PerformanceAnalytics (version 1.1.0)

TreynorRatio: calculate Treynor Ratio or modified Treynor Ratio of excess return over CAPM beta

Description

The Treynor ratio is similar to the Sharpe Ratio, except it uses beta as the volatility measure (to divide the investment's excess return over the beta).

Usage

TreynorRatio(Ra, Rb, Rf = 0, scale = NA,
    modified = FALSE)

Arguments

Ra
an xts, vector, matrix, data frame, timeSeries or zoo object of asset returns
Rb
return vector of the benchmark asset
Rf
risk free rate, in same period as your returns
scale
number of periods in a year (daily scale = 252, monthly scale = 12, quarterly scale = 4)
modified
a boolean to decide whether to return the Treynor ratio or Modified Treynor ratio

Details

To calculate modified Treynor ratio, we divide the numerator by the systematic risk instead of the beta.

Equation: $$TreynorRatio = \frac{\overline{(R_{a}-R_{f})}}{\beta_{a,b}}$$ $$ModifiedTreynorRatio = \frac{r_p - r_f}{\sigma_s}$$

References

http://en.wikipedia.org/wiki/Treynor_ratio, Carl Bacon, Practical portfolio performance measurement and attribution, second edition 2008 p.77

See Also

SharpeRatio SortinoRatio CAPM.beta

Examples

Run this code
data(portfolio_bacon)
data(managers)
round(TreynorRatio(managers[,1,drop=FALSE], managers[,8,drop=FALSE], Rf=.035/12),4)
round(TreynorRatio(managers[,1,drop=FALSE], managers[,8,drop=FALSE], Rf = managers[,10,drop=FALSE]),4)
round(TreynorRatio(managers[,1:6], managers[,8,drop=FALSE], Rf=.035/12),4)
round(TreynorRatio(managers[,1:6], managers[,8,drop=FALSE], Rf = managers[,10,drop=FALSE]),4)
round(TreynorRatio(managers[,1:6], managers[,8:7,drop=FALSE], Rf=.035/12),4)
round(TreynorRatio(managers[,1:6], managers[,8:7,drop=FALSE], Rf = managers[,10,drop=FALSE]),4)

print(TreynorRatio(portfolio_bacon[,1], portfolio_bacon[,2], modified = TRUE)) #expected 0.7975

print(TreynorRatio(managers['1996',1], managers['1996',8], modified = TRUE))
print(TreynorRatio(managers['1996',1:5], managers['1996',8], modified = TRUE))

Run the code above in your browser using DataLab