EWMA Volatility Update

Problem

Update an exponentially weighted moving average volatility estimate: sigma = sqrt(lam * prev_variance + (1 - lam) * ret^2).

Return 0.0 when the weighted variance is negative.

Hint

The decay lam weights yesterday's variance, so lam near 1 produces a smooth series.

case 1

in: [0.04,0.03,0.94]

expected: 0.19404638620700979

case 2

in: [0.01,0.1,0.5]

expected: 0.1

case 3

in: [0,0,0.9]

expected: 0

case 4

in: [0.09,0.05,0]

expected: 0.05

Starter codePython

def ewma_volatility_update(prev_variance, ret, lam):
    # Your code here
    pass

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