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MSquared

M squared of the return distribution


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]))

PerformanceAnalytics

Econometric Tools for Performance and Risk Analysis

v2.0.4
GPL-2 | GPL-3
Authors
Brian G. Peterson [cre, aut, cph], Peter Carl [aut, cph], Kris Boudt [ctb, cph], Ross Bennett [ctb], Joshua Ulrich [ctb], Eric Zivot [ctb], Dries Cornilly [ctb], Eric Hung [ctb], Matthieu Lestel [ctb], Kyle Balkissoon [ctb], Diethelm Wuertz [ctb], Anthony Alexander Christidis [ctb], R. Douglas Martin [ctb], Zeheng 'Zenith' Zhou [ctb], Justin M. Shea [ctb]
Initial release
2020-02-05

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