Volatility Autocorrelation

Problem

Compute the lag-k autocorrelation of squared returns, a standard measure of volatility clustering, using the biased 1/n estimator.

Return 0.0 if k is negative or at least the number of returns, or if the squared returns have zero variance.

Hint

Square the returns first so negative and positive shocks both count.

case 1

in: [[0.1,-0.2,0.1,-0.2],1]

expected: -0.75

case 2

in: [[1,2,3],0]

expected: 1

case 3

in: [[0,0],1]

expected: 0

case 4

in: [[1,-1,1,-1,1],2]

expected: 0

case 5

in: [[0.1,-0.2,0.3,-0.2,0.1],2]

expected: -0.6794392523364485

Starter codePython

def volatility_autocorrelation(returns, k):
    # Your code here
    pass

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