def vwap(plot):
instrument = ["lenovo", "mi"]
vwapWindowSize = 5
threshold = 0.01
# Download the bars.
feed = yahoofeed.Feed()
feed.addBarsFromCSV("lenovo", "D:/data2/600687.csv")
feed.addBarsFromCSV("mi", "D:/data2/600701.csv")
strat = pyalg_test.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 vwap(plot):
import os
instrument = ["lenovo", "mi"]
vwapWindowSize = 5
threshold = 0.01
# Download the bars.
if (True):
#mid 从dataFrame中加载,即直接加载tushare格式数据
feed = dataFramefeed.Feed()
dataRoot = os.path.abspath(
os.path.join(os.path.dirname(__file__), os.pardir, os.pardir,
os.pardir, 'histdata', 'tushare'))
code = '600209'
filename = dataRoot + os.sep + 'day' + os.sep + ('%s.csv' % code)
dat = pd.read_csv(filename, index_col=0, encoding='gbk')
feed.addBarsFromDataFrame("lenovo", dat)
code = '600051'
filename = dataRoot + os.sep + 'day' + os.sep + ('%s.csv' % code)
dat = pd.read_csv(filename, index_col=0, encoding='gbk')
feed.addBarsFromDataFrame("mi", dat)
else: #mid 加载tushare数据转化为yahoo格式后的数据
feed = yahoofeed.Feed()
feed.addBarsFromCSV("lenovo", "D:/data2/600687.csv")
feed.addBarsFromCSV("mi", "D:/data2/600701.csv")
strat = pyalg_test.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)
rs = ds.getReturns() #获取默认的交易信息，dic格式,可忽略
for items in rs:
print items[0], items[1]
if plot:
plt.plot()