def sharpe_ratio_2(returns,
riskFreeRate,
firstDateTime,
lastDateTime,
annualized=True):
ret = 0.0
# From http://en.wikipedia.org/wiki/Sharpe_ratio:
# if Rf is a constant risk-free return throughout the period, then stddev(R - Rf) = stddev(R).
volatility = stats.stddev(returns, 1)
if volatility != 0:
# We use 365 instead of 252 becuase we wan't the diff from 1/1/xxxx to 12/31/xxxx to be 1 year.
yearsTraded = days_traded(firstDateTime, lastDateTime) / 365.0
riskFreeRateForPeriod = riskFreeRate * yearsTraded
rfPerReturn = riskFreeRateForPeriod / float(len(returns))
avgExcessReturns = stats.mean(returns) - rfPerReturn
ret = avgExcessReturns / volatility
if annualized:
ret = ret * math.sqrt(len(returns) / yearsTraded)
return ret
def main():
import coloredlogs
coloredlogs.install(level='DEBUG',
fmt='[%(asctime)s] %(levelname)s %(message)s')
# Load the yahoo feed from CSV files.
feed = yahoofeed.Feed()
feed.addBarsFromCSV("aeti", "./tests/data/aeti-2011-yahoofinance.csv")
feed.addBarsFromCSV("egan", "./tests/data/egan-2011-yahoofinance.csv")
feed.addBarsFromCSV("glng", "./tests/data/glng-2011-yahoofinance.csv")
feed.addBarsFromCSV("simo", "./tests/data/simo-2011-yahoofinance.csv")
# Evaluate the strategy with the feed's bars.
myStrategy = MyStrategy(feed)
# Attach returns and sharpe ratio analyzers.
retAnalyzer = returns.Returns()
myStrategy.attachAnalyzer(retAnalyzer)
sharpeRatioAnalyzer = sharpe.SharpeRatio()
myStrategy.attachAnalyzer(sharpeRatioAnalyzer)
# Run the strategy
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)))
def main():
# 2.读取csv文件.
feed = GenericBarFeed(Frequency.DAY, None, None)
feed.addBarsFromCSV("a", "a.csv")
feed.addBarsFromCSV("b", "b.csv")
feed.addBarsFromCSV("c", "c.csv")
feed.addBarsFromCSV("d", "d.csv")
strat = MyStrategy(feed)
# 3.加入分析器
retAnalyzer = returns.Returns()
strat.attachAnalyzer(retAnalyzer)
sharpeRatioAnalyzer = sharpe.SharpeRatio()
strat.attachAnalyzer(sharpeRatioAnalyzer)
# 4.运行策略
strat.run()
# 5.输出结果
# 最终的投资组合价值
print("Final portfolio value: $%.2f" % strat.getResult())
# 年化平均收益率
print("Anual return: %.2f %%" % (retAnalyzer.getCumulativeReturns()[-1] * 100))
# 平均日收益
print("Average daily return: %.2f %%" % (stats.mean(retAnalyzer.getReturns()) * 100))
# 每日收益标准开发
print("Std. dev. daily return: %.4f" % (stats.stddev(retAnalyzer.getReturns())))
# 夏普比率
print("Sharpe ratio: %.2f" % (sharpeRatioAnalyzer.getSharpeRatio(0)))
def sharpe_ratio(returns, riskFreeRate, tradingPeriods, annualized=True):
ret = 0.0
# From http://en.wikipedia.org/wiki/Sharpe_ratio: if Rf is a constant risk-free return throughout the period,
# then stddev(R - Rf) = stddev(R).
volatility = stats.stddev(returns, 1)
if volatility != 0:
rfPerReturn = riskFreeRate / float(tradingPeriods)
avgExcessReturns = stats.mean(returns) - rfPerReturn
ret = avgExcessReturns / volatility
if annualized:
ret = ret * math.sqrt(tradingPeriods)
return ret
def main():
# Load the orders file.
ordersFile = OrdersFile("./tests/data/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") is 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)))