Treynor Ratio

Problem

Compute the Treynor ratio: (mean(returns) - rf) / beta, the excess return earned per unit of systematic risk.

Return 0.0 when returns is empty or beta is 0.

Hint

Only systematic risk (beta) is in the denominator.

case 1

in: [[0.1,0.2,0.3],1.5,0.02]

expected: 0.12

case 2

in: [[0.05],0,0]

expected: 0

case 3

in: [[0.1,-0.05],2,0]

expected: 0.0125

case 4

in: [[0.1,0.1],1,0.1]

expected: 0

Starter codePython

def treynor_ratio(returns, beta, rf):
    # Your code here
    pass

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