Risk adjusted returns based on volatility
| """ | |
| Note that this Gist uses functions made available in another Gist - | |
| https://gist.github.com/StuartGordonReid/67a1ec4fbc8a84c0e856 | |
| """ | |
| def treynor_ratio(er, returns, market, rf): | |
| return (er - rf) / beta(returns, market) | |
| def sharpe_ratio(er, returns, rf): | |
| return (er - rf) / vol(returns) | |
| def information_ratio(returns, benchmark): | |
| diff = returns - benchmark | |
| return numpy.mean(diff) / vol(diff) | |
| def modigliani_ratio(er, returns, benchmark, rf): | |
| np_rf = numpy.empty(len(returns)) | |
| np_rf.fill(rf) | |
| rdiff = returns - np_rf | |
| bdiff = benchmark - np_rf | |
| return (er - rf) * (vol(rdiff) / vol(bdiff)) + rf |
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