Run the cell below to create your tear sheet.
In [1]:
bt = get_backtest('5ed2f68a696b834749d09412')
bt.create_full_tear_sheet()
100% Time: 0:01:28|##########################################################|
| Start date | 2018-01-03 |
|---|---|
| End date | 2020-05-28 |
| Total months | 28 |
| Backtest | |
| Annual return | 4.314% |
| Cumulative returns | 10.652% |
| Annual volatility | 9.117% |
| Sharpe ratio | 0.51 |
| Calmar ratio | 0.59 |
| Stability | 0.81 |
| Max drawdown | -7.37% |
| Omega ratio | 1.10 |
| Sortino ratio | 0.75 |
| Skew | 0.44 |
| Kurtosis | 9.18 |
| Tail ratio | 1.00 |
| Daily value at risk | -1.13% |
| Gross leverage | 0.99 |
| Daily turnover | 24.595% |
| Alpha | 0.05 |
| Beta | 0.01 |
| Worst drawdown periods | Net drawdown in % | Peak date | Valley date | Recovery date | Duration |
|---|---|---|---|---|---|
| 0 | 7.37 | 2019-12-24 | 2020-03-18 | 2020-04-08 | 77 |
| 1 | 6.00 | 2020-04-09 | 2020-04-24 | NaT | NaN |
| 2 | 5.22 | 2019-02-13 | 2019-08-07 | 2019-09-12 | 152 |
| 3 | 2.42 | 2018-04-04 | 2018-04-30 | 2018-05-10 | 27 |
| 4 | 2.25 | 2018-05-11 | 2018-05-30 | 2018-07-02 | 37 |
| Stress Events | mean | min | max |
|---|---|---|---|
| New Normal | 0.02% | -2.68% | 3.74% |
| Top 10 long positions of all time | max |
|---|---|
| QEP-39778 | 3.06% |
| NVAX-14112 | 2.93% |
| PFGC-49455 | 2.77% |
| SRNE-33062 | 2.66% |
| TVTY-371 | 2.59% |
| CDEV-50376 | 2.54% |
| MFA-18590 | 2.49% |
| APY-51966 | 2.46% |
| HLX-17180 | 2.40% |
| TRTX-51054 | 2.39% |
| Top 10 short positions of all time | max |
|---|---|
| TLRY-52211 | -2.63% |
| PGEN-45239 | -2.63% |
| ENDP-21750 | -2.56% |
| VAL-2621 | -2.50% |
| OSTK-23714 | -2.50% |
| CPE-12011 | -2.40% |
| WLL-25707 | -2.33% |
| NE-5249 | -2.32% |
| SIG-9774 | -2.28% |
| WFT-19336 | -2.27% |
| Top 10 positions of all time | max |
|---|---|
| QEP-39778 | 3.06% |
| NVAX-14112 | 2.93% |
| PFGC-49455 | 2.77% |
| SRNE-33062 | 2.66% |
| TLRY-52211 | 2.63% |
| PGEN-45239 | 2.63% |
| TVTY-371 | 2.59% |
| ENDP-21750 | 2.56% |
| CDEV-50376 | 2.54% |
| VAL-2621 | 2.50% |
/venvs/py35/lib/python3.5/site-packages/statsmodels/nonparametric/kdetools.py:20: VisibleDeprecationWarning: using a non-integer number instead of an integer will result in an error in the future y = X[:m/2+1] + np.r_[0,X[m/2+1:],0]*1j
Performance Relative to Common Risk Factors¶
| Summary Statistics | |
|---|---|
| Annualized Specific Return | 6.72% |
| Annualized Common Return | -2.25% |
| Annualized Total Return | 4.26% |
| Specific Sharpe Ratio | 0.89 |
| Exposures Summary | Average Risk Factor Exposure | Annualized Return | Cumulative Return |
|---|---|---|---|
| basic_materials | -0.01 | 0.32% | 0.77% |
| consumer_cyclical | 0.01 | -0.19% | -0.46% |
| financial_services | 0.02 | -0.06% | -0.14% |
| real_estate | -0.01 | 0.69% | 1.67% |
| consumer_defensive | 0.01 | 0.07% | 0.17% |
| health_care | -0.04 | -1.27% | -3.01% |
| utilities | -0.00 | -0.09% | -0.22% |
| communication_services | -0.00 | -0.11% | -0.26% |
| energy | -0.01 | 0.69% | 1.65% |
| industrials | 0.01 | -0.58% | -1.38% |
| technology | -0.01 | -0.29% | -0.70% |
| momentum | -0.10 | -0.45% | -1.08% |
| size | -0.02 | -0.82% | -1.95% |
| value | 0.12 | -0.56% | -1.34% |
| short_term_reversal | 0.01 | 0.13% | 0.31% |
| volatility | 0.11 | 0.21% | 0.51% |
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