Insurance Premium

Problem

Compute the Arrow-Pratt approximation of a risk-loaded insurance premium.

Return loss_mean + 0.5 * gamma * loss_var / wealth, the expected loss plus the curvature-based risk loading.

Hint

The loading grows with risk aversion and loss variance but shrinks with wealth.

case 1

in: [100,10,25,2]

expected: 10.25

case 2

in: [50,5,4,1]

expected: 5.04

case 3

in: [200,0,0,3]

expected: 0

Starter codePython

def insurance_premium(wealth, loss_mean, loss_var, gamma):
    # Your code here
    pass

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