title: Calculate monthly returns from daily returns in pandas(cumpound)
body: <p>I was trying to calculate monthly returns for a particular stock, but I can't figure out a good method which doesn't use a big quantity of for cycles.
  The df has the following form</p>
  
  <pre><code>           MSFT-US  AAPL-US    GE    RF
   20150501    1.01   -0.33   -0.60   0.000
   20150504    0.32    0.06    0.16   0.000
   20150505   -1.19   -0.10    0.34   0.000
   20150506   -0.31    0.62   -0.20   0.000
   20150507    0.39    0.03   -0.43   0.000
   20150508    1.21   -0.54   -0.21   0.000
   20150511   -0.39    0.67   -0.11   0.000
   20150512   -0.27    0.00    0.11   0.000
   20150513    0.01    0.02   -0.06   0.000
   20150514    1.01   -0.10   -0.36   0.000
   20150515    0.05   -0.26   -0.01   0.000
   20150518    0.44    0.72   -0.09   0.000
   20150519   -0.09   -0.08    0.03   0.000
   20150520   -0.05    0.21   -0.09   0.000
   20150521    0.23   -0.31    0.09   0.000
   20150522   -0.22   -0.11   -0.14   0.000
   20150526   -1.01   -0.04   -0.02   0.000
   20150527    0.93    0.33   -0.39   0.000
   20150528   -0.11    0.11    0.07   0.000
   20150529   -0.58    0.02    0.05   0.000
  </code></pre>
  
  <p>So I want to have something like this (but coumpound not sum):</p>
  
  <pre><code>         MSFT-US   AAPL-US     GE      RF
   201505    1.36     0.92     -1.89    0.00
  </code></pre>