MSquared: M squared of the return distribution

In guillermozbta/portafolio-master: Econometric tools for performance and risk analysis.

Description

M squared is a risk adjusted return useful to judge the size of relative performance between differents portfolios. With it you can compare portfolios with different levels of risk.

Usage

MSquared(Ra, Rb, Rf = 0, ...)

Arguments

Ra	an xts, vector, matrix, data frame, timeSeries or zoo object of asset return
Rb	return vector of the benchmark asset
Rf	risk free rate, in same period as your returns
...	any other passthru parameters

Details

M squared = Rp + SR * (Market risk - Portfolio risk) = (Rp - Rf) * Market risk / Portfolio risk + Rf

where r_P is the portfolio return annualized, σ_M is the market risk and σ_P is the portfolio risk

Author(s)

Matthieu Lestel

References

Carl Bacon, Practical portfolio performance measurement and attribution, second edition 2008 p.67-68

Examples

data(portfolio_bacon)
print(MSquared(portfolio_bacon[,1], portfolio_bacon[,2])) #expected 0.10062

data(managers)
print(MSquared(managers['1996',1], managers['1996',8]))
print(MSquared(managers['1996',1:5], managers['1996',8]))

guillermozbta/portafolio-master documentation built on May 11, 2019, 7:20 p.m.