Additional Calculations & Roll, Up, Down Helpers

.travis.yml

@@ -9,18 +9,18 @@ matrix:
       env: PANDAS_VERSION=0.17.1 NUMPY_VERSION=1.10.4 SCIPY_VERSION=0.16.1 LIBGFORTRAN_VERSION=1.0
     - python: 2.7
       env: PANDAS_VERSION=0.18.1 NUMPY_VERSION=1.11.1 SCIPY_VERSION=0.17.1 LIBGFORTRAN_VERSION=3.0
-
-    - python: 3.4
-      env: PANDAS_VERSION=0.16.1 NUMPY_VERSION=1.9.2 SCIPY_VERSION=0.15.1 LIBGFORTRAN_VERSION=1.0
+    - python: 2.7
+      env: PANDAS_VERSION=0.19.2 NUMPY_VERSION=1.12.1 SCIPY_VERSION=0.19.0 LIBGFORTRAN_VERSION=3.0
+    - python: 2.7
+      env: PANDAS_VERSION=0.20.1 NUMPY_VERSION=1.12.1 SCIPY_VERSION=0.19.0 LIBGFORTRAN_VERSION=3.0
     - python: 3.4
       env: PANDAS_VERSION=0.17.1 NUMPY_VERSION=1.10.4 SCIPY_VERSION=0.16.1 LIBGFORTRAN_VERSION=1.0
     - python: 3.4
       env: PANDAS_VERSION=0.18.1 NUMPY_VERSION=1.11.1 SCIPY_VERSION=0.17.1 LIBGFORTRAN_VERSION=3.0
-
-    - python: 3.5
-      env: PANDAS_VERSION=0.17.1 NUMPY_VERSION=1.10.4 SCIPY_VERSION=0.16.1 LIBGFORTRAN_VERSION=1.0
     - python: 3.5
-      env: PANDAS_VERSION=0.18.1 NUMPY_VERSION=1.11.1 SCIPY_VERSION=0.17.1 LIBGFORTRAN_VERSION=3.0
+      env: PANDAS_VERSION=0.19.2 NUMPY_VERSION=1.12.1 SCIPY_VERSION=0.19.0 LIBGFORTRAN_VERSION=3.0
+    - python: 3.6
+      env: PANDAS_VERSION=0.20.1 NUMPY_VERSION=1.12.1 SCIPY_VERSION=0.19.0 LIBGFORTRAN_VERSION=3.0
 
 before_install:
   # We do this conditionally because it saves us some downloading if the

README.md

@@ -1,11 +1,77 @@
 # empyrical
+
 Common financial risk metrics.
 
-## Installation
+## Table of Contents
 
-### Installing with `pip`
+- [Installation](#installation)
+- [Usage](#usage)
+- [Support](#support)
+- [Contributing](#contributing)
+- [Testing](#testing)
 
+## Installation
 ```
 pip install empyrical
 ```
 
+## Usage
+
+Simple Statistics
+```python
+import numpy as np
+from empyrical import max_drawdown, alpha_beta
+
+returns = np.array([.01, .02, .03, -.4, -.06, -.02])
+benchmark_returns = np.array([.02, .02, .03, -.35, -.05, -.01])
+
+# calculate the max drawdown
+max_drawdown(returns)
+
+# calculate alpha and beta
+alpha, beta = alpha_beta(returns, benchmark_returns)
+
+```
+
+Rolling Measures
+```python
+import numpy as np
+from empyrical import roll_max_drawdown
+
+returns = np.array([.01, .02, .03, -.4, -.06, -.02])
+
+# calculate the rolling max drawdown
+roll_max_drawdown(returns, window=3)
+
+```
+
+Pandas Support
+```python
+import pandas as pd
+from empyrical import roll_up_capture, capture
+
+returns = pd.Series([.01, .02, .03, ... -.4, -.06, -.02])
+
+# calculate a capture ratio
+capture(returns)
+
+# calculate capture for up markets on a rolling 60 day basis
+roll_up_capture(returns, window=60)
+```
+
+## Support
+
+Please [open an issue](https://github.com/quantopian/empyrical/issues/new) for support.
+
+## Contributing
+
+Please contribute using [Github Flow](https://guides.github.com/introduction/flow/). Create a branch, add commits, and [open a pull request](https://github.com/quantopian/empyrical/compare/).
+
+## Testing
+- install requirements
+  - "nose>=1.3.7",
+  - "parameterized>=0.6.1"
+
+```
+python -m unittest
+```

empyrical/__init__.py

@@ -30,7 +30,7 @@
     sharpe_ratio,
     sortino_ratio,
     downside_risk,
-    information_ratio,
+    excess_sharpe,
     alpha_beta,
     alpha,
     beta,
@@ -40,6 +40,21 @@
     stability_of_timeseries,
     tail_ratio,
     cagr,
+    capture,
+    up_capture,
+    down_capture,
+    up_down_capture,
+    up_alpha_beta,
+    down_alpha_beta,
+    roll_max_drawdown,
+    roll_up_capture,
+    roll_down_capture,
+    roll_up_down_capture,
+    roll_alpha_beta,
+    roll_sharpe_ratio,
+)
+
+from .periods import (
     DAILY,
     WEEKLY,
     MONTHLY,

empyrical/periods.py

@@ -0,0 +1,17 @@
+APPROX_BDAYS_PER_MONTH = 21
+APPROX_BDAYS_PER_YEAR = 252
+
+MONTHS_PER_YEAR = 12
+WEEKS_PER_YEAR = 52
+
+DAILY = 'daily'
+WEEKLY = 'weekly'
+MONTHLY = 'monthly'
+YEARLY = 'yearly'
+
+ANNUALIZATION_FACTORS = {
+    DAILY: APPROX_BDAYS_PER_YEAR,
+    WEEKLY: WEEKS_PER_YEAR,
+    MONTHLY: MONTHS_PER_YEAR,
+    YEARLY: 1
+}