SharpeR (version 0.1306)

se: Standard error computation

Description

Estimates the standard error of the Sharpe ratio statistic.

Usage

se(z, type)
  ## S3 method for class '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 asLo.
• 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, as.sr.data.frame, as.sr.default, as.sr.lm, as.sr.xts, confint.sr, confint.sropt, dsr, is.sr, power.sr_test, print.sr, print.sropt, reannualize, reannualize.sr, reannualize.sropt, sr, sr_equality_test, sr_test

Examples

asr <- as.sr(rnorm(128,0.2))
anse <- se(asr,type="t")
anse <- se(asr,type="Lo")