Notebook

Run the cell below to create your tear sheet, or return to your algorithm.

In [1]:
bt = get_backtest('59c2936403ac71565f9e34ac')
bt.create_full_tear_sheet()
100% Time: 0:01:00|###########################################################|
Entire data start date: 2008-09-02
Entire data end date: 2017-09-18


Backtest Months: 108
Performance statistics Backtest
annual_return 0.11
cum_returns_final 1.66
annual_volatility 0.08
sharpe_ratio 1.45
calmar_ratio 1.01
stability_of_timeseries 0.91
max_drawdown -0.11
omega_ratio 1.30
sortino_ratio 2.24
skew 0.05
kurtosis 4.34
tail_ratio 1.19
common_sense_ratio 1.33
gross_leverage 1.00
information_ratio -0.00
alpha 0.10
beta 0.11
Worst drawdown periods net drawdown in % peak date valley date recovery date duration
0 11.35 2014-03-18 2014-10-14 2015-10-16 414
1 7.46 2012-04-27 2012-07-17 2012-11-05 137
2 5.46 2009-02-06 2009-03-11 2009-03-20 31
3 5.08 2011-08-31 2011-10-03 2011-10-10 29
4 4.62 2010-08-06 2010-08-31 2010-09-30 40

[-0.009 -0.018]
/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 -0.03% -2.06% 1.88%
US downgrade/European Debt Crisis 0.17% -1.38% 1.80%
Fukushima 0.04% -0.59% 0.68%
EZB IR Event 0.06% -0.34% 0.70%
Sept08 -0.03% -2.06% 1.88%
2009Q1 0.13% -1.42% 1.58%
2009Q2 0.13% -2.71% 1.89%
Flash Crash 0.18% -0.47% 0.83%
Apr14 -0.10% -2.73% 1.75%
Oct14 0.05% -1.30% 1.36%
Fall2015 0.06% -1.11% 1.49%
GFC Crash 0.18% -2.71% 2.19%
Recovery 0.04% -1.57% 2.37%
New Normal 0.03% -2.73% 1.75%