Notebook
In [1]:
bt = get_backtest('5884a39bb07bf961362be5f6')
100% Time: 0:00:46|###########################################################|
In [2]:
bt.create_full_tear_sheet()
Entire data start date: 2005-01-03
Entire data end date: 2017-01-20


Backtest Months: 144
Performance statistics Backtest
annual_return 0.07
annual_volatility 0.06
sharpe_ratio 1.21
calmar_ratio 1.02
stability_of_timeseries 0.98
max_drawdown -0.07
omega_ratio 1.29
sortino_ratio 1.95
skew 0.88
kurtosis 16.78
tail_ratio 1.24
common_sense_ratio 1.33
information_ratio 0.00
alpha 0.07
beta 0.07
Worst Drawdown Periods net drawdown in % peak date valley date recovery date duration
0 7.07 2010-02-04 2010-05-07 2010-12-17 227
1 6.34 2011-05-31 2011-08-08 2011-09-30 89
2 5.33 2008-11-04 2008-11-20 2008-12-01 20
3 5.09 2006-11-09 2007-08-24 2007-09-18 224
4 4.26 2008-10-16 2008-10-27 2008-10-31 12

[-0.007 -0.015]
/usr/local/lib/python2.7/dist-packages/numpy/lib/function_base.py:3834: RuntimeWarning: Invalid value encountered in percentile
  RuntimeWarning)
Stress Events mean min max
Lehmann -0.00% -2.85% 1.29%
US downgrade/European Debt Crisis 0.05% -3.09% 2.10%
Fukushima 0.05% -0.79% 0.44%
EZB IR Event -0.01% -0.32% 0.58%
Aug07 0.10% -0.90% 1.55%
Mar08 0.06% -0.62% 0.68%
Sept08 -0.05% -2.85% 0.99%
2009Q1 0.11% -1.22% 2.00%
2009Q2 0.14% -1.34% 2.04%
Flash Crash -0.11% -1.81% 2.13%
Apr14 0.08% -0.28% 0.60%
Oct14 0.04% -0.54% 0.70%
Fall2015 0.07% -0.52% 1.15%
Low Volatility Bull Market 0.00% -0.91% 0.79%
GFC Crash 0.06% -2.85% 3.62%
Recovery 0.04% -3.09% 2.60%
New Normal 0.02% -1.27% 1.38%