SharpeR (version 1.1.0)

se: Standard error computation

Description

Estimates the standard error of the Sharpe ratio statistic.

Usage

se(z, type)
# S3 method for sr
se(z, type = c("t", "Lo"))

Arguments

z

an observed Sharpe ratio statistic, of class sr.

type

estimator type. one of "t", "Lo", "exact"

...

further arguments to be passed to or from methods.

Value

an estimate of standard error.

Details

For an observed Sharpe ratio, estimate the standard error. There are two methods:

• The default, t, based on Johnson & Welch, with a correction for small sample size, also known as Lo.

• A method based on the exact variance of the non-central t-distribution, exact.

There should be very little difference between these except for very small sample sizes.

References

Sharpe, William F. "Mutual fund performance." Journal of business (1966): 119-138. http://ideas.repec.org/a/ucp/jnlbus/v39y1965p119.html

Johnson, N. L., and Welch, B. L. "Applications of the non-central t-distribution." Biometrika 31, no. 3-4 (1940): 362-389. http://dx.doi.org/10.1093/biomet/31.3-4.362

Lo, Andrew W. "The statistics of Sharpe ratios." Financial Analysts Journal 58, no. 4 (2002): 36-52. http://ssrn.com/paper=377260

Opdyke, J. D. "Comparing Sharpe Ratios: So Where are the p-values?" Journal of Asset Management 8, no. 5 (2006): 308-336. http://ssrn.com/paper=886728

Walck, C. "Hand-book on STATISTICAL DISTRIBUTIONS for experimentalists." 1996. http://www.stat.rice.edu/~dobelman/textfiles/DistributionsHandbook.pdf

See Also

sr-distribution functions, dsr

Other sr: as.sr, confint.sr, dsr, is.sr, plambdap, power.sr_test, predint, print.sr, reannualize, sr_equality_test, sr_test, sr_unpaired_test, sr_vcov, sr, summary

Examples

# NOT RUN {
asr <- as.sr(rnorm(128,0.2))
anse <- se(asr,type="t")
anse <- se(asr,type="Lo")

# }