def output_summary_stats(self):
"""
Creates a list of summary statistics for the portfolio.
"""
total_return = self.equity_curve['equity_curve'][-1]
returns = self.equity_curve['returns']
pnl = self.equity_curve['equity_curve']
sharpe_ratio = create_sharpe_ratio(returns, periods=252 * 60 * 6.5)
#import time
#time0 = time.time()
max_dd, dd_duration = create_drawdowns(pnl)
#time1 = time.time()
#print('timing create drawdown: {}'.format(time1 - time0))
stats = dict()
stats['Total Return'] = (total_return - 1.0)
stats['Annualized Return'] = (
total_return ** (365 / len(self.equity_curve.index))) - 1
stats['Length of Series'] = len(self.equity_curve.index)
stats['Sharpe Ratio'] = sharpe_ratio
stats['Max Drawdown'] = max_dd
stats['Drawdown Duration'] = floor(dd_duration)
self.equity_curve.to_csv('equity.csv')
return stats
def test_create_sharpe_ratio1(self):
"""
test for non volatility serie
"""
simm = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1]
prices = pd.Series(simm)
returns = prices.pct_change()
result = performance.create_sharpe_ratio(returns)
self.assertTrue(math.isnan(result))
def test_create_sharpe_ratio0(self):
"""
test for correct calculations
"""
simm = [10, 9, 11, 10, 12, 11, 13, 12, 14, 13, 15]
prices = pd.Series(simm)
returns = prices.pct_change()
result = performance.create_sharpe_ratio(returns)
expected = 5.85973697
self.assertAlmostEqual(result, expected)
def output_summary_stats(self):
"""
Crea un elenco di statistiche di riepilogo per il portafoglio
come lo Sharpe Ratio e le informazioni sul drowdown.
"""
total_return = self.equity_curve['equity_curve'][-1]
returns = self.equity_curve['returns']
pnl = self.equity_curve['equity_curve']
sharpe_ratio = create_sharpe_ratio(returns, periods=252 * 6.5 * 60)
drawdown, max_dd, dd_duration = create_drawdowns(pnl)
self.equity_curve['drawdown'] = drawdown
stats = [("Total Return", "%0.2f%%" % \
((total_return - 1.0) * 100.0)),
("Sharpe Ratio", "%0.2f" % sharpe_ratio),
("Max Drawdown", "%0.2f%%" % (max_dd * 100.0)),
("Drawdown Duration", "%d" % dd_duration)]
self.equity_curve.to_csv('equity.csv')
return stats
