Tracking Error

Problem

Compute the tracking error as the population standard deviation of the active returns portfolio[t] - benchmark[t].

Return 0.0 when the lists are empty or have different lengths.

Hint

Tracking error is the volatility of the return difference, not of either series.

case 1

in: [[0.02,0.03,0.01],[0.01,0.01,0]]

expected: 0.004714045207910316

case 2

in: [[0.05,0.05],[0.02,0.02]]

expected: 0

case 3

in: [[0.01,-0.01],[0,0]]

expected: 0.01

case 4

in: [[],[]]

expected: 0

Starter codePython

def tracking_error(portfolio, benchmark):
    # Your code here
    pass

4 test cases · run your code against them in the editor