sropt: Create an 'sropt' object.
In SharpeR: Statistical Significance of the Sharpe Ratio

Description Usage Arguments Details Value Note Author(s) See Also Examples

Spawns an object of class sropt.

1	sropt(z.s, df1, df2, drag = 0, ope = 1, epoch = "yr", T2 = NULL)

`z.s`	an optimum Sharpe ratio statistic.
`df1`	the number of assets in the portfolio.
`df2`	the number of observations.
`drag`	the 'drag' term, c0/R. defaults to 0. It is assumed that `drag` has been annualized, i.e. has been multiplied by sqrt(ope). This is in contrast to the `c0` term given to `sr`.
`ope`	the number of observations per 'epoch'. For convenience of interpretation, The Sharpe ratio is typically quoted in 'annualized' units for some epoch, that is, 'per square root epoch', though returns are observed at a frequency of `ope` per epoch. The default value is 1, meaning the code will not attempt to guess what the observation frequency is, and no annualization adjustments will be made.
`epoch`	the string representation of the 'epoch', defaulting to 'yr'.
`T2`	the Hotelling T^2 statistic. If not given, it is computed from the given information.

The sropt class contains information about a rescaled T^2-statistic. The following are list attributes of the object:

sropt: The (optimal) Sharpe ratio statistic.
df1: The number of assets.
df2: The number of observations.
drag: The drag term, which is the 'risk free rate' divided by the maximum risk.
ope: The 'observations per epoch'.
epoch: The string name of the 'epoch'.

For the most part, this constructor should not be called directly, rather as.sropt should be called instead to compute the needed statistics.

a list cast to class sropt, with the following attributes:

sropt: the optimal Sharpe statistic.
df1: the number of assets.
df2: the number of observed vectors.
drag: the input drag term.
ope: the input ope term.
epoch: the input epoch term.
T2: the Hotelling T^2 statistic.

2FIX: allow rownames?

Steven E. Pav shabbychef@gmail.com

reannualize

as.sropt

Other sropt: as.sropt(), confint.sr(), dsropt(), is.sropt(), pco_sropt(), power.sropt_test(), reannualize(), sropt_test()

# roll your own.
ope <- 253
zeta.s <- 1.0
df1 <- 10
df2 <- 6 * ope
set.seed(as.integer(charToRaw("fix seed")))
rvs <- rsropt(1,df1,df2,zeta.s,ope,drag=0)
roll.own <- sropt(z.s=rvs,df1,df2,drag=0,ope=ope)
print(roll.own)
# put a bunch in. naming becomes a problem.
rvs <- rsropt(5,df1,df2,zeta.s,ope,drag=0)
roll.own <- sropt(z.s=rvs,df1,df2,drag=0,ope=ope)
print(roll.own)