyzer)
dailyResultsAnalyzer = DailyTradingResults()
self.__strategy.attachAnalyzer(dailyResultsAnalyzer)
self.__tradesAnalyzer = Trades()
self.__strategy.attachAnalyzer(self.__tradesAnalyzer)
# Create plotters
self.__plotters = []
self.__plotters.append(
plotter.StrategyPlotter(self.__strategy,
plotAllInstruments=False,
plotPortfolio=True,
plotBuySell=False))
self.__plotters[0].getOrCreateSubplot("returns").addDataSeries(
"Simple returns", returnsAnalyzer.getReturns())
self.__plotters[0].getOrCreateSubplot("dailyresult").addDataSeries(
"Daily Results", dailyResultsAnalyzer.getTradeResults())
for i in range(0, len(instruments)):
p = plotter.StrategyPlotter(self.__strategy,
plotAllInstruments=False,
plotPortfolio=False)
p.getInstrumentSubplot(instruments[i])
self.__plotters.append(p)
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 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 run_strategy(smaPeriod):
# Load the bar feed from the CSV file
feed = quandlfeed.Feed()
feed.addBarsFromCSV(
"orcl",
"D:/Develop/project/python/PycharmProjects/python3/pyalgotrade/samples/data/WIKI-ORCL-2011-quandl.csv"
)
# Evaluate the strategy with the feed's bars
myStratege = MyStrategy(feed, "orcl", smaPeriod)
# Attach a returns analyzer to to strategy
returnsAnalyzer = returns.Returns()
myStratege.attachAnalyzer(returnsAnalyzer)
# Attach the plotter to the strategy
plt = plotter.StrategyPlotter(myStratege)
# Include the SMA in the instrument's subplot to get it displayed along with the closing prices
plt.getInstrumentSubplot("orcl").addDataSeries("SMA",
myStratege.getSMA())
# Plot the simple returns on each bar
#plt.getOrCreateSubplot("returns").addDataSeries("Simple Returns", returnsAnalyzer.getReturns())
myStratege.run()
myStratege.info("Final portfolio value: $%.2f" %
myStratege.getBroker().getEquity())
# Plot the strategy
plt.plot()
def main(plot):
instrument = "btc"
vwapWindowSize = 20
# Download the bars.
# feed = yahoofinance.build_feed([instrument], 2011, 2012, ".")
feed = coinfeed.Feed()
# startDate = datetime.datetime.strptime("2014-04-06 11:47:42", "%Y-%m-%d %H:%M:%S")
# endDate = datetime.datetime.strptime("2014-04-10 11:47:42", "%Y-%m-%d %H:%M:%S")
# feed.setDateRange(startDate, endDate)
feed.addBarsFromCSV(instrument, "data/ticker.csv")
myStrategy = MyStrategy(feed, instrument, vwapWindowSize)
if plot:
# plt = plotter.StrategyPlotter(myStrategy, True, False, True)
plt = plotter.StrategyPlotter(myStrategy)
plt.getInstrumentSubplot(instrument).addDataSeries("vwap", myStrategy.getVWAPDS())
myStrategy.run()
print "Result: %.2f" % myStrategy.getResult()
if plot:
plt.plot()
def main(plot):
instrument = "bitmex_LTCZ18"
initialCash = 1000
vwapWindowSize = 100
buyThreshold = 0.02
sellThreshold = 0.01
# barFeed = csvfeed.GenericBarFeed(bar.Frequency.MINUTE*30)
# barFeed.addBarsFromCSV(instrument, "30min-bitstampUSD.csv")
feed = Feed(Frequency.SECOND)
feed.loadBars('bitmex_LTCZ18', test_back=True)
brk = broker.BacktestingBroker(initialCash, feed)
strat = VWAPMomentum(feed, brk, instrument, vwapWindowSize, buyThreshold,
sellThreshold)
if plot:
plt = plotter.StrategyPlotter(strat)
plt.getInstrumentSubplot(instrument).addDataSeries(
"VWAP", strat.getVWAP())
strat.run()
if plot:
plt.plot()
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 main(plot):
instrument = "FG0"
sma_Period = 40
# Download the bars.
# feed = yahoofinance.build_feed([instrument], 2011, 2012, ".")
csv_path = os.path.abspath(
'../histdata/commodity') + '/' + instrument + '.csv'
feed = sf.Feed()
feed.addBarsFromCSV(instrument, csv_path)
# feed = csvfeed.Feed('Date', )
strat = SMACrossOver(feed, instrument, sma_Period)
sharpeRatioAnalyzer = sharpe.SharpeRatio()
strat.attachAnalyzer(sharpeRatioAnalyzer)
if plot:
plt = plotter.StrategyPlotter(strat, True, True, True)
plt.getInstrumentSubplot(instrument).addDataSeries(
"sma", strat.getSMA())
# 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()
pass
def __init__(self, feed, instrument):
super(SimpleBacktestStrategy, self).__init__(feed)
self.initial_capital = self.getResult()
self.positions = {}
for symbol in instrument:
self.positions[symbol] = {}
retAnalyzer = returns.Returns()
self.attachAnalyzerEx(retAnalyzer, 'retAnalyzer')
sharpeRatioAnalyzer = sharpe.SharpeRatio()
self.attachAnalyzerEx(sharpeRatioAnalyzer, 'sharpeRatioAnalyzer')
drawDownAnalyzer = drawdown.DrawDown()
self.attachAnalyzerEx(drawDownAnalyzer, 'drawDownAnalyzer')
tradesAnalyzer = trades.Trades()
self.attachAnalyzerEx(tradesAnalyzer, 'tradesAnalyzer')
self.plt = plotter.StrategyPlotter(self)
self.plt.getOrCreateSubplot("returns").addDataSeries(
"Net return", retAnalyzer.getReturns())
self.plt.getOrCreateSubplot("returns").addDataSeries(
"Cum. return", retAnalyzer.getCumulativeReturns())
self.strategy_id = 'backtest'
if not os.path.exists(self.strategy_id + '.csv'):
with open(self.strategy_id + '.csv', 'w') as f:
f.write('Date,Type,Signal,Symbol,Price,Shares,PnL,Cash\n')
def __init__(self, feed, brk, instrument):
super(LiveStrategy, self).__init__(feed, brk)
brk.addBitmexFeed(feed)
feed.getNewValuesEvent().subscribe(self.__onBarsImpl)
self.initial_capital = self.getResult()
brk.setStrategy(self)
self.positions = {}
for symbol in instrument:
self.positions[symbol] = brk.get_synced_position(self, symbol)
retAnalyzer = returns.Returns()
self.attachAnalyzerEx(retAnalyzer, 'retAnalyzer')
sharpeRatioAnalyzer = sharpe.SharpeRatio()
self.attachAnalyzerEx(sharpeRatioAnalyzer, 'sharpeRatioAnalyzer')
drawDownAnalyzer = drawdown.DrawDown()
self.attachAnalyzerEx(drawDownAnalyzer, 'drawDownAnalyzer')
tradesAnalyzer = trades.Trades()
self.attachAnalyzerEx(tradesAnalyzer, 'tradesAnalyzer')
self.plt = plotter.StrategyPlotter(self)
self.plt.getOrCreateSubplot("returns").addDataSeries(
"Net return", retAnalyzer.getReturns())
self.plt.getOrCreateSubplot("returns").addDataSeries(
"Cum. return", retAnalyzer.getCumulativeReturns())
self.strategy_id = brk.getStrategyId()
if not os.path.exists(self.strategy_id + '.csv'):
with open(self.strategy_id + '.csv', 'w') as f:
f.write('Date,Type,Signal,Symbol,Price,Shares,PnL,Cash\n')
if not os.path.exists(self.strategy_id + '_orders.csv'):
with open(self.strategy_id + '_orders.csv', 'w') as f:
f.write(
'Date,OrderDate,OrderId,Type,Signal,Symbol,Price,Size,Filled,Timedelta,StopHit\n'
)
def main(plot):
instrument = "000300.ss"
feed = yahoofinance.build_feed([instrument], 2013, 2015, ".")
period = 100
strat = HurstBasedStrategy(feed, instrument, period)
sharpeRatioAnalyzer = sharpe.SharpeRatio()
strat.attachAnalyzer(sharpeRatioAnalyzer)
# Attach a returns analyzers to the strategy.
returnsAnalyzer = returns.Returns()
strat.attachAnalyzer(returnsAnalyzer)
if plot:
plt = plotter.StrategyPlotter(strat, True, False, True)
plt.getOrCreateSubplot("hurst").addDataSeries("Hurst",
strat.getHurst())
plt.getOrCreateSubplot("hurst").addLine("random", 0.5)
# Plot the simple returns on each bar.
# plt.getOrCreateSubplot("returns").addDataSeries("Simple returns", returnsAnalyzer.getReturns())
strat.run()
strat.info("Final portfolio value: $%.2f" % strat.getResult())
# print "Sharpe ratio: %.2f" % sharpeRatioAnalyzer.getSharpeRatio(0.05)
if plot:
plt.plot()
def main(plot):
instrument = "yhoo"
bBandsPeriod = 40
# Download the bars.
feed = quandl.build_feed("WIKI", [instrument], 2011, 2012, ".")
strat = BBands(feed, instrument, bBandsPeriod)
sharpeRatioAnalyzer = sharpe.SharpeRatio()
strat.attachAnalyzer(sharpeRatioAnalyzer)
if plot:
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 analyzer(self,strat,instrument):
SPlotter = plotter.StrategyPlotter(strat, True, True, True) #mid (self, strat, plotAllInstruments=True, plotBuySell=True, plotPortfolio=True)
#SPlotter.getInstrumentSubplot(instrument).addDataSeries("upper", strat.getBollingerBands().getUpperBand())
#SPlotter.getInstrumentSubplot(instrument).addDataSeries("middle", strat.getBollingerBands().getMiddleBand())
SPlotter.getInstrumentSubplot(instrument).addDataSeries("short", strat.getSMA())
SPlotter.getInstrumentSubplot(instrument).addDataSeries("long", strat.getLMA())
#SPlotter.getOrCreateSubplot("Returns").addDataSeries("Simple returns", self.returnsAnalyzer.getReturns())
#SPlotter.getOrCreateSubplot("SharpeRatio").addDataSeries("Sharpe Ratio", self.sharpeRatioAnalyzer.getReturns())
#SPlotter.getOrCreateSubplot("SharpeRatio").addDataSeries("Sharpe Ratio", self.tradesAnalyzer.getCommissionsForAllTrades())
def addCallBack():
# mid 使用默认绘图类绘制自定义数据,此处是LineMarker
def midBars(bars):
midOpen = bars[self.instrument].getOpen()
midClose = bars[self.instrument].getClose()
print midOpen
return midClose
SPlotter.getOrCreateSubplot("orders").addCallback("mid's callback",midBars,plotter.LineMarker)
def addDataSeries():
feedDataSeries = self.feed.getDataSeries()
feedDataSerie = feedDataSeries.getCloseDataSeries()
SPlotter.getOrCreateSubplot("orders02").addDataSeries("mid's dataSeries",feedDataSerie,plotter.LineMarker)
#addCallBack()
#addDataSeries()
position = strat.getPositionVolume()
SPlotter.getOrCreateSubplot("position").addDataSeries("position", position)
return SPlotter
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")
# Evaluate the strategy with the feed.
myStrategy = MyStrategy(feed, index, smaShort, smaLong)
# Attach analyzers to the strategy.
sharpeAnalyzer = sharpe.SharpeRatio()
myStrategy.attachAnalyzer(sharpeAnalyzer)
# Attach a plotter to the strategy
plt = plotter.StrategyPlotter(myStrategy)
# Run the strategy
myStrategy.run()
myStrategy.info("Final portfolio value: $%.2f" %
myStrategy.getBroker().getEquity())
myStrategy.info("Annualized Sharpe Ratio: " +
str(sharpeAnalyzer.getSharpeRatio(0, True)))
# Plot the strategy.
plt.plot()
def main(plot):
get_ticker_list()
smaPeriod = 163
for instrument in ticker_list[:10]:
# Download the bars
feed = csvfeed.GenericBarFeed(frequency=300)
feed.addBarsFromCSV(
instrument,
r"C:/Users/Rohit/Python_source_code/nse 500 stock data/Date Time Data/"
+ instrument + ".csv")
strat = SMACrossOver(feed, instrument, smaPeriod)
sharpeRatioAnalyzer = sharpe.SharpeRatio()
strat.attachAnalyzer(sharpeRatioAnalyzer)
if plot:
plt = plotter.StrategyPlotter(strat, True, False, True)
plt.getInstrumentSubplot(instrument).addDataSeries(
"sma", strat.getSMA())
strat.run()
print(instrument)
print("Sharpe ratio: %.2f" % sharpeRatioAnalyzer.getSharpeRatio(0.05))
if plot:
plt.plot()
def main(plot):
instrument = "n225"
CalibratedBollingerBandsPeriod = 40
feed = yahoofeed.Feed()
feed.addBarsFromCSV(instrument, r".\Data\n225.csv")
strat = BollingerBandsStrategy(feed, instrument,
CalibratedBollingerBandsPeriod)
sharpeRatioAnalyzer = sharpe.SharpeRatio()
strat.attachAnalyzer(sharpeRatioAnalyzer)
if plot:
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()
strat.info("Final portfolio value: $%.2f" % strat.getResult())
print("Sharpe ratio: %.2f" % sharpeRatioAnalyzer.getSharpeRatio(0.05))
if plot:
plt.plot()
def main():
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)
retAnalyzer = returns.Returns()
strat.attachAnalyzer(retAnalyzer)
drawDownAnalyzer = drawdown.DrawDown()
strat.attachAnalyzer(drawDownAnalyzer)
tradesAnalyzer = trades.Trades()
strat.attachAnalyzer(tradesAnalyzer)
# ------
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()
plt.plot()
# ==============================
print("最终资产价值 Final portfolio value: $%.2f" % strat.getResult())
print("累计回报率 Cumulative returns: %.2f %%" % (retAnalyzer.getCumulativeReturns()[-1] * 100))
print("夏普比率 Sharpe ratio: %.2f" % (sharpeRatioAnalyzer.getSharpeRatio(0.05)))
print("最大回撤率 Max. drawdown: %.2f %%" % (drawDownAnalyzer.getMaxDrawDown() * 100))
print("最长回撤时间 Longest drawdown duration: %s" % (drawDownAnalyzer.getLongestDrawDownDuration()))
def turtle_test(loadtype='pgs', dataString='pyalg'):
"""
:param dataString:
:return:
"""
# 从postgres 中加载
if loadtype == 'pgs':
from api.stock.histmd import to_postgres_md as tpd
dat = tpd.get_h_data('600848')
else:
from api.stock.histmd.to_mongodb_md import k_data_dao as tmd
w = tmd.KdataDbCache()
dat = w.get_k_data(index=False,start='2015-02-05', end='2015-02-19',code='300426')
feed = dataFramefeed.Feed()
feed.addBarsFromDataFrame("orcl", dat)
myStrategy = pdr.turtle(feed, "orcl", 20, 10)
# Attach a returns analyzers to the strategy.
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 main(plot):
symbol = "yhoo"
priceCurrency = "USD"
instrument = "%s/%s" % (symbol, priceCurrency)
bBandsPeriod = 40
# Download the bars.
feed = quandl.build_feed("WIKI", [symbol], priceCurrency, 2011, 2012, ".")
broker = backtesting.Broker({priceCurrency: 1000000}, feed)
strat = BBands(feed, broker, instrument, bBandsPeriod)
sharpeRatioAnalyzer = sharpe.SharpeRatio(priceCurrency)
strat.attachAnalyzer(sharpeRatioAnalyzer)
if plot:
from pyalgotrade import plotter
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 main(plot):
"""
"""
# 初始化常量
instrument = 'BINA--BTC--USDT'
# 数据
# 1、从mysql导出csv数据
# 2、指定数据频率
# 3、读入csv给feed
sql_to_csv(True)
feed = GenericBarFeed(Frequency.DAY, None, None)
feed.addBarsFromCSV(instrument, instrument + '.csv')
# 评价器
# 1、初始化一个sharpratio评价器
sharpeRatioAnalyzer = sharpe.SharpeRatio()
# 注入
# 1、实例化一个策略
# 2、注入评价器
strat = close_above_sma(feed, instrument)
strat.attachAnalyzer(sharpeRatioAnalyzer)
if plot:
plt = plotter.StrategyPlotter(strat, True, True, True)
plt.getInstrumentSubplot(instrument).addDataSeries(
"sma", strat.getSma())
strat.run()
plt.plot()
print("Sharpe ratio: %.2f" % sharpeRatioAnalyzer.getSharpeRatio(0.05))
def main(plot):
symbol = sql_to_csv(True)
instrument = symbol
entrySMA = 200
exitSMA = 5
rsiPeriod = 2
overBoughtThreshold = 90
overSoldThreshold = 10
# Download the bars.
feed = GenericBarFeed(Frequency.DAY, None, None)
feed.addBarsFromCSV(symbol, symbol + '.csv')
strat = 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 main(plot):
symbol = "GORO"
priceCurrency = "USD"
instrument = "%s/%s" % (symbol, priceCurrency)
initialBalance = {priceCurrency: 1000000}
# Download GORO bars using WIKI source code.
feed = quandl.build_feed("WIKI", [symbol], "USD", 2006, 2012, ".")
# Load Quandl CSV downloaded from http://www.quandl.com/OFDP-Open-Financial-Data-Project/GOLD_2-LBMA-Gold-Price-London-Fixings-P-M
quandlFeed = csvfeed.Feed("Date", "%Y-%m-%d")
quandlFeed.setDateRange(datetime.datetime(2006, 1, 1),
datetime.datetime(2012, 12, 31))
quandlFeed.addValuesFromCSV("quandl_gold_2.csv")
myStrategy = MyStrategy(feed, quandlFeed, instrument, initialBalance)
if plot:
from pyalgotrade import plotter
plt = plotter.StrategyPlotter(myStrategy, True, False, False)
plt.getOrCreateSubplot("quandl").addDataSeries("USD",
quandlFeed["USD"])
plt.getOrCreateSubplot("quandl").addDataSeries("EUR",
quandlFeed["EUR"])
plt.getOrCreateSubplot("quandl").addDataSeries("GBP",
quandlFeed["GBP"])
myStrategy.run()
if plot:
plt.plot()
def main(plot):
instrument = "aapl"
vwapWindowSize = 5
threshold = 0.01
# Download the bars.
# feed = yahoofinance.build_feed([instrument], 2011, 2012, ".")
feed = yahoofeed.Feed()
feed.addBarsFromCSV(instrument, "dat\\aapl-201x.csv")
strat = VWAPMomentum(feed, instrument, vwapWindowSize, threshold)
sharpeRatioAnalyzer = sharpe.SharpeRatio()
strat.attachAnalyzer(sharpeRatioAnalyzer)
if plot:
plt = plotter.StrategyPlotter(strat, True, False, True)
plt.getInstrumentSubplot(instrument).addDataSeries(
"vwap", strat.getVWAP())
strat.run()
print
"Sharpe ratio: %.2f" % sharpeRatioAnalyzer.getSharpeRatio(0.05)
if plot:
plt.plot()
def main(plot):
symbol = "AAPL"
priceCurrency = "USD"
instrument = "%s/%s" % (symbol, priceCurrency)
initialBalance = {priceCurrency: 1000000}
vwapWindowSize = 5
threshold = 0.01
# Download the bars.
feed = quandl.build_feed("WIKI", [symbol], priceCurrency, 2011, 2012, ".")
strat = VWAPMomentum(feed, instrument, initialBalance, vwapWindowSize,
threshold)
sharpeRatioAnalyzer = sharpe.SharpeRatio(priceCurrency)
strat.attachAnalyzer(sharpeRatioAnalyzer)
if plot:
from pyalgotrade import plotter
plt = plotter.StrategyPlotter(strat, True, False, True)
plt.getInstrumentSubplot(instrument).addDataSeries(
"vwap", strat.getVWAP())
strat.run()
print("Sharpe ratio: %.2f" % sharpeRatioAnalyzer.getSharpeRatio(0.05))
if plot:
plt.plot()
def ENE(type='old', code='600281'):
dat = pd.read_csv("../../api/stock/csv/%sSH_5min.csv" % code, encoding='gbk')
dat = dat.fillna(method='pad')
dat['Adj Close'] = dat['Close']
dat = dat.rename(columns={'Open': 'open', 'High': 'high', 'Volume': 'volume', 'Close': 'close', 'Low': 'low'})
dat.index = dat['Date Time']
dat.index.name = 'date'
# dat = dat.ix[17000:18000,:]
feed = dataFramefeed.Feed(frequency=bar.Frequency.MINUTE)
feed.addBarsFromDataFrame("orcl", dat)
if type == 'macd':
myStrategy = mdd.ENE_backtest(feed, 'orcl')
elif type == 'old':
myStrategy = mdd.ENE_backtest(feed, 'orcl')
sharpeRatioAnalyzer = sharpe.SharpeRatio()
myStrategy.attachAnalyzer(sharpeRatioAnalyzer)
returnsAnalyzer = returns.Returns()
myStrategy.attachAnalyzer(returnsAnalyzer)
plt = plotter.StrategyPlotter(myStrategy, True, True, True)
plt.getOrCreateSubplot("returns").addDataSeries("Simple returns", returnsAnalyzer.getReturns())
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()
plt.plot()
print('最大回撤：\t%f\t 交易笔数：\t%d\t 盈利笔数：\t%d\n' % (ds.getMaxDrawDown(), ds.getCount(), ds.getProfitableCount()))
print('累计收益：\t%f\t 夏普比率：\t%f\t' % (returnsAnalyzer.getCumulativeReturns()[-1], ds.getSharpeRatio()))
def main(plot):
instruments = ["gld", "gdx"]
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:
fileName = "%s-%d-yahoofinance.csv" % (instrument, year)
print("Loading bars from %s" % fileName)
feed.addBarsFromCSV(instrument, fileName)
strat = StatArb(feed, instruments[0], instruments[1], windowSize)
sharpeRatioAnalyzer = sharpe.SharpeRatio()
strat.attachAnalyzer(sharpeRatioAnalyzer)
if plot:
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 main(plot):
instrument = "002941"
bBandsPeriod = 10
# Download the bars.
feed = yahoofeed.Feed()
feed.addBarsFromCSV("002941", "F:/shuju/002941-orcl.csv")
strat = BBands(feed, instrument, bBandsPeriod)
sharpeRatioAnalyzer = sharpe.SharpeRatio()
strat.attachAnalyzer(sharpeRatioAnalyzer)
if plot:
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 main(plot):
instrument = "yhoo"
bBandsPeriod = 10
# Download the bars.
# feed = yahoofinance.build_feed([instrument], 2011, 2012, ".")
feed = coinfeed.Feed()
startDate = datetime.datetime.strptime("2014-04-06 11:47:42",
"%Y-%m-%d %H:%M:%S")
endDate = datetime.datetime.strptime("2014-04-10 11:47:42",
"%Y-%m-%d %H:%M:%S")
# feed.setDateRange(startDate, endDate)
feed.addBarsFromCSV("btc", "data/ticker.csv")
myStrategy = MyStrategy(feed, "btc", bBandsPeriod)
if plot:
plt = plotter.StrategyPlotter(myStrategy, True, True, True)
plt.getInstrumentSubplot(instrument).addDataSeries(
"upper",
myStrategy.getBollingerBands().getUpperBand())
# plt.getInstrumentSubplot(instrument).addDataSeries("middle", myStrategy.getBollingerBands().getMiddleBand())
plt.getInstrumentSubplot(instrument).addDataSeries(
"lower",
myStrategy.getBollingerBands().getLowerBand())
myStrategy.run()
print "Result: %.2f" % myStrategy.getResult()
if plot:
plt.plot()
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, ".")
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 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(50000, feed, broker_commission)
# broker_brk = broker.backtesting.Broker(50000, feed)
# 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.info("Final portfolio value: $%.2f" % myStrategy.getResult())
# Plot the strategy.
plt.plot()
