Calculates the returns of an asset in excess of the given risk free rate

Calculates the returns of an asset in excess of the given "risk free rate" for the period.

Usage

Return.excess(R, Rf = 0)

Arguments

R: an xts, vector, matrix, data frame, timeSeries or zoo object of asset returns
Rf: risk free rate, in same period as your returns, or as a single digit average

Details

Ideally, your risk free rate will be for each period you have returns observations, but a single average return for the period will work too.

Mean of the period return minus the period risk free rate

$$\overline{(R_{a}-R_{f})}$$

mean of the period returns minus a single numeric risk free rate

$$\overline{R_{a}}-R_{f}$$

Note that while we have, in keeping with common academic usage, assumed that the second parameter will be a risk free rate, you may also use any other timeseries as the second argument. A common alteration would be to use a benchmark to produce excess returns over a specific benchmark, as demonstrated in the examples below.

References

Bacon, Carl. Practical Portfolio Performance Measurement and Attribution. Wiley. 2004. p. 47-52

Author

Peter Carl

Examples


data(managers)
head(Return.excess(managers[, 1, drop = FALSE], managers[, 10, drop = FALSE]))
#>            HAM1 > US 3m TR
#> 1996-01-31         0.00284
#> 1996-02-29         0.01532
#> 1996-03-31         0.01179
#> 1996-04-30        -0.01338
#> 1996-05-31         0.00317
#> 1996-06-30        -0.00802
head(Return.excess(managers[, 1, drop = FALSE], .04 / 12))
#>               HAM1 > Rf
#> 1996-01-31  0.004066667
#> 1996-02-29  0.015966667
#> 1996-03-31  0.012166667
#> 1996-04-30 -0.012433333
#> 1996-05-31  0.004266667
#> 1996-06-30 -0.007233333
head(Return.excess(managers[, 1:6], managers[, 10, drop = FALSE]))
#>            HAM1 > US 3m TR HAM2 > US 3m TR HAM3 > US 3m TR HAM4 > US 3m TR
#> 1996-01-31         0.00284              NA         0.03034         0.01764
#> 1996-02-29         0.01532              NA         0.03112         0.01552
#> 1996-03-31         0.01179              NA         0.02209        -0.01351
#> 1996-04-30        -0.01338              NA         0.04062         0.01932
#> 1996-05-31         0.00317              NA         0.03087        -0.00163
#> 1996-06-30        -0.00802              NA        -0.03442        -0.00602
#>            HAM5 > US 3m TR HAM6 > US 3m TR
#> 1996-01-31              NA              NA
#> 1996-02-29              NA              NA
#> 1996-03-31              NA              NA
#> 1996-04-30              NA              NA
#> 1996-05-31              NA              NA
#> 1996-06-30              NA              NA
head(Return.excess(managers[, 1, drop = FALSE], managers[, 8, drop = FALSE]))
#>            HAM1 > SP500 TR
#> 1996-01-31         -0.0266
#> 1996-02-29          0.0100
#> 1996-03-31          0.0059
#> 1996-04-30         -0.0238
#> 1996-05-31         -0.0182
#> 1996-06-30         -0.0077