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 testDownloadAndParseDaily(self):
instrument = "orcl/USD"
barFeed = yahoofeed.Feed()
barFeed.addBarsFromCSV(instrument, common.get_data_file_path("orcl-2000-yahoofinance.csv"))
strat = sma_crossover.SMACrossOver(barFeed, instrument, 20)
plt = plotter.StrategyPlotter(strat, True, True, True)
plt.getInstrumentSubplot(instrument).addDataSeries("sma", strat.getSMA())
strat.run()
with common.TmpDir() as tmpPath:
png = os.path.join(tmpPath, "plotter_test.png")
plt.savePlot(png)
# Check that file size looks ok.
self.assertGreater(os.stat(png).st_size, 44000)
def main(plot):
instrument = "AAPL"
smaPeriod = 30
# Download the bars.
feed = quandl.build_feed("WIKI", [instrument,"NVDA"], 2016, 2018, Constants.data_directory)
strategy = sma_crossover.SMACrossOver(feed, instrument, smaPeriod)
sharpeRatioAnalyzer = sharpe.SharpeRatio()
strategy.attachAnalyzer(sharpeRatioAnalyzer)
if plot:
plt = plotter.StrategyPlotter(strategy, True, True, True)
plt.getInstrumentSubplot(instrument).addDataSeries("sma", strategy.getSMA())
strategy.run()
print("Sharpe ratio: %.2f" % sharpeRatioAnalyzer.getSharpeRatio(0.05))
if plot:
plt.plot()
def main(plot):
instrument = "aapl"
smaPeriod = 20
feed = yahoofinance.build_feed([instrument], 2014, 2015, ".")
strat = sma_crossover.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 "Sharpe ratio: %.2f" % sharpeRatioAnalyzer.getSharpeRatio(0.05)
if plot:
plt.plot()
def testDownloadAndParseDaily(self):
instrument = "orcl"
barFeed = yahoofeed.Feed()
barFeed.addBarsFromCSV(
instrument,
common.get_data_file_path("orcl-2000-yahoofinance.csv"))
strat = sma_crossover.SMACrossOver(barFeed, instrument, 20)
plt = plotter.StrategyPlotter(strat, True, True, True)
plt.getInstrumentSubplot(instrument).addDataSeries(
"sma", strat.getSMA())
strat.run()
with common.TmpDir() as tmpPath:
fig = plt.buildFigure()
fig.set_size_inches(10, 8)
png = os.path.join(tmpPath, "plotter_test.png")
fig.savefig(png)
self.assertEquals(
open(common.get_data_file_path("plotter_test.png"),
"r").read(),
open(png, "r").read())
def main(plot):
instrument = "AAPL"
smaPeriod = 163
# Download the bars.
feed = quandl.build_feed("WIKI", [instrument], 2011, 2012, ".")
strat = sma_crossover.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("Sharpe ratio: %.2f" % sharpeRatioAnalyzer.getSharpeRatio(0.05))
if plot:
plt.plot()
def testDownloadAndParseDaily(self):
instrument = "orcl"
barFeed = yahoofeed.Feed()
barFeed.addBarsFromCSV(instrument, common.get_data_file_path("orcl-2000-yahoofinance.csv"))
strat = sma_crossover.SMACrossOver(barFeed, instrument, 20)
plt = plotter.StrategyPlotter(strat, True, True, True)
plt.getInstrumentSubplot(instrument).addDataSeries("sma", strat.getSMA())
strat.run()
with common.TmpDir() as tmpPath:
fig = plt.buildFigure()
fig.set_size_inches(10, 8)
png = os.path.join(tmpPath, "plotter_test.png")
fig.savefig(png)
# Check that file size looks ok.
# 118458 on Mac
# 116210 on Linux
self.assertGreater(
os.stat(png).st_size,
110000
)
def main(plot):
instrument = "aapl"
smaPeriod = 163
# Download the bars.
#feed = yahoofinance.build_feed([instrument], 2011, 2012, ".")
feed = yahoofeed.Feed()
feed.addBarsFromCSV(instrument, "dat\\aapl-201x.csv")
strat = sma_crossover.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 ("Sharpe ratio: %.2f" % sharpeRatioAnalyzer.getSharpeRatio(0.05))
if plot:
plt.plot()
# 无风险利率 risk free rate
r = 0.04
# Load the bar feed from the CSV file
instrument = "moutai"
feed = quandlfeed.Feed()
# 调整需要的CSV路径 Adjust CSV file
feed.addBarsFromCSV(instrument, 'E:\\backtest\\csv\\' + instrument + 'csv.csv')
# 修改长短期均线 Adjust fast and slow MA
fastMA = 5
slowMA = 20
##line 55 调整存储图片路径 Change the root of saving image
#========================================================================================
# Evaluate the strategy with the feed's bars.
myStrategy = sma_crossover.SMACrossOver(feed, instrument, fastMA, slowMA)
# Attach a returns analyzers to the strategy.
returnsAnalyzer = returns.Returns()
sharpeRatioAnalyzer = sharpe.SharpeRatio()
drawdown = drawdown.DrawDown()
trades = trades.Trades()
myStrategy.attachAnalyzer(returnsAnalyzer)
myStrategy.attachAnalyzer(sharpeRatioAnalyzer)
myStrategy.attachAnalyzer(drawdown)
myStrategy.attachAnalyzer(trades)
# 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(instrument).addDataSeries("fastSMA",
from pyalgotrade import plotter
from pyalgotrade.barfeed import quandlfeed
from pyalgotrade.stratanalyzer import returns
import sma_crossover
# Load the bar feed from the CSV file
feed = quandlfeed.Feed()
feed.addBarsFromCSV("orcl", "WIKI-ORCL-2000-quandl.csv")
# Evaluate the strategy with the feed's bars.
myStrategy = sma_crossover.SMACrossOver(feed, "orcl", 20)
# Attach a returns analyzers to the strategy.
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("SMA", myStrategy.getSMA())
# Plot the simple returns on each bar.
plt.getOrCreateSubplot("returns").addDataSeries("Simple returns",
returnsAnalyzer.getReturns())
# Run the strategy.
myStrategy.run()
myStrategy.info("Final portfolio value: $%.2f" % myStrategy.getResult())
# Plot the strategy.
plt.plot()
#place below command in console to magnify the plot
#>>import matplotlib.pyplot as plt
#>>plt.rc('figure',figsize=(50,50))
from pyalgotrade import plotter
from pyalgotrade.barfeed import yahoofeed
from pyalgotrade.stratanalyzer import returns
import sma_crossover
# Load the yahoo feed from the CSV file
feed = yahoofeed.Feed()
ticker = "amzn"
feed.addBarsFromCSV(ticker, r'D:\Workspace\data\%s.csv' % ticker)
# Evaluate the strategy with the feed's bars.
myStrategy = sma_crossover.SMACrossOver(feed, ticker, 15)
# Attach a returns analyzers to the strategy.
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(ticker).addDataSeries("SMA", myStrategy.getSMA())
# Plot the simple returns on each bar.
plt.getOrCreateSubplot("returns").addDataSeries("Simple returns",
returnsAnalyzer.getReturns())
# Run the strategy.
myStrategy.run()
from pyalgotrade import plotter
from pyalgotrade.barfeed import quandlfeed
from pyalgotrade.stratanalyzer import returns
import sma_crossover
priceCurrency = "USD"
# Load the bar feed from the CSV file
feed = quandlfeed.Feed()
feed.addBarsFromCSV("ORCL/USD", "WIKI-ORCL-2000-quandl.csv")
# Evaluate the strategy with the feed's bars.
myStrategy = sma_crossover.SMACrossOver(feed, "ORCL/USD", 20)
# Attach a returns analyzers to the strategy.
returnsAnalyzer = returns.Returns(priceCurrency)
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("SMA", myStrategy.getSMA())
# Plot the simple returns on each bar.
plt.getOrCreateSubplot("returns").addDataSeries("Simple returns", returnsAnalyzer.getReturns())
# Run the strategy.
myStrategy.run()
myStrategy.info("Final portfolio value: $%.2f" % myStrategy.getResult())
# Plot the strategy.
plt.plot()
from pyalgotrade import plotter
from pyalgotrade.barfeed import yahoofeed
from pyalgotrade.barfeed import feed
from pyalgotrade.stratanalyzer import returns
import sma_crossover
# Load the yahoo feed from the CSV file
feed = yahoofeed.Feed()
feed.addBarsFromCSV("601766", "000060.csv")
# Evaluate the strategy with the feed's bars.
myStrategy = sma_crossover.SMACrossOver(feed, "601766", 20)
# Attach a returns analyzers to the strategy.
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("601766").addDataSeries("SMA", myStrategy.getSMA())
# Plot the simple returns on each bar.
plt.getOrCreateSubplot("returns").addDataSeries("Simple returns", returnsAnalyzer.getReturns())
# Run the strategy.
myStrategy.run()
myStrategy.info("Final portfolio value: $%.2f" % myStrategy.getResult())
# Plot the strategy.
plt.plot()
QQ: 592440193
"""
from pyalgotrade import plotter
from pyalgotrade.barfeed import yahoofeed
from pyalgotrade.stratanalyzer import returns
import sma_crossover
# Load the yahoo feed from the CSV file
feed = yahoofeed.Feed()
feed.addBarsFromCSV("sz000651", "000651.csv")
# Evaluate the strategy with the feed's bars.
myStrategy = sma_crossover.SMACrossOver(feed, "sz000651", 20)
# Attach a returns analyzers to the strategy.
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("sz000651").addDataSeries("SMA", myStrategy.getSMA())
# Plot the simple returns on each bar.
plt.getOrCreateSubplot("returns").addDataSeries("Simple returns",
returnsAnalyzer.getReturns())
# Run the strategy.
myStrategy.run()
if frequency == bar.Frequency.MINUTE:
path = os.path.join(r'C:\Users\linner\Desktop\learn\pyalgo\histdata', 'minute')
elif frequency == bar.Frequency.DAY:
path = os.path.join( r'C:\Users\linner\Desktop\learn\pyalgo\histdata', 'day')
filepath = os.path.join(path, instrument + market + ".csv")
#############################################don't change ############################33
from pyalgotrade.cn.csvfeed import Feed
barfeed = Feed(frequency)
barfeed.setDateTimeFormat('%Y-%m-%d')
barfeed.loadBars(instrument, market, fromDate, toDate, filepath)
pyalgotrade_id = instrument + '.' + market
myStrategy = sma_crossover.SMACrossOver(barfeed,pyalgotrade_id, 10)
# Attach a returns analyzers to the strategy.
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("600288").addDataSeries("SMA", myStrategy.getSMA())
# Plot the simple returns on each bar.
plt.getOrCreateSubplot("returns").addDataSeries("Simple returns", returnsAnalyzer.getReturns())
# Run the strategy.
