def main():
# Load the orders file.
ordersFile = OrdersFile("orders.csv")
print "First date", ordersFile.getFirstDate()
print "Last date", ordersFile.getLastDate()
print "Symbols", ordersFile.get_symbols()
# Load the data from QSTK storage. QS environment variable has to be defined.
feed = yahoofeed.Feed()
feed.set_bar_filter(csvfeed.DateRangeFilter(ordersFile.getFirstDate(), ordersFile.getLastDate()))
feed.set_daily_bar_time(datetime.time(0, 0, 0)) # This is to match the dates loaded with the ones in the orders file.
for symbol in ordersFile.get_symbols():
feed.add_bars_from_csv(symbol, os.path.join(os.getenv("QS"), "QSData", "Yahoo", symbol + ".csv"))
# Run the strategy.
cash = 1000000
use_adjustedClose = True
myStrategy = MyStrategy(feed, cash, ordersFile, use_adjustedClose)
# Attach returns and sharpe ratio analyzers.
retAnalyzer = returns.Returns()
myStrategy.attach_analyzer(retAnalyzer)
sharpeRatioAnalyzer = sharpe.SharpeRatio()
myStrategy.attach_analyzer(sharpeRatioAnalyzer)
myStrategy.run()
# Print the results.
print "Final portfolio value: $%.2f" % myStrategy.get_result()
print "Anual return: %.2f %%" % (retAnalyzer.get_cumulative_returns()[-1] * 100)
print "Average daily return: %.2f %%" % (stats.mean(retAnalyzer.get_returns()) * 100)
print "Std. dev. daily return: %.4f" % (stats.stddev(retAnalyzer.get_returns()))
print "Sharpe ratio: %.2f" % (sharpeRatioAnalyzer.get_sharpe_ratio(0, 252))
def sharpe_ratio(returns, risk_free_rate, trading_periods, 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:
excess_returns = [daily_return - (risk_free_rate/float(trading_periods)) for daily_return in returns]
average_excess_returns = stats.mean(excess_returns)
ret = average_excess_returns / volatility
if annualized:
ret = ret * math.sqrt(trading_periods)
return ret
def sharpe_ratio(returns, risk_free_rate, trading_periods, 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:
excess_returns = [
daily_return - (risk_free_rate / float(trading_periods))
for daily_return in returns
]
average_excess_returns = stats.mean(excess_returns)
ret = average_excess_returns / volatility
if annualized:
ret = ret * math.sqrt(trading_periods)
return ret
def main():
# Load the orders file.
ordersFile = OrdersFile("orders.csv")
print "First date", ordersFile.getFirstDate()
print "Last date", ordersFile.getLastDate()
print "Symbols", ordersFile.get_symbols()
# Load the data from QSTK storage. QS environment variable has to be defined.
feed = yahoofeed.Feed()
feed.set_bar_filter(
csvfeed.DateRangeFilter(ordersFile.getFirstDate(),
ordersFile.getLastDate()))
feed.set_daily_bar_time(
datetime.time(0, 0, 0)
) # This is to match the dates loaded with the ones in the orders file.
for symbol in ordersFile.get_symbols():
feed.add_bars_from_csv(
symbol,
os.path.join(os.getenv("QS"), "QSData", "Yahoo", symbol + ".csv"))
# Run the strategy.
cash = 1000000
use_adjustedClose = True
myStrategy = MyStrategy(feed, cash, ordersFile, use_adjustedClose)
# Attach returns and sharpe ratio analyzers.
retAnalyzer = returns.Returns()
myStrategy.attach_analyzer(retAnalyzer)
sharpeRatioAnalyzer = sharpe.SharpeRatio()
myStrategy.attach_analyzer(sharpeRatioAnalyzer)
myStrategy.run()
# Print the results.
print "Final portfolio value: $%.2f" % myStrategy.get_result()
print "Anual return: %.2f %%" % (retAnalyzer.get_cumulative_returns()[-1] *
100)
print "Average daily return: %.2f %%" % (
stats.mean(retAnalyzer.get_returns()) * 100)
print "Std. dev. daily return: %.4f" % (stats.stddev(
retAnalyzer.get_returns()))
print "Sharpe ratio: %.2f" % (sharpeRatioAnalyzer.get_sharpe_ratio(0, 252))
def __testMeanImpl(self, values):
self.__assertEqFloat(stats.mean(values), stats.py_mean(values))
def __testMeanImpl(self, values):
self.__assertEqFloat(stats.mean(values), stats.py_mean(values))
def on_bars(self, bars):
pass
# Load the yahoo feed from CSV files.
feed = yahoofeed.Feed()
feed.add_bars_from_csv("aeti", "aeti-2011-yahoofinance.csv")
feed.add_bars_from_csv("egan", "egan-2011-yahoofinance.csv")
feed.add_bars_from_csv("glng", "glng-2011-yahoofinance.csv")
feed.add_bars_from_csv("simo", "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.attach_analyzer(retAnalyzer)
sharpeRatioAnalyzer = sharpe.SharpeRatio()
myStrategy.attach_analyzer(sharpeRatioAnalyzer)
# Run the strategy
myStrategy.run()
# Print the results.
print "Final portfolio value: $%.2f" % myStrategy.get_result()
print "Anual return: %.2f %%" % (retAnalyzer.get_cumulative_returns()[-1] * 100)
print "Average daily return: %.2f %%" % (stats.mean(retAnalyzer.get_returns()) * 100)
print "Std. dev. daily return: %.4f" % (stats.stddev(retAnalyzer.get_returns()))
print "Sharpe ratio: %.2f" % (sharpeRatioAnalyzer.get_sharpe_ratio(0, 252))
# Load the yahoo feed from CSV files.
feed = yahoofeed.Feed()
feed.add_bars_from_csv("aeti", "aeti-2011-yahoofinance.csv")
feed.add_bars_from_csv("egan", "egan-2011-yahoofinance.csv")
feed.add_bars_from_csv("glng", "glng-2011-yahoofinance.csv")
feed.add_bars_from_csv("simo", "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.attach_analyzer(retAnalyzer)
sharpeRatioAnalyzer = sharpe.SharpeRatio()
myStrategy.attach_analyzer(sharpeRatioAnalyzer)
# Run the strategy
myStrategy.run()
# Print the results.
print "Final portfolio value: $%.2f" % myStrategy.get_result()
print "Anual return: %.2f %%" % (retAnalyzer.get_cumulative_returns()[-1] *
100)
print "Average daily return: %.2f %%" % (
stats.mean(retAnalyzer.get_returns()) * 100)
print "Std. dev. daily return: %.4f" % (stats.stddev(
retAnalyzer.get_returns()))
print "Sharpe ratio: %.2f" % (sharpeRatioAnalyzer.get_sharpe_ratio(0, 252))