SharpeRatio.annualized {JFE}

calculate annualized Sharpe Ratio

Description

The Sharpe Ratio is a risk-adjusted measure of return that uses standard deviation to represent risk.

Usage

SharpeRatio.annualized(R, Rf = 0, alpha=0.05,scale = NA, geometric = TRUE, FUN = "StdDev")

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

alpha

Tail probability for VaR or ES, default alpha=.05

scale

number of periods in a year (daily scale = 252, monthly scale = 12, quarterly scale = 4)

geometric

utilize geometric chaining (TRUE) or simple/arithmetic chaining (FALSE) to aggregate returns,default TRUE

FUN

one of "StdDev" or "VaR" or "ES" to use as the denominator, default="StdDev"

Details

The Sharpe ratio is simply the return per unit of risk (represented by variance). The higher the Sharpe ratio, the better the combined performance of "risk" and return.

This function annualizes the number based on the scale parameter.

\frac{\sqrt[n]{prod(1+R_{a})^{scale}}-1}{\sqrt{scale}\cdot\sqrt{\sigma}}

Using an annualized Sharpe Ratio is useful for comparison of multiple return streams. The annualized Sharpe ratio is computed by dividing the annualized mean monthly excess return by the annualized monthly standard deviation of excess return.

William Sharpe now recommends Information Ratio preferentially to the original Sharpe Ratio.

Author(s)

Ho Tsung-wu <[e-mail]>, College of Management, National Taiwan Normal University.

References

Sharpe, W.F. The Sharpe Ratio,Journal of Portfolio Management,Fall 1994, 49-58.
See also package PerformanceAnalytics.

See Also

SharpeRatio
InformationRatio
TrackingError
ActivePremium
SortinoRatio

Examples

  data(assetReturns)
	R=assetReturns[, -29]
  SharpeRatio.annualized(R)