Perform the following steps to analyze stock returns:
First, let's calculate simple returns. NumPy has the
diff
function that returns an array built up of the difference between two consecutive array elements. This is sort of like differentiation in calculus. To get the returns, we also have to divide by the value of the previous day. We must be careful though. The array returned bydiff
is one element shorter than the close prices array. After careful deliberation, we get the following code:returns = np.diff( arr ) / arr[ : -1]
Notice that we don't use the last value in the divisor. Let's compute the standard deviation using the
std
function:print "Standard deviation =", np.std(returns)
This results in the following output:
Standard deviation = 0.0129221344368
The log return is even easier to calculate. We use the
log
function to get the log of the close price and then unleash thediff
function on the result.logreturns = np.diff( np.log(c) )
Normally...